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30 Mar 2020 at 01:37
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Bibliography on: Ecological Informatics


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RJR: Recommended Bibliography 30 Mar 2020 at 01:37 Created: 

Ecological Informatics

Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are the National Science Foundation's Datanet , DataONE and Data Conservancy projects.

Created with PubMed® Query: "ecology OR ecological" and ("data management" or informatics) NOT "assays for monitoring autophagy" NOT pmcbook NOT ispreviousversion

Citations The Papers (from PubMed®)

RevDate: 2020-03-27

Zhu C, Zhang Z, Wang H, et al (2020)

Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions.

Sensors (Basel, Switzerland), 20(6): pii:s20061795.

Soil organic matter (SOM) is a crucial indicator for evaluating soil quality and an important component of soil carbon pools, which play a vital role in terrestrial ecosystems. Rapid, non-destructive and accurate monitoring of SOM content is of great significance for the environmental management and ecological restoration of mining areas. Visible-near-infrared (Vis-NIR) spectroscopy has proven its applicability in estimating SOM over the years. In this study, 168 soil samples were collected from the Zhundong coal field of Xinjiang Province, Northwest China. The SOM content (g kg-1) was determined by the potassium dichromate external heating method and the soil reflectance spectra were measured by the spectrometer. Two spectral feature extraction strategies, namely, principal component analysis (PCA) and the optimal band combination algorithm, were introduced to choose spectral variables. Linear models and random forests (RF) were used for predictive models. The coefficient of determination (R2), root mean square error (RMSE), and the ratio of the performance to the interquartile distance (RPIQ) were used to evaluate the predictive performance of the model. The results indicated that the variables (2DI and 3DI) derived from the optimal band combination algorithm outperformed the PCA variables (1DV) regardless of whether linear or RF models were used. An inherent gap exists between 2DI and 3DI, and the performance of 2DI is significantly poorer than that of 3DI. The accuracy of the prediction model increases with the increasing number of spectral variable dimensions (in the following order: 1DV < 2DI < 3DI). This study proves that the 3DI is the first choice for the optimal band combination algorithm to derive sensitive parameters related to SOM in the coal mining area. Furthermore, the optimal band combination algorithm can be applied to hyperspectral or multispectral images and to convert the spectral response into image pixels, which may be helpful for a soil property spatial distribution map.

RevDate: 2020-03-24

Ma J, Lu Y, Chen F, et al (2020)

Molecular Ecological Network Complexity Drives Stand Resilience of Soil Bacteria to Mining Disturbances among Typical Damaged Ecosystems in China.

Microorganisms, 8(3): pii:microorganisms8030433.

Understanding the interactions of soil microbial species and how they responded to disturbances are essential to ecological restoration and resilience in the semihumid and semiarid damaged mining areas. Information on this, however, remains unobvious and deficiently comprehended. In this study, based on the high throughput sequence and molecular ecology network analysis, we have investigated the bacterial distribution in disturbed mining areas across three provinces in China, and constructed molecular ecological networks to reveal the interactions of soil bacterial communities in diverse locations. Bacterial community diversity and composition were classified measurably between semihumid and semiarid damaged mining sites. Additionally, we distinguished key microbial populations across these mining areas, which belonged to Proteobacteria, Acidobacteria, Actinobacteria, and Chloroflexi. Moreover, the network modules were significantly associated with some environmental factors (e.g., annual average temperature, electrical conductivity value, and available phosphorus value). The study showed that network interactions were completely different across the different mining areas. The keystone species in different mining areas suggested that selected microbial communities, through natural successional processes, were able to resist the corresponding environment. Moreover, the results of trait-based module significances showed that several environmental factors were significantly correlated with some keystone species, such as OTU_8126 (Acidobacteria), OTU_8175 (Burkholderiales), and OTU_129 (Chloroflexi). Our study also implied that the complex network of microbial interaction might drive the stand resilience of soil bacteria in the semihumid and semiarid disturbed mining areas.

RevDate: 2020-03-20
CmpDate: 2020-03-20

Xu L, Stige LC, Leirs H, et al (2019)

Historical and genomic data reveal the influencing factors on global transmission velocity of plague during the Third Pandemic.

Proceedings of the National Academy of Sciences of the United States of America, 116(24):11833-11838.

Quantitative knowledge about which natural and anthropogenic factors influence the global spread of plague remains sparse. We estimated the worldwide spreading velocity of plague during the Third Pandemic, using more than 200 years of extensive human plague case records and genomic data, and analyzed the association of spatiotemporal environmental factors with spreading velocity. Here, we show that two lineages, 2.MED and 1.ORI3, spread significantly faster than others, possibly reflecting differences among strains in transmission mechanisms and virulence. Plague spread fastest in regions with low population density and high proportion of pasture- or forestland, findings that should be taken into account for effective plague monitoring and control. Temperature exhibited a nonlinear, U-shaped association with spread speed, with a minimum around 20 °C, while precipitation showed a positive association. Our results suggest that global warming may accelerate plague spread in warm, tropical regions and that the projected increased precipitation in the Northern Hemisphere may increase plague spread in relevant regions.

RevDate: 2020-03-19

Ropert-Coudert Y, Van de Putte AP, Reisinger RR, et al (2020)

The retrospective analysis of Antarctic tracking data project.

Scientific data, 7(1):94 pii:10.1038/s41597-020-0406-x.

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.

RevDate: 2020-03-17

Piross IS, Solt S, Horváth É, et al (2020)

Sex-dependent changes in the louse abundance of red-footed falcons (Falco vespertinus).

Parasitology research pii:10.1007/s00436-020-06634-2 [Epub ahead of print].

Permanent ectoparasites live in stable environments; thus, their population dynamics are mostly adapted to changes in the host life cycle. We aimed to investigate how static and dynamic traits of red-footed falcons interplay with the dynamics of their louse subpopulations during breeding and how they affect the colonisation of new hosts by lice. We sampled red-footed falcon (Falco vespertinus) nestlings (two breeding seasons) and adults (one breeding season) in southern Hungary. The mean abundance of Colpocephalum subzerafae and Degeeriella rufa lice on the nestlings was modelled with generalized linear mixed models using clutch size and host sex in interaction with wing length. For adults, we used wing length and the number of days after laying the first egg, both in interaction with sex. D. rufa abundances increased with the nestlings' wing length. In one year, this trend was steeper on females. In adult birds, both louse species exhibited higher abundances on females at the beginning, but it decreased subsequently through the breeding season. Contrarily, abundances were constantly low on adult males. Apparently, D. rufa postpones transmission until nestlings develop juvenile plumage and choose the more feathered individual among siblings. The sexual difference in the observed abundance could either be caused by the different plumage, or by the females' preference for less parasitized males. Moreover, females likely have more time to preen during the incubation period, lowering their louse burdens. Thus, sex-biased infestation levels likely arise due to parasite preferences in the nestlings and host behavioural processes in the adult falcons.

RevDate: 2020-03-13

Thomas HJD, Bjorkman AD, Myers-Smith IH, et al (2020)

Global plant trait relationships extend to the climatic extremes of the tundra biome.

Nature communications, 11(1):1351 pii:10.1038/s41467-020-15014-4.

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

RevDate: 2020-03-13
CmpDate: 2020-03-13

Memarzadeh M, C Boettiger (2019)

Resolving the Measurement Uncertainty Paradox in Ecological Management.

The American naturalist, 193(5):645-660.

Ecological management and decision-making typically focus on uncertainty about the future, but surprisingly little is known about how to account for uncertainty of the present: that is, the realities of having only partial or imperfect measurements. Our primary paradigms for handling decisions under uncertainty-the precautionary principle and optimal control-have so far given contradictory results. This paradox is best illustrated in the example of fisheries management, where many ideas that guide thinking about ecological decision-making were first developed. We find that simplistic optimal control approaches have repeatedly concluded that a manager should increase catch quotas when faced with greater uncertainty about the fish biomass. Current best practices take a more precautionary approach, decreasing catch quotas by a fixed amount to account for uncertainty. Using comparisons to both simulated and historical catch data, we find that neither approach is sufficient to avoid stock collapses under moderate observational uncertainty. Using partially observed Markov decision process (POMDP) methods, we demonstrate how this paradox arises from flaws in the standard theory, which contributes to overexploitation of fisheries and increased probability of economic and ecological collapse. In contrast, we find that POMDP-based management avoids such overexploitation while also generating higher economic value. These results have significant implications for how we handle uncertainty in both fisheries and ecological management more generally.

RevDate: 2020-03-09
CmpDate: 2020-03-09

Mair C, Nickbakhsh S, Reeve R, et al (2019)

Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models.

PLoS computational biology, 15(12):e1007492.

It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.

RevDate: 2020-03-06

Cullen CM, Aneja KK, Beyhan S, et al (2020)

Emerging Priorities for Microbiome Research.

Frontiers in microbiology, 11:136.

Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19-23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration.

RevDate: 2020-02-18

Gallagher RV, Falster DS, Maitner BS, et al (2020)

Open Science principles for accelerating trait-based science across the Tree of Life.

Nature ecology & evolution pii:10.1038/s41559-020-1109-6 [Epub ahead of print].

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

RevDate: 2020-02-19
CmpDate: 2020-02-19

Hua ZS, Wang YL, Evans PN, et al (2019)

Insights into the ecological roles and evolution of methyl-coenzyme M reductase-containing hot spring Archaea.

Nature communications, 10(1):4574.

Several recent studies have shown the presence of genes for the key enzyme associated with archaeal methane/alkane metabolism, methyl-coenzyme M reductase (Mcr), in metagenome-assembled genomes (MAGs) divergent to existing archaeal lineages. Here, we study the mcr-containing archaeal MAGs from several hot springs, which reveal further expansion in the diversity of archaeal organisms performing methane/alkane metabolism. Significantly, an MAG basal to organisms from the phylum Thaumarchaeota that contains mcr genes, but not those for ammonia oxidation or aerobic metabolism, is identified. Together, our phylogenetic analyses and ancestral state reconstructions suggest a mostly vertical evolution of mcrABG genes among methanogens and methanotrophs, along with frequent horizontal gene transfer of mcr genes between alkanotrophs. Analysis of all mcr-containing archaeal MAGs/genomes suggests a hydrothermal origin for these microorganisms based on optimal growth temperature predictions. These results also suggest methane/alkane oxidation or methanogenesis at high temperature likely existed in a common archaeal ancestor.

RevDate: 2020-02-14
CmpDate: 2020-02-14

Kaczensky P, Khaliun S, Payne J, et al (2019)

Through the eye of a Gobi khulan - Application of camera collars for ecological research of far-ranging species in remote and highly variable ecosystems.

PloS one, 14(6):e0217772 pii:PONE-D-18-35632.

The Mongolian Gobi-Eastern Steppe Ecosystem is one of the largest remaining natural drylands and home to a unique assemblage of migratory ungulates. Connectivity and integrity of this ecosystem are at risk if increasing human activities are not carefully planned and regulated. The Gobi part supports the largest remaining population of the Asiatic wild ass (Equus hemionus; locally called "khulan"). Individual khulan roam over areas of thousands of square kilometers and the scale of their movements is among the largest described for terrestrial mammals, making them particularly difficult to monitor. Although GPS satellite telemetry makes it possible to track animals in near-real time and remote sensing provides environmental data at the landscape scale, remotely collected data also harbors the risk of missing important abiotic or biotic environmental variables or life history events. We tested the potential of animal born camera systems ("camera collars") to improve our understanding of the drivers and limitations of khulan movements. Deployment of a camera collar on an adult khulan mare resulted in 7,881 images over a one-year period. Over half of the images showed other khulan and 1,630 images showed enough of the collared khulan to classify the behaviour of the animals seen into several main categories. These khulan images provided us with: i) new insights into important life history events and grouping dynamics, ii) allowed us to calculate time budgets for many more animals than the collared khulan alone, and iii) provided us with a training dataset for calibrating data from accelerometer and tilt sensors in the collar. The images also allowed to document khulan behaviour near infrastructure and to obtain a day-time encounter rate between a specific khulan with semi-nomadic herders and their livestock. Lastly, the images allowed us to ground truth the availability of water by: i) confirming waterpoints predicted from other analyses, ii) detecting new waterpoints, and iii) compare precipitation records for rain and snow from landscape scale climate products with those documented by the camera collar. We discuss the added value of deploying camera collars on a subset of animals in remote, highly variable ecosystems for research and conservation.

RevDate: 2020-02-11
CmpDate: 2020-02-11

Jensen EL, Clement R, Kosta A, et al (2019)

A new widespread subclass of carbonic anhydrase in marine phytoplankton.

The ISME journal, 13(8):2094-2106.

Most aquatic photoautotrophs depend on CO2-concentrating mechanisms (CCMs) to maintain productivity at ambient concentrations of CO2, and carbonic anhydrase (CA) plays a key role in these processes. Here we present different lines of evidence showing that the protein LCIP63, identified in the marine diatom Thalassiosira pseudonana, is a CA. However, sequence analysis showed that it has a low identity with any known CA and therefore belongs to a new subclass that we designate as iota-CA. Moreover, LCIP63 unusually prefers Mn2+ to Zn2+ as a cofactor, which is potentially of ecological relevance since Mn2+ is more abundant than Zn2+ in the ocean. LCIP63 is located in the chloroplast and only expressed at low concentrations of CO2. When overexpressed using biolistic transformation, the rate of photosynthesis at limiting concentrations of dissolved inorganic carbon increased, confirming its role in the CCM. LCIP63 homologs are present in the five other sequenced diatoms and in other algae, bacteria, and archaea. Thus LCIP63 is phylogenetically widespread but overlooked. Analysis of the Tara Oceans database confirmed this and showed that LCIP63 is widely distributed in marine environments and is therefore likely to play an important role in global biogeochemical carbon cycling.

RevDate: 2020-02-06

Mascarenhas R, Ruziska FM, Moreira EF, et al (2019)

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Frontiers in genetics, 10:1344.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.

RevDate: 2020-01-17

Llanos-Garrido A, Pérez-Tris J, JA Díaz (2019)

The combined use of raw and phylogenetically independent methods of outlier detection uncovers genome-wide dynamics of local adaptation in a lizard.

Ecology and evolution, 9(24):14356-14367.

Local adaptation is a dynamic process by which different allele combinations are selected in different populations at different times, and whose genetic signature can be inferred by genome-wide outlier analyses. We combined gene flow estimates with two methods of outlier detection, one of them independent of population coancestry (CIOA) and the other one not (ROA), to identify genetic variants favored when ecology promotes phenotypic convergence. We analyzed genotyping-by-sequencing data from five populations of a lizard distributed over an environmentally heterogeneous range that has been changing since the split of eastern and western lineages ca. 3 mya. Overall, western lizards inhabit forest habitat and are unstriped, whereas eastern ones inhabit shrublands and are striped. However, one population (Lerma) has unstriped phenotype despite its eastern ancestry. The analysis of 73,291 SNPs confirmed the east-west division and identified nonoverlapping sets of outliers (12 identified by ROA and 9 by CIOA). ROA revealed ancestral adaptive variation in the uncovered outliers that were subject to divergent selection and differently fixed for eastern and western populations at the extremes of the environmental gradient. Interestingly, such variation was maintained in Lerma, where we found high levels of heterozygosity for ROA outliers, whereas CIOA uncovered innovative variants that were selected only there. Overall, it seems that both the maintenance of ancestral variation and asymmetric migration have counterbalanced adaptive lineage splitting in our model species. This scenario, which is likely promoted by a changing and heterogeneous environment, could hamper ecological speciation of locally adapted populations despite strong genetic structure between lineages.

RevDate: 2020-01-23

vonHoldt BM, DeCandia AL, Heppenheimer E, et al (2020)

Heritability of interpack aggression in a wild pedigreed population of North American grey wolves.

