A rapid tree diversity assessment method for cocoa agroforestry systems

Biodiversity is recognized as an essential part of sustainable development efforts, however reducing biodiversity loss is a key global challenge that requires updated data on biodiversity status at different scales. Cocoa agro-forests include tree species besides cocoa, a practice beneficial to biodiversity, ecosystem conservation and farming households. We present a stepwise procedure to test and select a method that rapidly assesses biodi-versity in cocoa agroforests based primarily on species richness and counts of non-cocoa trees. Three rapid assessment methodologies (RapidBAM) with different sampling procedures were tested in three phases: cali-bration, testing and evaluation. Results showed the method using the lowest number of sample plots with a minimum area coverage and a consistent sampling time (regardless of farm context) provided the most accurate and straightforward assessment. Farmers accurately reported qualitatively on species, complimenting quanti-tative data produced by RapidBAM. Collecting biodiversity data with RapidBAM proved valuable to collect data at large-scales and is applicable to different landscapes. Monitoring biodiversity with fewer required resources than conventional methods is a relevant outcome, which can help defining efficient biodiversity-friendly farming practices.

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Bibliographic Details
Main Authors: Raneri, Jessica E., Oliveira, Sandra, Demers, Nicole R., Asare, Richard, Nuamah, Seth, Dalaa, Mustapha A., Weise, Stephan
Format: Journal Article biblioteca
Language:English
Published: Elsevier 2021-11
Subjects:agroforestry systems, methods, data collection, biodiversity, sistemas agroforestales, métodos, colección de datos,
Online Access:https://hdl.handle.net/10568/114551
https://doi.org/10.1016/j.ecolind.2021.107993
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Summary:Biodiversity is recognized as an essential part of sustainable development efforts, however reducing biodiversity loss is a key global challenge that requires updated data on biodiversity status at different scales. Cocoa agro-forests include tree species besides cocoa, a practice beneficial to biodiversity, ecosystem conservation and farming households. We present a stepwise procedure to test and select a method that rapidly assesses biodi-versity in cocoa agroforests based primarily on species richness and counts of non-cocoa trees. Three rapid assessment methodologies (RapidBAM) with different sampling procedures were tested in three phases: cali-bration, testing and evaluation. Results showed the method using the lowest number of sample plots with a minimum area coverage and a consistent sampling time (regardless of farm context) provided the most accurate and straightforward assessment. Farmers accurately reported qualitatively on species, complimenting quanti-tative data produced by RapidBAM. Collecting biodiversity data with RapidBAM proved valuable to collect data at large-scales and is applicable to different landscapes. Monitoring biodiversity with fewer required resources than conventional methods is a relevant outcome, which can help defining efficient biodiversity-friendly farming practices.