Tree mortality in an agricultural landscape of Southwestern Panama assessed using remote sensing and field data

Agricultural tree cover is declining globally, including the loss of large, scattered trees that function as keystone structures. Understanding the drivers of agricultural tree loss could help prevent further declines. However, the drivers of agricultural tree mortality vary across scales, from individual trees to landscapes, complicating efforts to quantify mortality risk. We applied high-resolution remote sensing and multi-method occupancy models to test hypotheses of drivers of tree mortality in a pastoral landscape of Southwestern Panama. Our approach enabled us to identify individual tree mortality across a >20,000 ha area, encompassing a wide range of land use intensity. Neighboring tree cover was the strongest predictor of mortality, with a higher probability of death for isolated trees relative to trees with many neighbors. Landscape-level covariates also predicted mortality risk, including higher mortality closer to roads and in parcels with larger areas. These results implicate land use intensity as a primary driver of agricultural tree loss in our study area. At the individual tree level, we found that larger trees were more likely to die than smaller trees. Our study suggests that the trees with high ecosystem service value in a fragmented landscape—large, isolated trees—also face the highest mortality risk. Supporting agricultural practices that maintain trees in pastures is likely to decrease tree mortality in our study site, broadly representative of cattle ranching landscapes across Latin America. Our workflow could be implemented in other landscapes globally to prioritize agricultural tree conservation, paving the way for increased tree survival and improved ecosystem services.