Abstract

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

Highlights

  • Protected areas (PAs) are one of the main conservation strategies to counter the current biodiversity crisis [1]

  • The global characterization of PAs can provide multiple benefits and applications, such as (1) supporting short, mediumand long-term management actions, especially at the regional and global scales, that can ensure the maintenance of biodiversity and maximize the provision of ecosystem services [173,174], (2) evaluating the effects of climate change in PAs [175] and (3) informing policy initiatives, such as the European Biodiversity Strategy or the post-2020 Global

  • Locally derived variables are better descriptors of the ecosystems, global data sources are needed in order to systematically compare PAs across the globe and inform larger scale conservation actions

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Summary

Introduction

Protected areas (PAs) are one of the main conservation strategies to counter the current biodiversity crisis [1]. Among others, the monitoring of vegetation conditions, landscape and habitat changes, land degradation, the assessment of ecosystem services, the identification of disturbed areas and the monitoring of the spread of invasive species [25,26,27,28] They help to understand an ecosystem’s response and resilience to multiple stressors [29]. This study seeks to provide recommendations for the biophysical characterization of importance of taking into account structural and functional attributes, as well as integratterrestrial PAs at the global scale by means of RS Focusing on terrestrial areas, we areas (MPAs).a few examples of RS data used to characterize marine protected areas (MPAs)

Relevant
Global Input Variables and Data Sources
Global Environmental Stratifications
Global Characterization of Protected Areas
Computing Infrastructures
Concluding Remarks and Recommendations
Methods
Findings
A New Map of Global Ecological Land Units
Full Text
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