The influence of habitat homogenization on the trophic structure of fish fauna in tropical streams

Habitat homogenization is one of the most important drivers of change in riverine fauna. Therefore, the aim of this study was to determine whether habitat homogenization influences the trophic structure of fish assemblages in tropical streams. We sampled 78 streams located in pasture and crop lands to examine habitat variables and fish. Principal coordinates analysis, canonical analysis of principal coordinates, and a distance-based test for homogeneity of multivariate dispersions revealed two groups of streams, designated homogeneous and heterogeneous, based on the habitat variables. We determined trophic guilds according to the frequency and biovolume of food items. Seven guilds were identified: aquatic insectivores, terrestrial insectivores, detritivores, herbivores, omnivores, algivores, and detritivores-algivores. Homogeneous streams showed higher abundance and biomass of aquatic insectivores, detritivores, and algivores. Heterogeneous streams showed greater diversity of trophic guilds and higher abundance and biomass of terrestrial insectivores and herbivores than homogeneous streams. Our results demonstrate that trophic structure is influenced by habitat condition. Additionally, the riparian canopy and nearshore vegetation have a modulating role in the trophic structure of stream fishes due to their influence on resource supply and promotion of the physical heterogeneity of the channel.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

The ecological memory of fish assemblages in agroecosystems with different history of landscape changes

<p>Here, we presented the data (local, past and response) and R code (models_Zeni et al.) we used to investigate the relationship between past land use changes and instream habitat (explanatory variables) and fish biodiversity patterns (response variables) in streams from different regions in Brazil. </p>The dataset used in this study was obtained due to the financial support from São Paulo Research Foundation (FAPESP): Grants nº: 10/17494‐8; 12/05983‐0; and 16/01535‐3. FAPESP also provided funding to JOZ (grant nº 18/06033-1), GLB (grant nº 18/11954-9) and to TS (grant nº 19/04033-7 and 21/00619-7). And, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) provided fellowship to LC (grant nº 304403/2021-0) and to TS (grant nº 309496/2021-7

Taxonomic, functional, and phylogenetic beta diversity patterns of stream fish assemblages in tropical agroecosystems

This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionA multi‐faceted assessment of diversity is needed to improve our understanding of the mechanisms underlying biodiversity patterns and to reveal the impacts of land use alterations on β‐diversity. In this study, we analysed stream fish β‐diversity based on taxonomic, functional, and phylogenetic facets in an intensively cultivated tropical region. We sampled 43 stream reaches in the northwest of São Paulo State, south‐eastern Brazil. Each sampling site was characterised according to catchment‐scale features, landscape dynamic indicators, local‐scale features, and distance between stream reaches as network distance (a proxy for dispersal processes). As response variables, we considered taxonomic, functional, and phylogenetic β‐diversities coupled with a null‐model approach. For each β‐diversity metric, we calculated the mean overall value and tested whether the mean value was different from that expected by chance. To examine variation in β‐diversity for the three facets and determine the relative contributions of predictor variables, we used a distance‐based approach. Taxonomic and functional β‐diversities were higher from the expected value under a null model, suggesting that community assembly of these facets was dominated by deterministic processes. In contrast, phylogenetic β‐diversity was not different from that expected by chance, suggesting that the lineage composition of these assemblages was random. Furthermore, for all three facets, there was a positive environment‐β‐diversity relationship that was determined primarily by local‐scale features, whereas catchment features and landscape dynamic indicators were not important. In addition, none of the β‐diversity facets was correlated with stream network distance, indicating that dispersal processes were not strongly structuring fish assemblages. Our study suggested that although multiple facets of stream fish β‐diversity are ruled mainly by deterministic processes (e.g. species sorting), stochasticity is also important in community assembly. An interesting finding was the mismatch between phylogenetic versus taxonomic and functional β‐diversity. It is likely that the lack of non‐random structure in phylogenetic β‐diversity is due to the variation of phylogenetic signal in some functional traits. Given that landscape dynamic indicators were not correlated with measures of β‐diversity, we suggest that the recent sugarcane expansion in our study area probably has not critically affected stream fish β‐diversity. Also, it is possible that catchment variables presented little variability and did not overwhelm the effect of local environmental variables on β‐diversity. In conclusion, our study suggests that even highly disturbed tropical agroecosystems with a pool of species that is probably decimated, can still display a relatively high β‐diversity determined mainly by species sorting. These findings suggest key environmental features that must be considered in restoration or conservation of β‐diversity in agroecosystems. Specifically, since variation in β‐diversity was explained mainly by local‐scale environmental gradients, conservation schemes would ideally protect enough sites to capture this entire gradient. Overall, the knowledge of multiple facets can foment more effective conservation and restoration actions by providing a more comprehensive view of the structuring factors of assemblages

RivFishTIME: A global database of fish time‐series to study global change ecology in riverine systems

International audienceAbstract Motivation We compiled a global database of long‐term riverine fish surveys from 46 regional and national monitoring programmes and from individual academic research efforts, with which numerous basic and applied questions in ecology and global change research can be explored. Such spatially and temporally extensive datasets have been lacking for freshwater systems in comparison to terrestrial ones. Main types of variables contained The database includes 11,386 time‐series of riverine fish community catch data, including 646,270 species‐specific abundance records, together with metadata related to the geographical location and sampling methodology of each time‐series. Spatial location and grain The database contains 11,072 unique sampling locations (stream reach), spanning 19 countries, five biogeographical realms and 402 hydrographical basins world‐wide. Time period and grain The database encompasses the period 1951–2019. Each time‐series is composed of a minimum of two yearly surveys (mean = 8 years) and represents a minimum time span of 10 years (mean = 19 years). Major taxa and level of measurement The database includes 944 species of ray‐finned fishes (Class Actinopterygii). Software format csv. Main conclusion Our collective effort provides the most comprehensive long‐term community database of riverine fishes to date. This unique database should interest ecologists who seek to understand the impacts of human activities on riverine fish biodiversity and to model and predict how fish communities will respond to future environmental change. Together, we hope it will promote advances in macroecological research in the freshwater realm