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At least 415 records · Page 23Linked to original sources

bioRxiv2015

Historic and prehistoric human-driven extinctions have reshaped global mammal diversity patterns

AimTo assess the extent to which humans have reshaped Earths biodiversity, by estimating natural ranges of all late Quaternary mammalian species, and to compare diversity patterns based on these with diversity patterns based on current distributions.\n\nLocationGlobally\n\nMethodsWe estimated species, functional and phylogenetic diversity patterns based on natural ranges of all mammalian species (n=5747 species) as they could have been today in the complete absence of human influence through time. Following this we compared macroecological analyses of current and natural diversity patterns to assess if human-induced range changes bias for evolutionary and ecological analyses based on current diversity patterns.\n\nResultsWe find that current diversity patterns have been drastically modified by humans, mostly due to global extinctions and regional to local extirpations. Current and natural diversities exhibit marked deviations virtually everywhere outside sub-Saharan Africa. These differences are strongest for terrestrial megafauna, but also important for all mammals combined. The human-induced changes led to biases in estimates of environmental diversity drivers, especially for terrestrial megafauna, but also for all mammals combined.\n\nMain conclusionsOur results show that fundamental diversity patterns have been reshaped by human-driven extinctions and extirpations, highlighting humans as a major force in the Earth system. We thereby emphasize that estimating natural distributions and diversities is important to improve our understanding of the evolutionary and ecologically drivers of diversity as well as for providing a benchmark for conservation.

Ecology↗

bioRxiv2015

Evolutionarily induced alternative states and coexistence in systems with apparent competition

AO_SCPLOWBSTRACTC_SCPLOWPredators often consume multiple prey and by mutually subsidizing a shared predator, the prey may reciprocally harm each other. When predation levels are high, this apparent competition can culminate in a prey species being displaced. Coupling quantitative genetics and Lotka-Volterra models, we study how predator evolution alters this and other ecological outcomes. These models account for a trade-off between the predators attack rates on two prey species. We provide a mathematical characterization of a strong form of persistence-permanence-for which there is a global attractor bounded away from extinction. When the evolutionary dynamics occur at a sufficiently slower time scale than the ecological dynamics, we also characterize attractors and their basins of attraction using singular perturbation theory and a graphical approach to the eco-evolutionary dynamics. Our results show that eco-evolutionary feedbacks can mediate permanence at intermediate trade-offs in the attack rates. However, at strong trade-offs, permanence is lost. Despite this loss of permanence, there can be attractors supporting coexistence. These attractors, however, may coincide with attractors at which the predator is excluded. Our results highlight that evo-evolutionary feedbacks can alter community structure by mediating coexistence or leading to trait-dependent alternative stable states.

Ecology↗

bioRxiv2015

Inferring species interactions from co-occurrence data with Markov networks

Inferring species interactions from co-occurrence data is one of the most controversial tasks in community ecology. One difficulty is that a single pairwise interaction can ripple through an ecological network and produce surprising indirect consequences. For example, the negative correlation between two competing species can be reversed in the presence of a third species that is capable of outcompeting both of them. Here, I apply models from statistical physics, called Markov networks or Markov random fields, that can predict the direct and indirect consequences of any possible species interaction matrix. Interactions in these models can also be estimated from observed co-occurrence rates via maximum likelihood, controlling for indirect effects. Using simulated landscapes with known pairwise interaction strengths, I evaluated Markov networks and six existing approaches. The Markov networks consistently outperformed other methods, correctly isolating direct interactions between species pairs even when indirect interactions or abiotic factors largely overpowered them. Two computationally efficient approximations, based on controlling for indirect effects with linear or generalized linear models, also performed well. Indirect effects reliably caused a common null modeling approach to produce incorrect inferences, however.

Ecology↗

bioRxiv2015

A common framework for identifying linkage rules across different types of interactions