Molecular ecology [Epub ahead of print].

Aggression is a quantitative trait deeply entwined with individual fitness. Mapping the genomic architecture underlying such traits is complicated by complex inheritance patterns, social structure, pedigree information and gene pleiotropy. Here, we leveraged the pedigree of a reintroduced population of grey wolves (Canis lupus) in Yellowstone National Park, Wyoming, USA, to examine the heritability of and the genetic variation associated with aggression. Since their reintroduction, many ecological and behavioural aspects have been documented, providing unmatched records of aggressive behaviour across multiple generations of a wild population of wolves. Using a linear mixed model, a robust genetic relationship matrix, 12,288 single nucleotide polymorphisms (SNPs) and 111 wolves, we estimated the SNP-based heritability of aggression to be 37% and an additional 14% of the phenotypic variation explained by shared environmental exposures. We identified 598 SNP genotypes from 425 grey wolves to resolve a consensus pedigree that was included in a heritability analysis of 141 individuals with SNP genotype, metadata and aggression data. The pedigree-based heritability estimate for aggression is 14%, and an additional 16% of the phenotypic variation was explained by shared environmental exposures. We find strong effects of breeding status and relative pack size on aggression. Through an integrative approach, these results provide a framework for understanding the genetic architecture of a complex trait that influences individual fitness, with linkages to reproduction, in a social carnivore. Along with a few other studies, we show here the incredible utility of a pedigreed natural population for dissecting a complex, fitness-related behavioural trait.

RevDate: 2020-01-15
CmpDate: 2020-01-08

Kattge J, Bönisch G, Díaz S, et al (2020)

TRY plant trait database - enhanced coverage and open access.

Global change biology, 26(1):119-188.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

RevDate: 2020-01-17

Tomazatos A, Jansen S, Pfister S, et al (2019)

Ecology of West Nile Virus in the Danube Delta, Romania: Phylogeography, Xenosurveillance and Mosquito Host-Feeding Patterns.

Viruses, 11(12):.

The ecology of West Nile virus (WNV) in the Danube Delta Biosphere Reserve (Romania) was investigated by combining studies on the virus genetics, phylogeography, xenosurveillance and host-feeding patterns of mosquitoes. Between 2014 and 2016, 655,667 unfed and 3842 engorged mosquito females were collected from four sampling sites. Blood-fed mosquitoes were negative for WNV-RNA, but two pools of unfed Culex pipiens s.l./torrentium collected in 2014 were tested positive. Our results suggest that Romania experienced at least two separate WNV lineage 2 introductions: from Africa into Danube Delta and from Greece into south-eastern Romania in the 1990s and early 2000s, respectively. The genetic diversity of WNV in Romania is primarily shaped by in situ evolution. WNV-specific antibodies were detected for 19 blood-meals from dogs and horses, but not from birds or humans. The hosts of mosquitoes were dominated by non-human mammals (19 species), followed by human and birds (23 species). Thereby, the catholic host-feeding pattern of Culex pipiens s.l./torrentium with a relatively high proportion of birds indicates the species' importance as a potential bridge vector. The low virus prevalence in combination with WNV-specific antibodies indicate continuous, but low activity of WNV in the Danube Delta during the study period.

RevDate: 2020-01-08

Romanuk TN, Binzer A, Loeuille N, et al (2019)

Simulated evolution assembles more realistic food webs with more functionally similar species than invasion.

Scientific reports, 9(1):18242 pii:10.1038/s41598-019-54443-0.

While natural communities are assembled by both ecological and evolutionary processes, ecological assembly processes have been studied much more and are rarely compared with evolutionary assembly processes. We address these disparities here by comparing community food webs assembled by simulating introductions of species from regional pools of species and from speciation events. Compared to introductions of trophically dissimilar species assumed to be more typical of invasions, introducing species trophically similar to native species assumed to be more typical of sympatric or parapatric speciation events caused fewer extinctions and assembled more empirically realistic networks by introducing more persistent species with higher trophic generality, vulnerability, and enduring similarity to native species. Such events also increased niche overlap and the persistence of both native and introduced species. Contrary to much competition theory, these findings suggest that evolutionary and other processes that more tightly pack ecological niches contribute more to ecosystem structure and function than previously thought.

RevDate: 2019-11-21

Podar D, Macalik K, Réti KO, et al (2019)

Morphological, physiological and biochemical aspects of salt tolerance of halophyte Petrosimonia triandra grown in natural habitat.

Physiology and molecular biology of plants : an international journal of functional plant biology, 25(6):1335-1347.

Salt tolerance mechanisms of halophyte Petrosimonia triandra, growing in its natural habitat in Cluj County, Romania, were investigated via biomass, growth parameters, water status, ion content, photosynthetic and antioxidative system efficiency, proline accumulation and lipid degradation. Two sampling sites with different soil electrical conductivities were selected: site 1: 3.14 dS m-1 and site 2: 4.45 dS m-1. Higher salinity proved to have a positive effect on growth. The relative water content did not decline severely, Na+ and K+ content of the roots, stem and leaves was more, and the functions of the photosynthetic apparatus and photosynthetic pigment contents were not altered. The efficiency of the antioxidative defence system was found to be assured by coordination of several reactive oxygen species scavengers. The presence of higher salinity led to accumulation of the osmolyte proline, while degradation of membrane lipids was reduced. As a whole, P. triandra evolved different adaptational strategies to counteract soil salinity, including morphological and physiological adaptations, preservation of photosynthetic activity, development of an efficient antioxidative system and accumulation of the osmotic compound, proline.

RevDate: 2019-12-25

Wang Y, Qiao M, Baikeli Y, et al (2020)

Soft-templated mesoporous carbon-modified glassy carbon electrode for sensitive and selective detection of aristolochic acids.

Journal of hazardous materials, 385:121550.

In this study, ordered mesoporous carbon (OMC) was synthesized by applying a soft template method, and its mesoporous structure was characterized by scanning electron microscopy, transmission electron microscopy, and nitrogen adsorption-desorption techniques. X-ray diffraction and Raman spectroscopic analyses were conducted to demonstrate the high graphitization and topological defects at the sample surface. An electrochemical sensor based on an OMC-modified glassy carbon electrode (OMC/GCE) was constructed to detect aristolochic acids (AAs) using cyclic voltammetry and linear sweep voltammetry. The dependence of the experimental parameters including solution pH, scan rate, and accumulation time were examined and optimized. Under the optimal conditions, the response of OMC/GCE was linear over wide concentration ranges of AAs (0.6-10 μM and 10-50 μM), with sensitivities of -1.77 and -0.31 μA/μM, respectively. The limit of detection was calculated to be 0.186 μM (at S/N = 3). Furthermore, the proposed OMC/GCE was applied to detect AAs in Asarum sieboldini and the content of AAs was calculated to be 8.9 μg/g with high accuracy and precision. In addition, the modified electrode also exhibited good selectivity, reproducibility, and stability. Therefore, the OMC/GCE can be used as a platform for the determination of AAs.

RevDate: 2019-11-15

Näpflin K, O'Connor EA, Becks L, et al (2019)

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales.

PeerJ, 7:e8013.

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

RevDate: 2019-11-04

Tamburello L, Papa L, Guarnieri G, et al (2019)

Are we ready for scaling up restoration actions? An insight from Mediterranean macroalgal canopies.

PloS one, 14(10):e0224477.

Extensive loss of macroalgal forests advocates for large-scale restoration interventions, to compensate habitat degradation and recover the associated ecological functions and services. Yet, restoration attempts have generally been limited to small spatial extensions, with the principal aim of developing efficient restoration techniques. Here, the success of outplanting Cystoseira amentacea v. stricta germlings cultured in aquaria was experimentally explored at a scale of tens of kms, by means of a multifactorial experimental design. In the intertidal rocky shores of SE Italy, locations with a continuous distribution for hundreds of meters or with few thalli forming patches of few centimeters of C. amentacea canopy were selected. In each location, the effects of adult conspecifics and the exclusion of macrograzers (salema fish and sea urchins) on the survival of germlings were tested. We evaluated the most critical determinants of mortality for germlings, including the overlooked pressure of mesograzers (e.g. amphipods, small mollusks, polychaetes). Despite the high mortality observed during outplanting and early settlement stages, survival of C. amentacea germlings was consistently favored by the exclusion of macrograzers, while the presence of adult conspecifics had no effects. In addition, the cost analysis of the interventions showed the feasibility of the ex-situ method, representing an essential tool for preserving Cystoseira forests. Large scale restoration is possible but requires baseline information with an in-depth knowledge of the species ecology and of the areas to be restored, together with the development of specific cultivation protocols to make consistently efficient restoration interventions.

RevDate: 2019-11-17

Palomo I, Dujardin Y, Midler E, et al (2019)

Modeling trade-offs across carbon sequestration, biodiversity conservation, and equity in the distribution of global REDD+ funds.

Proceedings of the National Academy of Sciences of the United States of America, 116(45):22645-22650.

The program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) is one of the major attempts to tackle climate change mitigation in developing countries. REDD+ seeks to provide result-based incentives to promote emission reductions and increase carbon sinks in forest land while promoting other cobenefits, such as the conservation of biodiversity. We model different scenarios of international REDD+ funds distribution toward potential recipient countries using 2 carbon emission reduction targets (20% and 50% compared to the baseline scenario, i.e., deforestation and forest degradation without REDD+) by 2030. The model combines the prioritization of environmental outcomes in terms of carbon sequestration and biodiversity conservation and social equity, accounting for the equitable distribution of international REDD+ funds. Results highlight the synergy between carbon sequestration and biodiversity conservation under alternative fund allocation criteria, especially for scenarios of low carbon emission reduction. Trade-offs increase when distributional equity is considered as an additional criterion, especially under higher equity requirements. The analysis helps to better understand the inherent trade-offs between enhancing distributional equity and meeting environmental targets under alternative REDD+ fund allocation options.

RevDate: 2020-02-04
CmpDate: 2020-02-04

Shen L, Li XW, Meng XX, et al (2019)

Prediction of the globally ecological suitability of Panax quinquefolius by the geographic information system for global medicinal plants (GMPGIS).

Chinese journal of natural medicines, 17(7):481-489.

American ginseng (Panax quinquefolius L.) is a well-known Asian traditional herbal medicine with a large market demand. The plant is native to eastern North America, and its main producing areas worldwide are decreasing due to continuous cropping obstacles and environmental changes. Therefore, the identification of maximum similarities of new ecological distribution of P. quinquefolius, and prediction of its response to climate change in the future are necessary for plant introduction and cultivation. In this study, the areas with potential ecological suitability for P. quinquefolius were predicted using the geographic information system for global medicinal plants (GMPGIS) based on 476 occurrence points and 19 bioclimatic variables. The results indicate that the new ecologically suitable areas for P. quinquefolius are East Asia and the mid-eastern Europe, which are mainly distributed in China, Russia, Japan, Ukraine, Belarus, North Korean, South Korea, andRomania. Under global climate change scenarios, the suitable planting areas for P. quinquefolius would be increased by 9.16%-30.97%, and expandingnorth and west over the current ecologically suitable areas by 2070. The potential increased areas that are ecologically suitable include northern Canada, Eastern Europe, and the Lesser Khingan Mountains of China, and reduced regions are mainly in central China, the southern U.S., and southern Europe. Jackknife tests indicate that the precipitation of the warmest quarter was the important climatic factor controlling the distribution of P. quinquefolius. Our findings can be used as auseful guide for P. quinquefolius introduction and cultivation in ecologically suitable areas.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Becker AD, Wesolowski A, Bjørnstad ON, et al (2019)

Long-term dynamics of measles in London: Titrating the impact of wars, the 1918 pandemic, and vaccination.

PLoS computational biology, 15(9):e1007305 pii:PCOMPBIOL-D-19-00008.

A key question in ecology is the relative impact of internal nonlinear dynamics and external perturbations on the long-term trajectories of natural systems. Measles has been analyzed extensively as a paradigm for consumer-resource dynamics due to the oscillatory nature of the host-pathogen life cycle, the abundance of rich data to test theory, and public health relevance. The dynamics of measles in London, in particular, has acted as a prototypical test bed for such analysis using incidence data from the pre-vaccination era (1944-1967). However, during this timeframe there were few external large-scale perturbations, limiting an assessment of the relative impact of internal and extra demographic perturbations to the host population. Here, we extended the previous London analyses to include nearly a century of data that also contains four major demographic changes: the First and Second World Wars, the 1918 influenza pandemic, and the start of a measles mass vaccination program. By combining mortality and incidence data using particle filtering methods, we show that a simple stochastic epidemic model, with minimal historical specifications, can capture the nearly 100 years of dynamics including changes caused by each of the major perturbations. We show that the majority of dynamic changes are explainable by the internal nonlinear dynamics of the system, tuned by demographic changes. In addition, the 1918 influenza pandemic and World War II acted as extra perturbations to this basic epidemic oscillator. Our analysis underlines that long-term ecological and epidemiological dynamics can follow very simple rules, even in a non-stationary population subject to significant perturbations and major secular changes.

RevDate: 2020-02-05

Pranovi F, Libralato S, Zucchetta M, et al (2020)

Cumulative biomass curves describe past and present conditions of Large Marine Ecosystems.

Global change biology, 26(2):786-797.

Implementing the Ecosystem Approach in marine ecosystems is moving from preliminary steps-dedicated to defining the optimal features for indicators and developing efficient indicator frameworks-towards an operational phase where multisector marine management decisions are executed using this information. Within this operational context, emergent ecosystem properties are becoming quite promising as they have been demonstrated to be globally widespread and repeatable, and to be quite effective in detecting significant state variations of complex systems. Biomass accumulation across TLs (CumB-TL) combines two important emergent properties of an ecosystem (energy flow, in terms of transfer efficiency, and storage, expressed as biomass), both amenable to detecting rapid ecosystem change. However, for further application, it is crucial to understand which types of drivers an indicator is sensitive to and how robust it is in relation to modifications of the external conditions and/or the system state. Here we address some outstanding questions of these CumB-TL curves related to their sensitivity to various drivers by carrying out a global scale assessment (using data from 62 LMEs) over six decades (1950-2010). We confirm the consistency of the S-pattern across all the LMEs, independent from latitude, ecosystem, environmental conditions, and stress level. The dynamics of the curve shape showed a tendency to stretch (i.e. decrease of steepness), in the presence of external disturbance and conversely to increase in steepness and shift towards higher TL in the case of recovery from stressed conditions. Our results suggest the presence of three main types of ecosystem dynamics, those showing an almost continuous increase in ecological state over time, those showing a continuous decrease in ecological state over time, and finally those showing a mixed behaviour flipping between recovering and degrading phases. These robust patterns suggest that the CumB-TL curve approach has some useful properties for use in further advancing the implementation of the Ecosystem Approach, allowing us to detect the state of a given marine ecosystem based on the dynamics of its curve shape, by using readily available time series data. The value of being able to identify conditions that might require management actions is quite high and, in many respects, represents the main objective in the context of an Ecosystem Approach, with large applications for detecting and responding to global changes in marine ecosystems.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Reaney SM, Mackay EB, Haygarth PM, et al (2019)

Identifying critical source areas using multiple methods for effective diffuse pollution mitigation.

Journal of environmental management, 250:109366.

