SEARCH · Search bioRxiv

Results for “ecology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43Linked to original sources

bioRxiv2017

Loss of generalist plant species and functional diversity decreases the robustness of a seed dispersal network

Understanding cascading effects of species loss has become a major challenge for ecologists. Traditionally, the robustness of ecological networks has been evaluated based on simulation studies where primary extinctions occur at random or as a function of species specialization, ignoring other important biological factors. Here, we estimate the robustness of a seed dispersal network from a grassland-forest mosaic in southern Brazil, simulating distinct scenarios of woody plant species extinction, including scenarios where species are eliminated based on their evolutionary and functional distinctiveness. Our results suggest that the network is more robust when species are eliminated based on their evolutionary uniqueness, followed by random extinctions, the extinction of the most specialist species, functional distinctiveness and, at last, when the most generalist species are sequentially eliminated. Our results provide important information for grassland-forest mosaic management, as they indicate that loss of generalist species and functional diversity makes the system more likely to collapse.

ecology↗

bioRxiv2017

The Parasite Extinction Assessment & Red List: an open-source, online biodiversity database for neglected symbionts

Parasite conservation is a rapidly growing field at the intersection of ecology, epidemiology, parasitology, and public health. The overwhelming diversity of parasitic life on earth, and recent work showing that parasites and other symbionts face severe extinction risk, necessitates infrastructure for parasite conservation assessments. Here, we describe the release of the Parasite Extinction Assessment & Red List (PEARL) version 1.0, an open-access database of conservation assessments and distributional data for almost 500 macroparasitic invertebrates. The current approach to vulnerability assessment is based on range shifts and loss from climate change, and will be expanded as additional data (e.g., host-parasite associations and coextinction risk) is consolidated in PEARL. The web architecture is also open-source, scalable, and extensible, making PEARL a template for more eZcient red listing for other high-diversity, data-de1cient groups. Future iterations will also include new functionality, including a user-friendly open data pository and automated assessment and re-listing.

ecology↗

bioRxiv2017

Goodness of fit checks for binomial N-mixture models

O_LIBinomial N-mixture models are commonly applied to analyze population survey data. By estimating detection probabilities, N-mixture models aim at extracting information about abundances in terms of actual and not just relative numbers. This separation of detection probability and abundance relies on parametric assumptions about the distribution of individuals among sites and of detections of individuals among repeat visits to sites. Current methods for checking assumptions are limited, and their computational complexity have hindered evaluations of their performances.\nC_LIO_LIWe develop computationally efficient graphical goodness of fit checks and measures of overdispersion for binomial N-mixture models. These checks are illustrated in a case study, and evaluated in simulations under two scenarios. The two scenarios assume overdispersion in the abundance distribution via a negative binomial distribution or in the detection probability via a beta-binomial distribution. We evaluate the ability of the checks to detect lack of fit, and how lack of fit affects estimates of abundances.\nC_LIO_LIThe simulations show that if the parametric assumptions are incorrect there can be severe biases in estimated abundances: negatively if there is overdispersion in abundance relative to the fitted model and positively if there is overdispersion in detection. Our goodness of fit checks performed well in detecting lack of fit when the abundance distribution is overdispersed, but struggled to detect lack of fit when detections were overdispersed. We show that the inability to detect lack of fit due to overdispersed detection is caused by a fundamental similarity between N-mixture models with beta-binomial detections and N-mixture models with negative binomial abundances.\nC_LIO_LIThe strong biases in estimated abundances that can occur in the binomial N-mixture model when the distribution of individuals among sites, or the detection model, is mis-specified implies that checking goodness of fit is essential for sound inference in ecological studies that use these methods. To check the assumptions we provide computationally efficient goodness of fit checks that are available in an R-package nmixgof. However, even when a binomial N-mixture model appears to fit the data well, estimates are not robust in the presence of overdispersion unless additional information about detection is collected.\nC_LI

ecology↗

bioRxiv2017

Experimental warming reduces the diversity and functional potential of the Sphagnum microbiome

