Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal. (November 2022)

• Record Type: Journal Article
• Authors: Ndao, Babacar; Leroux, Louise; Hema, Aboubacar; Diouf, Abdoul Aziz; Bégué, Agnès; Sambou, Bienvenu
• Is Part Of: Ecological indicators. Volume 144(2023)
• Publication Date: 2022-11
• Subjects: Tree species -- SDM -- Agroforestry parkland -- Modeling approach -- Model benchmarking -- Senegal -- Species diversity indices; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109443
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: The tree species diversity of a Sahelian agroforestry parkland was analyzed using SDM. Benchmarking several modeling techniques allowed us strengthening the SDM performance. Maps of tree species diversity indices were derived from SDM predictions. The tree species diversity is related to the landscape heterogeneity and composition. The tree species diversity is sustained by anthropization in Sahelian parklands. Abstract: Around the world, SDMs have been widely used to support forest management planning and biodiversity conservation. Beyond the prediction of species distribution provided by the SDMs, this study aimed to analyze the spatial distribution of tree species diversity using SDMs. The study area is a Faidherbia albida parkland in Central Senegal. It is characterized by a tree-based farming system dominated by Faidherbia albida . Using a robust and representative dataset of 9258 tree species occurrence, we first determined by an SDM the current potential spatial distribution of the 16 main tree species forming the parkland. Specifically, using 6 SDM algorithms and applying several modeling techniques with different categories of predictor variables (e.g., climate, topography, soil properties and human impact) we benchmarked 576 SDMs to achieve best model predictions for tree species. Then, tree species diversity maps were created on the basis of the resulting SDM predictions. Finally, the spatial dynamics of tree species diversity were discussed in relation to landscape characteristics, including heterogeneity, composition and human impact. The results showed that there is no single 'best' SDM algorithm (among the 6 algorithms tested) or modeling approach for all species. Benchmarking several modeling techniques allowed strengthening SDM performance, achieving AUC values that ranged from 0.64 (intermediate accuracy) to 0.87 (very good accuracy). The spatial dynamics of tree species diversity is related to the landscape heterogeneity and composition. In the Sahelian agroforestry systems (AFS), tree diversity is sustained by anthropization. A significant negative correlation with the distance to the village was found, i.e. the closer you get to the village, the greater the diversity of trees. This study could be crucial for analyzing tree species diversity when abundance information is not available.