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in category ecology
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1,585 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.
1,585 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.
1,572 downloads ecology
Simon Roux, Jennifer R Brum, Bas E. Dutilh, Shinichi Sunagawa, Melissa B. Duhaime, Alexander Loy, Bonnie T Poulos, Natalie Solonenko, Elena Lara, Julie Poulain, Stephane PESANT, Stefanie Kandels-Lewis, Céline Dimier, Marc Picheral, Sarah Searson, Corinne Cruaud, Adriana Alberti, Carlos M. 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.
1,541 downloads ecology
Significance: Foraged leafy greens are consumed around the globe, including in urban areas, and may play a larger role when food is scarce or expensive. It is thus important to assess the safety and nutritional value of wild greens foraged in urban environments. Methods: Field observations, soil tests, and nutritional and toxicology tests on plant tissue were conducted for three sites, each roughly 9 square blocks, in disadvantaged neighborhoods in the East San Francisco Bay Area in 2014--2015. The sites included mixed-use areas and areas with high vehicle traffic. Results: Edible wild greens were abundant, even during record droughts. Soil at some survey sites had elevated concentrations of lead and cadmium, but tissue tests suggest that rinsed greens of the tested species are safe to eat. Daily consumption of standard servings comprise less than the EPA reference doses of lead, cadmium, and other heavy metals. Pesticides, glyphosate, and PCBs were below detection limits. The nutrient density of 6 abundant species compared favorably to that of the most nutritious domesticated leafy greens. Conclusions: Wild edible greens harvested in industrial, mixed-use, and high-traffic urban areas in the San Francisco East Bay area are abundant and highly nutritious. Even grown in soils with elevated levels of heavy metals, tested species were safe to eat after rinsing in tap water. This does not mean that all edible greens growing in contaminated soil are safe to eat--tests on more species, in more locations, and over a broader range of soil chemistry are needed to determine what is generally safe and what is not. But it does suggest that wild greens could contribute to nutrition, food security, and sustainability in urban ecosystems. Current laws, regulations, and public-health guidance that forbid or discourage foraging on public lands, including urban areas, should be revisited.
1,537 downloads ecology
Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (2012, Science 338: 1481-1484) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (1) test competing explanations for tropical arthropod megadiversity, (2) improve estimates of global eukaryotic species diversity, and (3) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous, and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity.
1,501 downloads ecology
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. 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. 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. 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. The argument developed here only addresses the "different parameters" criticism of model-averaged coefficients and is not advocating model averaging more generally.
1,495 downloads ecology
A database of curated genomes is needed to better assess soil microbial communities and their processes associated with differing land management and environmental impacts. Interpreting soil metagenomic datasets with existing sequence databases is challenging because these datasets are biased towards medical and biotechnology research and can result in misleading annotations. We have curated a database of 922 genomes of soil-associated organisms (888 bacteria and 34 archaea). Using this database, we evaluated phyla and functions that are enriched in soils as well as those that may be underrepresented in RefSoil. Our comparison of RefSoil to soil amplicon datasets allowed us to identify targets that if cultured or sequenced would significantly increase the biodiversity represented within RefSoil. To demonstrate the opportunities to access these underrepresented targets, we employed single cell genomics in a pilot experiment to sequence 14 genomes. This effort demonstrates the value of RefSoil in the guidance of future research efforts and the capability of single cell genomics as a practical means to fill the existing genomic data gaps.
1,469 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.
1,462 downloads ecology
Computational ecology, defined as the application of computational thinking to ecological problems, has the potential to transform the way ecologists think about the integration of data and models. As the practice is gaining prominence as a way to conduct ecological research, it is important to reflect on what its agenda could be, and how it fits within the broader landscape. In this contribution, we suggest areas in which empirical ecologists, modellers, and the emerging community of computational ecologists could engage in a constructive dialogue to build on one another expertise. We discuss how training can be amended to improve the computational literacy of ecologists can be improved.
