Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 84,134 bioRxiv papers from 362,280 authors.
Most downloaded bioRxiv papers, all time
in category ecology
3,598 results found. For more information, click each entry to expand.
1,970 downloads ecology
Philipp Lehmann, Tea Ammunét, Madeleine Barton, Andrea Battisti, Sanford D. Eigenbrode, Jane Uhd Jepsen, Gregor Kalinkat, Seppo Neuvonen, Pekka Niemelä, Bjørn Økland, John S. Terblanche, Christer Björkman
Phytophagous insect pests strongly affect the productivity and profitability of agriculture and forestry. Despite the well-known sensitivity of insects to abiotic effects such as temperature, their potential responses to ongoing climate change remain unclear. Here we compile and review documented climate change responses of 31 of the globally most severe insect pests of agriculture and forestry, focussing on species for which long-term, high-quality data are available. Most of the selected species show at least one response affecting their severity as pests, including changes in geographic range, population dynamics, life-history traits, and/or trophic interactions. The agricultural pests show strikingly more diverse and generally weaker responses to climate change than the forestry pests. However, the agricultural pests seem to increase more in detrimental ecological impact than do the forestry pests. Unexpectedly, 59% of the species show responses of reduced potential impacts as pests under ongoing climate change. This reduction in impact is further supported by a thermal sensitivity analysis showing little benefit of climate warming in relation to the optimal developmental temperatures for the majority of these pests under both current climate and future projections. The documented variation in responses indicates that efforts to mitigate undesirable climate change effects must target individual species, taking into account the complex ecological and evolutionary mechanisms underlying their responses.
1,968 downloads ecology
Long distance migrations are well known to occur in many baleen whale species. Yet, a global synthesis of this information is lacking. Here, we study baleen whales as a group and at a global scale, first analyzing the grey and peer-reviewed literature for information on the location of baleen whale calving and feeding grounds around the world. This information was then combined with modeled-data produced from an Earth System Model to estimate the global distribution of baleen whale calving and feeding habitats. A simple network theoretic heuristic was then used to identify the shortest over-water path connecting habitats. These shortest paths map well to known major migration routes for a number of species, suggesting that migration has evolved primarily to minimize travel distances. Identifying distance minimizing routes globally, that have demonstrable consistency to known migration routes for certain baleen whale species, offers a useful baseline perspective on large-scale migration patterns, from which many perturbations can by judged. As an example, we used our modeled migration routes to identify regions of the ocean that are likely hotspots of whale ship-strikes. Such information is useful for developing global conservation and management priorities for baleen whales.
1,966 downloads ecology
Erin A. Mordecai, Jeremy M. Cohen, Michelle V. Evans, Prithvi Gudapati, Leah R. Johnson, Catherine A. Lippi, Kerri Miazgowicz, Courtney C Murdock, Jason R. Rohr, Sadie J. Ryan, Van Savage, Marta S. Shocket, Anna Stewart Ibarra, Matthew B Thomas, Daniel P Weikel
Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.
1,964 downloads ecology
A diagnosis of heavy metal poisoning in sheep living on pasture in the vicinity of a zinc smelter was made based on laboratory tests and clinical signs in livestock in the Wumeng mountain area of China. Heavy metal contamination has generated serious harm to the health of local farmers after passing through the food chain. The levels of copper, zinc, cadmium, and lead in irrigation water, soil, forages, and animal tissues were measured in samples taken from within the vicinity of a zinc smelter and control samples. Heavy metal concentrations in foods (corn, rice, and wheat) and human tissues (blood and hair) from local farmers living in affected areas and controls were also determined. Hematological values were determined in human and animal samples. The copper, zinc, cadmium, and lead concentrations in irrigation water, soils, and forages were markedly higher than the levels in healthy pastures. Cadmium and lead concentrations were 177.82 and 16.61 times greater in forages than controls, respectively, and 68.71 and 15.66 times greater in soils than controls, respectively. Heavy metal concentrations in food (corn, rice, and wheat) in affected areas were markedly higher than in the control samples. Cadmium and lead concentrations in the tissues of affected sheep were markedly higher than in control animals (P < 0.01). Cadmium and lead concentrations in blood and hair samples from affected farmers were markedly higher than the control samples (P < 0.01). The occurrence of anemia in affected persons and animals followed a hypochromic and microcytic pattern. The intake of cadmium and lead was estimated according to herbage ingestion rates. It was found that the levels of cadmium and lead accumulated in sheep through the ingestion of vegetation growing in the sites closest to the zinc smelter were approximately 3.36 mg Cd/kg body wt./day and 38.47 mg Pb/kg body wt./day. This surpassed the fatal dosages for sheep of 1.13 mg Cd/kg body wt/day and 4.42 mg Pb/kg body wt./day. Serum total antioxidant capacity in affected humans and animals was significantly lower than in the controls (P < 0.01). The serum protein parameters in affected humans and animals were significantly reduced (P < 0.01). It was therefore concluded that heavy metal contamination has caused serious harm to sheep in this area. The heavy metal concentrations in food and grain also pose a significant risk to human health in the Chinese Wumeng mountain area.