Diffuse pollution from agriculture constitutes a key pressure on the water quality of freshwaters and is frequently the cause of ecological degradation. The problem of diffuse pollution can be conceptualised with a source-mobilisation-pathway (or delivery)-impact model, whereby the combination of high source risk and strong connected pathways leads to 'critical source areas' (CSAs). These areas are where most diffuse pollution will originate, and hence are the optimal places to implement mitigation measures. However, identifying the locations of these areas is a key problem across different spatial scales within catchments. A number of approaches are frequently used for this assessment, although comparisons of these assessments are rarely carried out. We evaluate the CSAs identified via traditional walkover surveys supported by three different approaches, highlighting their benefits and disadvantages. These include a custom designed smartphone app; a desktop geographic information system (GIS) and terrain analysis-based SCIMAP (Sensitive Catchment Integrated Modelling and Analysis Platform) approach; and the use of a high spatial resolution drone dataset as an improved input data for SCIMAP modelling. Each of these methods captures the locations of the CSAs, revealing similarities and differences in the prioritisation of CSA features. The differences are due to the temporal and spatial resolution of the three methods such as the use of static land cover information, the ability to capture small scale features, such as gateways and the incomplete catchment coverage of the walkover survey. The relative costs and output resolutions of the three methods indicate that they are suitable for application at different catchment scales in conjunction with other methods. Based on the results in this paper, it is recommended that a multi-evidence-based approach to diffuse pollution management is taken across catchment spatial scales, incorporating local knowledge from the walkover with the different data resolutions of the SCIMAP approach.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Pereira-Flores E, Glöckner FO, A Fernandez-Guerra (2019)

Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data.

BMC bioinformatics, 20(1):453 pii:10.1186/s12859-019-3031-y.

BACKGROUND: Metagenomics caused a quantum leap in microbial ecology. However, the inherent size and complexity of metagenomic data limit its interpretation. The quantification of metagenomic traits in metagenomic analysis workflows has the potential to improve the exploitation of metagenomic data. Metagenomic traits are organisms' characteristics linked to their performance. They are measured at the genomic level taking a random sample of individuals in a community. As such, these traits provide valuable information to uncover microorganisms' ecological patterns. The Average Genome Size (AGS) and the 16S rRNA gene Average Copy Number (ACN) are two highly informative metagenomic traits that reflect microorganisms' ecological strategies as well as the environmental conditions they inhabit.

RESULTS: Here, we present the ags.sh and acn.sh tools, which analytically derive the AGS and ACN metagenomic traits. These tools represent an advance on previous approaches to compute the AGS and ACN traits. Benchmarking shows that ags.sh is up to 11 times faster than state-of-the-art tools dedicated to the estimation AGS. Both ags.sh and acn.sh show comparable or higher accuracy than existing tools used to estimate these traits. To exemplify the applicability of both tools, we analyzed the 139 prokaryotic metagenomes of TARA Oceans and revealed the ecological strategies associated with different water layers.

CONCLUSION: We took advantage of recent advances in gene annotation to develop the ags.sh and acn.sh tools to combine easy tool usage with fast and accurate performance. Our tools compute the AGS and ACN metagenomic traits on unassembled metagenomes and allow researchers to improve their metagenomic data analysis to gain deeper insights into microorganisms' ecology. The ags.sh and acn.sh tools are publicly available using Docker container technology at https://github.com/pereiramemo/AGS-and-ACN-tools .

RevDate: 2019-12-03
CmpDate: 2019-12-03

Giri S, Zhang Z, Krasnuk D, et al (2019)

Evaluating the impact of land uses on stream integrity using machine learning algorithms.

The Science of the total environment, 696:133858.

A general pattern of declining aquatic ecological integrity with increasing urban land use has been well established for a number of watersheds worldwide. A more nuanced characterization of the influence of different urban land uses and the determination of cumulative thresholds will further inform watershed planning and management. To this end, we investigated the utility of two machine learning algorithms (Random Forests (RF) and Boosted Regression Trees (BRT)) to model stream impairment through multimetric macroinvertebrate index known as High Gradient Macroinvertebrate Index (HGMI) in an urbanizing watershed located in north-central New Jersey, United States. These machine learning algorithms were able to explain at least 50% of the variability of stream integrity based on watershed land use/land cover. While comparable in results, RF was found to be easier to train and was somewhat more robust to model overfitting compared to BRT. Our results document the influence of increasing high-medium density (> 30% Impervious Surface cover (ISC)), low density (15-30% ISC) urban and transitional/barren land had in negatively affecting stream biological integrity. The thresholds generated by partial plots suggest that the stream integrity decreased abruptly when the percentage of high-medium and low density urban, and transitional/barren land went above 10%, 8%, and 2% of the watershed, respectively. Additionally, when rural residential surpassed 30% threshold, it behaved similar to low density urban towards stream integrity. Identification of such cumulative thresholds can help watershed managers and policymakers to craft land use zoning regulations and design restoration programs that are grounded by objective scientific criteria.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Miele V, Guill C, Ramos-Jiliberto R, et al (2019)

Non-trophic interactions strengthen the diversity-functioning relationship in an ecological bioenergetic network model.

PLoS computational biology, 15(8):e1007269 pii:PCOMPBIOL-D-18-02071.

Ecological communities are undeniably diverse, both in terms of the species that compose them as well as the type of interactions that link species to each other. Despite this long recognition of the coexistence of multiple interaction types in nature, little is known about the consequences of this diversity for community functioning. In the ongoing context of global change and increasing species extinction rates, it seems crucial to improve our understanding of the drivers of the relationship between species diversity and ecosystem functioning. Here, using a multispecies dynamical model of ecological communities including various interaction types (e.g. competition for space, predator interference, recruitment facilitation in addition to feeding), we studied the role of the presence and the intensity of these interactions for species diversity, community functioning (biomass and production) and the relationship between diversity and functioning.Taken jointly, the diverse interactions have significant effects on species diversity, whose amplitude and sign depend on the type of interactions involved and their relative abundance. They however consistently increase the slope of the relationship between diversity and functioning, suggesting that species losses might have stronger effects on community functioning than expected when ignoring the diversity of interaction types and focusing on feeding interactions only.

RevDate: 2020-01-19

Lemos LN, Medeiros JD, Dini-Andreote F, et al (2019)

Genomic signatures and co-occurrence patterns of the ultra-small Saccharimonadia (phylum CPR/Patescibacteria) suggest a symbiotic lifestyle.

Molecular ecology, 28(18):4259-4271.

The size of bacterial genomes is often associated with organismal metabolic capabilities determining ecological breadth and lifestyle. The recently proposed Candidate Phyla Radiation (CPR)/Patescibacteria encompasses mostly unculturable bacterial taxa with relatively small genome sizes with potential for co-metabolism interdependencies. As yet, little is known about the ecology and evolution of CPR, particularly with respect to how they might interact with other taxa. Here, we reconstructed two novel genomes (namely, Candidatus Saccharibacter sossegus and Candidatus Chaer renensis) of taxa belonging to the class Saccharimonadia within the CPR/Patescibacteria using metagenomes obtained from acid mine drainage (AMD). By testing the hypothesis of genome streamlining or symbiotic lifestyle, our results revealed clear signatures of gene losses in these genomes, such as those associated with de novo biosynthesis of essential amino acids, nucleotides, fatty acids and cofactors. In addition, co-occurrence analysis provided evidence supporting potential symbioses of these organisms with Hydrotalea sp. in the AMD system. Together, our findings provide a better understanding of the ecology and evolution of CPR/Patescibacteria and highlight the importance of genome reconstruction for studying metabolic interdependencies between unculturable Saccharimonadia representatives.

RevDate: 2019-09-03
CmpDate: 2019-09-03

Wang QL, Han YJ, Zhang LP, et al (2019)

[GIS-based ecological climate suitability regionalization for Cordyceps sinensis in Shiqu County, Sichuan Province, China.].

Ying yong sheng tai xue bao = The journal of applied ecology, 30(7):2137-2144.

Based on the biological characteristics of Cordyceps sinensis, combined with the spatial and temporal distribution characteristics of local agro-climatic resources and the investigation data of C. sinensis resources, we investigated the ecological climate suitability regionalization and the spatial distribution of C. sinensis in Shiqu County using mathematical statistics analysis, optimization method and GIS spatial analysis. We used altitude, mean annual temperature, mean annual precipitation, vegetation, and soil as the leading indicators and topographic gradient as the auxiliary indicators, as the main basis for the suitability zoning of C. sinensis resources. The results showed that C. sinensis grew in most of the townships in Shiqu County, with their distribution areas being fragmented and scattered, showing sporadic patches and blocks. They were mainly distributed in east and west parts of the county and in the Zhaqu River basin in the central part. The suitable distribution area for C. sinensis in Shiqu was 4000-4700 m above sea level, with mean annual temperature of -2.5-3 ℃ and mean annual precipitation of 550-850 mm. The growth environment was generally alpine mea-dow and subalpine meadow with good hydrophobicity and slope of 15°-50°. The suitable growth environment and meteorological conditions were beneficial to the growth and development of feeding plants and bat moths. The unsuitable area was in the high mountain area above the river wide valley area, pastoral area, wetland, or snowline.

RevDate: 2020-01-08
CmpDate: 2019-10-17

Liu Y, Schwalm CR, Samuels-Crow KE, et al (2019)

Ecological memory of daily carbon exchange across the globe and its importance in drylands.

Ecology letters, 22(11):1806-1816.

How do antecedent (past) conditions influence land-carbon dynamics after those conditions no longer persist? In particular, quantifying such memory effects associated with the influence of past environmental (exogenous) and biological (endogenous) conditions is crucial for understanding and predicting the carbon cycle. Here we show, using data from 42 eddy covariance sites across six major biomes, that ecological memory-decomposed into environmental and biological memory components-of daily net carbon exchange (NEE) is critical for understanding the land-carbon metabolism, especially in drylands for which memory explains ~ 32% of the variation in NEE. The strong environmental memory in drylands was primarily driven by short- and long-term moisture status. Moreover, the strength of environmental memory scales with increasing water stress. This universal scaling relationship, emerging within and among major biomes, suggests a potential adaptive response to water limitation. Our findings underscore the necessity of considering ecological memory in experiments, observations and modelling.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Saedpanah S, J Amanollahi (2019)

Environmental pollution and geo-ecological risk assessment of the Qhorveh mining area in western Iran.

Environmental pollution (Barking, Essex : 1987), 253:811-820.

In order to evaluate the effect of mining activity on the environment of the Qhorveh mining area in the west of Iran, the geological, ecological and environmental data, related to social development and regional economic status, were used. The geological data included seven sub-indices, such as vegetation coverage, land utilization type, and fault activity; ecological data, with two sub-indices, such as degree of ecological environment recovery; and finally, environmental data, with three sub-indices, such as soil and dust pollutions. These were selected based on the literature and expert opinion which were utilized for environmental pollution and geo-ecological (EPGE) risk assessment of the study site. Remote sensing (RS) image, field sampling, digital elevation map, and data retrieved from different government agencies were used to generate layers for the sub-indices in the geographic information system (GIS) environment. In addition, the analytical hierarchy process (AHP) method was used to determine the weight of sub-indices. Five levels consisting of best, good, middle, poor and worst were used to describe the EPGE risk assessment of the Qhorveh mining area. Results showed that worst and poor levels of EPGE risk are in the east and northeast of the study area where the gold and pumice mines are located while best and good levels of EPGE risk are in its center where the stone mines are located. According to the results of this research, the EPGE risk assessment of the Qhorveh mining area is affected by the environmental pollution index with its highest weight (0.3908). It can be concluded that the integration of the RS, GIS and AHP methods proposed in this study improved the evaluation quality of EPGE risk assessment.

RevDate: 2020-01-08
CmpDate: 2019-12-11

Fountain-Jones NM, Machado G, Carver S, et al (2019)

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure.

The Journal of animal ecology, 88(10):1447-1461.

Predicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data are available on a subset of individuals and nonlinear relationships between variables are common. Here we provide a guide to the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex nonlinear relationships with minimal statistical assumptions from ecological data with missing data. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus. Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualize strong nonlinear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years. When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure that are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.

RevDate: 2019-07-26

Flórián N, Ladányi M, Ittzés A, et al (2019)

Effects of single and repeated drought on soil microarthropods in a semi-arid ecosystem depend more on timing and duration than drought severity.

PloS one, 14(7):e0219975 pii:PONE-D-18-35187.

Soil moisture is one of the most important factors affecting soil biota. In arid and semi-arid ecosystems, soil mesofauna is adapted to temporary drought events, but, until now, we have had a limited understanding of the impacts of the different magnitudes and frequencies of drought predicted to occur according to future climate change scenarios. The present study focuses on how springtails and mites respond to simulated repeated drought events of different magnitudes in a field experiment in a Hungarian semi-arid sand steppe. Changes in soil arthropod activities were monitored with soil trapping over two years in a sandy soil. In the first year (2014), we applied an extreme drought pretreatment, and in the consecutive year, we applied less devastating treatments (severe drought, moderate drought, water addition) to these sites. In the first year, the extreme drought pretreatment tended to have a negative effect (either significantly or not significantly) on the capture of all Collembola groups, whereas all mite groups increased in activity density. However, in the consecutive year, between the extreme drought and control treatments, we only detected differences in soil microbial biomass. In the cases of severe drought, moderate drought and water addition, we did not find considerable changes across the microarthropods, except in the case of epedaphic Collembola. In the cases of the water addition and drought treatments, the duration and timing of the manipulation seemed to be more important for soil mesofauna than their severity (i.e., the level of soil moisture decrease). We suggest that in these extreme habitats, soil mesofauna are able to survive extreme conditions, and their populations recover rapidly, but they may not be able to cope with very long drought periods.

RevDate: 2019-11-22
CmpDate: 2019-11-21

di Porcia E Brugnera M, Meunier F, Longo M, et al (2019)

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests.

Global change biology, 25(11):3767-3780.

There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana-specific plant functional type and mechanisms representing liana-tree interactions (such as light competition, liana-specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta-analysis. We tested the model for an old-growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner-derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 tC ha-1 year-1 , which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above-ground biomass after 70 years of regrowth by up to 20 tC /ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old-growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana-rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.

RevDate: 2019-12-17
CmpDate: 2019-12-09

Meola M, Rifa E, Shani N, et al (2019)

DAIRYdb: a manually curated reference database for improved taxonomy annotation of 16S rRNA gene sequences from dairy products.

BMC genomics, 20(1):560 pii:10.1186/s12864-019-5914-8.

BACKGROUND: Reads assignment to taxonomic units is a key step in microbiome analysis pipelines. To date, accurate taxonomy annotation of 16S reads, particularly at species rank, is still challenging due to the short size of read sequences and differently curated classification databases. The close phylogenetic relationship between species encountered in dairy products, however, makes it crucial to annotate species accurately to achieve sufficient phylogenetic resolution for further downstream ecological studies or for food diagnostics. Curated databases dedicated to the environment of interest are expected to improve the accuracy and resolution of taxonomy annotation.

RESULTS: We provide a manually curated database composed of 10'290 full-length 16S rRNA gene sequences from prokaryotes tailored for dairy products analysis (https://github.com/marcomeola/DAIRYdb). The performance of the DAIRYdb was compared with the universal databases Silva, LTP, RDP and Greengenes. The DAIRYdb significantly outperformed all other databases independently of the classification algorithm by enabling higher accurate taxonomy annotation down to the species rank. The DAIRYdb accurately annotates over 90% of the sequences of either single or paired hypervariable regions automatically. The manually curated DAIRYdb strongly improves taxonomic annotation accuracy for microbiome studies in dairy environments. The DAIRYdb is a practical solution that enables automatization of this key step, thus facilitating the routine application of NGS microbiome analyses for microbial ecology studies and diagnostics in dairy products.

RevDate: 2020-01-20
CmpDate: 2020-01-20

Edwards RA, Vega AA, Norman HM, et al (2019)

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage.

Nature microbiology, 4(10):1727-1736.

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

RevDate: 2020-01-08
CmpDate: 2020-01-08

Watson AK, Lannes R, Pathmanathan JS, et al (2019)

The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution.

Methods in molecular biology (Clifton, N.J.), 1910:271-308.

