Species niches, not traits, determine abundance and occupancy patterns: A multi‐site synthesis

International audienceAim: Locally abundant species are usually widespread, and this pattern has been related to properties of the niches and traits of species. However, such explanations fail to account for the potential of traits to determine species niches and often overlook statistical artefacts. Here, we examine how trait distinctiveness determines the abilities of species to exploit either common habitats (niche position) or a range of habitats (niche breadth) and how niche position and breadth, in turn, affect abundance and occupancy. We also examine how statistical artefacts moderate these relationships. Location: Sixteen sites in the Neotropics. Time period 1993–2014. Major taxa studied Aquatic invertebrates from tank bromeliads. Methods: We measured the environmental niche position and breadth of each species and calculated its trait distinctiveness as the average trait difference from all other species at each site. Then, we used a combination of structural equation models and a meta-analytical approach to test trait–niche relationships and a null model to control for statistical artefacts. Results: The trait distinctiveness of each species was unrelated to its niche properties, abundance and occupancy. In contrast, niche position was the main predictor of abundance and occupancy; species that used the most common environmental conditions found across bromeliads were locally abundant and widespread. Contributions of niche breadth to such patterns were attributable to statistical artefacts, indicating that effects of niche breadth might have been overestimated in previous studies. Main conclusions: Our study reveals the generality of niche position in explaining one of the most common ecological patterns. The robustness of this result is underscored by the geographical extent of our study and our control of statistical artefacts. We call for a similar examination across other systems, which is an essential task to understand the drivers of commonness across the tree of life

Data from: The influence of spatial sampling scales on ant-plant interaction network architecture

1.Despite great interest in metrics to quantify the structure of ecological networks, the effects of sampling and scale remain poorly understood. In fact, one of the most challenging issues in ecology is how to define suitable scales (i.e., temporal or spatial) to accurately describe and understand ecological systems. 2.Here, we sampled a series of ant‐plant interaction networks in the southern Brazilian Amazon rainforest in order to determine whether the spatial sampling scale, from local to regional, affects our understanding of the structure of these networks. 3.To this end, we recorded ant‐plant interactions in adjacent 25 x 30 m subplots (local sampling scale) nested within twelve 250 x 30 m plots (regional sampling scale). Moreover, we combined adjacent or random subplots and plots in order to increase the spatial sampling scales at the local and regional levels. We then calculated commonly used binary and quantitative network‐level metrics for both sampling scales (i.e., number of species and interactions, nestedness, specialization, and modularity), all of which encompass a wide array of structural patterns in interaction networks. 4.We observed increasing species and interactions across sampling scales, and while most network descriptors remained relatively constant at the local level, there was more variation at the regional scale. Among all metrics, specialization was most constant across different spatial sampling scales. Furthermore, we observed that adjacent assembly did not generate more variation in network descriptor values compared to random assembly. This finding indicates that the spatially aggregated distribution of species/individuals and abiotic conditions does not affect the organization of these interacting assemblages. 5.Our results have a direct impact on our empirical and theoretical understanding of the ecological dynamics of species interactions by demonstrating that small spatial sampling scales should suffice to record some patterns commonly found in ant‐plant interaction networks in a highly diverse tropical rainforest

Dissecting phylogenetic fuzzy weighting: theory and application in metacommunity phylogenetics

CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPERGS - FUNDAÇÃO DE AMPARO A PESQUISA DO ESTADO DO RIO GRANDE DO SULMetacommunity phylogenetics aims at evaluating environmental and/or historical factors driving clade distribution. Phylogenetic fuzzy weighting (PFW) describes clade distribution across metacommunities based on fuzzy sets defined by phylogenetic relatedness among species. The method enables analysing environmental and/or biogeographic determinants of clade distribution. PFW also offers an exploratory tool for visualizing clade distribution via Principal Coordinates of Phylogenetic Structure (PCPS). In this article, we describe the theoretical properties and biological backgrounds of PFW and evaluate its statistical performance (type I error and statistical power) in assessing environmental and phylogenetic determinants of species distribution in comparison with other phylobetadiversity methods (COMDIST, COMDISTNT, Rao's H and UniFrac). The statistical performance of PFW and the other phylobetadiversity metrics was tested by (i) simulating metacommunities under different species assembly scenarios (species distribution influenced or not by environment and/or phylogeny), niche breadth tolerance and species pool sizes; (ii) submitting community matrices to PFW and deriving pairwise phylogenetic dissimilarities between communities (D-P) and PCPS; (iii) submitting these metrics and the other phylobetadiversity methods to different analytical approaches (Mantel test, regression on dissimilarity matrices - ADONIS, and GLM) to evaluate the influence of environment and phylogeny on metacommunity phylogenetic structure; and (iv) estimating type I error and power estimates via alternative permutation procedures. Results demonstrated that PFW provides robust assessment of environmental and phylogenetic drivers of species distribution across metacommunities. Although all methods had acceptable type I error for both Mantel test and ADONIS, only PFW showed acceptable power for both tests. Rao's H had acceptable power only for Mantel test, while COMDIST had acceptable power only for ADONIS. COMDISTNT and UniFrac showed poor statistical performance for both tests. Conversely, GLM had acceptable power only for the first PCPS. Performing ADONIS on D-P provides a robust overall assessment of environmental and phylogenetic drivers of species distribution. On the other hand, performing PCPS analysis after rejecting the null hypotheses via ADONIS allows identifying the phylogenetic nodes mostly associated with environmental gradients. PFW enables synthesizing and analysing phylogenetic patterns in metacommunities, allowing attaining a more complete portrait of ecological and evolutionary drivers of species distribution.Metacommunity phylogenetics aims at evaluating environmental and/or historical factors driving clade distribution. Phylogenetic fuzzy weighting (PFW) describes clade distribution across metacommunities based on fuzzy sets defined by phylogenetic relatedness among species. The method enables analysing environmental and/or biogeographic determinants of clade distribution. PFW also offers an exploratory tool for visualizing clade distribution via Principal Coordinates of Phylogenetic Structure (PCPS). In this article, we describe the theoretical properties and biological backgrounds of PFW and evaluate its statistical performance (type I error and statistical power) in assessing environmental and phylogenetic determinants of species distribution in comparison with other phylobetadiversity methods (COMDIST, COMDISTNT, Rao's H and UniFrac). The statistical performance of PFW and the other phylobetadiversity metrics was tested by (i) simulating metacommunities under different species assembly scenarios (species distribution influenced or not by environment and/or phylogeny), niche breadth tolerance and species pool sizes; (ii) submitting community matrices to PFW and deriving pairwise phylogenetic dissimilarities between communities (D-P) and PCPS; (iii) submitting these metrics and the other phylobetadiversity methods to different analytical approaches (Mantel test, regression on dissimilarity matrices - ADONIS, and GLM) to evaluate the influence of environment and phylogeny on metacommunity phylogenetic structure; and (iv) estimating type I error and power estimates via alternative permutation procedures. Results demonstrated that PFW provides robust assessment of environmental and phylogenetic drivers of species distribution across metacommunities. Although all methods had acceptable type I error for both Mantel test and ADONIS, only PFW showed acceptable power for both tests. Rao's H had acceptable power only for Mantel test, while COMDIST had acceptable power only for ADONIS. COMDISTNT and UniFrac showed poor statistical performance for both tests. Conversely, GLM had acceptable power only for the first PCPS. Performing ADONIS on D-P provides a robust overall assessment of environmental and phylogenetic drivers of species distribution. On the other hand, performing PCPS analysis after rejecting the null hypotheses via ADONIS allows identifying the phylogenetic nodes mostly associated with environmental gradients. PFW enables synthesizing and analysing phylogenetic patterns in metacommunities, allowing attaining a more complete portrait of ecological and evolutionary drivers of species distribution.78937946CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPERGS - FUNDAÇÃO DE AMPARO A PESQUISA DO ESTADO DO RIO GRANDE DO SULCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPERGS - FUNDAÇÃO DE AMPARO A PESQUISA DO ESTADO DO RIO GRANDE DO SUL303534/2012-5; 302585/2011-7; 307689/2014-0; 563271/2010-8; 457531/2012-62011/50225-32011/2185-

Influences of sampling effort on detected patterns and structuring processes of a Neotropical plant-hummingbird network

Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 '), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks

Effects of defoliation frequencies on above- and belowground biodiversity and ecosystem processes in subtropical grasslands of southern Brazil

The links between vegetation and soil biota are responsible for a variety of ecosystem processes and services that can be affected by grazing. In this study, we aimed to evaluate the effects of grazing frequency in natural grasslands’ biodiversity (plant and collembola communities) and on ecosystem processes (decomposition and biomass accumulation). For so, we carried out a clipping experiment over a natural area of subtropical grassland in southern Brazil. The plots were submitted during three years to three different clipping frequencies (high, intermediate, and low) to simulate defoliation caused by grazing. We found the highest aboveground biomass accumulation and detritivore activity in the low defoliation frequency, which also promoted the dominance of tussocks. The synergies between higher vegetation height and biomass tend to provide microclimatic conditions that favors decomposition, which releases nutrients to plants, promoting their growth. The defoliation frequencies applied in this study were not sufficient to provide effects on plant community, since its co-evolutionary history with grazing. The Collembola community was not affected by defoliation. It seems to be more influenced by other factors associated with grazing.Funding: This research was financially supported by Fundação de Apoio à Pesquisa do Rio Grande do Sul, FAPERGS, Brazil (scientific initiation scholarship given to B.C.S. Jorge), by Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq, Brazil, F.M.F. received a PhD scholarship by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Ministry of Education, Federal Government of Brazil. The experiment was founded by the project AN Integration of Mitigation and Adaptation options for sustainable Livestock production under climate CHANGE (ANIMAL CHANGE). V.D.P. was supported by the Brazilian National Research Council (CNPq grant 307689/2014-0)