1,936 downloads ecology
Ants are among the most ecologically successful organisms on Earth, with a global distribution and diverse nesting and foraging ecologies. Ants are also social organisms, living in crowded, dense colonies that can range up to millions of individuals. Understanding the ecological success of the ants requires understanding how they have mitigated one of the major costs of social living- infection by parasitic organisms. Additionally, the ecological diversity of ants suggests that they may themselves harbor a diverse, and largely unknown, assemblage of parasites. As a first step, we need to know the taxonomic and functional diversity of the parasitic organisms infecting ants. To that end, we provide a comprehensive review of the parasitic organisms infecting ants by collecting all extant records. We synthesize major patterns in parasite ecology by categorizing how parasites encounter their ant hosts, whether they require host death as a developmental necessity, and how they transmit to future hosts. We report 1,415 records of parasitic organisms infecting ants, the majority of which come from order Diptera (34.8%), phylum Fungi (25.6%), and order Hymenoptera (25.1%). Most parasitic organisms infecting ants are parasitoids (89.6%), requiring the death of their host as developmental necessity and most initially encounter their hosts in the extranidal environment (68.6%). Importantly, though most parasitic organisms infecting ants only need a single host to complete their life cycle (89.2%), the vast majority need to leave the nest before transmission to the next ant host can occur (88.3%), precluding ant-to-ant transmission within the nest. With respect to the host, we only found records for 9 out of 17 extant ant sub-families, and for 82 out of the currently recognized 334 ant genera. Though there is likely bias in the records reported, both host and parasite ecological traits and evolutionary histories underlie the pattern of ant-parasite association reported here. This work provides a foundation for future work that will begin to untangle the ecological drivers of ant-parasite relationships and the evolutionary implications thereof.
1,876 downloads ecology
Species distribution modeling is a valuable tool with many applications across ecology and evolutionary biology. The selection of biologically meaningful environmental variables that determine relative habitat suitability is a crucial aspect of the modeling pipeline. The 19 bioclimatic variables from WorldClim are frequently employed, primarily because they are easily accessible and available globally for past, present and future climate scenarios. Yet, the availability of relatively few other comparable environmental datasets potentially limits our ability to select appropriate variables that will most successfully characterize a species' distribution. We identified a set of 16 climatic and two topographic variables in the literature, which we call the envirem dataset, many of which are likely to have direct relevance to ecological or physiological processes determining species distributions. We generated this set of variables at the same resolutions as WorldClim, for the present, mid-Holocene, and Last Glacial Maximum (LGM). For 20 North American vertebrate species, we then assessed whether including the envirem variables led to improved species distribution models compared to models using only the existing WorldClim variables. We found that including the envirem dataset in the pool of variables to select from led to substantial improvements in niche modeling performance in 17 out of 20 species. We also show that, when comparing models constructed with different environmental variables, differences in projected distributions were often greater in the LGM than in the present. These variables are worth consideration in species distribution modeling applications, especially as many of the variables have direct links to processes important for species ecology. We provide these variables for download at multiple resolutions and for several time periods at envirem.github.io. Furthermore, we have written the "envirem" R package to facilitate the generation of these variables from other input datasets.
