Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal
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 Faidher...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22009165 |
| _version_ | 1811337117266083840 |
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| author | Babacar Ndao Louise Leroux Aboubacar Hema Abdoul Aziz Diouf Agnès Bégué Bienvenu Sambou |
| author_facet | Babacar Ndao Louise Leroux Aboubacar Hema Abdoul Aziz Diouf Agnès Bégué Bienvenu Sambou |
| author_sort | Babacar Ndao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T17:50:17Z |
| format | Article |
| id | doaj.art-0b8e3e3061314388ae21e429fe0b0fc1 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-13T17:50:17Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-0b8e3e3061314388ae21e429fe0b0fc12022-12-22T02:36:44ZengElsevierEcological Indicators1470-160X2022-11-01144109443Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in SenegalBabacar Ndao0Louise Leroux1Aboubacar Hema2Abdoul Aziz Diouf3Agnès Bégué4Bienvenu Sambou5Centre de Suivi Ecologique, Dakar, Senegal; Institut des sciences de l’environnement, Faculté des sciences et techniques, Université Cheikh Anta Diop de Dakar, Senegal; Corresponding author.Centre de Suivi Ecologique, Dakar, Senegal; CIRAD, UPR AIDA, Dakar, Senegal; AIDA, Univ. Montpellier, CIRAD, Montpellier, FranceÉcole Nationale de la Statistique et de l’Analyse Économique, Dakar, SenegalCentre de Suivi Ecologique, Dakar, SenegalCIRAD, UMR TETIS, F-34398 Montpellier, France; TETIS, Univ. Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier, FranceInstitut des sciences de l’environnement, Faculté des sciences et techniques, Université Cheikh Anta Diop de Dakar, SenegalAround 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.http://www.sciencedirect.com/science/article/pii/S1470160X22009165Tree speciesSDMAgroforestry parklandModeling approachModel benchmarkingSenegal |
| spellingShingle | Babacar Ndao Louise Leroux Aboubacar Hema Abdoul Aziz Diouf Agnès Bégué Bienvenu Sambou Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal Ecological Indicators Tree species SDM Agroforestry parkland Modeling approach Model benchmarking Senegal |
| title | Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal |
| title_full | Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal |
| title_fullStr | Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal |
| title_full_unstemmed | Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal |
| title_short | Tree species diversity analysis using species distribution models: A Faidherbia albida parkland case study in Senegal |
| title_sort | tree species diversity analysis using species distribution models a faidherbia albida parkland case study in senegal |
| topic | Tree species SDM Agroforestry parkland Modeling approach Model benchmarking Senegal |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22009165 |
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