Climate change may reduce biodiversity leading to a reduction in ecosystem productivity. Despite numerous reports of a strong correlation of microbial diversity and ecosystem productivity, little is known about the warming effects on plant associated microbes. Here we explore the impact of experimental warming on the microbial and nitrogen-fixing (diazotroph) community associated with the widespread and ecologically relevant Sphagnum genus in a field warming experiment. To quantify changes in the abundance, diversity, and community composition of Sphagnum microbiomes with warming we utilized qPCR and Illumina sequencing of the 16S SSU rRNA and nifH gene. Microbial and diazotroph community richness and Shannon diversity decreased with warming (p<0.05). The diazotroph communities shifted from diverse communities to domination by primarily Nostocaceae (25% in control samples to 99% in elevated temperature samples). In addition, the nitrogen fixation activity measured with the acetylene reduction assay (ARA) decreased with warming treatment. This suggests the negative correlation of temperature and microbial diversity corresponds to a reduction in functional potential within the diazotroph community. The results indicate that climate warming may alter the community structure and function in peat moss microbiomes, with implications for impacts to host fitness and ecosystem productivity, and carbon uptake potential of peatlands.

ecology↗

bioRxiv2017

Enriched pathogen diversity under host-type heterogeneity and immune-mediated competition

Pathogen strains can stably coexist if they specialize on different hosts. Multiple strains can also coexist on a single host through negative frequency-dependent interactions mediated by partial cross-immunity. Understanding pathogen diversity remains a challenge however when both host specificity and cross-immunity are acting and may be functionally linked, as has been proposed for rotavirus, where a single protein is both antigenically important and determines host specificity by binding to the genetically encoded human blood group antigens. This situation is akin to the more general question in ecology of species coexistence when stabilizing and equalizing mechanisms interact. We examine this interaction with a theoretical model motivated by rotavirus and apply an adaptive dynamics framework to show how these two kinds of competition, typically considered separately, affect diversity. When cross-immunity depends on host-pathogen affinity, diversity is magnified as long-term evolution allows for the coexistence of multiple semi-specialized strains, similar to observations in rotavirus. In contrast, the simultaneous co-occurrence of several semi-specialized individuals is not observed when the degree of cross-immunity is independent from affinity distance among strains. The interplay of equalizing and stabilizing mechanisms fundamentally modifies diversity patterns and should be considered when addressing strain coexistence.

ecology↗

bioRxiv2017

DIETARY AND DEVELOPMENTAL SHIFTS IN BUTTERFLY-ASSOCIATED BACTERIAL COMMUNITIES

Bacterial communities associated with insects can substantially influence host ecology, evolution and behavior. Host diet is a key factor that shapes bacterial communities, but the impact of dietary transitions across insect development is poorly understood. We analyzed bacterial communities of 12 butterfly species across different development stages, using 16S rDNA amplicon sequencing. Butterfly larvae typically consume leaves of a single host plant, whereas adults are more generalist nectar feeders. Thus, we expected bacterial communities to vary substantially across butterfly development. Surprisingly, very few species showed significant developmental transitions in bacterial communities, suggesting weak impacts of dietary transitions across butterfly development. On the other hand, bacterial communities were strongly influenced by butterfly species identity and dietary variation across species. Larvae of most butterfly species largely mirrored bacterial community composition of their diets, suggesting passive acquisition rather than active selection. Overall, our results suggest that although butterflies harbor distinct microbiomes across taxonomic groups and dietary guilds, the dramatic dietary shifts that occur during development do not impose strong selection to maintain distinct bacterial communities.

ecology↗

bioRxiv2017

Carbon pool trends and dynamics within a subtropical peatland during long-term restoration

BackgroundThe Florida Everglades has undergone significant ecological change spanning the continuum of disturbance to restoration. While the restoration effort is not complete and the ecosystem continues to experience short duration perturbations, a better understanding of long-term C dynamics of the Everglades is needed to facilitate new restoration efforts. This study evaluated temporal trends of different aquatic carbon (C) pools of the northern Everglades Protection Area over a 20-year period to gauge historic C cycling patterns. Dissolved inorganic C (DIC), dissolved organic C (DOC), particulate organic C (POC), and surface water carbon dioxide (pCO2(aq)) were investigated between May 1, 1994 and April 30, 2015.\n\nResultsAnnual mean concentrations of DIC, DOC, POC, and pCO2(aq) significantly decreased through time or remained constant across the Water Conservation Areas (WCAs). Overall, the magnitude of the different C pools in the water column significantly differed between regions. Outgassing of CO2 was dynamic across the Everglades ranging from 420 to 2001 kg CO2 yr-1. Overall the historic trend in CO2 flux from the marsh declined across our study area while pCO2(aq) largely remained somewhat constant with the exception of Water Conservation Area 2 which experienced significant declines in pCO2(aq). Particulate OC concentrations were consistent between WCAs, but a significantly decreasing trend in annual POC concentrations were observed.\n\nConclusionsHydrologic condition and nutrient inputs significantly influenced the balance, speciation, and flux of C pools across WCAs suggesting a subsidy-stress response in C dynamics relative to landscape scale responses in nutrient availability. The interplay between nutrient inputs and hydrologic condition exert a driving force on the balance between DIC and DOC production via the metabolism of organic matter which forms the base of the aquatic foodweb. Along the restoration trajectory as water quality and hydrology continues to improve it is expected that C pools will respond accordingly.