1,828 downloads ecology
1. Model-averaged regression coefficients have been criticized for averaging over a set of models with parameters that have different meanings from model to model. This criticism arises because of confusion between two different parameters estimated by the coefficients of a statistical model. 2. Ever since Fisher, the textbook definition of a coefficient (a “differences in conditional means”) takes its meaning from probabilistic conditioning ( P ( Y | X )). Because the parameter estimated with probabilistic conditioning is conditional on a specific set of covariates, its meaning varies from model to model. 3. The coefficients in many applied statistical models, however, take their meaning from causal conditioning ( P ( Y | do ( X ))) and these coefficients estimate causal effect parameters (or simply, causal effects or Average Treatment Effects). Causal effect parameters are also differences in conditional expectations, but the event conditioned on is not the set of covariates in a statistical model but a hypothetical intervention. Because an effect parameter takes its meaning from causal and not probabilistic conditioning, it is the same from model to model, and an averaged coefficient has a straightforward interpretation as an estimate of a causal effect. 4. Because an effect parameter is the same from model to model, the estimates of the parameter will generally be biased. By contrast, with probabilistic conditioning, the coefficients are consistent estimates of their parameter in every model, but the parameter differs from model to model. Confounding and omitted variable bias, which are central to explanatory modeling, are meaningless in statistical modeling as mere description. 5. The argument developed here only addresses the “different parameters” criticism of model-averaged coefficients and is not advocating model averaging more generally.
1,814 downloads ecology
The rate of carbon uptake by land plants depends on the ratio of leaf-internal to ambient carbon dioxide partial pressures, here termed χ. This quantity is a key determinant of both primary production and transpiration and the relationship between them. But current models for χ are empirical and incomplete, contributing to the many uncertainties afflicting model estimates and future projections of terrestrial carbon uptake. Here we show that a simple evolutionary optimality hypothesis generates functional relationships between χ and growth temperature, vapour pressure deficit and elevation that are precisely and quantitatively consistent with empirical χ values from a worldwide data set containing > 3500 stable carbon isotope measurements. A single global equation embodying these relationships then unifies the empirical light use efficiency model with the standard model of C3photosynthesis, and successfully predicts gross primary production as measured at flux sites. This achievement is notable because of the equation′s simplicity (with just two parameters, both independently estimated) and applicability across biomes and plant functional types. Thereby it provides a theoretical underpinning, grounded in eco-evolutionary principles, for large-scale analysis of the CO2 and water exchanges between atmosphere and land.
1,813 downloads ecology
Drahomíra Faktorová, R Ellen R Nisbet, José A. Fernández Robledo, Elena Casacuberta, Lisa Sudek, Andrew E. Allen, Manuel Ares, Cristina Aresté, Cecilia Balestreri, Adrian C Barbrook, Patrick Beardslee, Sara Bender, David S. Booth, François-Yves Bouget, Chris Bowler, Susana A. Breglia, Colin Brownlee, Gertraud Burger, Heriberto Cerutti, Rachele Cesaroni, Miguel A. Chiurillo, Thomas Clemente, Duncan B. Coles, Jackie L. Collier, Elizabeth C. Cooney, Kathryn Coyne, Roberto Docampo, Christopher L. Dupont, Virginia Edgcomb, Elin Einarsson, Pía A. Elustondo, Fernan Federici, Veronica Freire-Beneitez, Nastasia J. Freyria, Kodai Fukuda, Paulo A. García, Peter R. Girguis, Fatma Gomaa, Sebastian G. Gornik, Jian Guo, Vladimír Hampl, Yutaka Hanawa, Esteban R. Haro-Contreras, Elisabeth Hehenberger, Andrea Highfield, Yoshihisa Hirakawa, Amanda Hopes, Christopher J Howe, Ian Hu, Jorge Ibañez, Nicholas AT Irwin, Yuu Ishii, Natalia Ewa Janowicz, Adam C Jones, Ambar Kachale, Konomi Fujimura-Kamada, Binnypreet Kaur, Jonathan Z. Kaye, Eleanna Kazana, Patrick J. Keeling, Nicole King, Lawrence A. Klobutcher, Noelia Lander, Imen Lassadi, Zhuhong Li, Senjie Lin, Jean-Claude Lozano, Fulei Luan, Shinichiro Maruyama, Tamara Matute, Cristina Miceli, Jun Minagawa, Mark Moosburner, Sebastián R. Najle, Deepak Nanjappa, Isabel C. Nimmo, Luke Noble, Anna M.G. Novák Vanclová, Mariusz Nowacki, Isaac Nuñez, Arnab Pain, Angela Piersanti, Sandra Pucciarelli, Jan Pyrih, Joshua S. Rest, Mariana Rius, Deborah Robertson, Albane Ruaud, Iñaki Ruiz-Trillo, Monika A. Sigg, Pamela A. Silver, Claudio H. Slamovits, G. Jason Smith, Brittany N Sprecher, Rowena Stern, Estienne C. Swart, Anastasios D. Tsaousis, Lev Tsypin, Aaron Turkewitz, Jernej Turnšek, Matus Valach, Valérie Vergé, Peter von Dassow, Tobias von der Haar, Ross F. Waller, Lu Wang, Xiaoxue Wen, Glen Wheeler, April Woods, Huan Zhang, Thomas Mock, Alexandra Z. Worden, Julius Lukeš
