Sampling strategy matters to accurately estimate response curves' parameters in species distribution models

نویسندگان

چکیده

Aim Assessing how different sampling strategies affect the accuracy and precision of species response curves estimated by parametric distribution models. Major Taxa Studied Virtual plant species. Location Abruzzo (Italy). Time Period Timeless (simulated data). Methods We simulated occurrence two virtual with ecology (generalist vs specialist) extent. sampled their following strategies: random, stratified, systematic, topographic, uniform within environmental space (hereafter, uniform) close to roads. For each design species, we ran 500 simulations at increasing efforts (total: 42,000 replicates). replicate, fitted a binomial generalised linear model, extracted model coefficients for precipitation temperature, compared them true from known species' equation. evaluated quality computing bias, variance root mean squared error (RMSE). Additionally, (i) assessed impact missing covariates on performance approaches (ii) effect incompletely approach. Results generalist found lowest RMSE when uniformly space, while data roads provided worst performance. specialist all designs showed comparable outcomes. Excluding important predictors similarly affected strategies. Sampling limited portions reduced approach, regardless portion surveyed. Main Conclusions Our results suggest that proper estimate curve can be obtained choice strategy is guided ecology. Overall, seems more efficient wide tolerances. The advantage seeking most appropriate vanishes modelling narrow realised niches.

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ژورنال

عنوان ژورنال: Global Ecology and Biogeography

سال: 2023

ISSN: ['1466-8238', '1466-822X']

DOI: https://doi.org/10.1111/geb.13725