Abstract
Global commitments to protect 30% of land by 2030 present an opportunity to combat the biodiversity crisis, but reducing extinction risk will depend on where countries expand protection. Here, we explore a range of 30×30 conservation scenarios that vary what dimension of biodiversity is prioritized (taxonomic groups, species-at-risk, biodiversity facets) and how protection is coordinated (transnational, national, or regional approaches) to test which decisions influence our ability to capture biodiversity in spatial planning. Using Canada as a model nation, we evaluate how well each scenario captures biodiversity using scalable indicators while accounting for climate change, data bias, and uncertainty. We find that only 15% of all terrestrial vertebrates, plants, and butterflies (representing only 6.6% of species-at-risk) are adequately represented in existing protected land. However, a nationally coordinated approach to 30×30 could protect 65% of all species representing 40% of all species-at-risk. How protection is coordinated has the largest impact, with regional approaches protecting up to 38% fewer species and 65% fewer species-at-risk, while the choice of biodiversity incurs much smaller trade-offs. These results demonstrate the potential of 30×30 while highlighting the critical importance of biodiversity-informed national strategies.
| Original language | English |
|---|---|
| Article number | 7113 |
| Pages (from-to) | 1-11 |
| Number of pages | 11 |
| Journal | Nature Communications |
| Volume | 14 |
| DOIs | |
| Publication status | Published - 6 Nov 2023 |
Bibliographical note
Funding Information:The authors would like to acknowledge that while they were able to account for ceded Indigenous land in their analysis, much of what we now call Canada remains unceded, rich with a history of Indigenous oppression. As such, the establishment of new protected areas and Canada’s path to 30×30 should involve Indigenous communities, knowledge, and perspectives so as to advance Indigenous rights and title. Additionally, the authors would like to thank Darren Li and Cole Lee for their work in gathering the functional trait data, Stefano Mammola for his help with computing functional hypervolumes, and Abbie Gail Jones and Olivia Rahn for their many helpful comments throughout the duration of the project. This work was supported by NSERC DG grant RGPIN-2019-05771 (L.J.P.) and by a NSERC CGS-D award (I.E.).
Publisher Copyright:
© 2023, The Author(s).