Species interactions, ranging from antagonisms to mutualisms, form the architecture of biodiversity and determine ecosystem functioning. Understanding the rules responsible for who interacts with whom, as well as the functional consequences of these interspecific interactions, is central to predicting community dynamics and stability. Species traits sensu lato may affect different ecological processes determining species interactions through a two-step process. First, ecological and life-history traits govern species distributions and abundance, and hence determine species co-occurrence, which is a prerequisite for them to interact. Second, morphological traits between co-occurring potential interaction partners should match for the realization of an interaction. Moreover, inferring functioning from a network of interactions may require the incorporation of interaction efficiency. This efficiency may be also trait-mediated, and can depend on the extent of matching, or on morphological, physiological or behavioural traits. It has been shown that both neutral and trait-based models can predict the general structure of networks, but they rarely accurately predict individual interactions, suggesting that these models may be predicting the right structure for the wrong reason. We propose to move away from testing null models with a framework that explicitly models the probability of interaction among individuals given their traits. The proposed models integrate both neutral and trait-matching constraints while using only information about known interactions, thereby overcoming problems originating from under-sampling of rare interactions (i.e. missing links). They can easily accommodate qualitative or quantitative data, and can incorporate trait variation within species, such as values that vary along developmental stages or environmental gradients. We use three case studies to show that they can detect strong trait matching (e.g. predator-prey system), relaxed trait matching (e.g. herbivore-plant system) and barrier trait matching (e.g. plant-pollinator systems). Only by elucidating which species traits are important in each process, i.e. in determining interaction establishment, frequency, and efficiency, can we advance in explaining how species interact and the consequences for ecosystem functioning.

Ecology↗

bioRxiv2015

COMADRE: a global database of animal demography

O_LIThe open-access scientific philosophy has been widely adopted and proven to promote considerable progress in the fields of ecology and evolution. Openaccess global databases now exist on animal migration, the distribution of species, and conservation status, to mention a few. However, a gap exists for databases on population dynamics spanning the rich diversity of the animal kingdom. This information is fundamental to our understanding of the conditions that have shaped variation in animal life histories and their relationships with the environment. Furthermore, an animal populations schedules of reproduction and mortality determine its invasive potential, and its risk of local extinction, which are at the core of conservation biology.\nC_LIO_LIMatrix population models (MPMs) are among the most widely used demographic tools by animal ecologists. MPMs project population dynamics in terms of reproduction, mortality, and development over the entire life cycle. The results of MPMs have direct biological interpretations, facilitating comparisons among animal species as different as Caenorhabditis elegans, Loxodonta africana and Homo sapiens.\nC_LIO_LIThousand of animal demographic records exist in the form of MPMs, but they are dispersed throughout the literature, rendering comparative analyses difficult. Here, we introduce the COMADRE Animal Matrix Database version 1.0.0, an open-source online repository containing data on 402 species worldwide, from 272 studies, with a total of 1,575 population projection matrices. COMADRE also contains ancillary information (e.g. ecoregion, taxonomy, biogeography, etc.) that facilitates interpretation of the numerous demographic metrics that can be derived from its MPMs.\nC_LIO_LISynthesis: We introduce the COMADRE Animal Matrix Database, a resource for animal demography. The open access nature of this database, together with its ancillary information will facilitate comparative analysis, as will the growing availability of databases focusing on other traits, and tools to query and combine them. Through future frequent updates of COMADRE, and its integration with other online resources, we encourage animal ecologists to tackle global ecological and evolutionary questions with unprecedented statistical power.\nC_LI

Ecology↗

bioRxiv2015

Can functional traits explain phylogenetic signal in the composition of a plant community?

Phylogeny-based and functional trait-based analyses are two principle ways to study community assembly and underlying ecological processes. In principle, knowing all information about species traits would make phylogenetic information redundant, at least that component of phylogenetic signal in the distribution of species among communities that is caused by phylogenetically related species sharing similar traits. In reality, phylogenies may contain more information than a set of singular, discretely measured traits because we cannot measure all species traits and may misjudge which are most important. The extent to which functional trait information makes phylogenetic information redundant, however, has not been explicitly studied with empirical data in community ecology. Here, we use phylogenetic linear mixed models to analyze community assembly of 55 understory plant species in 30 forest sites in central Wisconsin. These communities show strong phylogenetic attraction, yet variation among sites in 20 environmental variables could not account for this pattern. Most of the 15 functional traits we measured had strong phylogenetic signal, but only three varied strongly among sites in ways that affected species abundances. These three traits explained only 19% of variation in phylogenetic patterns of species co-occurrence. Thus, phylogenies appear to provide considerably more information about community assembly than the functional traits measured in this study, demonstrating the value of phylogeny in studying of community assembly processes even with abundant functional traits.