ecology↗

bioRxiv2017

Asymmetric migration decreases stability but increases resilience in a heterogeneous metacommunity

Many natural communities are spatially distributed, forming a network of subcommunities linked by migration. Migration patterns are often asymmetric and heterogeneous, with important consequences on the ecology and evolution of the species. Here we investigated experimentally how asymmetric migration and heterogeneous structure affect a simple metacommunity of budding yeast, formed by one strain that produces a public good and a non-producer strain that benefits from it. We find that asymmetric migration increases the fraction of producers in all subpopulations of the metacommunity. Furthermore, asymmetric migration decreases the metacommunitys tolerance to challenging environments, but increases its resilience to transient perturbations. This apparent paradox occurs because tolerance to a constant challenge depends on the weakest subpopulations of the network, while resilience to a transient perturbation depends on the strongest ones.\n\nOne Sentence SummaryAsymmetric migration decreases the stability of experimental yeast metacommunities but increases their resilience to transient shocks.

ecology↗

bioRxiv2017

Emergent Simplicity in Microbial Community Assembly

Microbes assemble into complex, dynamic, and species-rich communities that play critical roles in human health and in the environment. The complexity of natural environments and the large number of niches present in most habitats are often invoked to explain the maintenance of microbial diversity in the presence of competitive exclusion. Here we show that soil and plant-associated microbiota, cultivated ex situ in minimal synthetic environments with a single supplied source of carbon, universally re-assemble into large and dynamically stable communities with strikingly predictable coarse-grained taxonomic and functional compositions. We find that generic, non-specific metabolic cross-feeding leads to the assembly of dense facilitation networks that enable the coexistence of multiple competitors for the supplied carbon source. The inclusion of universal and non-specific cross-feeding in ecological consumer-resource models is sufficient to explain our observations, and predicts a simple determinism in community structure, a property reflected in our experiments.

ecology↗

bioRxiv2017

mobsim: An R package for the simulation and measurement of biodiversity across spatial scales

1. Estimating biodiversity and its changes in space and time poses serious methodological challenges. First, there has been a long debate on how to quantify biodiversity, and second, measurements of biodiversity change are scale-dependent. Therefore comparisons of biodiversity metrics between communities are ideally carried out across scales. Simulation can be used to study the utility of biodiversity metrics across scales, but most approaches are system specific and plagued by large parameter spaces and therefore cumbersome to use and interpret. However, realistic spatial biodiversity patterns can be generated without reference to ecological processes, which suggests a simple simulation framework could provide an important tool for ecologists.\n\n2. Here, we present the R package mobsim that allows users to simulate the abundances and the spatial distribution of individuals of different species. Users can define key properties of communities, including the total numbers of individuals and species, the relative abundance distribution, and the degree of spatial aggregation. Furthermore, the package provides functions that derive biodiversity patterns from simulated communities, or from observed data, as well as functions that simulate different sampling designs.\n\n3. We show several example applications of the package. First, we illustrate how species rarefaction and accumulation curves can be used to disentangle changes in the fundamental biodiversity components: (i) total abundance, (ii) relative abundance distribution, (iii) and species aggregation. Second, we demonstrate how mobsim can be used to assess the performance of species-richness estimators. The latter indicates how spatial aggregation challenges classical non-spatial species-richness estimators.\n\n4. mobsim allows the simulation and analysis of a large range of biodiversity scenarios and sampling designs in an efficient and comprehensive way. The simplicity and control provided by the package can also make it a useful didactic tool. The combination of controlled simulations and their analysis will facilitate a more rigorous interpretation of real world data that exhibit sampling effects and scale-dependence.

ecology↗

bioRxiv2017

An empirical test of the temperature dependence of carrying capacity

Predicting population persistence and dynamics in the context of global change is a major challenge for ecology. A widely held prediction is that population abundance at carrying capacity decreases with warming, assuming no change in resource supply, due to increased individual resource demands associated with higher metabolic rates. However, this prediction, which is based on metabolic scaling theory (MST), has not been tested empirically. Here we experimentally tested whether effects of temperature on short-term metabolic performance (rates of photosynthesis and respiration) translate directly to effects of temperature on population rates in a phytoplankton species. We found that effects of temperature on organismal metabolic rates matched theoretical predictions, and that the temperature dependence of individual metabolic performance translated to population abundance. Population abundance at carrying capacity, K, decreased with temperature less than expected based on the temperature dependence of photosynthesis. Concurrent with declines in abundance, we observed a linear decline in cell size of approximately 2.3% {degrees}C-1, which is consistent with broadly observed patterns in unicellular organisms, known as the temperature-size rule. When theoretical predictions include higher densities allowed by shifts toward smaller individual size, observed declines in K were quantitatively consistent with theoretical predictions. Our results indicate that outcomes of population dynamics across a range of temperatures reflect organismal responses to temperature via metabolic scaling, providing a general basis for forecasting population responses to global change.

