Browsing by Author "Bini, L. Mauricio"
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- Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regressionPublication . Bini, L. Mauricio; Diniz-Filho, J. Alexandre F.; Rangel, Thiago F. L. V. B.; Akre, Thomas S. B.; Albaladejo, Rafael G.; Albuquerque, Fabio S.; Aparicio, Abelardo; Araújo, Miguel B.; Baselga, Andrés; Beck, Jan; Bellocq, M. Isabel; Böhning-Gaese, Katrin; Borges, Paulo A. V.; Castro-Parga, Isabel; Chey, Vun Khen; Chown, Steven L.; Marco, Paulo de Jr; Dobkin, David S.; Ferrer-Castán, Dolores; Field, Richard; Filloy, Julieta; Fleishman, Erica; Gómez, Jose F.; Hortal, Joaquín; Iverson, John B.; Kerr, Jeremy T.; Kissling, W. Daniel; Kitching, Ian J.; León-Cortés, Jorge L.; Lobo, Jorge M.; Montoya, Daniel; Morales-Castilla, Ignacio; Moreno, Juan C.; Oberdorff, Thierry; Olalla-Tárraga, Miguel Á.; Pausas, Juli G.; Qian, Hong; Rahbek, Carsten; Rodríguez, Miguel Á.; Rueda, Marta; Ruggiero, Adriana; Sackmann, Paula; Sanders, Nathan J.; Terribile, Levi Carina; Vetaas, Ole R.; Hawkins, Bradford A.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation.
- Current climate, but also long‐term climate changes and human impacts, determine the geographic distribution of European mammal diversityPublication . Santos, Ana M. C.; Cianciaruso, Marcus V.; Barbosa, Ana Márcia; Bini, L. Mauricio; Diniz‐Filho, J. Alexandre F.; Faleiro, Frederico V.; Gouveia, Sidney F.; Loyola, Rafael; Medina, Nagore G.; Rangel, Thiago F.; Tessarolo, Geiziane; Hortal, JoaquínAIM: Historical climate variations, current climate and human impacts are known to influence current species richness, but their effects on phylogenetic and trait diversity have been seldom studied. We investigated the relationship of these three factors with the independent variations of species, phylogenetic and trait diversity of European mammals. Considering the position of the 0 ⁰C isotherm in the Last Glacial Maximum as a tipping point, we tested the following hypotheses: northern European assemblages host fewer species than southern European ones; northern areas harbour trait and phylogenetically clustered assemblages, while the more stable southern areas host random or overdispersed assemblages; and species richness correlates positively with human influence, while phylogenetic and trait diversity show clustered patterns in areas with stronger human influence. LOCATION: Western Palaearctic. TIME PERIOD: Current and Late Pleistocene effects on present-day diversity. MAJOR TAXA STUDIED: Terrestrial mammals. METHODS: We used a novel analytical approach based on distance matrices to separate the independent variations of species, phylogenetic and trait diversity, and assessed their relationships with current climate, climate stability and human influence through structural equation models. RESULTS: The species-poor assemblages from northern Europe show higher phylogenetic and trait clustering than the more stable richer southern areas. However, no assemblage presented trait or phylogenetic over dispersion. Current climate is the primary driver of phylogenetic and trait diversity, while species richness is affected similarly by both current and past climates. Higher human influence correlates positively with species richness and trait diversity, both directly and by mediating indirect effects of present climate. MAIN CONCLUSIONS: Current climate, climate stability and human influence affect the studied aspects of diversity, although the form and magnitude of their effects vary through space. Importantly, higher levels of human disturbances correlate with more species rich and trait diverse assemblages, an apparently counterintuitive result that deserves further study.