Sharma, Roshan, Jones, Simon, Bastin, Lucy and Gordon, Ascelin (2025). Private protected areas exhibit greater bias towards unproductive land compared to public protected areas. Environmental Research Communications, 7 (4),
Abstract
Globally, private protected areas (PPAs) have become an important tool for biodiversity conservation. While they are expanding in size and number, there is limited evidence on their potential impact on avoiding biodiversity loss, and how this impact compares to the public protected areas (public PAs). The impact of protection is measured as the actual biodiversity outcome within the area protected relative to the hypothetical outcome without protection. To maximise this positive impact, PAs need to be placed strategically on land that both harbours biodiversity and would be at risk of losing some of the biodiversity if it were not protected. We evaluate and compare the locations of PPAs and public PAs relative to random sites of similar governance type, and a range of covariates that capture biodiversity and the risk of biodiversity loss. We utilised data from a national PA database, and high-resolution data on nationally significant threatened species and indicators that capture risk of biodiversity loss at a continental scale in Australia. We find that PPAs tend to target areas of high threatened species richness. However, on average, PPAs are placed in areas that have lower risk of being cleared compared to randomly selected private land. We observe that this bias towards unproductive land is more prominent in PPAs when compared to public PAs. As nations work towards effectively conserving and managing at least 30% of the world's lands by 2030 under the new Kunming-Montreal Global Biodiversity Framework, it becomes essential to prioritise PAs and PPAs that deliver impacts on avoiding biodiversity loss rather than solely focusing on areas that represent biodiversity.
Publication DOI: | https://doi.org/10.1088/2515-7620/adc546 |
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Divisions: | College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics |
Additional Information: | Copyright © 2025 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
Uncontrolled Keywords: | biodiversity conservation,land suitability,land use bias,threatened species,protected areas,conservation impact,SDG 15 - Life on Land,SDG 11 - Sustainable Cities and Communities,SDG 17 - Partnerships for the Goals |
Data Access Statement: | The data will also be utilised for another study; therefore, we will provide access upon request. The data that support the findings of this study are available upon reasonable request from the authors. https://github.com/<br/>wildeco/ppa_bias. Data will be available from 15 December 2024. |
Last Modified: | 10 Apr 2025 07:36 |
Date Deposited: | 07 Apr 2025 09:30 |
Full Text Link: | |
Related URLs: |
https://iopscie ... 515-7620/adc546
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2025-04 |
Published Online Date: | 2025-04-04 |
Accepted Date: | 2025-03-25 |
Authors: |
Sharma, Roshan
Jones, Simon Bastin, Lucy ( ![]() Gordon, Ascelin |