Ecology↗

bioRxiv2016

The Effect of Anthropogenic Land Cover Change on Pollen-Vegetation Relationships in the American Midwest

Fossil pollen assemblages are widely used to reconstruct past vegetation community composition at time scales ranging from centuries to millennia. These reconstructions often are based on the observed relationships between the proportions of plant taxa in the source vegetation and the proportions of the corresponding pollen types in pollen assemblages collected from surface sediments. Pollen-vegetation models rely upon parameters whose values typically are assumed to be stable through time, but this assumption is largely unevaluated, due in part to the rarity of comprehensive forest data, particularly for earlier time periods.\n\nHere we present a new dataset of early settlement-era pollen records for the upper Midwest of North America and combine it with three other pollen and forest composition datasets to assess the stability of the relationship between relative pollen composition and relative abundances of tree genera for two time periods: immediately prior to Euro-American settlement, and the late 20th Century. Over this time interval, Euro-American settlement resulted in widespread forest clearance for agriculture and logging, producing major changes to forest composition and structure and the pollen assemblages produced by these forests. These major changes provide an opportunity to test the constancy of the relationship between pollen and forest vegetation during a period of large vegetation change. Pollen-vegetation relationships are modeled, using a Generalized Linear Model, for thirteen upper Midwestern tree genera.\n\nWe find that estimates of pollen source radius for the gridded mesoscale data are 25-85 kilometers, consistent with prior studies. Pollen-vegetation relationships are significantly altered for several genera: Fagus, Betula, Tsuga, Quercus, Pinus, and Picea (p < 0.05). The use of contemporary pollen-vegetation relationships to model settlement era community composition significantly under-predicts the presence of Fagus, Betula, Tsuga, Quercus and Picea at all tree densities. Pinus is over-predicted at low relative proportions (<25%), but under-predicted at greater abundances. The divergence of pollen-vegetation relationships appears to be greatest for late-successional taxa characterized by high shade tolerance and low fire tolerance, although the statistical power is low for this analysis.\n\nHence, the ongoing rapid changes in land use and ecological communities associated with the Anthropocene affect not just our ability to make confident ecological forecasts for the future, but can also modify our inferences about the past. In the Anthropocene era, characterized by its rapidly changing vegetation and climates, paleoecology must move from its traditional reliance on spatial calibration datasets assumed to represent a single \"present\". Instead, when possible, paleoecologists should develop calibration datasets of pollen and forest composition that are distributed across major vegetation changes in time and space. Multitemporal calibration datasets are increasingly possible given the growing length and availability of vegetation observational data and will enable paleoecologists to better understand the complex processes governing pollen-vegetation relationships and make better-informed reconstructions of past vegetation dynamics.

Ecology↗

bioRxiv2016

Bimodal occupancy-frequency distributions uncover the importance of regional dynamics in shaping marine microbial biogeography

Metapopulation theory developed in terrestrial ecology provides applicable frameworks for interpreting the role of local and regional processes in shaping species distribution patterns. Yet, empirical testing of metapopulation models on microbial communities is essentially lacking. Here we determined regional bacterioplankton dynamics from monthly transect sampling in the Baltic Sea Proper (16 sites, 11 occasions, 2010-2011) using 16S rRNA gene pyrosequencing. A strong positive correlation was found between local relative abundance and occupancy of populations. Notably, the occupancy-frequency distributions (the number of populations occupying different number of sites) were significantly bimodal with a satellite mode of mostly rare endemic populations and a core mode of abundant cosmopolitan populations (e.g. Synechococcus, SAR11 and SAR86 clade members). Observed temporal changes in population distributions supported theoretical predictions that stochastic variation in local extinction and colonization rates accounted for observed bimodality. Moreover, bimodality was found for bacterioplankton across the entire Baltic Sea, and was also frequent in globally distributed datasets where average Bray-Curtis distances were significantly different between bimodal and non-bimodal datasets. Still, datasets spanning waters with distinct physicochemical characteristics or environmental gradients, e.g. brackish and marine or surface to deep waters, typically lacked significant bimodal patterns. When such datasets were divided into subsets with coherent environmental conditions, bimodal patterns emerged, highlighting the importance of positive feedbacks between local abundance and occupancy within specific biomes. Thus, metapopulation theory applied to microbial biogeography can provide novel insights into the mechanisms governing shifts in biodiversity resulting from natural or anthropogenically induced changes in the environment.\n\nSignificance statementMarine bacteria regulate global cycles of elements essential to life and respond rapidly to environmental change. Yet, the ecological factors that determine distribution and activity patterns of microbial populations across different spatial scales and environmental gradients remain basically unconstrained. Our metapopulation model-based analyses show that dispersal-driven processes contribute to structuring the biogeography of marine microorganisms from small to large geographical areas. Discovery of bimodal distribution patterns pinpointed satellite microbial populations with highly restricted ranges and defined abundant core populations widely distributed in coherence with environmental conditions. Thus, application of metapopulation models on microbial community structure may allow the definition of biogeographic regions critical for interpreting the outcome of future ocean changes.\n\nClassificationBiological Sciences, Environmental Sciences

Ecology↗

bioRxiv2016

A Family of Interaction-Adjusted Indices of Community Similarity

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assess the performance of two specific indices which are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.

