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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F23%3A97260" target="_blank" >RIV/60460709:41330/23:97260 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14310/23:00132164

Result on the web

<a href="http://dx.doi.org/10.1111/geb.13725" target="_blank" >http://dx.doi.org/10.1111/geb.13725</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/geb.13725" target="_blank" >10.1111/geb.13725</a>

Result language

angličtina

Original language name

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

Original language description

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

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10618 - Ecology

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

GLOBAL ECOLOGY AND BIOGEOGRAPHY

ISSN

1466-822X

e-ISSN

1466-822X

Volume of the periodical

32

Issue of the periodical within the volume

10

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

13

Pages from-to

1717-1729

UT code for WoS article

001025355200001

EID of the result in the Scopus database

2-s2.0-85164585065