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

Published online by Cambridge University Press:  18 September 2014

M. M. P. Cobben ,
R. van Treuren ,
N. P. Castañeda-Álvarez ,
C. K. Khoury ,
C. Kik  and
T. J. L. van Hintum
M. M. P. Cobben*
Affiliation:
Centre for Genetic Resources, The Netherlands (CGN), PO Box 16, 6700 AAWageningen, The Netherlands Netherlands Institute of Ecology (NIOO-KNAW), PO Box 50, 6700 ABWageningen, The Netherlands
R. van Treuren
Affiliation:
Centre for Genetic Resources, The Netherlands (CGN), PO Box 16, 6700 AAWageningen, The Netherlands
N. P. Castañeda-Álvarez
Affiliation:
International Center for Tropical Agriculture (CIAT), Apartado Aéreo 6713, Calí, Colombia
C. K. Khoury
Affiliation:
International Center for Tropical Agriculture (CIAT), Apartado Aéreo 6713, Calí, Colombia Centre for Crop Systems Analysis, Wageningen University, PO Box 16, 6700 AAWageningen, The Netherlands
C. Kik
Affiliation:
Centre for Genetic Resources, The Netherlands (CGN), PO Box 16, 6700 AAWageningen, The Netherlands
T. J. L. van Hintum
Affiliation:
Centre for Genetic Resources, The Netherlands (CGN), PO Box 16, 6700 AAWageningen, The Netherlands
*
*Corresponding author. E-mail: m.cobben@nioo.knaw.nl
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Abstract

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.

Keywords

collecting expeditiongenebankLactucaMaxentniche modellingplant genetic resourcesspecies distribution modelling
Type
Research Article
Information
Plant Genetic Resources , Volume 13 , Issue 2 , August 2015 , pp. 153 - 161
Copyright
Copyright © NIAB 2014 

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