Ecology↗

bioRxiv2016

The behaviour of hoverfly larvae (Diptera, Syrphidae) lessens the effects of floral subsidy in agricultural landscapes

Modern agricultural landscapes favour crop pests: herbivores benefit from resource concentration and/or the absence of natural enemies in large areas of intensively farmed fields interspersed by small fragments of natural or non-crop habitats.\n\nConservation biological control (CBC) aims at increasing the functional diversity of agricultural landscapes to make them more hospitable to natural enemies, and less to herbivores. Although natural enemies readily respond to this management, very few studies assess if they succeed in effectively protecting crops.\n\nWe set up a field experiment to study if an ecological infrastructure varying in size and consisting of the provision of floral resources at the centre of lettuce plots would influence the number of eggs laid by hoverflies, and ultimately the control of lettuce aphids. We found that the hoverfly females lay more eggs in the plots with the larger flower resource compared to the control. However, this response had no impact on the abundance of aphids on the lettuces.\n\nWe designed two laboratory experiments to understand this absence of response. We found mutual interference between hoverfly larvae, and suggest it may undermine the biological control of aphids.\n\nThis mismatch between landscape management and the response of hoverflies indicates CBC should take into account insect behaviour, particularly their response to conspecific density, additionally to landscape ecology.

Ecology↗

bioRxiv2016

Empirical modelling of trait selection by partitioning selection into direct selection and selection that is mediated by interspecific interactions

Trait selection has received considerable attention in the pursuit to understand niche-based community assembly processes and to generate ecological predictions. To further advance the study of trait selection, a conceptual statistical model is presented that outlines and discuss the possibilities of i) estimating the effect of interspecific interactions on traits rather than just testing weather selection has had an effect on the observed trait distributions, ii) discriminating between environmental filtering and niche partitioning processes and estimate the characteristic features and importance of both processes, and iii) predicting the effect of environmental changes and gradients on trait selection. To achieve these goals a number of necessary assumptions have to be specified and these assumptions are discussed and assessed. Simulated plant cover data from a simple uniform environment was successfully fitted to the model and the results indicates that it is possible to partition direct population growth and population growth that is mediated by interspecific interaction. The data requirements of the model are modest, i.e. time series data on plant species abundance and a species trait matrix. Consequently, the model concept may be used to model trait selection, including the effect of interspecific interactions, in many existing plant ecological datasets.

Ecology↗

bioRxiv2016

Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts

Multiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virusmicrobe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean-field model. We also observe longtails in the distribution of the multiplicity of infection (MOI) in contrast to mean-field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.

Ecology↗

bioRxiv2016

Modeling Joint Abundance of Multiple Species Using Dirichlet Process Random Effects

We present a method for modeling multiple species distributions simultaneously using Dirichlet Process random effects to cluster species into guilds. Guilds are ecological groups of species that behave or react similarly to some environmental conditions. By modeling latent guild structure, we capture the cross-correlations in abundance or occurrence of species over surveys. In addition, ecological information about the community structure is obtained as a byproduct of the model. By clustering species into similar functional groups, prediction uncertainty of community structure at additional sites is reduced over treating each species separately. The method is illustrated with a small simulation demonstration, as well as an analysis of a mesopelagic fish survey from the eastern Bering Sea near Alaska. The simulation data analysis shows that guild membership can be extracted as the differences between groups become larger and if guild differences are small the model naturally collapses all the species into a small number of guilds which increases predictive efficiency by reducing the number of parameters to that which is supported by the data.

Ecology↗

bioRxiv2016

Significant competitive dominance in mid-latitude European plant communities

Understanding the main determinants of species coexistence across space and time is a central question in ecology. However, ecologists still know little about the scales and conditions at which biotic interactions matter and their interplay with the environment to structure species assemblages. Here we develop ecological theory to analyze plant distribution and trait data across Europe and find that plant height clustering is related to evapotranspiration and gross primary productivity. Our analysis suggests competitive dominance as a plausible mechanism underlying community assembly patterns over these continental scales. In particular, we find a clear signal of plant-to-plant competition in mid-latitude ecoregions, where conditions for growth (reflected in actual evapotranspiration rates and gross primary productivities) are optimal. Under severe conditions, either climate is too harsh and overrides the effect of competition or other interactions play a relevant role. Our approach bridges the gap between modern coexistence theory and large-scale species distribution data analysis.