In the post genomic era, large and complex molecular datasets from genome and metagenome sequencing projects expand the limits of what is possible for bioinformatic analyses. Network-based methods are increasingly used to complement phylogenetic analysis in studies in molecular evolution, including comparative genomics, classification, and ecological studies. Using network methods, the vertical and horizontal relationships between all genes or genomes, whether they are from cellular chromosomes or mobile genetic elements, can be explored in a single expandable graph. In recent years, development of new methods for the construction and analysis of networks has helped to broaden the availability of these approaches from programmers to a diversity of users. This chapter introduces the different kinds of networks based on sequence similarity that are already available to tackle a wide range of biological questions, including sequence similarity networks, gene-sharing networks and bipartite graphs, and a guide for their construction and analyses.

RevDate: 2019-10-24
CmpDate: 2019-08-30

Ha S, Z Yang (2019)

Evaluation for landscape aesthetic value of the Natural World Heritage Site.

Environmental monitoring and assessment, 191(8):483.

The landscape aesthetic value (LAV) is one essential component of outstanding universal value (OUV) for a Natural World Heritage Site (NWHS). In the identification of LAV, there is the subjectivity of methodology suggested by IUCN in the operation manual, and the expert-led evaluation is insufficient for reflecting all observers' opinions. This study focuses on establishing a universal system combining the subjectivity and objectivity, the experts' and the public's opinions to evaluate the LAV of an NWHS. We used the NWHS criteria, the ecological environment, and the viewing experience as established indicators; nine metrics were applied as corresponding layers respectively to map and give a final spatial evaluation based on the ArcGIS overlay analysis with their comprehensive weights from 3 groups of decision makers. In order to verify the rationality of our model, the LAV of a case study in Bayanbulak of NWHS Xinjiang Tianshan has been evaluated. It is demonstrated that central region of Bayanbulak with unique landscape that taking rivers, lakes, and swamps as base interlacing with wetland meadows has particularly high LAV; it basically shows a concentric circle-like distribution feature that LAV decreases from inside to outside and is consistent with practical protection status. This study responds to the UNESCO's request to monitor and evaluate the OUV of the NWHS; we believe results can provide a useful reference for the planning and decision-making of relevant scenic spots.

RevDate: 2019-12-19
CmpDate: 2019-12-19

Ruess J, Pleška M, Guet CC, et al (2019)

Molecular noise of innate immunity shapes bacteria-phage ecologies.

PLoS computational biology, 15(7):e1007168 pii:PCOMPBIOL-D-19-00148.

Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems.

RevDate: 2020-01-08

Pepin KM, Pedersen K, Wan XF, et al (2019)

Individual-Level Antibody Dynamics Reveal Potential Drivers of Influenza A Seasonality in Wild Pig Populations.

Integrative and comparative biology, 59(5):1231-1242.

Swine are important in the ecology of influenza A virus (IAV) globally. Understanding the ecological role of wild pigs in IAV ecology has been limited because surveillance in wild pigs is often for antibodies (serosurveillance) rather than IAVs, as in humans and domestic swine. As IAV antibodies can persist long after an infection, serosurveillance data are not necessarily indicative of current infection risk. However, antibody responses to IAV infections cause a predictable antibody response, thus time of infection can be inferred from antibody levels in serological samples, enabling identification of risk factors of infection at estimated times of infection. Recent work demonstrates that these quantitative antibody methods (QAMs) can accurately recover infection dates, even when individual-level variation in antibody curves is moderately high. Also, the methodology can be implemented in a survival analysis (SA) framework to reduce bias from opportunistic sampling. Here we integrated QAMs and SA and applied this novel QAM-SA framework to understand the dynamics of IAV infection risk in wild pigs seasonally and spatially, and identify risk factors. We used national-scale IAV serosurveillance data from 15 US states. We found that infection risk was highest during January-March (54% of 61 estimated peaks), with 24% of estimated peaks occurring from May to July, and some low-level of infection risk occurring year-round. Time-varying IAV infection risk in wild pigs was positively correlated with humidity and IAV infection trends in domestic swine and humans, and did not show wave-like spatial spread of infection among states, nor more similar levels of infection risk among states with more similar meteorological conditions. Effects of host sex on IAV infection risk in wild pigs were generally not significant. Because most of the variation in infection risk was explained by state-level factors or infection risk at long-distances, our results suggested that predicting IAV infection risk in wild pigs is complicated by local ecological factors and potentially long-distance translocation of infection. In addition to revealing factors of IAV infection risk in wild pigs, our framework is broadly applicable for quantifying risk factors of disease transmission using opportunistic serosurveillance sampling, a common methodology in wildlife disease surveillance. Future research on the factors that determine individual-level antibody kinetics will facilitate the design of serosurveillance systems that can extract more accurate estimates of time-varying disease risk from quantitative antibody data.

RevDate: 2019-12-02
CmpDate: 2019-12-02

Michalska-Smith MJ, S Allesina (2019)

Telling ecological networks apart by their structure: A computational challenge.

PLoS computational biology, 15(6):e1007076 pii:PCOMPBIOL-D-18-01703.

Ecologists have been compiling ecological networks for over a century, detailing the interactions between species in a variety of ecosystems. To this end, they have built networks for mutualistic (e.g., pollination, seed dispersal) as well as antagonistic (e.g., herbivory, parasitism) interactions. The type of interaction being represented is believed to be reflected in the structure of the network, which would differ substantially between mutualistic and antagonistic networks. Here, we put this notion to the test by attempting to determine the type of interaction represented in a network based solely on its structure. We find that, although it is easy to separate different kinds of nonecological networks, ecological networks display much structural variation, making it difficult to distinguish between mutualistic and antagonistic interactions. We therefore frame the problem as a challenge for the community of scientists interested in computational biology and machine learning. We discuss the features a good solution to this problem should possess and the obstacles that need to be overcome to achieve this goal.

RevDate: 2019-10-07
CmpDate: 2019-10-04

Bastille-Rousseau G, G Wittemyer (2019)

Leveraging multidimensional heterogeneity in resource selection to define movement tactics of animals.

Ecology letters, 22(9):1417-1427.

Increasing interest in the complexity, variation and drivers of movement-related behaviours promise new insight into fundamental components of ecology. Resolving the multidimensionality of spatially explicit behaviour remains a challenge for investigating tactics and their relation to niche construction, but high-resolution movement data are providing unprecedented understanding of the diversity of spatially explicit behaviours. We introduce a framework for investigating individual variation in movement-defined resource selection that integrates the behavioural and ecological niche concepts. We apply it to long-term tracking data of 115 African elephants (Loxodonta africana), illustrating how a behavioural hypervolume can be defined based on differences between individuals and their ecological settings, and applied to explore population heterogeneity. While normative movement behaviour is frequently used to characterise population behaviour, we demonstrate the value of leveraging heterogeneity in the behaviour to gain greater insight into population structure and the mechanisms driving space-use tactics.

RevDate: 2019-11-19
CmpDate: 2019-10-11

Norton BA, Bending GD, Clark R, et al (2019)

Urban meadows as an alternative to short mown grassland: effects of composition and height on biodiversity.

Ecological applications : a publication of the Ecological Society of America, 29(6):e01946.

There are increasing calls to provide greenspace in urban areas, yet the ecological quality, as well as quantity, of greenspace is important. Short mown grassland designed for recreational use is the dominant form of urban greenspace in temperate regions but requires considerable maintenance and typically provides limited habitat value for most taxa. Alternatives are increasingly proposed, but the biodiversity potential of these is not well understood. In a replicated experiment across six public urban greenspaces, we used nine different perennial meadow plantings to quantify the relative roles of floristic diversity and height of sown meadows on the richness and composition of three taxonomic groups: plants, invertebrates, and soil microbes. We found that all meadow treatments were colonized by plant species not sown in the plots, suggesting that establishing sown meadows does not preclude further locally determined grassland development if management is appropriate. Colonizing species were rarer in taller and more diverse plots, indicating competition may limit invasion rates. Urban meadow treatments contained invertebrate and microbial communities that differed from mown grassland. Invertebrate taxa responded to changes in both height and richness of meadow vegetation, but most orders were more abundant where vegetation height was longer than mown grassland. Order richness also increased in longer vegetation and Coleoptera family richness increased with plant diversity in summer. Microbial community composition seems sensitive to plant species composition at the soil surface (0-10 cm), but in deeper soils (11-20 cm) community variation was most responsive to plant height, with bacteria and fungi responding differently. In addition to improving local residents' site satisfaction, native perennial meadow plantings can produce biologically diverse grasslands that support richer and more abundant invertebrate communities, and restructured plant, invertebrate, and soil microbial communities compared with short mown grassland. Our results suggest that diversification of urban greenspace by planting urban meadows in place of some mown amenity grassland is likely to generate substantial biodiversity benefits, with a mosaic of meadow types likely to maximize such benefits.

RevDate: 2019-11-08
CmpDate: 2019-11-08

Boza G, Worsley SF, Yu DW, et al (2019)

Efficient assembly and long-term stability of defensive microbiomes via private resources and community bistability.

PLoS computational biology, 15(5):e1007109 pii:PCOMPBIOL-D-19-00034.

Understanding the mechanisms that promote the assembly and maintenance of host-beneficial microbiomes is an open problem. Empirical evidence supports the idea that animal and plant hosts can combine 'private resources' with the ecological phenomenon known as 'community bistability' to favour some microbial strains over others. We briefly review evidence showing that hosts can: (i) protect the growth of beneficial strains in an isolated habitat, (ii) use antibiotics to suppress non-beneficial, competitor strains, and (iii) provide resources that only beneficial strains are able to translate into an increased rate of growth, reproduction, or antibiotic production. We then demonstrate in a spatially explicit, individual-based model that these three mechanisms act similarly by selectively promoting the initial proliferation of preferred strains, that is, by acting as a private resource. The faster early growth of preferred strains, combined with the phenomenon of 'community bistability,' allows those strains to continue to dominate the microbiome even after the private resource is withdrawn or made public. This is because after a beneficial colony reaches a sufficiently large size, it can resist invasion by parasites without further private support from the host. We further explicitly model localized microbial interactions and diffusion dynamics, and we show that an intermediate level of antibiotic diffusion is the most efficient mechanism in promoting preferred strains and that there is a wide range of parameters under which hosts can promote the assembly of a self-sustaining defensive microbiome. This in turn supports the idea that hosts readily evolve to promote host-beneficial defensive microbiomes.

RevDate: 2019-11-20

Piross IS, Harnos A, L Rózsa (2019)

Rensch's rule in avian lice: contradictory allometric trends for sexual size dimorphism.

Scientific reports, 9(1):7908 pii:10.1038/s41598-019-44370-5.

Rensch's rule (RR) postulates that in comparisons across closely related species, male body size relative to female size increases with the average size of the species. This holds true in several vertebrate and also in certain free-living invertebrate taxa. Here, we document the validity of RR in avian lice using three families (Philopteridae, Menoponidae, and Ricinidae). Using published data on the body length of 989 louse species, subspecies, or distinct intraspecific lineages, we applied phylogenetic reduced major axis regression to analyse the body size of females vs. males while accounting for phylogenetic non-independence. Our results indicate that philopterid and menoponid lice follow RR, while ricinids exhibit the opposite pattern. In the case of philopterids and menoponids, we argue that larger-bodied bird species tend to host lice that are both larger in size and more abundant. Thus, sexual selection acting on males makes them relatively larger, and this is stronger than fecundity selection acting on females. Ricinids exhibit converse RR, likely because fecundity selection is stronger in their case.

RevDate: 2019-11-14
CmpDate: 2019-11-14

Blažek J, Zukal J, Bandouchova H, et al (2019)

Numerous cold arousals and rare arousal cascades as a hibernation strategy in European Myotis bats.

Journal of thermal biology, 82:150-156.

Hibernating bats optimise the duration of torpor bouts and arousals in relation to hibernaculum microclimatic conditions and fat reserves. Clustering has significant physiological and ecological benefits, promoting successful hibernation of individuals. Such aggregations may help maintain optimal temperatures, allowing better energy utilisation than in solitarily bats. However, aroused bats in a cluster could conceivably disturb those still hibernating, starting an energy-demanding arousal process. Our study was conducted over two winters in two different hibernacula (cave and mine) in the Czech Republic, where Greater mouse-eared bats (Myotis myotis) have previously been diagnosed with white-nose syndrome. In 118 arousal episodes we recorded 193 individual arousals in which a warming phase was observed, 135 (69.9%) being cold arousals, where bats ceased increasing their body temperatures at ≤ 10 °C. The remaining arousals were standard normothermic arousals, where body (fur) surface temperatures reached > 20 °C. Cold arousals occurred during the mid- and late hibernation periods, suggesting they were a response to disturbance by a neighbour in the same cluster. Arousal cascades, where bats aroused in series, were rare (12.7%) and reached a maximum in mid-January. Our data suggest that Myotis bats prolong their torpor bouts using numerous cold arousals but few arousal cascades. Upon arrival of a bat, the clustered bats show tolerance to disturbing by conspecifics.

RevDate: 2019-11-29
CmpDate: 2019-11-29

Liu YY, Jin WT, Wei XX, et al (2019)

Cryptic speciation in the Chinese white pine (Pinus armandii): Implications for the high species diversity of conifers in the Hengduan Mountains, a global biodiversity hotspot.

Molecular phylogenetics and evolution, 138:114-125.

Conifers are the largest and ecologically and economically most important component group of the gymnosperms. Despite their slow rate of molecular evolution, rapid and recent diversification was unexpectedly prevalent in this ancient group in the Hengduan Mountains, a world's biodiversity hotspot and gymnosperm diversity center in Southwest China. In this study, we investigated the underlying mechanisms and disentangled the interactions of geography and ecology in speciation and evolution in Pinus armandii, an important forest tree species endemic to China, by integrating analyses of population transcriptomics, population genetics and ecological niche modeling. Many lines of evidence suggest that cryptic speciation has occurred in P. armandii. During the process, geologically induced formation of Mount Gongga and other massive peaks might trigger the initial vicariance isolation of the northern and southern subdivisions, and ecologically based selection then reinforced their differentiation and local adaptation. Our ecological niche analysis and earlier reciprocal transplant experiments in P. armandii provided convincing evidences for the critical role of ecology in the process of speciation. These findings suggest that both geography and ecology contributed significantly to the abundance of very recent and rapid species divergences, which promoted the rising of the extremely high conifer diversity in the Hengduan Mountains.

RevDate: 2019-11-20

Warwick-Dugdale J, Solonenko N, Moore K, et al (2019)

Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche-defining genomic islands.

PeerJ, 7:e6800 pii:6800.

Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in host culturing and a lack of reference genomes and 'universal' gene markers to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution, but their assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the most abundant viruses on Earth. Such features also challenge assembly across genomic islands containing niche-defining genes that drive ecological speciation. These populations and features may be successfully captured by single-virus genomics and fosmid-based approaches, at least in abundant taxa, but at considerable cost and technical expertise. Here we established a low-cost, low-input, high throughput alternative sequencing and informatics workflow to improve viral metagenomic assemblies using short-read and long-read technology. The 'VirION' (Viral, long-read metagenomics via MinION sequencing) approach was first validated using mock communities where it was found to be as relatively quantitative as short-read methods and provided significant improvements in recovery of viral genomes. We then then applied VirION to the first metagenome from a natural viral community from the Western English Channel. In comparison to a short-read only approach, VirION: (i) increased number and completeness of assembled viral genomes; (ii) captured abundant, highly microdiverse virus populations, and (iii) captured more and longer genomic islands. Together, these findings suggest that VirION provides a high throughput and cost-effective alternative to fosmid and single-virus genomic approaches to more comprehensively explore viral communities in nature.

