Robustness and accuracy of Maxent niche modelling for Lactuca species distributions in light of collecting expeditions

TY - JOUR

T1 - Robustness and accuracy of Maxent niche modelling for Lactuca species distributions in light of collecting expeditions

AU - Cobben, M.M.P.

AU - van Treuren, R.

AU - Castañeda-Álvarez, N.P.

AU - Khoury, C.K.

AU - Kik, C.

AU - van Hintum, T.J.L.

N1 - Reporting year: 2014 Metis note: 5666, AnE PDF aangevraagd bij TUD, mag na 1 jaar Open You may post the VoR version of the article (in PDF or HTML form) in the Institutional Repository of the institution in which you worked at the time the article was first submitted, or (for appropriate journals) in PubMed Central or UK PubMed Central or ArXiV, no sooner than one year after first publication of the article in the Journal; Data archiving: data archived at GitHub

PY - 2015

Y1 - 2015

N2 - Niche modelling software can be used to assess the probability of detecting a population of a plant species at a certain location. In this study, we used the distribution of the wild relatives of lettuce (Lactuca spp.) to investigate the applicability of Maxent species distribution models for collecting missions. Geographic origin data of genebank and herbarium specimens and climatic data of the origin locations were used as input. For Lactuca saligna, we varied the input data by omitting the specimens from different parts of the known distribution area to assess the robustness of the predicted distributions. Furthermore, we examined the accuracy of the modelling by comparing the predicted probabilities of population presence against recent expedition data for the endemic Lactuca georgica and the cosmopolitan Lactuca serriola. We found Maxent to be quite robust in its predictions, although its usefulness was higher for endemic taxa than for more widespread species. The exclusion of occurrence data from the perceived range margins of the species can result in important information about local adaptation to distinct climatic conditions. We discuss the potential for enhanced use of Maxent in germplasm collecting planning.

AB - Niche modelling software can be used to assess the probability of detecting a population of a plant species at a certain location. In this study, we used the distribution of the wild relatives of lettuce (Lactuca spp.) to investigate the applicability of Maxent species distribution models for collecting missions. Geographic origin data of genebank and herbarium specimens and climatic data of the origin locations were used as input. For Lactuca saligna, we varied the input data by omitting the specimens from different parts of the known distribution area to assess the robustness of the predicted distributions. Furthermore, we examined the accuracy of the modelling by comparing the predicted probabilities of population presence against recent expedition data for the endemic Lactuca georgica and the cosmopolitan Lactuca serriola. We found Maxent to be quite robust in its predictions, although its usefulness was higher for endemic taxa than for more widespread species. The exclusion of occurrence data from the perceived range margins of the species can result in important information about local adaptation to distinct climatic conditions. We discuss the potential for enhanced use of Maxent in germplasm collecting planning.

KW - international

UR - https://github.com/mcobben/2015-Plant_Genetic_Resources

U2 - 10.1017/S1479262114000847

DO - 10.1017/S1479262114000847

M3 - Article

SN - 1479-2621

VL - 13

SP - 153

EP - 161

JO - Plant Genetic Resources

JF - Plant Genetic Resources

IS - 2

ER -