1,455 downloads ecology
Mobile phones can be found almost everywhere across the globe, upholding a direct point-to-point connection between the device and the broadcast tower. The emission of radiofrequency electromagnetic radiation (RF-EMF) puts the surrounding environment inevitably into contact with this pollutant. We have therefore exposed honey bee queen larvae to the radiation of a common mobile phone device (GSM) during all stages of their pre-adult development including pupation. After 14 days of exposure, hatching of adult queens was assessed and mating success after further 11 days, respectively. Moreover, full colonies were established of five of the untreated and four of the treated queens to contrast population dynamics. We found that mobile phone radiation had significantly reduced the hatching ratio but not the mating success. If treated queens were successfully mated, colony development was not adversely affected. We provide evidence that RF-EMF only acts detrimental within the sensitivity of pupal development, once succeeded this point, no further impairment has manifested in adulthood. Our results are discussed against the background of long-lasting consequences for colony performance and the possible implication on periodic colony losses.
1,442 downloads ecology
Competition and mutualism are inevitable processes in microbial ecology, and a central question is which and how many taxa will persist in the face of these interactions. Ecological theory has demonstrated that when direct, pairwise interactions among a group of species are too numerous, or too strong, then the coexistence of these species will be unstable to any slight perturbation. This instability worsens when mutualistic interactions complement competition. Here, we refine and to some extent overturn that understanding, by considering explicitly the resources that microbes consume and produce. In contrast to more complex organisms, microbial cells consume primarily abiotic resources, and mutualistic interactions are often mediated by these same abiotic resources through the mechanism of cross-feeding. Our model therefore considers the consumption and production of a set of abiotic resources by a group of microbial species. We show that if microbes consume, but do not produce resources, then any positive equilibrium will always be stable to small perturbations. We go on to show that in the presence of crossfeeding, stability is no longer guaranteed. However, stability still holds when mutualistic interations are either symmetric, or sufficiently weak.
1,438 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.
1,421 downloads ecology
Antibiotic resistance genes (ARG) are pervasive in gut microbiota, but it remains unclear how often ARG are transferred, particularly to pathogens. Traditionally, ARG spread is attributed to horizontal transfer mediated either by DNA transformation, bacterial conjugation or generalized transduction. However, recent viral metagenome (virome) analyses suggest that ARG are frequently carried by phages, which is inconsistent with the traditional view that phage genomes rarely encode ARG. Here we used exploratory and conservative bioinformatic strategies found in the literature to detect ARG in phage genomes, and experimentally assessed a subset of ARG predicted using exploratory thresholds. ARG abundances in 1,181 phage genomes were vastly over-estimated using exploratory thresholds (421 predicted vs 2 known), due to low similarities and matches to protein unrelated to antibiotic resistance. Consistent with this, 4 ARG predicted using exploratory thresholds were experimentally evaluated and failed to confer antibiotic resistance in Escherichia coli. Re-analysis of available human- or mouse-associated viromes for ARG and their genomic context suggested that bona fide ARG attributed to phages in viromes were previously over-estimated. These findings provide guidance for documentation of ARG in viromes, and re-assert that ARG are rarely encoded in phages.
1,416 downloads ecology
Citizen science data are valuable for addressing a wide range of ecological research questions, and there has been a rapid increase in the scope and volume of data available. However, data from large-scale citizen science projects typically present a number of challenges that can inhibit robust ecological inferences. These challenges include: species bias, spatial bias, variation in effort, and variation in observer skill. To demonstrate key challenges in analysing citizen science data, we use the example of estimating species distributions with data from eBird, a large semi-structured citizen science project. We estimate three widely applied metrics for describing species distributions: encounter rate, occupancy probability, and relative abundance. For each method, we outline approaches for data processing and modelling that are suitable for using citizen science data for estimating species distributions. Model performance improved when data processing and analytical methods addressed the challenges arising from citizen science data. The largest gains in model performance were achieved with two key processes 1) the use of complete checklists rather than presence-only data, and 2) the use of covariates describing variation in effort and detectability for each checklist. Including these covariates accounted for heterogeneity in detectability and reporting, and resulted in substantial differences in predicted distributions. The data processing and analytical steps we outlined led to improved model performance across a range of sample sizes. When using citizen science data it is imperative to carefully consider the appropriate data processing and analytical procedures required to address the bias and variation. Here, we describe the consequences and utility of applying our suggested approach to semi-structured citizen science data to estimate species distributions. The methods we have outlined are also likely to improve other forms of inference and will enable researchers to conduct robust analyses and harness the vast ecological knowledge that exists within citizen science data.
