Methods for prioritizing protected areas using individual and aggregate rankings

Abstract

Despite their legal protection status, protected areas (PAs) can benefit from priority ranks when ongoing threats to their biodiversity and habitats outpace the financial resources available for their conservation. It is essential to develop methods to prioritize PAs that are not computationally demanding in order to suit stakeholders in developing countries where technical and financial resources are limited. We used expert knowledge-derived biodiversity measures to generate individual and aggregate priority ranks of 98 mostly terrestrial PAs on Madagascar. The five variables used were state of knowledge (SoK), forest loss, forest loss acceleration, PA size and relative species diversity, estimated by using standardized residuals from negative binomial models of SoK regressed onto species diversity. We compared our aggregate ranks generated using unweighted averages and principal component analysis (PCA) applied to each individual variable with those generated via Markov chain (MC) and PageRank algorithms. SoK significantly affected the measure of species diversity and highlighted areas where more research effort was needed. The unweighted-and PCA-derived ranks were strongly correlated, as were the MC and PageRank ranks. However, the former two were weakly correlated with the latter two. We recommend using these methods simultaneously in order to provide decision-makers with the flexibility to prioritize those PAs in need of additional research and conservation efforts.

Noninvasive Technologies for Primate Conservation in the 21st Century

“…Detection, Presence-Absence, Prioritization An important first step in wildlife conservation is detecting a species presence and thereafter, identifying priority areas (Groves et al 2002). In most cases, this involves weighing important metrics such as forest loss and forest loss rate, size of the area in need of protection, relative species (or overall phylogenetic) diversity, and measures of irreplaceability or vulnerability (Carvalho et al 2020;Isaac et al 2007;Ondei et al 2019). Just as important is assessing a species presence, especially for cryptic, elusive, or rare species where distribution and ranging patterns are unknown.…”

Effects of anthropic activity dynamics on mangrove ecosystems’ degradation in Caracol County – Haiti

“…Besides, some socioeconomic factors seem to worsen the degradation scenario in mangroves due to severe environmental consequences, to the hard time reestablishing them and to the regeneration limitations of neighbor ecosystems and habitats (Pérez-Ceballos, et al, 2020). Decision-makers can use variable 'profession' to plan integrated management actions based on local initiatives to make the extraction of resources natural to mangroves' ecosystems more effective and sustainable (Carvalho, et al, 2020). On the other hand, they can increase mangroves' vulnerability because of actors' interest in land use and occupation, although they are aware of their harming effect on the environment (Robson & Klooster, 2018).…”

Spatial conservation prioritization considering socioeconomic costs and degradation conditions in the Southwest China Biodiversity Hotspot

“…Since 2000, KASC PA coverage has gradually increased (UNEP-WCMC et al 2021); however, biodiversity continues to be lost at an alarming rate (Pimm et al 2014, Yang et al 2020. PAs in the region are mostly ineffective, isolated from other PAs and immersed within a degraded or unproductive matrix (Carvalho et al 2020). Without comprehensive planning and given the disjointed PA categories (Xu et al 2019), the current PA network fails to adequately represent regional biodiversity and suffers from fragmented management.…”