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The increase of tree density in forests of the American Southwest promotes extreme fire events, understory biodiversity losses, and degraded habitat conditions for many wildlife species. To ameliorate these changes, managers and scientists have begun planning treatments aimed at reducing fuels and increasing understory biodiversity. However, spatial variability in tree density across the landscape is not well-characterized, and if better known, could greatly influence planning efforts. We used reflectance values from individual Landsat 8 bands (bands 2, 3, 4, 5, 6, and 7) and calculated vegetation indices (difference vegetation index, simple ratios, and normalized vegetation indices) to estimate tree density in an area planned for treatment in the Jemez Mountains, New Mexico, characterized by multiple vegetation types and a complex topography. Because different vegetation types have different spectral signatures, we derived models with multiple predictor variables for each vegetation type, rather than using a single model for the entire project area, and compared the model-derived values to values collected from on-the-ground transects. Among conifer-dominated areas (73% of the project area), the best models (as determined by corrected Akaike Information Criteria (AICc)) included Landsat bands 2, 3, 4, and 7 along with simple ratios, normalized vegetation indices, and the difference vegetation index (R2 values for ponderosa: 0.47, piñon-juniper: 0.52, and spruce-fir: 0.66). On the other hand, in aspen-dominated areas (9% of the project area), the best model included individual bands 4 and 2, simple ratio, and normalized vegetation index (R2 value: 0.97). Most areas dominated by ponderosa, pinyon-juniper, or spruce-fir had more than 100 trees per hectare. About 54% of the study area has medium to high density of trees (100–1000 trees/hectare), and a small fraction (4.5%) of the area has very high density (>1000 trees/hectare). Our results provide a better understanding of tree density for identifying areas in need of treatment and planning for more effective treatment. Our analysis also provides an integrated method of estimating tree density across complex landscapes that could be useful for further restoration planning.

The increasing frequency and severity of wildfires in semi-arid conifer forests as a result of global change pressures has raised concern over potential impacts on biodiversity. Ground-dwelling arthropod communities represent a substantial portion of diversity in conifer forests, and could be particularly impacted by wildfires. In addition to direct mortality, wildfires can affect ground-dwelling arthropods by altering understory characteristics and associated deterministic community assembly processes (e.g., environmental sorting). Alternatively, disturbances have been reported to increase the importance of stochastic community assembly processes (e.g., probabilistic dispersal and colonization rates). Utilizing pitfall traps to capture ground-dwelling arthropods within forest stands that were burned by one or two wildfires since 1996 in the Jemez Mountains of northern New Mexico, United States (USA), we examined the potential influences of deterministic versus stochastic processes on the assembly of these diverse understory communities. Based on family-level and genera-level arthropod identifications, we found that the multivariate community structures differed among the four fire groups surveyed, and were significantly influenced by the quantities of duff, litter, and coarse woody debris, in addition to tree basal area and graminoid cover. Taxon diversity was positively related to duff quantities, while taxon turnover was positively linked to exposed-rock cover and the number of logs on the ground. Despite the significant effects of these understory properties on the arthropod community structure, a combination of null modeling and metacommunity analysis revealed that both deterministic and stochastic processes shape the ground-dwelling arthropod communities in this system. However, the relative influence of these processes as a function of time since the wildfires or the number of recent wildfires was not generalizable across the fire groups. Given that different assembly processes shaped arthropod communities among locations that had experienced similar disturbances over time, increased efforts to understand the processes governing arthropod community assembly following disturbance is required in this wildfire-prone landscape.