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A novel citizen science-based wildlife monitoring and management tool for oil palm plantations

Maharani, N.; Nardiyono, N.; Swayanuar, P.; Munthe, C. R.; NiMatullah, S.; Sueif, S.; Zaini, S.; Supriatna, J.; Kusrini, M.; Dennis, R.; van Balen, B.; van Strien, A.; Meijaard, E.

2025-01-13 scientific communication and education
10.1101/2025.01.12.632638 bioRxiv
Show abstract

Agricultural expansion is one of the greatest threats to global biodiversity. At the same time, many wildlife species survive or even thrive in agricultural landscapes that retain patches of natural ecosystems. This is especially true for tropical oil palm (Elaeis guineensis, Jacq.) plantations that have both replaced tropical forest and other species-rich ecosystems, but as perennial crops can also function as wildlife habitat, especially if fragments of natural ecosystems are retained. There is an urgent need to understand how to manage and monitor wildlife in these fragmented oil palm landscapes. Still, the lack of large, quantitative datasets on species abundance impedes learning. We piloted a novel citizen science-based biodiversity monitoring system in Austindo Nusantara Jayas seven Indonesian oil palm estates, across different biogeographical regions, over a 5-year period. The company-wide monitoring system called PENDAKI, the Indonesian acronym for Care for Biodiversity, is the first of its kind in the palm oil industry. Here we demonstrate that such unstructured and opportunistic data collected mainly by lay people can result in valuable information on temporal and spatial changes in species occupancy. Between September 2019 and June 2024, PENDAKI has resulted in 148,286 wildlife observations, that included 699 reliably identified faunal and 186 floral species, with contributions from 3,950 employee contributors. We estimate species-specific occupancy rates using Bayesian occupancy modeling, ideally suited for opportunistic data where survey effort is unknown. We show that these occupancy data can reliably show temporal and spatial changes in the distribution of iconic wildlife such as orangutans (Pongo pygmaeus). We combined data from reliably identified species with at least 50 records to create the "Living Plantation Index", an estate-specific annual index of wildlife diversity based on occupancy estimates. We conclude that citizen science-based biodiversity monitoring works remarkably well in oil palm plantations because of the large number of people typically working there. In the process we discovered the emergence of co-benefits such as increasing environmental stewardship awareness across the workforce, raising the profile of the conservation department within the company. We also noted the benefits in terms of suitable data to meet regulatory and voluntary disclosure requirements.

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