Optimizing Conservation Efforts: The Role of Spatial Prioritization

Introduction

The global biodiversity crisis is driven by habitat loss, climate change, and economic pressures for resource extraction. Traditionally, protected areas have been the primary conservation strategy. For instance, the Convention on Biological Diversity aimed to double the extent of protected areas between 2011 and 2020 (Aichi Target 11).

Nowadays, ecosystem restoration is also being promoted as a complementary conservation effort. The UN Decade on Ecosystem Restoration aims to restore 350 million hectares of degraded ecosystems by 2030, reaffirming the Bonn Challenge from the Paris Agreement.

In practice, financial constraints and land-use conflicts necessitate optimizing the allocation of areas for conservation. Spatial prioritization is a decision-making tool that helps determine where, how, and when to allocate conservation efforts in landscapes with spatial heterogeneity in biodiversity and threats.

to be cleared, leaving only remnants of original habitats for conservation when biodiversity protection becomes a priority. For example, the world’s largest national park is in Greenland, where extreme cold and ice cover limit other land uses. In less extreme environments, conservation areas are typically in regions of low economic interest, such as steep slopes or remote locations.

Marine conservation areas often encompass low-productivity zones with minimal commercial fishing pressure due to low economic value fish diversity. Studies suggest restored areas may not maximize biodiversity indicators, often being chosen based on socio-political factors.

Geographical biases occur because conservation area decisions historically focused on scenic beauty, recreational value, and unsuitability for other land uses, rarely incorporating biodiversity aspects beyond species richness. This has resulted in protected areas predominantly comprising ecosystems with low competition for land use, such as arid, infertile, and rugged habitats.

Effective spatial prioritization relies on comprehensive data on biodiversity distribution and threats. Data-driven exercises need bio-physical indicators and socio-political constraints. However, knowledge gaps, such as the Linnean (unknown species) and Wallacean (unknown species distribution) shortfalls, necessitate using biodiversity surrogates as indicators.

Objectives

The goal is to create a priority area system that conserves/restores as much biodiversity as possible across different spatial scales and ecological levels, considering long-term persistence. Spatial prioritization should ideally incorporate ecological processes, maintaining genetic and demographic flows to ensure resilience to landscape conversion and climate change.

Data availability and environmental variations are major uncertainties. Historical species occurrence data may not reflect current habitat suitability due to environmental changes. Future climate change will further affect habitat suitability.

Dilemmas

Prioritizing low-risk areas ensures long-term biodiversity persistence but may leave vulnerable populations unprotected. Conversely, high-risk area management is costly and uncertain. For restoration, moderately degraded sites are more feasible and likely to succeed, while highly degraded sites may be too costly and unlikely to recover.

Conclusions

Amidst the global biodiversity crisis and financial constraints, spatial prioritization principles are essential for effective conservation strategies. Comprehensive, representative data and the use of appropriate biodiversity indicators can guide the creation of non-random, ecologically sound priority areas. Systematic conservation/restoration planning, incorporating spatial prioritization, optimizes resource use and enhances long-term outcomes, balancing ecosystem preservation with human food production needs.