ecology↗

bioRxiv2017

Exploiting delayed transitions to sustain semiarid ecosystems after catastrophic shifts

Semiarid ecosystems (including arid, semiarid and dry-subhumid ecosystems) span more than 40% of extant habitats and a similar percentage of human population. As a consequence of global warming, these habitats face future potential shifts towards the desert state characterized by an accelerated loss of diversity and stability leading to collapse. Such possibility has been raised by several mathematical and computational models, along with several early warning signal methods applied to spatial vegetation patterns. Here we show that just after a catastrophic shift has taken place an expected feature is the presence of a ghost, i.e., a delayed extinction associated to the underlying dynamical flows. As a consequence, a system might exhibit for very long times an apparent stationarity hiding in fact an inevitable collapse. Here we explore this problem showing that the ecological ghost is a generic feature of standard models of green-desert transitions including facilitation. If present, the ghost could hide warning signals, since statistical patterns are not be expected to display growing fluctuations over time. We propose and computationally test a novel intervention method based on the restoration of small fractions of desert areas with vegetation as a way to maintain the fragile ecosystem beyond the catastrophic shift caused by a saddle-node bifurcation, taking advantage of the delaying capacity of the ghost just after the bifurcation.

ecology↗

bioRxiv2017

Mouse lemurs and degraded habitat

Madagascar is known for its unique biodiversity including its endemic primates, the lemurs. This biodiversity is threatened by deforestation, forest degradation and anthropogenic disturbances. Several mouse lemurs (genus Microcebus) have been shown to cope with habitat disturbances and degradation. However, there are 24 recognized mouse lemur species living in very different habitats, and it is not clear whether all these species respond similarly to forest degradation. Here, we review the literature on mouse lemur use of degraded habitat. We further question whether mouse lemurs show variation in degraded habitat use, with respect to forest type, conservation status and distribution range. We show that data on degraded forest (DF) use is available for 14 species and geographically aggregated in a few locations. However, data are scarce for most species, and lacking for almost half of the currently recognized species. Our results however confirm that most mouse lemur species are able to cope with, but do not necessarily respond positively to habitat degradation. We found no variation in degraded habitat use, with respect to forest type, conservation status and distribution range. However, we identified food resources availability, understory structure, predation, and tree hole availability to be the most frequently invoked factors potentially influencing DF use. The relative frequency of these four factors vary among forest types suggesting that differences may exist but still require research efforts for ecological and environmental differences among regions to be fully understood.\n\nRESEARCH HIGHLIGHTSO_LILittle differences in the use of degraded forest (DF) between forest types, distribution ranges or conservation status.\nC_LIO_LIVarying factors potentially affecting DF use, such as food resources, forest structure, tree hole availability and predation.\nC_LI

ecology↗

bioRxiv2017

An agent-based model of cattle grazing toxic Geyer’s larkspur

By killing cattle and otherwise complicating management, the many species of larkspur (Delphinium spp.) present a serious, intractable, and complex challenge to livestock grazing management in the western United States. Among the many obstacles to improving our understanding of cattle-larkspur dynamics has been the difficulty of testing different grazing management strategies in the field, as the risk of dead animals is too great. Agent-based models (ABMs) provide an effective method of testing alternate management strategies without risk to livestock. ABMs are especially useful for modeling complex systems such as livestock grazing management, and allow for realistic bottom-up encoding of cattle behavior. Here, we introduce a spatially-explicit, behavior-based ABM of cattle grazing in a pasture with a dangerous amount of Geyers larkspur (D. geyeri). This model tests the role of herd cohesion and stocking density in larkspur intake, finds that both are key drivers of larkspur-induced toxicosis, and indicates that alteration of these factors within realistic bounds can mitigate risk. Crucially, the model points to herd cohesion, which has received little attention in the discipline, as playing an important role in lethal acute toxicosis. As the first ABM to model grazing behavior at realistic scales, this study also demonstrates the tremendous potential of ABMs to illuminate grazing management dynamics, including fundamental aspects of livestock behavior amidst ecological heterogeneity.

ecology↗

bioRxiv2017

Predator-prey feedback in a gyrfalcon-ptarmigan system?