Diverse microbial ecosystems underpin life in the sea. Among these microbes are many unicellular eukaryotes that span the diversity of the eukaryotic tree of life. However, genetic tractability has been limited to a few species, which do not represent eukaryotic diversity or environmentally relevant taxa. Here, we report on the development of genetic tools in a range of protists primarily from marine environments. We present evidence for foreign DNA delivery and expression in 13 species never before transformed and advancement of tools for 8 other species, as well as potential reasons for why transformation of yet another 17 species tested was not achieved. Our resource in genetic manipulation will provide insights into the ancestral eukaryotic lifeforms, general eukaryote cell biology, protein diversification and the evolution of cellular pathways.
1,806 downloads ecology
The gut microbiomes of birds and other animals are increasingly being studied in ecological and evolutionary contexts. While methods for preserving samples and processing high-throughput sequence data to characterise bacterial communities have received considerable attention, there has been little evaluation of non-invasive sampling methods. Numerous studies on birds and reptiles have made inferences about gut microbiota using cloacal sampling, however, it is not known whether the bacterial community of the cloaca provides an accurate representation of the avian gut microbiome. We examined the accuracy with which cloacal swabs and faecal samples measure the microbiota in three different parts of the gastrointestinal tract (ileum, caecum, and colon) using a case study on juvenile ostriches, Struthio camelus, and high-throughput 16S rRNA sequencing. We found that faeces were significantly better than cloacal swabs in representing the bacterial community of the colon. Cloacal samples had a higher abundance of Gammaproteobacteria and fewer Clostridia relative to the gut and faecal samples. However, both faecal and cloacal samples were poor representatives of the microbial communities in the caecum and ileum. Furthermore, the accuracy of the sampling methods in measuring the abundance of different bacterial taxa was highly variable: Bacteroidetes was the most highly correlated phylum between all three gut sections and both methods, whereas colonic Actinobacteria correlated strongly only with faecal samples. This study demonstrates that sampling methods can have significant effects on the inferred gut microbiome in studies of birds. Based on our results, we recommend sampling faeces, whenever possible, as this provides the most accurate assessment of the colon microbiome. The fact that neither sampling technique portrayed the bacterial community of the ileum or the caecum illustrates the difficulty in non-invasively monitoring gut bacteria located further up in the gastrointestinal tract. These results have important implications for the interpretation of avian gut microbiome studies.
1,802 downloads ecology
Complex adaptive systems provides a unified framework for explaining ecosystem phenomena. In the past twenty years, complex adaptive systems has been sharpened from an abstract concept into a series of tools that can be used to solve concrete problems. These advances have been led by the development of new techniques for coupling ecological and evolutionary dynamics, for integrating dynamics across multiple scales of organization, and for using data to infer the complex interactions among different components of ecological systems. Focusing on the development and usage of these new methods, we explore how they have led to an improved understanding of three universal features of complex adaptive systems, emergent patterns; tipping points and critical phenomena; and cooperative behavior. We restrict our attention primarily to marine ecosystems, which provide numerous successful examples of the application of complex adaptive systems. Many of these are currently undergoing dramatic changes due to anthropogenic perturbations, and we take the opportunity to discuss how complex adaptive systems can be used to improve the management of public goods and to better preserve critical ecosystem services.
