Modeling of the spatial distribution of species of interest in agriculture for their conservation: case of Punica granatum L.

Abstract

Abstract Modeling the spatial distribution of species is an important step in biodiversity conservation. The models used can be helpful in predicting the impacts of climate change on the geographical distribution of species and in identifying areas where they are most likely to occur. The purpose of this work was to model the spatial distribution of the pomegranate species (Punica granatum L.) in Morocco according to the principle of maximum entropy (Maxent). This modelling method is widely used in ecology and biogeography because of its ability to work with datasets, and to produce accurate predictions of species distribution. Based on agro-ecological data such as topographical factors and climatic variables and focusing on regions where pomegranate cultivation is significant, these data can be collected at different spatial and temporal scales. They are typically integrated into Geographic Information Systems (GIS) for utilization within the simulation model. The resulting model depicts the potential spatial distribution of pomegranate cultivation throughout Morocco. The model obtained agrees perfectly with the actual distribution of the species in different regions of the country, especially since it is known for its hardiness and its adaptation to variable environmental conditions. Thus, the modeling showed that other geographical areas present favorable conditions for the development of pomegranate cropping. The determination of spatial distribution constitutes a first step to predict possible evolution of the pomegranate cropping according to climate change. The importance of this process for biodiversity conservation lies in several aspects, such as the identification of areas at risk, conservation planning, and the assessment of impacts on ecosystems.