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.