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.