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Effectiveness of South Africa’s network of protected areas: Unassessed vascular plants predicted to be threatened using deep neural networks are all located in protected areas
  • B. Samuel Kandolo,
  • Kowiyou Yessoufou,
  • Mahlatse Kganyago
B. Samuel Kandolo
University of Johannesburg
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Kowiyou Yessoufou
University of Johannesburg

Corresponding Author:kowiyouyessoufou1@gmail.com

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Mahlatse Kganyago
University of Johannesburg
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Abstract

Globally, biodiversity is at risk of extinction, and megadiverse countries become key targets for conservation. South Africa, the only country hosting three biodiversity hotspots, harbours tremendous diversity of at-risk species deserving to be protected. However, the lengthy risk assessment process and the lack of required data to complete assessments is a serious limitation to conservation since several species may slide into extinction while awaiting risk assessment. Here, we employed deep neural network model integrating species climatic and geographic features to predict the conservation status of 116 unassessed plant species. Our analysis involved in total 1072 plant species and 112 066 occurrence points. The best-performing model exhibits high accuracy, reaching up to 83.6% at the binary classification and 56.8% at the detailed classification. Our best-performing model predicts that 32% and 8% of Data Deficient and Not-Evaluated species are likely threatened, respectively, amounting to a proportion of 24.1% of unassessed species facing a risk of extinction. Interestingly, all unassessed species predicted to be threatened are in protected areas, revealing the effectiveness of the South Africa’s network of protected areas in conservation, although these likely threatened species are more abundant outside protected areas. Considering the limitation in assessing only species with available data, there remains a possibility of a higher proportion of unassessed species being imperiled.
Submitted to Ecology and Evolution
15 Apr 2024Submission Checks Completed
15 Apr 2024Assigned to Editor
11 May 2024Review(s) Completed, Editorial Evaluation Pending
15 May 2024Editorial Decision: Revise Minor
19 Jul 20241st Revision Received
22 Jul 2024Submission Checks Completed
22 Jul 2024Assigned to Editor
22 Jul 2024Review(s) Completed, Editorial Evaluation Pending
09 Aug 2024Editorial Decision: Accept