Biology subjects

Peres-Neto, P. R.

Publications and source records attributed to Peres-Neto, P. R..

5 recordsLinked to original sources

bioRxiv2024

rarestR: An R package using rarefaction metrics to estimate α-diversity (species richness) and β-diversity (species shared) for incomplete samples

Species abundance data is commonly used to study biodiversity patterns. In this context, estimating - and {beta}-diversity based on incomplete samples can lead to undersampling biases. It is therefore essential to employ methods that enable accurate comparisons of - and {beta}-diversity across varying sample sizes. This involves relying on biodiversity measures that are focused on accurately estimating the total number of species within a community, as well as the total number of species shared by two communities. Rarefaction offers such a method, where -diversity is estimated for standardized sample sizes. Rarefaction methods can also be used as a basis for {beta}-diversity calculations for standardized sample sizes. In this application note, we introduce a new R package, rarestR, designed to estimate abundance-based - and {beta}-diversity measures for inconsistent samples using rarefaction metrics. Additionally, the package offers parametric extrapolations to estimate the total expected number of species within a single community and the total expected number of species shared between two communities. Furthermore, it provides visualization for the curve fitting associated with these estimators. Overall, the rarestR package is useful in estimating - and {beta}-diversity values for incomplete samples, for example in studies involving highly mobile or species-rich taxa. These species estimators offer a complementary approach to non-parametric methods, such as the Chao series of estimators.

ecology↗

bioRxiv2023

Vive la difference: why, how, and what trait combinations improve functional community ecology

Analyses of functional trait variation across ecological communities offer valuable insights into the factors that influence and predict trait composition, deepening our understanding of community structure. These analyses also shed light on patterns of trait dispersion, including underdispersion and overdispersion, which are often linked to the mechanisms underlying community assembly. However, striking a balance between characterizing complex phenotypes through the integration of comprehensive set of traits while ensuring the preservation of the distinct signals of overdispersion and underdispersion can pose significant challenges. This is because some trait combinations can result in high functional dispersion or overdispersion, while others may lead to underdispersion within the same community. In this study, we provide a rationale for the importance of trait selection in community ecology and develop a framework that optimizes patterns of functional trait variation among communities. We explored the responses of six trait sets along large-scale environmental gradients, using [~]700 lake-fish communities in Ontario (Canada). We started by adopting the conventional approaches of combining all traits as well as leveraging prior knowledge in fish biology to group traits that are functionally related (Diet, Morphology, Temperature Preference). We contrasted these approaches with a novel computational method to select combinations of traits that maximise overdispersion and minimise underdispersion. We found that separating traits according to their functions or by their patterns revealed signals in communities that appeared random when all the traits were pooled together. Combining our computational approach with environmental models revealed that functional patterns could be very well explained by multiple environmental predictors (model R2 up to 0.7). Our study also outlines future selection procedures to further uncover more complex patterns of species associations based on their traits.

ecology↗

bioRxiv2023

Ecological selection of dispersal strategies in metacommunities: impact of landscape features and competitive dynamics

Dispersal is simultaneously a cause and a consequence of metacommunity dynamics. While the influence of dispersal on metacommunities is subject of intense research, we still do not understand how species-species and species-environment relationships determine the success of different dispersal strategies in metacommunities. To address this, we employed simulation models considering species with distinct context-dependent dispersal strategies involved in the three stages of dispersal (departure, transience, and settlement). These species were allowed to reach coexistence at the metacommunity scale under various competitive hierarchies and different levels of spatial and temporal environmental variability. By assessing the dispersal strategies of species that persisted and dominated metacommunities, we could understand how metacommunity dynamics impose ecological selection on dispersal. Our simulation model reproduced empirical patterns in species dispersal across different scales, ranging from changes in the success of dispersal strategies caused by local intraspecific and interspecific competition, to observed shifts in dispersal strategies along broad-scale ecological gradients. Additionally, we derived new empirically testable predictions regarding how metacommunity dynamics select for different dispersal strategies. Collectively, our results foster a comprehensive understanding of the factors influencing the success and diversity of dispersal strategies in a large array of ecological contexts.

ecology↗

bioRxiv2021

Metacommunities from bacteria to birds: stronger environmental effects in Mediterranean than in tropical ponds.

The metacommunity concept provides a theoretical framework that aims at explaining organism distributions by a combination of environmental filtering, dispersal and drift. With the development of statistical tools to quantify and partially isolate the role of each of these processes, empirical metacommunity studies have multiplied worldwide. However, few works attempt a multi-taxon approach and even fewer compare two distant biogeographical regions using the same methodology. Under this framework, we tested the expectation that temperate (mediterranean-climate) pond metacommunities would be more influenced by environmental and spatial processes than tropical ones, because of stronger environmental gradients and greater isolation of waterbodies. We surveyed 30 tropical and 32 mediterranean temporary ponds from Costa Rica and Spain, respectively, and obtained data on 49 environmental variables (including limnological, hydrogeomorphological, biotic, climatic, and landscape variables). We characterized the biological communities of Bacteria and Archaea (from both the water column and the sediments), phytoplankton, zooplankton, benthic invertebrates, amphibians and birds, and estimated the relative role of space and environment on metacommunity organization for each group and region, by means of variation partitioning using Generalized Additive Models (GAMs). Environmental selection was important in both tropical and mediterranean ponds, but markedly stronger in the latter, probably due to their larger limnological heterogeneity. Spatialized environment and pure spatial effects were greater in the tropics, related to higher climatic heterogeneity and dispersal processes (e.g. restriction, surplus) acting at different scales. The variability between taxonomic groups in spatial and environmental contributions was very wide. Effects on passive and active dispersers were similar within regions but different across regions, with higher environmental effects in mediterranean active dispersers. The residual (unexplained) variation was larger in tropical pond metacommunities, suggesting a higher role for stochastic processes and/or effects of biotic interactions in the tropics. Overall, these results provide support, for a wide variety of organisms related to aquatic habitats, for the classical view of stronger abiotic niche constraints in temperate areas compared to the tropics.

ecology↗

bioRxiv2018

Towards an applied metaecology

The complexity of ecological systems is a major challenge for practitioners and decision-makers who work to avoid, mitigate and manage environmental change. Here, we illustrate how metaecology - the study of spatial interdependencies among ecological systems through fluxes of organisms, energy, and matter - can enhance understanding and improve managing environmental change at multiple spatial scales. We present several case studies illustrating how the framework has leveraged decision-making in conservation, restoration and risk management. Nevertheless, an explicit incorporation of metaecology is still uncommon in the applied ecology literature, and in action guidelines addressing environmental change. This is unfortunate because the many facets of environmental change can be framed as modifying spatial context, connectedness and dominant regulating processes - the defining features of metaecological systems. Narrowing the gap between theory and practice will require incorporating system-specific realism in otherwise predominantly conceptual studies, as well as deliberately studying scenarios of environmental change.

ecology↗