Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a crucial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data and Random Forest (RF) models, to develop 30-m maps of the presence (i.e., any occurrence) and severity (i.e., cumulative percent basal area mortality) of beetle-caused tree mortality 1997–2019 in subalpine forests throughout the Southern Rocky Mountains, USA. Using resultant maps, we also quantified spatial patterns of cumulative tree mortality throughout the region, an important yet poorly understood concept in beetle-affected forests. RF models using LTS products to predict presence and severity performed well, with 80.3% correctly classified (Kappa = 0.61) and R2
= 0.68 (RMSE = 17.3), respectively. We found that ≥10,256 km2
of subalpine forest area (39.5% of the study area) was affected by bark beetles and 19.3% of the study area experienced ≥70% tree mortality over the twenty-three year period. Variograms indicated that severity was autocorrelated at scales < 250 km. Interestingly, cumulative patch-size distributions showed that areas with a near-total loss of the overstory canopy (i.e., ≥90% mortality) were relatively small (<0.24 km2
) and isolated throughout the study area. Our findings help to inform an understanding of the variable effects of bark beetle outbreaks across complex forested regions and provide insight into patterns of disturbance legacies, landscape connectivity, and susceptibility to future disturbance.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited