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Associations Between Habitat Quality and Body Size in the Carpathian-Podolian Land Snail Vestia turgida (Gastropoda, Clausiliidae): Species Distribution Model Selection and Assessment of Performance
Author(s) -
Volodymyr Tytar
Publication year - 2021
Publication title -
zoodiversity
Language(s) - English
Resource type - Journals
eISSN - 2707-7268
pISSN - 2707-725X
DOI - 10.15407/zoo2021.01.025
Subject(s) - habitat , variance (accounting) , ecology , linear regression , statistics , selection (genetic algorithm) , regression , rank (graph theory) , environmental science , biology , mathematics , computer science , accounting , combinatorics , business , artificial intelligence
Species distribution models (SDMs) are generally thought to be good indicators of habitat suitability, and thus of species’ performance. Consequently SDMs can be validated by checking whether the areas projected to have the greatest habitat quality are occupied by individuals or populations with higher than average fi tness. We hypothesized a positive and statistically signifi cant relationship between observed in the fi eld body size of the snail V. turgida (Rossmässler, 1836) and modelled habitat suitability, tested this relationship with linear mixed models, and found that indeed, larger individuals tend to occupy high-quality areas, as predicted by the SDMs. However, by testing several SDM algorithms, we found varied levels of performance in terms of expounding this relationship. Marginal R2 expressing the variance explained by the fi xed terms in the regression models, was adopted as a measure of functional accuracy, and used to rank the SDMs accordingly. In this respect, the Bayesian additive regression trees (BART) algorithm gave the best result, despite the low AUC and TSS. By restricting our analysis to the BART algorithm only, a variety of sets of environmental variables commonly or less used in the construction of SDMs were explored and tested according to their functional accuracy. In this respect, the SDM produced using the ENVIREM data set gave the best result.

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