Network structure of avian mixed-species flocks decays with elevation and latitude across the Andes.

Birds in mixed-species flocks benefit from greater foraging efficiency and reduced predation, but also face costs related to competition and activity matching. Because this cost-benefit trade-off is context-dependent (e.g. abiotic conditions and habitat quality), the structure of flocks is expected to vary along elevational, latitudinal and disturbance gradients. Specifically, we predicted that the connectivity and cohesion of flocking networks would (i) decline towards tropical latitudes and lower elevations, where competition and activity matching costs are higher, and (ii) increase with lower forest cover and greater human disturbance. We analysed the structure of 84 flock networks across the Andes and assessed the effect of elevation, latitude, forest cover and human disturbance on network characteristics. We found that Andean flocks are overall open-membership systems (unstructured), though the extent of network structure varied across gradients. Elevation was the main predictor of structure, with more connected and less modular flocks upslope. As expected, flocks in areas with higher forest cover were less cohesive, with better defined flock subtypes. Flocks also varied across latitude and disturbance gradients as predicted, but effect sizes were small. Our findings indicate that the unstructured nature of Andean flocks might arise as a strategy to cope with harsh environmental conditions. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'

Consequences of Intraspecific Variation in Seed Dispersal for Plant Demography, Communities, Evolution and Global Change

As the single opportunity for plants to move, seed dispersal has an important impact on plant fitness, species distributions and patterns of biodiversity. However, models that predict dynamics such as risk of extinction, range shifts and biodiversity loss tend to rely on the mean value of parameters and rarely incorporate realistic dispersal mechanisms. By focusing on the mean population value, variation among individuals or variability caused by complex spatial and temporal dynamics is ignored. This calls for increased efforts to understand individual variation in dispersal and integrate it more explicitly into population and community models involving dispersal. However, the sources, magnitude and outcomes of intraspecific variation in dispersal are poorly characterized, limiting our understanding of the role of dispersal in mediating the dynamics of communities and their response to global change. In this manuscript, we synthesize recent research that examines the sources of individual variation in dispersal and emphasize its implications for plant fitness, populations and communities. We argue that this intraspecific variation in seed dispersal does not simply add noise to systems, but, in fact, alters dispersal processes and patterns with consequences for demography, communities, evolution and response to anthropogenic changes. We conclude with recommendations for moving this field of research forward

Consequences of Intraspecific Variation in Seed Dispersal for Plant Demography, Communities, Evolution and Global Change

As the single opportunity for plants to move, seed dispersal has an important impact on plant fitness, species distributions and patterns of biodiversity. However, models that predict dynamics such as risk of extinction, range shifts and biodiversity loss tend to rely on the mean value of parameters and rarely incorporate realistic dispersal mechanisms. By focusing on the mean population value, variation among individuals or variability caused by complex spatial and temporal dynamics is ignored. This calls for increased efforts to understand individual variation in dispersal and integrate it more explicitly into population and community models involving dispersal. However, the sources, magnitude and outcomes of intraspecific variation in dispersal are poorly characterized, limiting our understanding of the role of dispersal in mediating the dynamics of communities and their response to global change. In this manuscript, we synthesize recent research that examines the sources of individual variation in dispersal and emphasize its implications for plant fitness, populations and communities. We argue that this intraspecific variation in seed dispersal does not simply add noise to systems, but, in fact, alters dispersal processes and patterns with consequences for demography, communities, evolution and response to anthropogenic changes. We conclude with recommendations for moving this field of research forward

AVONET: Morphological, ecological and geographical data for all birds

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.Fil: Tobias, Joseph A.. Imperial College London; Reino Unido. University of Oxford; Reino UnidoFil: Sheard, Catherine. University of Oxford; Reino Unido. University of Bristol; Reino UnidoFil: Pigot, Alex L.. University of Oxford; Reino Unido. University College London; Estados UnidosFil: Devenish, Adam J. M.. Imperial College London; Reino UnidoFil: Yang, Jingyi. Imperial College London; Reino UnidoFil: Sayol, Ferran. University College London; Estados UnidosFil: Neate Clegg, Montague H. C.. University of Oxford; Reino Unido. University of Utah; Estados UnidosFil: Alioravainen, Nico. University of Oxford; Reino Unido. Natural Resources Institute Finland; FinlandiaFil: Weeks, Thomas L.. Imperial College London; Reino Unido. Natural History Museum; Reino UnidoFil: Barber, Robert A.. Imperial College London; Reino UnidoFil: Walkden, Patrick A.. Imperial College London; Reino Unido. Natural History Museum; Reino UnidoFil: MacGregor, Hannah E. A.. University of Oxford; Reino Unido. University of Bristol; Reino UnidoFil: Jones, Samuel E. I.. University of Oxford; Reino Unido. University of London; Reino UnidoFil: Vincent, Claire. Organización de Las Naciones Unidas; ArgentinaFil: Phillips, Anna G.. Senckenberg Biodiversity And Climate Research Centre; AlemaniaFil: Marples, Nicola M.. Trinity College; Estados UnidosFil: Montaño Centellas, Flavia A.. Universidad Mayor de San Andrés; Bolivia. University of Florida; Estados UnidosFil: Leandro Silva, Victor. Universidade Federal de Pernambuco; BrasilFil: Claramunt, Santiago. University of Toronto; Canadá. Royal Ontario Museum; CanadáFil: Darski, Bianca. Universidade Federal do Rio Grande do Sul; BrasilFil: Freeman, Benjamin G.. University of British Columbia; CanadáFil: Bregman, Tom P.. University of Oxford; Reino Unido. Future-Fit Foundation; Reino UnidoFil: Cooney, Christopher R.. University Of Sheffield; Reino UnidoFil: Hughes, Emma C.. University Of Sheffield; Reino UnidoFil: Capp, Elliot J. R.. University Of Sheffield; Reino UnidoFil: Varley, Zoë K.. University Of Sheffield; Reino Unido. Natural History Museum; Reino UnidoFil: Friedman, Nicholas R.. Okinawa Institute of Science and Technology Graduate University; JapónFil: Korntheuer, Heiko. Johannes Gutenberg Universitat Mainz; AlemaniaFil: Corrales Vargas, Andrea. Universidad Nacional de Costa Rica; Costa RicaFil: García, Natalia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; Argentin