1,798 downloads ecology
Spatial heterogeneity in the environment induces variation in population demographic rates and dispersal patterns, which result in spatio-temporal variation in density and gene flow. Unfortunately, applying theory to learn about the role of spatial structure on populations has been hindered by the lack of mechanistic spatial models and inability to make precise observations of population structure. Spatial capture-recapture (SCR) represents an individual-based analytic framework for overcoming this fundamental obstacle that has limited the utility of ecological theory. SCR methods make explicit use of spatial encounter information on individuals in order to model density and other spatial aspects of animal population structure, and have been widely adopted in the last decade. We review the historical context and emerging developments in SCR models that enable the integration of explicit ecological hypotheses about landscape connectivity, movement, resource selection, and spatial variation in density, directly with individual encounter history data obtained by new technologies (e.g., camera trapping, non-invasive DNA sampling). We describe ways in which SCR methods stand to revolutionize the study of animal population ecology.
1,795 downloads ecology
Joint Species Distribution Modelling (JSDM) is becoming an increasingly popular statistical method for analyzing data in community ecology. JSDM allow the integration of community ecology data with data on environmental covariates, species traits, phylogenetic relationships, and the spatio-temporal context of the study, providing predictive insights into community assembly processes from non-manipulative observational data of species communities. Hierarchical Modelling of Species Communities (HMSC) is a general and flexible framework for fitting JSDMs, yet its full range of functionality has remained restricted to Matlab users only. To make HMSC accessible to the wider community of ecologists, we introduce HMSC-R 3.0, a user-friendly R implementation of the framework described in Ovaskainen et al (Ecology Letters, 20 (5), 561-576, 2017) and further extended in several later publications. We illustrate the use of the package by providing a series of five vignettes that apply HMSC-R 3.0 to simulated and real data. HMSC-R applications to simulated data involve single-species models, models of small communities, and models of large species communities. They demonstrate the estimation of species responses to environmental covariates and how these depend on species traits, as well as the estimation of residual species associations. They further demonstrate how HMSC-R can be applied to normally distributed data, count data, and presence-absence data. The real data consist of bird counts in a spatio-temporally structured dataset, environmental covariates, species traits and phylogenetic relationships. The vignettes demonstrate how to construct and fit many kinds of models, how to examine MCMC convergence, how to examine the explanatory and predictive powers of the models, how to assess parameter estimates, and how to make predictions. The package, along with the extended vignettes, makes JSDM fitting and post-processing easily accessible to ecologists familiar with R.
1,781 downloads ecology
Survival in aquatic environments requires organisms to have effective means of collecting information from their surroundings through various sensing strategies. In this study, we explore how sensing mode and range depend on body size. We find a hierarchy of sensing modes determined by body size. With increasing body size, a larger battery of modes becomes available (chemosensing, mechanosensing, vision, hearing, and echolocation, in that order) while the sensing range also increases. This size-dependent hierarchy and the transitions between primary sensory modes are explained on the grounds of limiting factors set by physiology and the physical laws governing signal generation, transmission and reception. We theoretically predict the body size limits for various sensory modes, which align well with size ranges found in literature. The treatise of all ocean life, from unicellular organisms to whales, demonstrates how body size determines available sensing modes, and thereby acts as a major structuring factor of aquatic life.
1,778 downloads ecology
The use of DNA data is ubiquitous across animal sciences. DNA may be obtained from an organism for a myriad of reasons including identification and distinction between cryptic species, sex identification, comparisons of different morphocryptic genotypes or assessments of relatedness between organisms prior to a behavioural study. DNA should be obtained while minimizing the impact on the fitness, behaviour or welfare of the subject being tested, as this can bias experimental results and cause long-lasting effects on wild animals. Furthermore, minimizing impact on experimental animals is a key Refinement principle within the ‘3Rs’ framework which aims to ensure that animal welfare during experimentation is optimised. The term ‘non-invasive DNA sampling’ has been defined to indicate collection methods that do not require capture or cause disturbance to the animal, including any effects on behaviour or fitness. In practice this is not always the case, as the term ‘non-invasive’ is commonly used in the literature to describe studies where animals are restrained or subjected to aversive procedures. We reviewed the non-invasive DNA sampling literature for the past six years (380 papers published in 2013-2018) and uncovered the existence of a significant gap between the current use of this terminology (i.e. ‘non-invasive DNA sampling’) and its original definition. We show that 58% of the reviewed papers did not comply with the original definition. We discuss the main experimental and ethical issues surrounding the potential confusion or misuse of the phrase ‘non-invasive DNA sampling’ in the current literature and provide potential solutions. In addition, we introduce the terms ‘non-disruptive’ and ‘minimally disruptive’ DNA sampling, to indicate methods that eliminate or minimise impacts not on the physical integrity/structure of the animal, but on its behaviour, fitness and welfare, which in the literature reviewed corresponds to the situation for which an accurate term is clearly missing. Furthermore, we outline when these methods are appropriate to use.
