There is an urgent need for a global transition to sustainable and wildlife-friendly farming systems that provide social and economic equity and protect ecosystem services on which agriculture depends. Java is home to 60% of Indonesia’s population and harbors many endemic species; thus, managing agriculture alongside human well-being and biodiversity is vital. Within a community of ~400 coffee farmers in the province of West Java, we assessed the steps to develop a wildlife-friendly program until reaching certification between February 2019 and October 2020. We adopted an adaptive management approach that included developing common objectives through a process of stakeholder consultation and co-learning. We firstly investigated via interviews the expectations and the issues encountered by 25 farmers who converted to organic production in 2016. Their main expectations were an increase in income and an increase in coffee quality, while they had issues mainly in finding high quality fertilizers, reducing pests, and increasing productivity. We used this information to establish a problem-solving plan for the transition to community-wide wildlife-friendly practices. As part of the adaptive evaluation, we assessed the quality of coffee plantations before and after the implementation of coproduced actions. The quality of coffee significantly improved after our interventions to reduce the coffee berry borer, especially in the fields that started as inorganic and converted to organic. We uncovered additional issues to meet the standards for certification, including banning hunting and trapping activities and increasing coffee quality for international export. We describe the coproduced actions (agroforestry, conservation education, local law, organic alternatives) and phases of the program and discuss the potential barriers. We provide novel evidence of adaptive management framework successfully used to implement management actions and reach shared goals.

Complex agroforestry systems can host similar biodiversity levels to adjacent continuous forests and can offer important ecosystem services for wildlife. Species inhabiting adjacent forests, as well as species that prefer agroforestry systems, can benefit from this habitat matrix. It is necessary, however, to understand the species-specific adaptability to such a complex matrix. Indonesia is a biodiversity hotspot and hosts many endemic species that are threatened with extinction. Its human population relies heavily on agriculture, meaning that finding a balance between crop productivity and biodiversity is key for the long-term sustainability of local communities and wildlife. We aim to determine the influence of the presence of shade trees and distance to the forest on the detection rates of wildlife in coffee home gardens. In West Java, Indonesia, we monitored 23 gardens between April 2018 and March 2021 via camera traps, totalling 3856 days of monitoring in shade-grown and 3338 days in sun-exposed gardens. We also collected data in the nearby montane rainforest, totalling 1183 days of monitoring. We used Generalized Additive Models to estimate the influence of shade cover and distance to the forest on the detection rates of wildlife. The Sunda leopard cat Prionailurus javanensis was found more frequently in shade-grown gardens and used both the forest and agroforest matrix. Wild boars Sus scrofa mostly occurred in gardens adjacent to the forest, while barred buttonquails Turnix suscitator were associated with gardens far (>1 km) from the forest. Several species (civets Viverricula indica and Paradoxus musangus javanicus, Horsfield’s treeshrew Tupaia javanica, Javan ferret badger Melogale orientalis, Javan mongoose Herpestes javanicus) were not influenced by shade cover and distance to the forest, suggesting they are well adapted to the agroforestry system. Still, species of high conservation importance, such as Javan leopard Panthera pardus melas, Sunda porcupine Hystrix javanica, and grizzled langur Presbytis comata, were present in the forest but not in the agroforest, suggesting that the replacement of the forest by the agroforestry matrix is still detrimental. Nevertheless, it is important to maintain the complexity of the agroforestry system and connectivity with the neighbouring continuous forest to favour the long-term sustainability of this environment and the conservation of endemic species.

Agroforestry has been widely suggested as a tool for storing carbon while also providing other ecosystem services like food and income production. A greater understanding of how carbon storage in agroforestry systems varies, and particularly how it is intertwined with the productivity of these systems, could enable farmers and policymakers to make changes that simultaneously increase carbon storage and alleviate poverty. In this study, we used allometric equations to evaluate the carbon storage in the biomass of two complex agroforestry systems in Bali, Indonesia—rustic where a native tree canopy is still present, and polyculture where all native trees have been removed, and the canopy consists only of cropping trees. We then compared these figures to that of a nearby primary forest and linked carbon storage to productivity for both agroforestry systems. We found that the primary forest (277.96 ± 149.05 Mg C ha⁻¹) stored significantly more carbon than either the rustic (144.72 ± 188.14 Mg C ha⁻¹) or polyculture (105.12 ± 48.65 Mg C ha⁻¹) agroforestry systems, which were not significantly different from each other. We found productivity and carbon storage to be significantly positively correlated with each other within the polyculture system but not within the rustic system. We also found that for the rustic system, an increase in the density of native trees is accompanied by an increase in carbon storage, but no significant change in productivity. Consequently, we conclude that within the rustic system, carbon storage can be increased or maintained at a high value by the preservation and encouragement of large native trees, and that this need not necessarily result in a decrease in productivity.