Specialist predators with oscillating dynamics are often strongly affected by the population dynamics of their prey, yet they do not always participate in a predator-prey cycle. Only those that exert strong population regulation of their prey do so. Inferring the strength and direction of the predator-prey coupling from time series therefore requires contrasting models with top-down versus bottom-up predator-prey dynamics. We examine such population-level coupling using multivariate autoregressive models. The models translate several hypotheses for the joint dynamics of population densities of the Icelandic gyrfalcon Falco rusticolus, and its prey, the rock ptarmigan Lagopus muta. The dynamics of both species are likely not only linked to each other but also to stochastic weather variables acting as confounding factors on the joint dynamics. The classical MAR(1) model, used most often in ecology, predicts that the times series exhibit predator-prey feedback (i.e., Granger causality): the predator helps to explain prey dynamics and the prey helps to explain predator dynamics. Weather, in the form of spring temperature, influences gyrfalcon population growth but not ptarmigan population growth, despite individual-level evidence that ptarmigan chicks can be strongly affected by weather. MAR(2) models, allowing for species to cycle independently from each other, further suggests alternative scenarios where a cyclic prey influence its predator but not the other way around; such bottom-up models produce a better fit but less realistic cross-correlation patterns. Simulations of MAR(1) and MAR(2) models further demonstrate that the top-down MAR(1) models are most likely to be misidentified as bottom-up dynamics than vice-versa. We therefore conclude that predator-prey feedback in the gyrfalcon-ptarmigan system is very likely, though bottom-up dynamics cannot be excluded with certainty. We finally discuss what sort of information is needed to advance the characterization of joint predator-prey dynamics in birds and other vertebrates.

ecology↗

bioRxiv2017

The feasibility and stability of large complex biological networks: a random matrix approach

In his theoretical work of the 70s, Robert May introduced a Random Matrix Theory (RMT) approach for studying the stability of large complex biological systems. Unlike the established paradigm, May demonstrated that complexity leads to instability in generic models of biological networks. The RMT approach has since similarly been applied in many disciplines. Central to the approach is the famous \"circular law\" that describes the eigenvalue distribution of an important class of random matrices. However the \"circular law\" generally does not apply for ecological and biological systems in which density-dependence (DD) operates. Here we directly determine the far more complicated eigenvalue distributions of complex DD systems. A simple mathematical solution falls out, that allows us to explore the connection between feasible systems (i.e., having all equilibrium populations positive) and stability. In particular, for these RMT systems, almost all feasible systems are stable. The degree of stability, or resilience, is shown to depend on the minimum equilibrium population, and not directly on factors such as network topology.

ecology↗

bioRxiv2017

Demographic causes of adult sex ratio variation and their consequences for parental cooperation

The adult sex ratio (ASR) is a fundamental concept in population biology, sexual selection, and social evolution. However, it remains unclear which demographic processes generate ASR variation and how biases in ASR in turn affect social behaviour. Here, we evaluate the demographic mechanisms shaping ASR and their consequences for parental cooperation using detailed survival, fecundity, and behavioural data on 6,119 individuals from six wild shorebird populations exhibiting flexible parental strategies. We show that these closely related populations express strikingly different ASRs, despite having similar ecologies and life histories, and that ASR variation is largely driven by sex differences in the apparent survival of juveniles. Furthermore, families in populations with biased ASRs were predominantly tended by a single parent, suggesting that parental cooperation breaks down with unbalanced sex ratios. Taken together, our results indicate that sex biases emerging during early life have profound consequences for social behaviour.

ecology↗

bioRxiv2017

Metabolic traits predict the effects of warming on phytoplankton competition

Understanding how changes in temperature affect interspecific competition is critical for predicting changes in ecological communities as the climate warms. Here we develop a simple theoretical model that links interspecific differences in metabolic traits, which capture the temperature-dependence of resource acquisition, to the outcome of pairwise competition in phytoplankton. We parameterised our model with metabolic traits derived from six species of freshwater phytoplankton and tested its ability to predict the outcome of competition in all pairwise combinations of the species in a factorial experiment, manipulating temperature and nutrient availability. The model correctly predicted the outcome of competition in 71% of the pairwise experiments. These results demonstrate that metabolic traits play a key role in determining how changes in temperature influence interspecific competition and lay the foundation for developing theory to predict the effects of warming in complex, multi-species communities.

ecology↗