A Remote Sensing Approach to Understanding Patterns of Secondary Succession in Tropical Forest

Eric Chraibi,Haley Arnold,Anne Magurran,Sandra Luque,Jean-Baptiste Féret,Amy Deacon

doi:10.3390/rs13112148

Abstract

Monitoring biodiversity on a global scale is a major challenge for biodiversity conservation. Field assessments commonly used to assess patterns of biodiversity and habitat condition are costly, challenging, and restricted to small spatial scales. As ecosystems face increasing anthropogenic pressures, it is important that we find ways to assess patterns of biodiversity more efficiently. Remote sensing has the potential to support understanding of landscape-level ecological processes. In this study, we considered cacao agroforests at different stages of secondary succession, and primary forest in the Northern Range of Trinidad, West Indies. We assessed changes in tree biodiversity over succession using both field data, and data derived from remote sensing. We then evaluated the strengths and limitations of each method, exploring the potential for expanding field data by using remote sensing techniques to investigate landscape-level patterns of forest condition and regeneration. Remote sensing and field data provided different insights into tree species compositional changes, and patterns of alpha- and beta-diversity. The results highlight the potential of remote sensing for detecting patterns of compositional change in forests, and for expanding on field data in order to better understand landscape-level patterns of forest diversity.

Highlights

Biodiversity is under unprecedented threat [1,2,3,4], driven largely by habitat loss [5,6,7].Rapid changes in biodiversity [8,9,10] put ecosystem functioning at risk and jeopardize the essential services that we rely on [11]
We evaluated the relationship between Principal Coordinate Analysis (PCoA) from the S2-based Bray Curtis dissimilarity (BC) and forest age in the 19 surveyed forest sites, and used the most relevant axis to generate a map of forest ages in the region of interest
This study highlights the potential benefits of using Remote sensing (RS) to measure tropical forest biodiversity, as well as its limitations

Summary

Introduction

Biodiversity is under unprecedented threat [1,2,3,4], driven largely by habitat loss [5,6,7]. Rapid changes in biodiversity [8,9,10] put ecosystem functioning at risk and jeopardize the essential services that we rely on [11]. While the Aichi global biodiversity targets [12]. We mainly focus on the variability of biodiversity in tropical forests [13]; with a focus on tree species richness and evenness, while considering compositional change over succession. Tropical forests are important biodiversity hotspots which support many endemic and threatened species [14,15,16,17,18,19], these habitats continue to experience record losses across the globe. The reduction in the extent of primary forest in 2019 was

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