1,410 downloads ecology
Andrew T. Nottingham, Noah Fierer, Benjamin L Turner, Jeanette Whitaker, Nick J. Ostle, Niall P. McNamara, Richard D. Bardgett, Jonathan W Leff, Norma Salinas, Miles Silman, Loeske Kruuk, Patrick Meir
More than 200 years ago, von Humboldt reported decreases in tropical plant species richness with increasing elevation and decreasing temperature. Surprisingly, co-ordinated patterns in plant, bacterial and fungal diversity on tropical mountains are yet to be observed, despite the central role of soil microorganisms in terrestrial biogeochemistry. We studied an Andean transect traversing 3.5 km in elevation to test whether the species diversity and composition of tropical forest plants, soil bacteria and fungi can follow similar biogeographical patterns with shared environmental drivers. We found co-ordinated changes with elevation in all three groups: species richness declined as elevation increased, and the compositional-dissimilarity of communities increased with increased separation in elevation, although changes in plant diversity were larger than in bacteria and fungi. Temperature was the dominant driver of these diversity gradients, with weak influences of edaphic properties, including soil pH. The gradients in microbial diversity were strongly correlated with the activities of enzymes involved in organic matter cycling, and were accompanied by a transition in microbial traits towards slower-growing, oligotrophic taxa at higher elevations. We provide the first evidence of co-ordinated temperature-driven patterns in the diversity and distribution of three major biotic groups in tropical ecosystems: soil bacteria, fungi and plants. These findings suggest that, across landscape scales of relatively constant soil pH, inter-related patterns of plant and microbial communities with shared environmental drivers can occur, with large implications for tropical forest communities under future climate change.
1,409 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.
1,395 downloads ecology
The study of aggressive interactions between species has, to date, usually been restricted to interactions among small numbers of ecologically close competitors. Nothing is known about interspecific dominance hierarchies that include numerous, ecologically varied species. Such hierarchies are of interest because they could be used to address a variety of research questions, e.g. do similarly ranked species tend to avoid each other in time or space, and what will happen when such species come into contact as climates change? Here, we propose a method for creating a continental-scale hierarchy, and we make initial analyses based on this hierarchy. We quantified the extent to which a dominance hierarchy of feeder birds was linear, as intransitivities can promote local species' coexistence. Using the existing network of citizen scientists participating in Project FeederWatch, we collected the data with which to create a continent-spanning interspecific dominance hierarchy that included species that do not currently have overlapping geographic distributions. Overall, the hierarchy was nearly linear, and largely predicted by body mass, although there were clade-specific deviations from the average mass-dominance relationship. Most of the small number of intransitive relationships in the hierarchy were based on small samples of observations. Few observations were made of interactions between close relatives and ecological competitors like Melanerpes woodpeckers and chickadees, as such species often have only marginally overlapping geographic distributions. Yet, these species' ranks--emergent properties of the interaction network--were usually in agreement with published literature on dominance relationships between them.
1,382 downloads ecology
Substrate Induced Respiration (SIR) is a standard method to study microbial biomass in soil. It is observed that the soil microbial CO 2 respiration goes up with the glucose concentration till a certain concentration, and afterwards decreases and stabilizes. There are two possible mechanisms via which this can happen: increased osmotic pressure can kill off a group of microbial population or the Crabtree effect takes over the population. An experiment was designed using the SIR; to find the reason for the same and prove or disprove one of these hypothesises.
1,381 downloads ecology
Trait-based approaches are widespread throughout ecological research, offering great potential for trait data to deliver general and mechanistic conclusions. Accordingly, a wealth of trait data is available for many organism groups, but, due to a lack of standardisation, these data come in heterogeneous formats. We review current initiatives and infrastructures for standardising trait data and discuss the importance of standardisation for trait data hosted in distributed open-access repositories. In order to facilitate the standardisation and harmonisation of distributed trait datasets, we propose a general and simple vocabulary as well as a simple data structure for storing and sharing ecological trait data. Additionally, we provide an R-package that enables the transformation of any tabular dataset into the proposed format. This also allows trait datasets from heterogeneous sources to be harmonised and merged, thus facilitating data compilation for any particular research focus. With these decentralised tools for trait-data harmonisation, we intend to facilitate the exchange and analysis of trait data within ecological research and enable global syntheses of traits across a wide range of taxa and ecosystems.
1,376 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.
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