Small-to mid-sized forest carnivores, also known as mesocarnivores, are an important part of the animal community within national forests. Many forest mesocarnivores are of conservation concern and are listed as threatened or endangered under the Endangered Species Act (ESA), have been petitioned for listing under the ESA multiple times, or have designations within the Forest Service that warrant consideration in decisions about planning, projects, or restoration. Mesocarnivores also receive heightened public attention and, as a result, are frequently the center of lawsuits brought against the Forest Service. However, there is no current monitoring framework in place to provide meaningful information about these species across larger scales. In addition, they are difficult to detect, occur in low densities, and have large home ranges.We propose an approach for monitoring fisher (Pekania pennanti), Canada lynx (Lynx canadensis), American marten (Martes americana), Pacific marten (M. caurina), montane red fox (Vulpes vulpes sspp.), and wolverine (Gulo gulo) across the western United States. This approach was developed with close collaboration between the Forest Service Rocky Mountain Research Station and the National Forest System (NFS), and focuses on answering three basic monitoring questions: (1) Is a species present? (2) Are multiple individuals of a single sex present? and (3) Are multiple individuals, including both sexes, present? To answer these questions we designed a goal efficient monitoring (GEM) framework with four occupancy states related to a rare species population. We developed a Bayesian multistate dynamic occupancy model to analyze this information over time and estimate the probability that a population is likely to remain in one of these four occupancy states or transition to a different state. This document elucidates the process that led to the decision to use this framework and outlines the conceptual basis for GEM. A practitioner's guide with detailed GEM implementation instructions will follow in a subsequent publication.

Canada lynx (Lynx canadensis) is a federally threatened species in the contiguous United States. Within National Forests covered by the Northern Rockies Lynx Management Direction, Federal land managers must consider the effect of management activities on Canada lynx habitat. A common method to assess Canada lynx habitat used by the U.S. Forest Service is to measure horizontal cover using a cover board. We used field measurements and airborne Light Detection and Ranging (LIDAR) metrics to test beta regression models that predict estimates of horizontal cover on the Nez Perce–Clearwater National Forest, Idaho, USA, 2009–2015. We also investigated the effect on model predictions when the cover board was blocked by the main stem of a tree. Model fit statistics for normalized root mean square errors (RMSE%) were 30.8–33.7% and pseudo‐R2 ranged from 0.64 to 0.71. Using independent validation data, model performance statistics for RMSE% were 24.6–33.5% and R2 ranged from 0.51 to 0.69. We found that removing cover board measurements where the main stem of a tree blocked >75% of the cover board produced the best model statistics. These models can be applied across LIDAR extents resulting in maps of horizontal cover estimates, which may be used in assessing effects of management activities on Canada lynx habitat. © 2019 The Wildlife Society.