Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism
The objective of this study is to address the complex task of identifying optimal locations for reintroducing Ammotragus lervia in a semi-arid area in the Eastern High Atlas of Morocco, considering three topographical factors. The study assesses the effectiveness of a commonly used machine learning...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Scientific African |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468227624003867 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850100851942621184 |
|---|---|
| author | Lahbib Naimi El Mahi Bouziane Lamya Benaddi Abdeslam Jakimi Mohamed Manaouch |
| author_facet | Lahbib Naimi El Mahi Bouziane Lamya Benaddi Abdeslam Jakimi Mohamed Manaouch |
| author_sort | Lahbib Naimi |
| collection | DOAJ |
| description | The objective of this study is to address the complex task of identifying optimal locations for reintroducing Ammotragus lervia in a semi-arid area in the Eastern High Atlas of Morocco, considering three topographical factors. The study assesses the effectiveness of a commonly used machine learning classifier (MLC) in mapping potential areas for introducing these species, which is crucial for promoting and enhancing local biodiversity. To begin with, an extensive inventory of 88 remaining sites where these Barbary sheep still living was conducted, and precise measurements of three topographical parameters were collected at each site. Subsequently, a machine learning algorithm called Bagging was employed to develop a predictive model. The predictive model demonstrated a high level of performance, as evidenced by an area under the curve (AUC) value of 0.929. Bagging effectively identified favorable areas, encompassing around 13.8 % of the study region, which were predominantly located in the western part. These areas were characterized by mountainous terrain, shorter slopes, and higher altitudes. The research findings provide valuable guidance to decision-makers, offering a roadmap to reintroduce these species for enhancing the local biodiversity in the region. |
| format | Article |
| id | doaj-art-a8f46e48b45b4cd4b9f5dd2a66e40626 |
| institution | DOAJ |
| issn | 2468-2276 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Scientific African |
| spelling | doaj-art-a8f46e48b45b4cd4b9f5dd2a66e406262025-08-20T02:40:11ZengElsevierScientific African2468-22762024-12-0126e0244410.1016/j.sciaf.2024.e02444Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourismLahbib Naimi0El Mahi Bouziane1Lamya Benaddi2Abdeslam Jakimi3Mohamed Manaouch4Software Engineering and information Systems Engineering Team, Department of Informatics, FST of Errachidia, Moulay Smail University, Errachidia 52000, MoroccoSoftware Engineering and information Systems Engineering Team, Department of Informatics, FST of Errachidia, Moulay Smail University, Errachidia 52000, MoroccoSoftware Engineering and information Systems Engineering Team, Department of Informatics, FST of Errachidia, Moulay Smail University, Errachidia 52000, MoroccoSoftware Engineering and information Systems Engineering Team, Department of Informatics, FST of Errachidia, Moulay Smail University, Errachidia 52000, MoroccoDepartment of Geography, Faculty of Humanities and Social Sciences, Ibn Tofail University, Kenitra 14000, Morocco; Corresponding author.The objective of this study is to address the complex task of identifying optimal locations for reintroducing Ammotragus lervia in a semi-arid area in the Eastern High Atlas of Morocco, considering three topographical factors. The study assesses the effectiveness of a commonly used machine learning classifier (MLC) in mapping potential areas for introducing these species, which is crucial for promoting and enhancing local biodiversity. To begin with, an extensive inventory of 88 remaining sites where these Barbary sheep still living was conducted, and precise measurements of three topographical parameters were collected at each site. Subsequently, a machine learning algorithm called Bagging was employed to develop a predictive model. The predictive model demonstrated a high level of performance, as evidenced by an area under the curve (AUC) value of 0.929. Bagging effectively identified favorable areas, encompassing around 13.8 % of the study region, which were predominantly located in the western part. These areas were characterized by mountainous terrain, shorter slopes, and higher altitudes. The research findings provide valuable guidance to decision-makers, offering a roadmap to reintroduce these species for enhancing the local biodiversity in the region.http://www.sciencedirect.com/science/article/pii/S2468227624003867Machine learningEcotourismAmmotragus lerviaSemi-arid areaSE Morocco |
| spellingShingle | Lahbib Naimi El Mahi Bouziane Lamya Benaddi Abdeslam Jakimi Mohamed Manaouch Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism Scientific African Machine learning Ecotourism Ammotragus lervia Semi-arid area SE Morocco |
| title | Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism |
| title_full | Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism |
| title_fullStr | Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism |
| title_full_unstemmed | Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism |
| title_short | Assessing habitat suitability for aoudad (Ammotragus lervia) reintroduction in southeastern morocco to promote ecotourism |
| title_sort | assessing habitat suitability for aoudad ammotragus lervia reintroduction in southeastern morocco to promote ecotourism |
| topic | Machine learning Ecotourism Ammotragus lervia Semi-arid area SE Morocco |
| url | http://www.sciencedirect.com/science/article/pii/S2468227624003867 |
| work_keys_str_mv | AT lahbibnaimi assessinghabitatsuitabilityforaoudadammotraguslerviareintroductioninsoutheasternmoroccotopromoteecotourism AT elmahibouziane assessinghabitatsuitabilityforaoudadammotraguslerviareintroductioninsoutheasternmoroccotopromoteecotourism AT lamyabenaddi assessinghabitatsuitabilityforaoudadammotraguslerviareintroductioninsoutheasternmoroccotopromoteecotourism AT abdeslamjakimi assessinghabitatsuitabilityforaoudadammotraguslerviareintroductioninsoutheasternmoroccotopromoteecotourism AT mohamedmanaouch assessinghabitatsuitabilityforaoudadammotraguslerviareintroductioninsoutheasternmoroccotopromoteecotourism |