Ecology↗

bioRxiv2016

Managing Marine Ecosystems as Complex Adaptive Systems: Emergent Patterns, Critical Transitions, and Public Goods

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.

Ecology↗

bioRxiv2016

The Forest, the Trees, and the Phylo-diversity Jungle

The joint use of phylogenetic trees and ecological data has proven useful for many aspects of ecology. However, there are a multitude of phylo-diversity metrics with complex interdependencies and mathematical redundancies (the so-called jungle of metrics). Several recentpapers have been trying to map this jungle but appear at a first glance to contradict each other. We suggest that these contradictory results are in fact complementary and reflect two approaches to understand diversity metrics: the first focuses on general mathematical properties,the second focuses on assessing metric performance in relation to particular questions.In this manuscript, we discuss the complementarity of the two approaches and in particular how recent papers fit into this categorisation.

Ecology↗

bioRxiv2016

Morphological structure of ant assemblages in tropical and temperate forests

Morphological variation in co-occurring species often is used to infer species assembly rules and other processes structuring ecological assemblages. We compared the morphological structure of ant assemblages in two biogeographic regions along two extensive latitudinal gradients to examine common patterns and unique characteristics of trait distribution. We sampled ant assemblages along extensive latitudinal gradients in Tropical Atlantic Forest in eastern Brazil and temperate forests in the eastern United States. We quantified 14 morphological traits related to the ecology and life history of each of 599 ant species and defined the morphological space occupied by different ant assemblages. Null models were used to test whether tropical and temperate ant assemblages differed from random expectation in morphological structure. Correlations between traits and climate were used to infer associations between habitat characteristics and morphological space occupied by ant assemblages. Tropical ant assemblages had higher morphological diversity and variation in the space of occupied morphospace, whereas temperate assemblages had higher variance in size. Although tropical ant assemblages had smaller morphological distances among species, species packing (i.e., mean nearest-neighbor distance) did not differ between regions. Null model analysis revealed scant evidence of habitat filtering or niche differentiation within assemblages. Different traits had different means, variances, skewness, and kurtosis values along each environmental gradient. Mean trait values within assemblages were associated mainly with region and correlated with temperature but trait variances had more complex responses to climate, including interactions between temperature and precipitation in the models. The higher functional diversity in tropical ant assemblages occurs by expansion of the morphospace rather than through an increase in species packing. Different traits vary independently along environmental gradients. Analysis of individual traits together with categorization of the moments of trait distributions (statistical central tendencies) provide new directions for quantifying morphological diversity in ant assemblages.

Ecology↗

bioRxiv2016

Evolution of natal dispersal in spatially heterogenous environments

Understanding the evolution of dispersal is an important issue in evolutionary ecology. For continuous time models in which individuals disperse throughout their lifetime, it has been shown that a balanced dispersal strategy, which results in an ideal free distribution, is evolutionary stable in spatially varying but temporally constant environments. Many species, however, primarily disperse prior to reproduction (natal dispersal) and less commonly between reproductive events (breeding dispersal). These species include territorial species such as birds and reef fish, and sessile species such as plants, and mollusks. As demographic and dispersal terms combine in a multiplicative way for models of natal dispersal, rather than the additive way for the previously studied models, we develop new mathematical methods to study the evolution of natal dispersal for continuous-time and discrete-time models. A fundamental ecological dichotomy is identified for the non-trivial equilibrium of these models: (i) the per-capita growth rates for individuals in all patches are equal to zero, or (ii) individuals in some patches experience negative per-capita growth rates, while individuals in other patches experience positive per-capita growth rates. The first possibility corresponds to an ideal-free distribution, while the second possibility corresponds to a \"source-sink\" spatial structure. We prove that populations with a dispersal strategy leading to an ideal-free distribution displace populations with dispersal strategy leading to a source-sink spatial structure. When there are patches which can not sustain a population, ideal-free strategies can be achieved by sedentary populations, and we show that these populations can displace populations with any irreducible dispersal strategy. Collectively, these results support that evolution selects for natal or breeding dispersal strategies which lead to ideal-free distributions in spatially heterogenous, but temporally homogenous, environments.

Ecology↗