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Effects of functional traits on the prediction accuracy of species richness models
Author(s) -
Zurell Damaris,
Zimmermann Niklaus E.,
Sattler Thomas,
Nobis Michael P.,
Schröder Boris
Publication year - 2016
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/ddi.12450
Subject(s) - species richness , ecology , generalist and specialist species , habitat , functional diversity , gamma diversity , community , species diversity , generalized additive model , biology , taxon , beta diversity , statistics , mathematics
Aim We assess main ecological determinants affecting the comparative performance of macroecological models ( MEM s) that model species richness directly, and stacked species distribution models based on stacking probabilities ( pS ‐ SDM s) and binary predictions ( bS ‐ SDM s). Specifically, we aimed to understand how statistical effects such as prevalence and environmental heterogeneity are entangled with species' ecology in Swiss avian assemblages. Location Switzerland. Methods We tested for statistical and ecological effects on overprediction and underprediction by regressing species richness residuals against community‐averaged values of prevalence, functional traits and functional dissimilarity. Further, we defined bird functional groups through hierarchical clustering and compared accuracy of species richness predictions between groups to understand the differences between model types and ecological determinants thereof. Last, we tested how accuracy of species assemblages constructed from bS ‐ SDM s relates to species' functional characteristics. Results Underprediction of high diversity sites by pS ‐ SDM s and MEM s was mainly explained by prevalence, whereas overprediction of low diversity sites was strongly affected by diet and habitat traits, and increased with functional dissimilarity. Model performances varied strongly between functional groups with more accurate and less biased predictions for generalist species groups. Critically, overprediction bias in richness predictions by bS ‐ SDM s was uncorrelated with assemblage prediction success. Main conclusions The reliability of all community models tested here strongly depended on functional species' characteristics related mainly to diet, foraging and breeding habitat. This underlines the need to incorporate all relevant and species‐specific or functional group‐specific ecological filters in the models. Improved prediction accuracy of species richness will require finer‐resolved environmental predictors that better describe available niche space and account for specific spatial and resource requirements of different species. More research is needed to understand the relationship between accuracy of species richness and species assemblage predictions in bS ‐ SDM s as well as the role of biotic interactions.

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