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 impli..., The study was conducted in Southwestern Panama, covering a 23,000-hectare area in Los Santos province. This region experiences a dry season from December to March, with most of its 1,700 mm of annual rainfall occurring between April and November. Historically, the landscape was dominated by dry tropical forests, but extensive cattle ranching has reduced forest cover to a small fraction of its original extent. The current landscape consists of active pastures, riparian corridors, and second-growth forests, with ongoing agricultural de-intensification and reforestation efforts.
To assess tree mortality between 2012 and 2019, data were integrated from three sources: field measurements of individual trees, aerial hyperspectral-lidar imagery, and high-resolution satellite imagery. Field data were collected during initial surveys in 2012 and 2013, when individual trees were identified, georeferenced, and classified by species. These trees were revisited in 2019 to determine survival, with dea..., , # Tree mortality in an agricultural landscape of Southwestern Panama assessed using remote sensing and field data

[https://doi.org/10.5061/dryad.gxd2547xt](https://doi.org/10.5061/dryad.gxd2547xt)

## Description of the data and file structure

These data represent field and remotely sensed measurements of tree mortality, along with landscape- and individual-level covariates for tree mortality. The file titled **\"y.csv\"** contains two columns. The first column represents the 269 trees whose mortality was measured directly in the field. The second column represents mortality estimated from remotely sensed data for 6,154 trees. Each row corresponds to a single tree. A value of 1 indicates tree survival, while a value of 0 indicates tree death. Values of -1 indicate trees that were measured using remotely sensed data but not field data.

The file titled **\"field.csv\"** includes a single column with an index indicating which trees were measured in the field (out of 6,154 total trees). Simi...,