1,766 downloads ecology
Simon Roux, Jennifer R Brum, Bas E. Dutilh, S Sunagawa, Melissa B. Duhaime, Alexander Loy, Bonnie T Poulos, Natalie Solonenko, Elena Lara, Julie Poulain, Stéphane Pesant, Stefanie Kandels-Lewis, Céline Dimier, Marc Picheral, Sarah Searson, Corinne Cruaud, Adriana Alberti, Carlos M. Duarte, Josep M. Gasol, Dolors Vaqué, Tara Oceans Coordinators, Peer Bork, Silvia G. Acinas, Patrick Wincker, Matthew B. Sullivan, Emmanuel Boss, Chris Bowler, Colomban de Vargas, Michael Follows, Gabriel Gorsky, Nigel Grimsley, Pascal Hingamp, Daniele Iudicone, Olivier Jaillon, Lee Karp-Boss, Eric Karsenti, Uros Krzic, Fabrice Not, Hiroyuki Ogata, Stephane Pesant, Jeroen Raes, Emmanuel G. Reynaud, Christian Sardet, Mike Sieracki, Sabrina Speich, Lars Stemmann, Didier Velayoudon
Ocean microbes drive global-scale biogeochemical cycling, but do so under constraints imposed by viruses on host community composition, metabolism, and evolutionary trajectories. Due to sampling and cultivation challenges, genome-level viral diversity remains poorly described and grossly understudied in nature such that <1% of observed surface ocean viruses, even those that are abundant and ubiquitous, are ′known′. Here we analyze a global map of abundant, double stranded DNA (dsDNA) viruses and viral-encoded auxiliary metabolic genes (AMGs) with genomic and ecological contexts through the Global Ocean Viromes (GOV) dataset, which includes complete genomes and large genomic fragments from both surface and deep ocean viruses sampled during the Tara Oceans and Malaspina research expeditions. A total of 15,222 epi- and mesopelagic viral populations were identified that comprised 867 viral clusters (VCs, approximately genus-level groups). This roughly triples known ocean viral populations, doubles known candidate bacterial and archaeal virus genera, and near-completely samples epipelagic communities at both the population and VC level. Thirty-eight of the 867 VCs were identified as the most impactful dsDNA viral groups in the oceans, as these were locally or globally abundant and accounted together for nearly half of the viral populations in any GOV sample. Most of these were predicted in silico to infect dominant, ecologically relevant microbes, while two thirds of them represent newly described viruses that lacked any cultivated representative. Beyond these taxon-specific ecological observations, we identified 243 viral-encoded AMGs in GOV, only 95 of which were known. Deeper analyses of 4 of these AMGs revealed that abundant viruses directly manipulate sulfur and nitrogen cycling, and do so throughout the epipelagic ocean. Together these data provide a critically-needed organismal catalog and functional context to begin meaningfully integrating viruses into ecosystem models as key players in nutrient cycling and trophic networks.
1,723 downloads ecology
The feeding functional response is one of the most widespread mathematical frameworks in Ecology, Marine Biology, Freshwater Biology, Microbiology and related scientific fields describing the resource-dependent uptake of a consumer. Since the exact knowledge of its parameters is crucial in order to predict, for example, the efficiency of biocontrol agents, population dynamics, food web structure and subsequently biodiversity, a trustful parameter estimation is of utmost importance for scientists using this framework. Classical approaches for estimating functional response parameters lack flexibility and can often only serve as approximation for a correct parameter estimation. Moreover, they do not allow to incorporate side effects such as resource growth or background mortality. Both call for a new method to be established solving these problems. Here, we combined ordinary differential equation models (ODE models), that were numerically solved using computer simulations, with an iterative maximum likelihood fitting approach. We compared our method to classical approaches of fitting functional responses, using data both with and without additional resource growth and mortality. We found that for classical functional response models, like the often used type II and type III functional response, the established fitting methods are reliable. However, using more complex and flexible functional responses, our new established method outperforms the traditional methods. Additionally, only our method allows to analyze experiments correctly when resources experience growth or background mortality. Our method will enable researchers from different scientific fields that are measuring functional responses to estimate parameters correctly. These estimates will enable community ecologists to parameterize their models more precisely, allowing for a deeper understanding of complex ecological systems, and will increase the quality of ecological prediction models.
