Quantifying drought-induced tree mortality in the open canopy woodlands of central Texas

Abstract

Abstract During 2011, Texas experienced a severe drought, which caused substantial tree mortality. Drought-induced tree mortality can have significant ecological impacts and is expected to increase in many locations with climate change. This disturbance is unique because it often is limited to only subtle and diffuse changes in forest cover. Thus we developed new methods to quantify drought-driven canopy loss using remotely sensed imagery, across a Landsat scene in central Texas (> 30,000 km2). First, fine-scale canopy loss maps were created by classifying 17 1-m orthophotos (each ~ 50 km2) from the US National Agriculture Imagery Program. These classifications were highly correlated (R2 = 0.90) with field estimates of canopy cover loss measured in 21 plots at 4 sites across central Texas. These fine-scale canopy loss maps were then used to calibrate and validate coarser-scale Landsat imagery. In scaling up to create regional canopy loss maps, we assembled a Landsat time-series and separated mortality pixels experiencing persistent canopy loss from pixels with only background noise by applying the Landtrendr algorithm. We then estimated percent tree canopy loss within each of these mortality pixels by comparing two models capable of handling zero-inflated continuous proportions: random forest and a zero-or-one inflated beta (ZOIB) regression model. We found that the ZOIB regression model had the highest accuracy in predicting canopy loss (mean absolute error = 5.16%, root mean square error = 8.01%). The 2011 drought caused a decrease in canopy cover within the study area, equivalent to 1124 km2 of canopy loss, ~ 10% of the 10,850 km2 area of live canopy present before the drought. Our methods address the need to detect drought-induced tree mortality as extreme droughts are predicted to increase with climate change. More detailed canopy loss maps could then be used (1) to quantify potential impacts to carbon cycling, biophysics, and species compositions and (2) to understand the factors controlling tree mortality, now and in the future.