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

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 pressure...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2021-06, Vol.13 (11), p.2148
Main Authors: Chraibi, Eric, Arnold, Haley, Luque, Sandra, Deacon, Amy, Magurran, Anne, Féret, Jean-Baptiste
Format: Article
Language:English
Subjects:
Agroforestry
alpha-diversity
Anthropogenic factors
Archives & records
beta-diversity
Biodiversity
biodiversity monitoring
diversity indices
Ecological succession
Endangered & extinct species
Environmental Sciences
Farmers
Forests
Landscape
Plant species
Regeneration
Remote sensing
Sentinel-2
Taxonomy
Trees
Tropical forests
Vegetation
Wildlife conservation
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Summary: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.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13112148