Northern Blue Mountains wildlife monitoring, 2022–2023

As part of the Collaborative Forest Landscape Restoration Program (CFLRP), USDA Forest Service Region 6 is implementing silviculture and prescribed-fire treatments to restore forests to historical structure and composition in the northern Blue Mountains of the Pacific Northwest on the Wallowa-Whitman and Umatilla National Forests. In 2021, we began a pilot monitoring effort to evaluate the efficacy of using passive acoustic recording units (ARUs) to monitor white-headed woodpecker (Picoides albolarvatus, hereafter WHWO) habitat use, and we demonstrated that ARUs are more efficient and more effective for white-headed woodpecker monitoring. Given these initial findings, in 2022, we expanded our monitoring objectives to the following: 1) develop, implement, and evaluate a sampling design to monitor the distribution of WHWO and other species of wildlife in the northern Blue Mountains; 2) estimate WHWO nest site selection and nest success in relation to the size and spatial arrangements of management treatments; and 3) estimate WHWO home range size and foraging habitat use in relation to the size and spatial arrangements of management treatments. 

We also had two short-term objectives that included 1) uncovering logistical challenges for conducting fieldwork at this scale in this region and 2) collecting enough training data (i.e., example calls/songs of target species) to develop supervised learning algorithms to efficiently and effectively process large volumes of audio data in future years. 

Furthermore, we had two long-term objectives, including 1) developing a sampling design that allows for data integration with other large-scale monitoring programs focused on wildlife community habitat use and 2) establishing a monitoring program that can support spatially explicit decision-support models to inform management decision 1 making using an adaptive management framework. 

This report describes accomplishments, preliminary results, and lessons learned in year 2 and 3 (i.e., 2022 and 2023) of this monitoring effort. Thus far, we have successfully tagged and tracked approximately 40 adult WHWO and collected nest success data at approximately 20 WHWO nests. Using these data, we are beginning to better understand nest site selection, nest success, and space use patterns for WHWO in this area. Furthermore, we have collected over 100,000 hrs of audio data at over 400 survey stations across two national forests. Using these audio data, we have been able to contribute to a global effort to track wildlife communities using passive acoustic monitoring, have conducted some of the first formal evaluations of embedding searches and transfer learning to process large volumes of acoustic data with limited training data, have accumulated what we believe to be the largest acoustic training dataset for east-side avian species in the Pacific Northwest, have begun to understand avian community dynamics in the Blue Mountains, and more. Viewed together, this project monitors wildlife biodiversity responses to management actions and produces the requisite monitoring data needed to integrate monitoring, models, and management to implement adaptive management for wildlife resources. 

This is the first largescale wildlife monitoring program in this relatively understudied region to collect data on the entire avian community successfully. Notably, this effort improves upon previous CFLRP monitoring efforts by simultaneously monitoring the entire avian community with the same level of field effort typically used for point counts of focal species. Through our data and information sharing, we have been able to help biologists across the Pacific Northwest understand and process their own audio data to efficiently collect species occurrence data during the project planning phase of the National Environmental Policy Act (NEPA) process. Thus, it provides data and tools that managers have long sought to help inform data-driven management decision making. Actions to reduce fuels/wildfire risk are ubiquitous across much of the west and the techniques and models developed herein can be transferred to other forests. As an example, this study has already begun to reshape the way managers monitor for avian species to inform decisions in a way that is effective, efficient, and can be integrated with other largescale monitoring efforts in the Pacific Northwest.

For more information on this collaborative project, please refer to the project website.