AVONET: morphological, ecological and geographical data for all birds

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species‐level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity

Ecological drivers of avian community assembly along a tropical elevation gradient

Community assembly theory hypothesizes that two main niche-based processes act to shape composition and organization of biological assemblages: abiotic filtering and biological interactions. Here, we conducted repeated surveys of bird abundance along an undisturbed elevational gradient in the tropical Andes to investigate 1) signals of deterministic processes driving community assembly and 2) potential mechanisms by which these forces operate (temperature, habitat complexity, fruit and insect availability), while correcting for imperfect detection and modeling species abundances with N-mixture models. We observed strong signals of abiotic filtering driving functionally and phylogenetically clustered assemblages towards higher elevations, and a weaker signal of limiting similarity resulting in few overdispersed assemblages at lower elevations. Whereas the decay in species richness with increasing elevation was explained by temperature, trait and phylogenetic dispersion were explained by both temperature and vegetation structure, implying that an interplay of abiotic and biotic mechanisms determines abundance-based community structure in our montane assemblages. Interestingly, trait and phylogenetic dispersion consistently decreased until ~3000 m but increased above this elevation, highlighting a potential role of competition in resource-scarce habitats. Combined, our findings suggest abiotic filters are still the main process shaping montane biotas across elevations, whereas resource availability might act locally upon assemblages further modifying them. Our study challenges recent studies in tropical mountains that suggest that biotic filters are a stronger force than abiotic filters in shaping tropical montane assemblages, and exemplifies how accounting for imperfect detection might overcome potential biases in detecting environmental filtering signals in community assembly studies

Taxonomic and Phylogenetic Determinants of Functional Composition of Bolivian Bat Assemblages.

Understanding diversity patterns and the potential mechanisms driving them is a fundamental goal in ecology. Examination of different dimensions of biodiversity can provide insights into the relative importance of different processes acting upon biotas to shape communities. Unfortunately, patterns of diversity are still poorly understood in hyper-diverse tropical countries. Here, we assess spatial variation of taxonomic, functional and phylogenetic diversity of bat assemblages in one of the least studied Neotropical countries, Bolivia, and determine whether changes in biodiversity are explained by the replacement of species or functional groups, or by differences in richness (i.e., gain or loss of species or functional groups). Further, we evaluate the contribution of phylogenetic and taxonomic changes in the resulting patterns of functional diversity of bats. Using well-sampled assemblages from published studies we examine noctilionoid bats at ten study sites across five ecoregions in Bolivia. Bat assemblages differed from each other in all dimensions of biodiversity considered; however, diversity patterns for each dimension were likely structured by different mechanisms. Within ecoregions, differences were largely explained by species richness, suggesting that the gain or loss of species or functional groups (as opposed to replacement) was driving dissimilarity patterns. Overall, our results suggest that whereas evolutionary processes (i.e., historical connection and dispersal routes across Bolivia) create a template of diversity patterns across the country, ecological mechanisms modify these templates, decoupling the observed patterns of functional, taxonomic and phylogenetic diversity in Bolivian bats. Our results suggests that elevation represents an important source of variability among diversity patterns for each dimension of diversity considered. Further, we found that neither phylogenetic nor taxonomic diversity can fully account for patterns of functional diversity, highlighting the need for examining different dimensions of biodiversity of bats in hyperdiverse ecosystems

UPGMA clustering dendrograms for (A) functional, (B) phylogenetic and (C) taxonomic diversity of bats in ten assemblages across ecoregions in Bolivia.

<p>UPGMAs are calculated on relative abundance data and based on Sorensen’s dissimilarity indexes for functional and taxonomic diversity, and on the UniFrac metric for phylogenetic diversity.</p

Fit of cluster algorithms to distance matrices of functional, taxonomic and phylogenetic diversity, as explained by the cophenetic correlation and the agglomerative coefficient.

<p>Fit of cluster algorithms to distance matrices of functional, taxonomic and phylogenetic diversity, as explained by the cophenetic correlation and the agglomerative coefficient.</p