1,681 downloads ecology
Helen R P Phillips, Carlos A. Guerra, Marie L C Bartz, Maria J. I. Briones, George Brown, Olga Ferlian, Konstantin B Gongalsky, Julia Krebs, Alberto Orgiazzi, Benjamin Schwarz, Elizabeth M Bach, Joanne Bennett, Ulrich Brose, Thibaud Decaëns, Franciska T De Vries, Birgitta König-Ries, Michel Loreau, Jérôme Mathieu, Christian Mulder, Wim H. van der Putten, Kelly S Ramirez, Matthias C. Rillig, David Russell, Michiel Rutgers, Madhav P Thakur, Diana H. Wall, David Wardle, Data Providers (see bulk upload sheet), Erin Cameron, Nico Eisenhauer
Soil organisms provide crucial ecosystem services that support human life. However, little is known about their diversity, distribution, and the threats affecting them. Here, we compiled a global dataset of sampled earthworm communities from over 7000 sites in 56 countries to predict patterns in earthworm diversity, abundance, and biomass. We identify the environmental drivers shaping these patterns. Local species richness and abundance typically peaked at higher latitudes, while biomass peaked in the tropics, patterns opposite to those observed in aboveground organisms. Similar to many aboveground taxa, climate variables were more important in shaping earthworm communities than soil properties or habitat cover. These findings highlight that, while the environmental drivers are similar, conservation strategies to conserve aboveground biodiversity might not be appropriate for earthworm diversity, especially in a changing climate. One sentence summary Global patterns of earthworm diversity, abundance and biomass are driven by climate but patterns differ from many aboveground taxa.
1,666 downloads ecology
The current outbreak of Zika virus poses a threat of unknown magnitude to human health. While the range of the virus has been cataloged growing slowly over the last 50 years, the recent explosive expansion in the Americas indicates that the full potential distribution of Zika remains uncertain. Moreover, most current epidemiology relies on its similarities to dengue fever, a phylogenetically closely related disease of unknown similarity in spatial range or ecological niche. Here we compile the first spatially explicit global occurrence dataset from Zika viral surveillance and serological surveys, and construct ecological niche models to test basic hypotheses about its spread and potential establishment. The hypothesis that the outbreak of cases in Mexico and North America are anomalous and outside the ecological niche of the disease, and may be linked to El Nino or similar climatic events, remains plausible at this time. Comparison of the Zika niche against the known distribution of dengue fever suggests that Zika is more constrained by the seasonality of precipitation and diurnal temperature fluctuations, likely confining the disease to the tropics outside of pandemic scenarios. Projecting the range of the diseases in conjunction with vector species (Aedes africanus, Ae. aegypti, and Ae. albopictus) that transmit the pathogens, under climate change, suggests that Zika has potential for northward expansion; but, based on current knowledge, Zika is unlikely to fill the full range its vectors occupy. With recent sexual transmission of the virus known to have occurred in the United States, we caution that our results only apply to the vector-borne aspect of the disease, and while the threat of a mosquito-carried Zika pandemic may be overstated in the media, other transmission modes of the virus may emerge and facilitate naturalization worldwide.
1,659 downloads ecology
Billions of animals cross the globe each year during seasonal migrations, but efforts to monitor them are hampered by the irregularity and relative unpredictability of their movements. We developed a bird migration forecast system with continental scope by leveraging 23 years of spring observations to learn associations between atmospheric conditions and bird migration intensity. Our models explained up to 81% of variation in migration intensity across the United States at altitudes of 0-3000 m, and performance remained high when forecasting events 24-72 h into the future (68-72% variation explained). We infer that avian migratory movements across the United States frequently exceed 200 million individuals per night and exceed 500 million individuals per night during peak passage. Accurately forecasting bird migration will allow stakeholders to reduce collisions with illuminated buildings, airplanes, and wind turbines, predict movements under climate change scenarios, and engage the public.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!