RevDate: 2019-11-20

Bátori Z, Vojtkó A, Maák IE, et al (2019)

Karst dolines provide diverse microhabitats for different functional groups in multiple phyla.

Scientific reports, 9(1):7176 pii:10.1038/s41598-019-43603-x.

Fine-scale topographic complexity creates important microclimates that can facilitate species to grow outside their main distributional range and increase biodiversity locally. Enclosed depressions in karst landscapes ('dolines') are topographically complex environments which produce microclimates that are drier and warmer (equator-facing slopes) and cooler and moister (pole-facing slopes and depression bottoms) than the surrounding climate. We show that the distribution patterns of functional groups for organisms in two different phyla, Arthropoda (ants) and Tracheophyta (vascular plants), mirror this variation of microclimate. We found that north-facing slopes and bottoms of solution dolines in northern Hungary provided key habitats for ant and plant species associated with cooler and/or moister conditions. Contrarily, south-facing slopes of dolines provided key habitats for species associated with warmer and/or drier conditions. Species occurring on the surrounding plateau were associated with intermediate conditions. We conclude that karst dolines provide a diversity of microclimatic habitats that may facilitate the persistence of taxa with diverse environmental preferences, indicating these dolines to be potential safe havens for multiple phyla under local and global climate oscillations.

RevDate: 2020-01-14
CmpDate: 2020-01-14

Hofman MPG, Hayward MW, Heim M, et al (2019)

Right on track? Performance of satellite telemetry in terrestrial wildlife research.

PloS one, 14(5):e0216223 pii:PONE-D-18-33139.

Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

RevDate: 2019-12-10
CmpDate: 2019-08-15

Švec P, Hönig V, Zubriková D, et al (2019)

The use of multi-criteria evaluation for the selection of study plots for monitoring of I. ricinus ticks - Example from Central Europe.

Ticks and tick-borne diseases, 10(4):905-910.

Research projects in the field of eco-epidemiology of tick-borne diseases often require extensive sampling of arthropod vectors in the field. The aim of our study was to use geographical information systems (GIS) to select appropriate sampling sites of Ixodes ricinus ticks in central European habitat for further ecological studies of vector-borne pathogens (tick-borne encephalitis virus and Borrelia burgdorferi sensu lato). The model area was the Czech-German borderland (the region of South Bohemia and two regions in Germany: the Upper Palatinate and Lower Bavaria) where numerous human tick-borne encephalitis cases are reported annually. We prepared the sampling site design as a multi-criteria evaluation (MCE) task. In the GIS environment, we conducted MCE with a set of environmental, socio-economic and epidemiological data (altitude, vegetation cover, number of tick-borne encephalitis cases recorded in the past, tourist activity). The MCE classified the surveyed area into two classes: suitable for tick collection and unsuitable for tick collection. Subsequently, 50 tick sampling sites were randomly selected in the suitable area: 30 in South Bohemia (Czech Republic) and 20 in the Upper Palatinate and Lower Bavaria regions (Bavaria, Germany). The sampling sites were identified and surveyed in the field. The presence of ticks was confirmed by flagging at each of the selected plots. The described MCE system represents a versatile tool for semi-randomized design of tick sampling sites for research projects in the field of tick-borne pathogen ecology as well as for tick-borne pathogen surveillance programs run by local health authorities.

RevDate: 2020-01-09
CmpDate: 2020-01-09

Niku J, Brooks W, Herliansyah R, et al (2019)

Efficient estimation of generalized linear latent variable models.

PloS one, 14(5):e0216129 pii:PONE-D-18-34077.

Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estimation algorithms based on a combination of either the Laplace approximation method or variational approximation method, and automatic optimization techniques implemented in R software. An extensive set of simulation studies is used to assess the performances of different methods, from which it is shown that the variational approximation method used in conjunction with automatic optimization offers a powerful tool for estimation.

RevDate: 2020-01-31

Gregory AC, Zayed AA, Conceição-Neto N, et al (2019)

Marine DNA Viral Macro- and Microdiversity from Pole to Pole.

Cell, 177(5):1109-1123.e14.

Microbes drive most ecosystems and are modulated by viruses that impact their lifespan, gene flow, and metabolic outputs. However, ecosystem-level impacts of viral community diversity remain difficult to assess due to classification issues and few reference genomes. Here, we establish an ∼12-fold expanded global ocean DNA virome dataset of 195,728 viral populations, now including the Arctic Ocean, and validate that these populations form discrete genotypic clusters. Meta-community analyses revealed five ecological zones throughout the global ocean, including two distinct Arctic regions. Across the zones, local and global patterns and drivers in viral community diversity were established for both macrodiversity (inter-population diversity) and microdiversity (intra-population genetic variation). These patterns sometimes, but not always, paralleled those from macro-organisms and revealed temperate and tropical surface waters and the Arctic as biodiversity hotspots and mechanistic hypotheses to explain them. Such further understanding of ocean viruses is critical for broader inclusion in ecosystem models.

RevDate: 2019-11-12
CmpDate: 2019-11-12

Park DS, Akuffo AA, Muench DE, et al (2019)

Clonal hematopoiesis of indeterminate potential and its impact on patient trajectories after stem cell transplantation.

PLoS computational biology, 15(4):e1006913 pii:PCOMPBIOL-D-18-00635.

Clonal hematopoiesis of indeterminate potential (CHIP) is a recently identified process where older patients accumulate distinct subclones defined by recurring somatic mutations in hematopoietic stem cells. CHIP's implications for stem cell transplantation have been harder to identify due to the high degree of mutational heterogeneity that is present within the genetically distinct subclones. In order to gain a better understanding of CHIP and the impact of clonal dynamics on transplantation outcomes, we created a mathematical model of clonal competition dynamics. Our analyses highlight the importance of understanding competition intensity between healthy and mutant clones. Importantly, we highlight the risk that CHIP poses in leading to dominance of precancerous mutant clones and the risk of donor derived leukemia. Furthermore, we estimate the degree of competition intensity and bone marrow niche decline in mice during aging by using our modeling framework. Together, our work highlights the importance of better characterizing the ecological and clonal composition in hematopoietic donor populations at the time of stem cell transplantation.

RevDate: 2019-05-14
CmpDate: 2019-05-14

Rund SSC, Braak K, Cator L, et al (2019)

MIReAD, a minimum information standard for reporting arthropod abundance data.

Scientific data, 6(1):40 pii:10.1038/s41597-019-0042-5.

Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit arthropod population time-series data are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Such data have been collected world-wide for over a century, but remain scattered and largely inaccessible. In particular, with the ever-present and growing threat of arthropod pests and vectors of infectious diseases, there are numerous historical and ongoing surveillance efforts, but the data are not reported in consistent formats and typically lack sufficient metadata to make reuse and re-analysis possible. Here, we present the first-ever minimum information standard for arthropod abundance, Minimum Information for Reusable Arthropod Abundance Data (MIReAD). Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re)usability from the "FAIR," (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests.

RevDate: 2019-11-20

Thomas HJD, Myers-Smith IH, Bjorkman AD, et al (2019)

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome.

Global ecology and biogeography : a journal of macroecology, 28(2):78-95.

Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.

Location: Tundra biome.

Time period: Data collected between 1964 and 2016.

Major taxa studied: 295 tundra vascular plant species.

Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits.

Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression.

Main conclusions: Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.

RevDate: 2019-12-10
CmpDate: 2019-05-28

Stone L, Simberloff D, Y Artzy-Randrup (2019)

Network motifs and their origins.

PLoS computational biology, 15(4):e1006749 pii:PCOMPBIOL-D-18-01805.

Modern network science is a new and exciting research field that has transformed the study of complex systems over the last 2 decades. Of particular interest is the identification of small "network motifs" that might be embedded in a larger network and that indicate the presence of evolutionary design principles or have an overly influential role on system-wide dynamics. Motifs are patterns of interconnections, or subgraphs, that appear in an observed network significantly more often than in compatible randomized networks. The concept of network motifs was introduced into Systems Biology by Milo, Alon and colleagues in 2002, quickly revolutionized the field, and it has had a huge impact in wider scientific domains ever since. Here, we argue that the same concept and tools for the detection of motifs were well known in the ecological literature decades into the last century, a fact that is generally not recognized. We review the early history of network motifs, their evolution in the mathematics literature, and their recent rediscoveries.

RevDate: 2019-08-01
CmpDate: 2019-08-01

Louro R, Santos-Silva C, T Nobre (2019)

What is in a name? Terfezia classification revisited.

Fungal biology, 123(4):267-273.

Desert truffles (mycorrhizal hypogeous Ascomycota) are found in arid and semi-arid areas of the globe and have great ecological and economic importance. Terfezia is undoubtedly the most diversified of all desert truffle genera, but its taxonomy is far from resolved. Specifically, the large number of newly described species plus the high intraspecific morphological variability observed within some Terfezia lineages as rendered the use of molecular techniques mandatory for specimen's discrimination. But the subsequent increasing amount of sequence data produced also a huge number of undescribed taxa that required determination. We compiled and used the public available ITS data on Terfezia spp. on the custom-curated UNITE database to reconstruct the genus phylogeny. We found at least 17 distinct lineages within the genus and successfully resolved some of the more pressing taxonomic issues, namely the T. leptoderma/olbiensis complex and some misapplied synonymy. Based on this resolved phylogeny, and motivated by the recent new described species, we proposed an identification key to Terfezia genus highlighting the importance of morphological and ecological characterization.

RevDate: 2019-12-17
CmpDate: 2019-12-12

Fletcher RJ, Hefley TJ, Robertson EP, et al (2019)

A practical guide for combining data to model species distributions.

Ecology, 100(6):e02710.

Understanding and accurately modeling species distributions lies at the heart of many problems in ecology, evolution, and conservation. Multiple sources of data are increasingly available for modeling species distributions, such as data from citizen science programs, atlases, museums, and planned surveys. Yet reliably combining data sources can be challenging because data sources can vary considerably in their design, gradients covered, and potential sampling biases. We review, synthesize, and illustrate recent developments in combining multiple sources of data for species distribution modeling. We identify five ways in which multiple sources of data are typically combined for modeling species distributions. These approaches vary in their ability to accommodate sampling design, bias, and uncertainty when quantifying environmental relationships in species distribution models. Many of the challenges for combining data are solved through the prudent use of integrated species distribution models: models that simultaneously combine different data sources on species locations to quantify environmental relationships for explaining species distribution. We illustrate these approaches using planned survey data on 24 species of birds coupled with opportunistically collected eBird data in the southeastern United States. This example illustrates some of the benefits of data integration, such as increased precision in environmental relationships, greater predictive accuracy, and accounting for sample bias. Yet it also illustrates challenges of combining data sources with vastly different sampling methodologies and amounts of data. We provide one solution to this challenge through the use of weighted joint likelihoods. Weighted joint likelihoods provide a means to emphasize data sources based on different criteria (e.g., sample size), and we find that weighting improves predictions for all species considered. We conclude by providing practical guidance on combining multiple sources of data for modeling species distributions.

RevDate: 2019-11-20

Stucky BJ, Balhoff JP, Barve N, et al (2019)

Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions.

Biodiversity data journal, 7:e33303 pii:33303.

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data.

RevDate: 2019-08-19
CmpDate: 2019-08-19

Peters MK, Hemp A, Appelhans T, et al (2019)

Climate-land-use interactions shape tropical mountain biodiversity and ecosystem functions.

Nature, 568(7750):88-92.

Agriculture and the exploitation of natural resources have transformed tropical mountain ecosystems across the world, and the consequences of these transformations for biodiversity and ecosystem functioning are largely unknown1-3. Conclusions that are derived from studies in non-mountainous areas are not suitable for predicting the effects of land-use changes on tropical mountains because the climatic environment rapidly changes with elevation, which may mitigate or amplify the effects of land use4,5. It is of key importance to understand how the interplay of climate and land use constrains biodiversity and ecosystem functions to determine the consequences of global change for mountain ecosystems. Here we show that the interacting effects of climate and land use reshape elevational trends in biodiversity and ecosystem functions on Africa's largest mountain, Mount Kilimanjaro (Tanzania). We find that increasing land-use intensity causes larger losses of plant and animal species richness in the arid lowlands than in humid submontane and montane zones. Increases in land-use intensity are associated with significant changes in the composition of plant, animal and microorganism communities; stronger modifications of plant and animal communities occur in arid and humid ecosystems, respectively. Temperature, precipitation and land use jointly modulate soil properties, nutrient turnover, greenhouse gas emissions, plant biomass and productivity, as well as animal interactions. Our data suggest that the response of ecosystem functions to land-use intensity depends strongly on climate; more-severe changes in ecosystem functioning occur in the arid lowlands and the cold montane zone. Interactions between climate and land use explained-on average-54% of the variation in species richness, species composition and ecosystem functions, whereas only 30% of variation was related to single drivers. Our study reveals that climate can modulate the effects of land use on biodiversity and ecosystem functioning, and points to a lowered resistance of ecosystems in climatically challenging environments to ongoing land-use changes in tropical mountainous regions.

RevDate: 2019-05-09
CmpDate: 2019-05-09

Szabó B, Lang Z, Bakonyi G, et al (2019)

Transgenerational and multigenerational stress gene responses to the insecticide etofenprox in Folsomia candida (Collembola).

Ecotoxicology and environmental safety, 175:181-191.

Insecticide exposure may cause both transgenerational and multigenerational effects on populations, but the molecular mechanisms of these changes remain largely unclear. Many studies have focused on either transgenerational or multigenerational mechanisms but did neglect the comparative aspects. This study assessed whether the pyrethroid insecticide etofenprox (formulation Trebon® 30 EC) shows transgenerational and/or multigenerational effects on the survival and reproduction of Folsomia candida (Collembola). The activation of stress-related genes was studied to detect whether etofenprox modifies the expression of reproduction-associated genes in trans- and multigenerational treatments. A laboratory study was carried out for three generations with five insecticide concentrations in LUFA 2.2 soil. In the transgenerational treatment, only the parent generation (P) was exposed, but the subsequent generations were not. In the multigenerational treatment, all three generations were exposed to the insecticide in the same manner. Multigenerational exposure resulted in reduced reproduction effects over generations, suggesting that F. candida is capable of acclimating to enhanced concentration levels of etofenprox during prolonged exposure over multiple generations. In the transgenerational treatment, the heat shock protein 70 was up-regulated and cytochrome oxidase 6N4v1 expression down-regulated in a dose-dependent manner in the F2 generation. This finding raises the possibility of the epigenetic inheritance of insecticide impacts on parents. Furthermore, CYP6N4v1 expression was oppositely regulated in the trans- and multigenerational treatments. Our results draw attention to the differences in molecular level responses of F. candida to trans- and multigenerational etofenprox exposure.

RevDate: 2019-07-10
CmpDate: 2019-07-10

Piao S, Liu Q, Chen A, et al (2019)

Plant phenology and global climate change: Current progresses and challenges.

Global change biology, 25(6):1922-1940.

Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground- and remote sensing- based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process-based phenology modeling, and on the scaling of phenology from species to landscape-level.

RevDate: 2019-12-17
CmpDate: 2019-12-09

Giezendanner J, Bertuzzo E, Pasetto D, et al (2019)

A minimalist model of extinction and range dynamics of virtual mountain species driven by warming temperatures.

PloS one, 14(3):e0213775 pii:PONE-D-18-21549.

A longstanding question in ecology concerns the prediction of the fate of mountain species under climate change, where climatic and geomorphic factors but also endogenous species characteristics are jointly expected to control species distributions. A significant step forward would single out reliably landscape effects, given their constraining role and relative ease of theoretical manipulation. Here, we address population dynamics in ecosystems where the substrates for ecological interactions are mountain landscapes subject to climate warming. We use a minimalist model of metapopulation dynamics based on virtual species (i.e. a suitable assemblage of focus species) where dispersal processes interact with the spatial structure of the landscape. Climate warming is subsumed by an upward shift of species habitat altering the metapopulation capacity of the landscape and hence species viability. We find that the landscape structure is a powerful determinant of species survival, owing to the specific role of the predictably evolving connectivity of the various habitats. Range shifts and lags in tracking suitable habitat experienced by virtual species under warming conditions are singled out in different landscapes. The range of parameters is identified for which these virtual species (characterized by comparable viability thus restricting their possible fitnesses and niche widths) prove unable to cope with environmental change. The statistics of the proportion of species bound to survive is identified for each landscape, providing the temporal evolution of species range shifts and the related expected occupation patterns. A baseline dynamic model for predicting species fates in evolving habitats is thus provided.

RevDate: 2019-04-09
CmpDate: 2019-04-09

George PBL, Lallias D, Creer S, et al (2019)

Divergent national-scale trends of microbial and animal biodiversity revealed across diverse temperate soil ecosystems.

Nature communications, 10(1):1107 pii:10.1038/s41467-019-09031-1.

Soil biota accounts for ~25% of global biodiversity and is vital to nutrient cycling and primary production. There is growing momentum to study total belowground biodiversity across large ecological scales to understand how habitat and soil properties shape belowground communities. Microbial and animal components of belowground communities follow divergent responses to soil properties and land use intensification; however, it is unclear whether this extends across heterogeneous ecosystems. Here, a national-scale metabarcoding analysis of 436 locations across 7 different temperate ecosystems shows that belowground animal and microbial (bacteria, archaea, fungi, and protists) richness follow divergent trends, whereas β-diversity does not. Animal richness is governed by intensive land use and unaffected by soil properties, while microbial richness was driven by environmental properties across land uses. Our findings demonstrate that established divergent patterns of belowground microbial and animal diversity are consistent across heterogeneous land uses and are detectable using a standardised metabarcoding approach.

RevDate: 2019-11-20

Sumsion GR, Bradshaw MS, Hill KT, et al (2019)

Remote sensing tree classification with a multilayer perceptron.

PeerJ, 7:e6101 pii:6101.

To accelerate scientific progress on remote tree classification-as well as biodiversity and ecology sampling-The National Institute of Science and Technology created a community-based competition where scientists were invited to contribute informatics methods for classifying tree species and genus using crown-level images of trees. We classified tree species and genus at the pixel level using hyperspectral and LiDAR observations. We compared three algorithms that have been implemented extensively across a broad range of research applications: support vector machines, random forests, and multilayer perceptron. At the pixel level, the multilayer perceptron algorithm classified species or genus with high accuracy (92.7% and 95.9%, respectively) on the training data and performed better than the other two algorithms (85.8-93.5%). This indicates promise for the use of the multilayer perceptron (MLP) algorithm for tree-species classification based on hyperspectral and LiDAR observations and coincides with a growing body of research in which neural network-based algorithms outperform other types of classification algorithm for machine vision. To aggregate patterns across the images, we used an ensemble approach that averages the pixel-level outputs of the MLP algorithm to classify species at the crown level. The average accuracy of these classifications on the test set was 68.8% for the nine species.

RevDate: 2019-06-13
CmpDate: 2019-06-10

Song W, Wemheuer B, Zhang S, et al (2019)

MetaCHIP: community-level horizontal gene transfer identification through the combination of best-match and phylogenetic approaches.

Microbiome, 7(1):36 pii:10.1186/s40168-019-0649-y.

BACKGROUND: Metagenomic datasets provide an opportunity to study horizontal gene transfer (HGT) on the level of a microbial community. However, current HGT detection methods cannot be applied to community-level datasets or require reference genomes. Here, we present MetaCHIP, a pipeline for reference-independent HGT identification at the community level.

RESULTS: Assessment of MetaCHIP's performance on simulated datasets revealed that it can predict HGTs with various degrees of genetic divergence from metagenomic datasets. The results also indicated that the detection of very recent gene transfers (i.e. those with low levels of genetic divergence) from metagenomics datasets is largely affected by the read assembly step. Comparison of MetaCHIP with a previous analysis on soil bacteria showed a high level of consistency for the prediction of recent HGTs and revealed a large number of additional non-recent gene transfers, which can provide new biological and ecological insight. Assessment of MetaCHIP's performance on real metagenomic datasets confirmed the role of HGT in the spread of genes related to antibiotic resistance in the human gut microbiome. Further testing also showed that functions related to energy production and conversion as well as carbohydrate transport and metabolism are frequently transferred among free-living microorganisms.

CONCLUSION: MetaCHIP provides an opportunity to study HGTs among members of a microbial community and therefore has several applications in the field of microbial ecology and evolution. MetaCHIP is implemented in Python and freely available at https://github.com/songweizhi/MetaCHIP .

RevDate: 2019-07-02
CmpDate: 2019-07-02

Wu Z, Lei S, He BJ, et al (2019)

Assessment of Landscape Ecological Health: A CaseStudy of a Mining City in a Semi-Arid Steppe.

International journal of environmental research and public health, 16(5): pii:ijerph16050752.

The ecological status of the semi-arid steppes in China is fragile. Under the long-term and high-intensity development of mining, the ecological integrity and biodiversity of steppe landscapes have been destroyed, causing soil pollution, grassland degradation, landscape function defect, and so on. Previous studies have mainly focused on ecosystem health assessment in mining areas. Landscape ecological health (LEH) pays more attention to the interactions between different ecosystems. Therefore, the ecological assessment of mining cities is more suitable on a landscape scale. Meanwhile, the existing LEH assessment index systems are not applicable in ecologically fragile areas with sparse population, underdeveloped economy, and in relatively small research areas. The purpose of this study was to construct a LEH assessment index system and evaluate the LEH of a mining city located in a semi-arid steppe. Xilinhot is a typical semi-arid steppe mining city in China. The contradictions between the human, land and ecological environment are serious. A new model Condition, Vigor, Organization, Resilience, and Ecosystem (CVORE) model was constructed that integrated five subsystems (services) from the perspectives of ecology, landscape ecology, mining science, and geography. This study used the CVORE model to systematically evaluate the LEH in Xilinhot city in terms of five LEH levels, including very healthy, healthy, sub-healthy, unhealthy and morbid landscape. Research results show that the areas of the very healthy, healthy, sub-healthy, unhealthy and morbid landscapes are 13.23, 736.35, 184.5, 66.76 and 20.63 km², respectively. The healthy landscapes area accounts for 72.08% and most grasslands are healthy. The sub-healthy landscapes are mainly located around areas with higher disturbances due to human activities. The morbid or unhealthy landscapes are concentrated in the mining areas. The proposed CVORE model can enrich the foundations for the quantitative assessment of Landscape Ecological Health of Mining Cities in Semi-arid Steppe (LEHMCSS). This study provided a new LEH assessment approach (CVORE model), which can support landscape ecological restoration, ecological environmental protection and urban planning of the semi-arid steppe mining cities.

RevDate: 2019-12-27
CmpDate: 2019-03-25

López-Pérez M, Jayakumar JM, Haro-Moreno JM, et al (2019)

Evolutionary Model of Cluster Divergence of the Emergent Marine Pathogen Vibrio vulnificus: From Genotype to Ecotype.

mBio, 10(1): pii:mBio.02852-18.

Vibrio vulnificus, an opportunistic pathogen, is the causative agent of a life-threatening septicemia and a rising problem for aquaculture worldwide. The genetic factors that differentiate its clinical and environmental strains remain enigmatic. Furthermore, clinical strains have emerged from every clade of V. vulnificus In this work, we investigated the underlying genomic properties and population dynamics of the V. vulnificus species from an evolutionary and ecological point of view. Genome comparisons and bioinformatic analyses of 113 V. vulnificus isolates indicate that the population of V. vulnificus is made up of four different clusters. We found evidence that recombination and gene flow between the two largest clusters (cluster 1 [C1] and C2) have drastically decreased to the point where they are diverging independently. Pangenome and phenotypic analyses showed two markedly different lifestyles for these two clusters, indicating commensal (C2) and bloomer (C1) ecotypes, with differences in carbohydrate utilization, defense systems, and chemotaxis, among other characteristics. Nonetheless, we identified frequent intra- and interspecies exchange of mobile genetic elements (e.g., antibiotic resistance plasmids, novel "chromids," or two different and concurrent type VI secretion systems) that provide high levels of genetic diversity in the population. Surprisingly, we identified strains from both clusters in the mucosa of aquaculture species, indicating that manmade niches are bringing strains from the two clusters together. We propose an evolutionary model of V. vulnificus that could be broadly applicable to other pathogenic vibrios and facultative bacterial pathogens to pursue strategies to prevent their infections and emergence.IMPORTANCEVibrio vulnificus is an emergent marine pathogen and is the cause of a deadly septicemia. However, the genetic factors that differentiate its clinical and environmental strains and its several biotypes remain mostly enigmatic. In this work, we investigated the underlying genomic properties and population dynamics of the V. vulnificus species to elucidate the traits that make these strains emerge as a human pathogen. The acquisition of different ecological determinants could have allowed the development of highly divergent clusters with different lifestyles within the same environment. However, we identified strains from both clusters in the mucosa of aquaculture species, indicating that manmade niches are bringing strains from the two clusters together, posing a potential risk of recombination and of emergence of novel variants. We propose a new evolutionary model that provides a perspective that could be broadly applicable to other pathogenic vibrios and facultative bacterial pathogens to pursue strategies to prevent their infections.

RevDate: 2019-10-11
CmpDate: 2019-10-11

Robinson KF, Fuller AK, Stedman RC, et al (2019)

Integration of social and ecological sciences for natural resource decision making: challenges and opportunities.

Environmental management, 63(5):565-573.

The last 25 years have witnessed growing recognition that natural resource management decisions depend as much on understanding humans and their social interactions as on understanding the interactions between non-human organisms and their environment. Decision science provides a framework for integrating ecological and social factors into a decision, but challenges to integration remain. The decision-analytic framework elicits values and preferences to help articulate objectives, and then evaluates the outcomes of alternative management actions to achieve these objectives. Integrating social science into these steps can be hindered by failing to include social scientists as more than stakeholder-process facilitators, assuming that specific decision-analytic skills are commonplace for social scientists, misperceptions of social data as inherently qualitative, timescale mismatches for iterating through decision analysis and collecting relevant social data, difficulties in predicting human behavior, and failures of institutions to recognize the importance of this integration. We engage these challenges, and suggest solutions to them, helping move forward the integration of social and biological/ecological knowledge and considerations in decision-making.

RevDate: 2019-10-08
CmpDate: 2019-03-13

Marsland R, Cui W, Goldford J, et al (2019)

Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities.

PLoS computational biology, 15(2):e1006793 pii:PCOMPBIOL-D-18-01910.

A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a "resource-limited" regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species' consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

RevDate: 2019-04-22
CmpDate: 2019-04-22

Reiczigel J, Marozzi M, Fábián I, et al (2019)

Biostatistics for Parasitologists - A Primer to Quantitative Parasitology.

Trends in parasitology, 35(4):277-281.

The aggregated distributions of host-parasite systems require several different infection parameters to characterize them. We advise readers how to choose infection indices with clear and distinct biological interpretations, and recommend statistical tests to compare them across samples. A user-friendly and free software is available online to overcome technical difficulties.

RevDate: 2019-08-23
CmpDate: 2019-08-23

Gill BA, Musili PM, Kurukura S, et al (2019)

Plant DNA-barcode library and community phylogeny for a semi-arid East African savanna.

Molecular ecology resources, 19(4):838-846.

Applications of DNA barcoding include identifying species, inferring ecological and evolutionary relationships between species, and DNA metabarcoding. These applications require reference libraries that are not yet available for many taxa and geographic regions. We collected, identified, and vouchered plant specimens from Mpala Research Center in Laikipia, Kenya, to develop an extensive DNA-barcode library for a savanna ecosystem in equatorial East Africa. We amassed up to five DNA barcode markers (rbcL, matK, trnL-F, trnH-psbA, and ITS) for 1,781 specimens representing up to 460 species (~92% of the known flora), increasing the number of plant DNA barcode records for Africa by ~9%. We evaluated the ability of these markers, singly and in combination, to delimit species by calculating intra- and interspecific genetic distances. We further estimated a plant community phylogeny and demonstrated its utility by testing if evolutionary relatedness could predict the tendency of members of the Mpala plant community to have or lack "barcode gaps", defined as disparities between the maximum intra- and minimum interspecific genetic distances. We found barcode gaps for 72%-89% of taxa depending on the marker or markers used. With the exception of the markers rbcL and ITS, we found that evolutionary relatedness was an important predictor of barcode-gap presence or absence for all of the markers in combination and for matK, trnL-F, and trnH-psbA individually. This plant DNA barcode library and community phylogeny will be a valuable resource for future investigations.

RevDate: 2019-11-04
CmpDate: 2019-11-04

Yenni GM, Christensen EM, Bledsoe EK, et al (2019)

Developing a modern data workflow for regularly updated data.

PLoS biology, 17(1):e3000125 pii:PBIOLOGY-D-18-00033.

Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline.

RevDate: 2019-03-26
CmpDate: 2019-03-26

Liu Z, Tai P, Li X, et al (2019)

Deriving site-specific water quality criteria for ammonia from national versus international toxicity data.

Ecotoxicology and environmental safety, 171:665-676.

A key question to be asked when developing regional water quality criteria with scarce toxicity data is whether such data need to be locally derived. To address this, ammonia toxicity data from local aquatic species in the Liao River were compared against data from species native and non-native to China, based on comparisons of the overall trends of species sensitivity distributions and derived water quality criteria. Liao River data were acquired by acute and chronic tests using five local freshwater invertebrate species, and then compiled alongside published data from Chinese national guidelines and international literature. Models of best fit using three species sensitivity distribution approaches (log-logistic, log-normal, and Burr III) did not vary markedly (r2 >0.9), and no specific model provided a best fit across all data sets. The comparisons of the overall trend of species sensitivity distribution curves showed no significant differences at either a national (Chinese native taxa tested in China versus non-native taxa) or regional level (Liao River taxa versus non-Liao River taxa). The comparisons also revealed that the inclusion or exclusions of different ecological groups had little influence on the overall trends of species sensitivity distributions. These findings suggested data on non-local and non-native species, and data from local species tested elsewhere, could be appropriate for guiding the derivation of ammonia water quality criteria for regions such as Liao River. However, caution is needed when using hazardous concentration 5% values in the development of site-specific water quality criteria for a river basin due to the considerable variation observed for ammonia (16.8-56.6 mg/L), although these differences were not statistically significant. Based on the toxicity test evaluation, a preliminary acute value of 10.0 mg/L and chronic value of 1.7 mg/L (at pH of 7.0 and 20 °C) are proposed as site-specific ammonia water quality criteria for the Liao River, China.

RevDate: 2020-01-16
CmpDate: 2019-02-19

Perkins DM, Perna A, Adrian R, et al (2019)

Energetic equivalence underpins the size structure of tree and phytoplankton communities.

Nature communications, 10(1):255 pii:10.1038/s41467-018-08039-3.

The size structure of autotroph communities - the relative abundance of small vs. large individuals - shapes the functioning of ecosystems. Whether common mechanisms underpin the size structure of unicellular and multicellular autotrophs is, however, unknown. Using a global data compilation, we show that individual body masses in tree and phytoplankton communities follow power-law distributions and that the average exponents of these individual size distributions (ISD) differ. Phytoplankton communities are characterized by an average ISD exponent consistent with three-quarter-power scaling of metabolism with body mass and equivalence in energy use among mass classes. Tree communities deviate from this pattern in a manner consistent with equivalence in energy use among diameter size classes. Our findings suggest that whilst universal metabolic constraints ultimately underlie the emergent size structure of autotroph communities, divergent aspects of body size (volumetric vs. linear dimensions) shape the ecological outcome of metabolic scaling in forest vs. pelagic ecosystems.

RevDate: 2019-10-22
CmpDate: 2019-10-21

Ožana S, Burda M, Hykel M, et al (2019)

Dragonfly Hunter CZ: Mobile application for biological species recognition in citizen science.

PloS one, 14(1):e0210370 pii:PONE-D-18-25631.

Citizen science and data collected from various volunteers have an interesting potential in aiding the understanding of many biological and ecological processes. We describe a mobile application that allows the public to map and report occurrences of the odonata species (dragonflies and damselflies) found in the Czech Republic. The application also helps in species classification based on observation details such as date, GPS coordinates, and the altitude, biotope, suborder, and colour. Dragonfly Hunter CZ is a free Android application built on the open-source framework NativeScript using the JavaScript programming language which is now fully available on Google Play. The server side is powered by Apache Server with PHP and MariaDB SQL database. A mobile application is a fast and accurate way to obtain data pertaining to the odonata species, which can be used after expert verification for ecological studies and conservation basis like Red Lists and policy instruments. We expect it to be effective in encouraging Citizen Science and in promoting the proactive reporting of odonates. It can also be extended to the reporting and monitoring of other plant and animal species.

RevDate: 2019-05-03
CmpDate: 2019-05-03

Shimamoto CY, Padial AA, da Rosa CM, et al (2018)

Restoration of ecosystem services in tropical forests: A global meta-analysis.

PloS one, 13(12):e0208523 pii:PONE-D-18-22344.

To reverse the effects of deforestation, tropical areas have expanded restoration efforts in recent years. As ecological restoration positively affects the structure and function of degraded ecosystems, understanding to what extent restoration recovers ecosystem services (ES) is an important step in directing large-scale restoration actions. We evaluated the effect of restoration in increasing the provision of ES in tropical forests. We performed a global meta-analysis of ecological indicators of the ES provided in restored areas, degraded areas and reference ecosystems. We tested for the effects of different restoration strategies, different types of degradation and for the effects of restoration over time. Overall, restoration actions contributed to a significant increase in levels of ecological indicators of ES (carbon pool, soil attributes and biodiversity protection) compared to disturbed areas. Among the restoration strategies, the natural regeneration was the most effective. Biodiversity protection and carbon recovered better than soil attributes. All other restoration strategies recovered ES to a substantially lesser degree, and reforestation with exotics decreased the ES of areas degraded by agriculture. In areas degraded by pasture, restoration was more effective in recovering the biodiversity protection, whereas in areas degraded by agriculture, the restoration recovered mainly the carbon pool. Our results show that by choosing the correct strategy, restoration can recover much of the ES lost by the degradation of tropical forests. These results should be considered for large-scale conservation and management efforts for this biome.

RevDate: 2019-04-03
CmpDate: 2019-04-03

Bochkareva OO, Moroz EV, Davydov II, et al (2018)

Genome rearrangements and selection in multi-chromosome bacteria Burkholderia spp.

BMC genomics, 19(1):965 pii:10.1186/s12864-018-5245-1.

BACKGROUND: The genus Burkholderia consists of species that occupy remarkably diverse ecological niches. Its best known members are important pathogens, B. mallei and B. pseudomallei, which cause glanders and melioidosis, respectively. Burkholderia genomes are unusual due to their multichromosomal organization, generally comprised of 2-3 chromosomes.

RESULTS: We performed integrated genomic analysis of 127 Burkholderia strains. The pan-genome is open with the saturation to be reached between 86,000 and 88,000 genes. The reconstructed rearrangements indicate a strong avoidance of intra-replichore inversions that is likely caused by selection against the transfer of large groups of genes between the leading and the lagging strands. Translocated genes also tend to retain their position in the leading or the lagging strand, and this selection is stronger for large syntenies. Integrated reconstruction of chromosome rearrangements in the context of strains phylogeny reveals parallel rearrangements that may indicate inversion-based phase variation and integration of new genomic islands. In particular, we detected parallel inversions in the second chromosomes of B. pseudomallei with breakpoints formed by genes encoding membrane components of multidrug resistance complex, that may be linked to a phase variation mechanism. Two genomic islands, spreading horizontally between chromosomes, were detected in the B. cepacia group.

CONCLUSIONS: This study demonstrates the power of integrated analysis of pan-genomes, chromosome rearrangements, and selection regimes. Non-random inversion patterns indicate selective pressure, inversions are particularly frequent in a recent pathogen B. mallei, and, together with periods of positive selection at other branches, may indicate adaptation to new niches. One such adaptation could be a possible phase variation mechanism in B. pseudomallei.

RevDate: 2019-02-26
CmpDate: 2019-02-26

Somveille M, Firth JA, Aplin LM, et al (2018)

Movement and conformity interact to establish local behavioural traditions in animal populations.

PLoS computational biology, 14(12):e1006647 pii:PCOMPBIOL-D-18-01098.

The social transmission of information is critical to the emergence of animal culture. Two processes are predicted to play key roles in how socially-transmitted information spreads in animal populations: the movement of individuals across the landscape and conformist social learning. We develop a model that, for the first time, explicitly integrates these processes to investigate their impacts on the spread of behavioural preferences. Our results reveal a strong interplay between movement and conformity in determining whether locally-variable traditions establish across a landscape or whether a single preference dominates the whole population. The model is able to replicate a real-world cultural diffusion experiment in great tits Parus major, but also allows for a range of predictions for the emergence of animal culture under various initial conditions, habitat structure and strength of conformist bias to be made. Integrating social behaviour with ecological variation will be important for understanding the stability and diversity of culture in animals.

RevDate: 2019-10-08
CmpDate: 2019-05-23

Strassburg BBN, Beyer HL, Crouzeilles R, et al (2019)

Strategic approaches to restoring ecosystems can triple conservation gains and halve costs.

Nature ecology & evolution, 3(1):62-70.

International commitments for ecosystem restoration add up to one-quarter of the world's arable land. Fulfilling them would ease global challenges such as climate change and biodiversity decline but could displace food production and impose financial costs on farmers. Here, we present a restoration prioritization approach capable of revealing these synergies and trade-offs, incorporating ecological and economic efficiencies of scale and modelling specific policy options. Using an actual large-scale restoration target of the Atlantic Forest hotspot, we show that our approach can deliver an eightfold increase in cost-effectiveness for biodiversity conservation compared with a baseline of non-systematic restoration. A compromise solution avoids 26% of the biome's current extinction debt of 2,864 plant and animal species (an increase of 257% compared with the baseline). Moreover, this solution sequesters 1 billion tonnes of CO2-equivalent (a 105% increase) while reducing costs by US$28 billion (a 57% decrease). Seizing similar opportunities elsewhere would offer substantial contributions to some of the greatest challenges for humankind.

RevDate: 2019-04-03
CmpDate: 2019-04-03

Haller BC, Galloway J, Kelleher J, et al (2019)

Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes.

Molecular ecology resources, 19(2):552-566.

There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual-based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree-sequence recording method (Kelleher, Thornton, Ashander, & Ralph, 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward-time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn-in to be constructed extremely efficiently after the fact, using "recapitation"; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a population's genealogy that can be analysed in Python using the msprime package. We have implemented the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary simulation software package) and extended it to allow the recording of non-neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modelling and exploration of evolutionary processes.

RevDate: 2019-05-08
CmpDate: 2019-05-08

Taff CC, Freeman-Gallant CR, Streby HM, et al (2018)

Geolocator deployment reduces return rate, alters selection, and impacts demography in a small songbird.

PloS one, 13(12):e0207783 pii:PONE-D-18-11589.

In the past few years, miniature light-level geolocators have been developed for tracking wild bird species that were previously too small to track during their full annual cycle. Geolocators offer an exciting opportunity to study the full annual cycle for many species. However, the potential detrimental effects of carrying geolocators are still poorly understood, especially for small-bodied birds. Here, we deployed light-level geolocators on common yellowthroat warblers (Geothlypis trichas). Over two years, we monitored return rates and neighborhood demography for 40 warblers carrying a geolocator and 20 reference birds that did not carry a geolocator. We compared the two groups with long-term data from 108 unmanipulated birds breeding at the same location in previous and subsequent years. Overall, we found that individuals carrying a geolocator were less likely to return to the study site in the following year (21% to 33% returned, depending on inclusion criteria) than either contemporaneous controls (55%) or long-term controls (55%). Among birds marked with geolocators, we also detected viability selection for greater wing length, whereas this pattern was not present in control birds. Finally, in each year after geolocator deployment, inexperienced breeders colonized vacant territories and this demographic effect persisted for two years after deployment. Sexual selection and ornamentation are strongly age-dependent in this system, and behavioral data collected after geolocator deployment is likely to differ systematically from natural conditions. Clearly geolocators will continue to be useful tools, but we suggest that future studies should carefully consider the potential for biased returns and the ecological validity of behavioral data collected from geolocator marked populations.

RevDate: 2019-11-20

Jenkins MF, White EP, AH Hurlbert (2018)

The proportion of core species in a community varies with spatial scale and environmental heterogeneity.

PeerJ, 6:e6019.

Ecological communities are composed of a combination of core species that maintain local viable populations and transient species that occur infrequently due to dispersal from surrounding regions. Preliminary work indicates that while core and transient species are both commonly observed in community surveys of a wide range of taxonomic groups, their relative prevalence varies substantially from one community to another depending upon the spatial scale at which the community was characterized and its environmental context. We used a geographically extensive dataset of 968 bird community time series to quantitatively describe how the proportion of core species in a community varies with spatial scale and environmental heterogeneity. We found that the proportion of core species in an assemblage increased with spatial scale in a positive decelerating fashion with a concomitant decrease in the proportion of transient species. Variation in the shape of this scaling relationship between sites was related to regional environmental heterogeneity, with lower proportions of core species at a given scale associated with high environmental heterogeneity. Understanding this influence of scale and environmental heterogeneity on the proportion of core species may help resolve discrepancies between studies of biotic interactions, resource availability, and mass effects conducted at different scales, because the importance of these and other ecological processes are expected to differ substantially between core and transient species.

RevDate: 2019-09-02
CmpDate: 2019-09-02

Taylor SD, Meiners JM, Riemer K, et al (2019)

Comparison of large-scale citizen science data and long-term study data for phenology modeling.

Ecology, 100(2):e02568.

Large-scale observational data from citizen science efforts are becoming increasingly common in ecology, and researchers often choose between these and data from intensive local-scale studies for their analyses. This choice has potential trade-offs related to spatial scale, observer variance, and interannual variability. Here we explored this issue with phenology by comparing models built using data from the large-scale, citizen science USA National Phenology Network (USA-NPN) effort with models built using data from more intensive studies at Long Term Ecological Research (LTER) sites. We built statistical and process based phenology models for species common to each data set. From these models, we compared parameter estimates, estimates of phenological events, and out-of-sample errors between models derived from both USA-NPN and LTER data. We found that model parameter estimates for the same species were most similar between the two data sets when using simple models, but parameter estimates varied widely as model complexity increased. Despite this, estimates for the date of phenological events and out-of-sample errors were similar, regardless of the model chosen. Predictions for USA-NPN data had the lowest error when using models built from the USA-NPN data, while LTER predictions were best made using LTER-derived models, confirming that models perform best when applied at the same scale they were built. This difference in the cross-scale model comparison is likely due to variation in phenological requirements within species. Models using the USA-NPN data set can integrate parameters over a large spatial scale while those using an LTER data set can only estimate parameters for a single location. Accordingly, the choice of data set depends on the research question. Inferences about species-specific phenological requirements are best made with LTER data, and if USA-NPN or similar data are all that is available, then analyses should be limited to simple models. Large-scale predictive modeling is best done with the larger-scale USA-NPN data, which has high spatial representation and a large regional species pool. LTER data sets, on the other hand, have high site fidelity and thus characterize inter-annual variability extremely well. Future research aimed at forecasting phenology events for particular species over larger scales should develop models that integrate the strengths of both data sets.

RevDate: 2019-11-16
CmpDate: 2018-12-19

Felipe-Lucia MR, Soliveres S, Penone C, et al (2018)

Multiple forest attributes underpin the supply of multiple ecosystem services.

Nature communications, 9(1):4839.

Trade-offs and synergies in the supply of forest ecosystem services are common but the drivers of these relationships are poorly understood. To guide management that seeks to promote multiple services, we investigated the relationships between 12 stand-level forest attributes, including structure, composition, heterogeneity and plant diversity, plus 4 environmental factors, and proxies for 14 ecosystem services in 150 temperate forest plots. Our results show that forest attributes are the best predictors of most ecosystem services and are also good predictors of several synergies and trade-offs between services. Environmental factors also play an important role, mostly in combination with forest attributes. Our study suggests that managing forests to increase structural heterogeneity, maintain large trees, and canopy gaps would promote the supply of multiple ecosystem services. These results highlight the potential for forest management to encourage multifunctional forests and suggest that a coordinated landscape-scale strategy could help to mitigate trade-offs in human-dominated landscapes.

RevDate: 2020-02-03
CmpDate: 2020-02-03

Portnoy GA, Relyea MR, Decker S, et al (2018)

Understanding Gender Differences in Resilience Among Veterans: Trauma History and Social Ecology.

Journal of traumatic stress, 31(6):845-855.

A social-ecological framework for resilience underscores the importance of conceptualizing individuals embedded within their context when evaluating a person's vulnerability and adaptation to stress. Despite a high level of trauma exposure, most veterans exhibit psychological resilience following a traumatic event. Interpersonal trauma is associated with poorer psychological outcomes than noninterpersonal trauma and is experienced more frequently across the lifespan by women as compared to men. In the present study, we examined gender differences in trauma exposure, resilience, and protective factors among veterans. Participants included 665 veterans who completed a baseline survey assessing traumatic events; 544 veterans (81.8%) completed a 1-year follow-up survey assessing resilience, combat exposure, deployment social support, deployment preparedness, and military sexual trauma (MST). Principal component analyses revealed the Traumatic Life Events Questionnaire categorized into four meaningful components: sexual abuse, interpersonal violence, stranger violence, and accidents/unexpected trauma. Women reported greater exposure to sexual abuse, d = 0.76; interpersonal violence, d = 0.31; and MST, Cramer's V = 0.54; men reported greater exposure to stranger violence, accidents/unexpected trauma, and combat exposure, ds = 0.24-0.55. Compared to women, men also reported greater social support during deployment, d = 0.46. Hierarchical linear regression indicated that men's resilience scores were higher than women's, β = .10, p = .032, yet this association was no longer significant once we accounted for trauma type, β = .07, p = .197. Results indicate that trauma type is central to resilience and suggest one must consider the social-ecological context that can promote or inhibit resilient processes.

RevDate: 2019-08-27
CmpDate: 2019-08-27

Lozano-Jaramillo M, Bastiaansen JWM, Dessie T, et al (2019)

Use of geographic information system tools to predict animal breed suitability for different agro-ecological zones.

Animal : an international journal of animal bioscience, 13(7):1536-1543.

Predicting breed-specific environmental suitability has been problematic in livestock production. Native breeds have low productivity but are thought to be more robust to perform under local conditions than exotic breeds. Attempts to introduce genetically improved exotic breeds are generally unsuccessful, mainly due to the antagonistic environmental conditions. Knowledge of the environmental conditions that are shaping the breed would be needed to determine its suitability to different locations. Here, we present a methodology to predict the suitability of breeds for different agro-ecological zones using Geographic Information Systems tools and predictive habitat distribution models. This methodology was tested on the current distribution of two introduced chicken breeds in Ethiopia: the Koekoek, originally from South Africa, and the Fayoumi, originally from Egypt. Cross-validation results show this methodology to be effective in predicting breed suitability for specific environmental conditions. Furthermore, the model predicts suitable areas of the country where the breeds could be introduced. The specific climatic parameters that explained the potential distribution of each of the breeds were similar to the environment from which the breeds originated. This novel methodology finds application in livestock programs, allowing for a more informed decision when designing breeding programs and introduction programs, and increases our understanding of the role of the environment in livestock productivity.

RevDate: 2019-11-20

Mazel F, Davis KM, Loudon A, et al (2018)

Is Host Filtering the Main Driver of Phylosymbiosis across the Tree of Life?.

mSystems, 3(5):.

Host-associated microbiota composition can be conserved over evolutionary time scales. Indeed, closely related species often host similar microbiota; i.e., the composition of their microbiota harbors a phylogenetic signal, a pattern sometimes referred to as "phylosymbiosis." Elucidating the origins of this pattern is important to better understand microbiota ecology and evolution. However, this is hampered by our lack of theoretical expectations and a comprehensive overview of phylosymbiosis prevalence in nature. Here, we use simulations to provide a simple expectation for when we should expect this pattern to occur and then review the literature to document the prevalence and strength of phylosymbiosis across the host tree of life. We demonstrate that phylosymbiosis can readily emerge from a simple ecological filtering process, whereby a given host trait (e.g., gut pH) that varies with host phylogeny (i.e., harbors a phylogenetic signal) filters preadapted microbes. We found marked differences between methods used to detect phylosymbiosis, so we proposed a series of practical recommendations based on using multiple best-performing approaches. Importantly, we found that, while the prevalence of phylosymbiosis is mixed in nature, it appears to be stronger for microbiotas living in internal host compartments (e.g., the gut) than those living in external compartments (e.g., the rhizosphere). We show that phylosymbiosis can theoretically emerge without any intimate, long-term coevolutionary mechanisms and that most phylosymbiosis patterns observed in nature are compatible with a simple ecological process. Deviations from baseline ecological expectations might be used to further explore more complex hypotheses, such as codiversification. IMPORTANCE Phylosymbiosis is a pattern defined as the tendency of closely related species to host microbiota whose compositions resemble each other more than host species drawn at random from the same tree. Understanding the mechanisms behind phylosymbiosis is important because it can shed light on rules governing the assembly of host-associated microbiotas and, potentially, their coevolutionary dynamics with hosts. For example, is phylosymbiosis a result of coevolution, or can it be generated by simple ecological filtering processes? Beyond qualitative theoretical models, quantitative theoretical expectations can provide new insights. For example, deviations from a simple baseline of ecological filtering may be used to test more-complex hypotheses (e.g., coevolution). Here, we use simulations to provide evidence that simple host-related ecological filtering can readily generate phylosymbiosis, and we contrast these predictions with real-world data. We find that while phylosymbiosis is widespread in nature, phylosymbiosis patterns are compatible with a simple ecological model in the majority of taxa. Internal compartments of hosts, such as the animal gut, often display stronger phylosymbiosis than expected from a purely ecological filtering process, suggesting that other mechanisms are also involved.

RevDate: 2019-01-20
CmpDate: 2019-01-18

Sánchez-Giraldo C, JM Daza (2019)

Getting better temporal and spatial ecology data for threatened species: using lightweight GPS devices for small primate monitoring in the northern Andes of Colombia.

Primates; journal of primatology, 60(1):93-102.

The use of GPS telemetry has been a reliable research tool for the study of primate biology in recent years. Although in the past technological restrictions limited its use mainly to large primates, recent improvements in battery size make it possible to use this technology for small species. We used GPS devices for monitoring two adult white-footed tamarins (Saguinus leucopus) from a free-ranging group, and assessed its applicability for recording spatial and ecological data. GPS devices were operational for 66 and 85 days, recording 221 positions (36.6% acquisition rate; 73% of which were highly accurate) and 3195 activity values for both individuals. Depending on the estimation method, we calculated the home range size for the group to be 19.4 and 22.9 ha, which were within the range for the species in other localities. The animals were active each day for 11 h, with high activity during the early morning. The monkeys showed a constant and alternate use of four sleeping sites with a limited reuse of the same site on consecutive nights. These daily activity and sleeping site use patterns are similar to those reported for other Saguinus species. Based on the kind and quality of the data recorded, we consider GPS telemetry to be an efficient and advantageous method for tracking and obtaining ecological information from S. leucopus. In comparison to other data collection methods, GPS telemetry required fewer personnel and less time commitment to record data without compromising the accuracy of the spatial and activity information we obtained.

RevDate: 2019-04-26
CmpDate: 2019-02-27

Trotter RT, Lininger MR, Camplain R, et al (2018)

A Survey of Health Disparities, Social Determinants of Health, and Converging Morbidities in a County Jail: A Cultural-Ecological Assessment of Health Conditions in Jail Populations.

International journal of environmental research and public health, 15(11):.

The environmental health status of jail populations in the United States constitutes a significant public health threat for prisoners and the general population. The ecology of jails creates a dynamic condition in relation to general population health due to the concentrated potential exposure to infectious diseases, difficult access to treatment for chronic health conditions, interruption in continuity of care for serious behavioral health conditions, as well as on-going issues for the prevention and treatment of substance abuse disorders. This paper reports on elements of a cross-sectional survey embedded in a parent project, "Health Disparities in Jail Populations." The overall project includes a comprehensive secondary data analysis of the health status of county jail populations, along with primary data collection that includes a cross-sectional health and health care services survey of incarcerated individuals, coupled with collection of biological samples to investigate infectious disease characteristics of a county jail population. This paper reports on the primary results of the survey data collection that indicate that this is a population with complex and interacting co-morbidities, as well as significant health disparities compared to the general population.

RevDate: 2018-11-27
CmpDate: 2018-11-27

Munos MK, Maiga A, Do M, et al (2018)

Linking household survey and health facility data for effective coverage measures: a comparison of ecological and individual linking methods using the Multiple Indicator Cluster Survey in Côte d'Ivoire.

Journal of global health, 8(2):020803.

Background: Population-based measures of intervention coverage are used in low- and middle-income countries for program planning, prioritization, and evaluation. There is increased interest in effective coverage, which integrates information about service quality or health outcomes. Approaches proposed for quality-adjusted effective coverage include linking data on need and service contact from population-based surveys with data on service quality from health facility surveys. However, there is limited evidence about the validity of different linking methods for effective coverage estimation.

Methods: We collaborated with the 2016 Côte d'Ivoire Multiple Indicator Cluster Survey (MICS) to link data from a health provider assessment to care-seeking data collected by the MICS in the Savanes region of Côte d'Ivoire. The provider assessment was conducted in a census of public and non-public health facilities and pharmacies in Savanes in May-June 2016. We also included community health workers managing sick children who served the clusters sampled for the MICS. The provider assessment collected information on structural and process quality for antenatal care, delivery and immediate newborn care, postnatal care, and sick child care. We linked the MICS and provider data using exact-match and ecological linking methods, including aggregate linking and geolinking methods. We compared the results obtained from exact-match and ecological methods.

Results: We linked 731 of 786 care-seeking episodes (93%) from the MICS to a structural quality score for the provider named by the respondent. Effective coverage estimates computed using exact-match methods were 13%-63% lower than the care-seeking estimates from the MICS. Absolute differences between exact match and ecological linking methods were ±7 percentage points for all ecological methods. Incorporating adjustments for provider category and weighting by service-specific utilization into the ecological methods generally resulted in better agreement between ecological and exact match estimates.

Conclusions: Ecological linking may be a feasible and valid approach for estimating quality-adjusted effective coverage when a census of providers is used. Adjusting for provider type and caseload may improve agreement with exact match results. There remain methodological questions to be addressed to develop guidance on using linking methods for estimating quality-adjusted effective coverage, including the effect of facility sampling and time displacement.

RevDate: 2019-05-08
CmpDate: 2019-05-08

Kubelka V, Šálek M, Tomkovich P, et al (2018)

Global pattern of nest predation is disrupted by climate change in shorebirds.

Science (New York, N.Y.), 362(6415):680-683.

Ongoing climate change is thought to disrupt trophic relationships, with consequences for complex interspecific interactions, yet the effects of climate change on species interactions are poorly understood, and such effects have not been documented at a global scale. Using a single database of 38,191 nests from 237 populations, we found that shorebirds have experienced a worldwide increase in nest predation over the past 70 years. Historically, there existed a latitudinal gradient in nest predation, with the highest rates in the tropics; however, this pattern has been recently reversed in the Northern Hemisphere, most notably in the Arctic. This increased nest predation is consistent with climate-induced shifts in predator-prey relationships.

RevDate: 2018-12-12
CmpDate: 2018-12-12

Bamisile BS, Dash CK, Akutse KS, et al (2018)

Prospects of endophytic fungal entomopathogens as biocontrol and plant growth promoting agents: An insight on how artificial inoculation methods affect endophytic colonization of host plants.

Microbiological research, 217:34-50.

Entomopathogenic fungi (EPF) can be established as endophytes in the host plants to offer a long-term preventive measure for pests and diseases. This practice serves as a better alternative to the common practice of periodic direct application of EPF on plants or the target pests as a short-term defense strategy against pests and diseases. These fungal endophytes, aside from their role in pests and diseases prevention, also act as plant growth promoters. Several fungal endophytes have been associated with improvement in plant height, dry and wet weight and other growth parameters. However, many limiting factors have been identified as mitigating the successful colonization of the host plants by EPF. The inoculation methods used have been identified as one, but sadly, this has received little or less attention. Some previous studies carried out comparison between various artificial inoculation methods; foliar application, seedling dipping, soil drenching, seed inoculation, direct injection and others. In separate studies, some authors had suggested different application methods that are best suitable for certain fungal entomopathogens. For instance, leaf inoculation with conidial suspensions was suggested to be the best inoculation method for Beauveria bassiana in sorghum, stem injection was suggested as the most suitable for coffee, while, root dipping method proved the most successful for B. bassiana colonization of tomato plants for the management of Helicoverpa armigera. Here, we discussed entomopathogenic fungal endophytes as bio-control agents, plant growth promoters and highlighted the effect of various artificial inoculation methods on their endophytic colonization of the host plants.

RevDate: 2018-12-17
CmpDate: 2018-12-11

Meng X, Wang F, Xie Y, et al (2018)

An Ontology-Driven Approach for Integrating Intelligence to Manage Human and Ecological Health Risks in the Geospatial Sensor Web.

Sensors (Basel, Switzerland), 18(11):.

Due to the rapid installation of a massive number of fixed and mobile sensors, monitoring machines are intentionally or unintentionally involved in the production of a large amount of geospatial data. Environmental sensors and related software applications are rapidly altering human lifestyles and even impacting ecological and human health. However, there are rarely specific geospatial sensor web (GSW) applications for certain ecological public health questions. In this paper, we propose an ontology-driven approach for integrating intelligence to manage human and ecological health risks in the GSW. We design a Human and Ecological health Risks Ontology (HERO) based on a semantic sensor network ontology template. We also illustrate a web-based prototype, the Human and Ecological Health Risk Management System (HaEHMS), which helps health experts and decision makers to estimate human and ecological health risks. We demonstrate this intelligent system through a case study of automatic prediction of air quality and related health risk.

RevDate: 2019-11-12
CmpDate: 2019-10-25

Gopalakrishnan S, Sinding MS, Ramos-Madrigal J, et al (2018)

Interspecific Gene Flow Shaped the Evolution of the Genus Canis.

Current biology : CB, 28(21):3441-3449.e5.

The evolutionary history of the wolf-like canids of the genus Canis has been heavily debated, especially regarding the number of distinct species and their relationships at the population and species level [1-6]. We assembled a dataset of 48 resequenced genomes spanning all members of the genus Canis except the black-backed and side-striped jackals, encompassing the global diversity of seven extant canid lineages. This includes eight new genomes, including the first resequenced Ethiopian wolf (Canis simensis), one dhole (Cuon alpinus), two East African hunting dogs (Lycaon pictus), two Eurasian golden jackals (Canis aureus), and two Middle Eastern gray wolves (Canis lupus). The relationships between the Ethiopian wolf, African golden wolf, and golden jackal were resolved. We highlight the role of interspecific hybridization in the evolution of this charismatic group. Specifically, we find gene flow between the ancestors of the dhole and African hunting dog and admixture between the gray wolf, coyote (Canis latrans), golden jackal, and African golden wolf. Additionally, we report gene flow from gray and Ethiopian wolves to the African golden wolf, suggesting that the African golden wolf originated through hybridization between these species. Finally, we hypothesize that coyotes and gray wolves carry genetic material derived from a "ghost" basal canid lineage.


RJR Experience and Expertise


Robbins holds BS, MS, and PhD degrees in the life sciences. He served as a tenured faculty member in the Zoology and Biological Science departments at Michigan State University. He is currently exploring the intersection between genomics, microbial ecology, and biodiversity — an area that promises to transform our understanding of the biosphere.


Robbins has extensive experience in college-level education: At MSU he taught introductory biology, genetics, and population genetics. At JHU, he was an instructor for a special course on biological database design. At FHCRC, he team-taught a graduate-level course on the history of genetics. At Bellevue College he taught medical informatics.


Robbins has been involved in science administration at both the federal and the institutional levels. At NSF he was a program officer for database activities in the life sciences, at DOE he was a program officer for information infrastructure in the human genome project. At the Fred Hutchinson Cancer Research Center, he served as a vice president for fifteen years.


Robbins has been involved with information technology since writing his first Fortran program as a college student. At NSF he was the first program officer for database activities in the life sciences. At JHU he held an appointment in the CS department and served as director of the informatics core for the Genome Data Base. At the FHCRC he was VP for Information Technology.


While still at Michigan State, Robbins started his first publishing venture, founding a small company that addressed the short-run publishing needs of instructors in very large undergraduate classes. For more than 20 years, Robbins has been operating The Electronic Scholarly Publishing Project, a web site dedicated to the digital publishing of critical works in science, especially classical genetics.


Robbins is well-known for his speaking abilities and is often called upon to provide keynote or plenary addresses at international meetings. For example, in July, 2012, he gave a well-received keynote address at the Global Biodiversity Informatics Congress, sponsored by GBIF and held in Copenhagen. The slides from that talk can be seen HERE.


Robbins is a skilled meeting facilitator. He prefers a participatory approach, with part of the meeting involving dynamic breakout groups, created by the participants in real time: (1) individuals propose breakout groups; (2) everyone signs up for one (or more) groups; (3) the groups with the most interested parties then meet, with reports from each group presented and discussed in a subsequent plenary session.


Robbins has been engaged with photography and design since the 1960s, when he worked for a professional photography laboratory. He now prefers digital photography and tools for their precision and reproducibility. He designed his first web site more than 20 years ago and he personally designed and implemented this web site. He engages in graphic design as a hobby.

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This is a must read book for anyone with an interest in invasion biology. The full title of the book lays out the author's premise — The New Wild: Why Invasive Species Will Be Nature's Salvation. Not only is species movement not bad for ecosystems, it is the way that ecosystems respond to perturbation — it is the way ecosystems heal. Even if you are one of those who is absolutely convinced that invasive species are actually "a blight, pollution, an epidemic, or a cancer on nature", you should read this book to clarify your own thinking. True scientific understanding never comes from just interacting with those with whom you already agree. R. Robbins

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Collection of publications by R J Robbins

Reprints and preprints of publications, slide presentations, instructional materials, and data compilations written or prepared by Robert Robbins. Most papers deal with computational biology, genome informatics, using information technology to support biomedical research, and related matters.

Research Gate page for R J Robbins

ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. According to a study by Nature and an article in Times Higher Education , it is the largest academic social network in terms of active users.

Curriculum Vitae for R J Robbins

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Curriculum Vitae for R J Robbins

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