Report on the use of passive acoustic monitoring in Wood Buffalo National Park
Abstract
Passive acoustic monitoring has proven to be a valuable tool for monitoring vocalizing species. Environmental sensors are becoming increasingly easy to program and can autonomously generate extensive data sets of the soundscape, becoming an invaluable resource for ecological integrity monitoring. Wood Buffalo National Park deployed autonomous recording units (ARUs) across 91 locations during a comprehensive five-year survey. ARUs detected a total of 168 species including birds, amphibians and mammals. The analysis revealed
Land Acknowledgement
In the spirit of Reconciliation, we respectfully acknowledge that the lands of Wood Buffalo National Park where this study took place are the traditional territories of the Mikisew Cree First Nation, Athabasca Chipewyan First Nation, Fort Chipewyan Métis, Salt River First Nation, K’atl’odeeche First Nation, Deninu Kue First Nation, Fort Smith Métis Council, Hay River Métis Council, and the Fort Resolution Métis Council.
Introduction
Human activities have been identified as key pressures and contributors to the global decline in forest wildlife (Allan et al. (2017)). The repercussions of habitat fragmentation (Fahrig (2003)) and loss (Hanski (2011)), climate change (Mantyka-pringle, Martin, and Rhodes (2012), Sattar et al. (2021), Abrahms et al. (2023)), and increased access to sensitive areas exert direct and indirect pressures on forest biodiversity, particularly in managed regions in Canada (Lemieux et al. (2011)).
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In 2018, Wood Buffalo National Park’s Forested Region initiated a program incorporating autonomous recording units (ARUs) for passive acoustic monitoring (PAM) of the Park’s wildlife. ARUs are compact environmental sensors that are designed to passively record the environment (Shonfield and Bayne (2017)), capturing vocalizing species like birds and amphibians, which is growing in use across the globe (Sugai et al. (2018)). This technology enables resource managers to conduct prolonged surveys with minimal human interference. The subsequent data collected by these units contribute valuable information to ecological integrity metrics such as species richness, diversity, occupancy, and trends over time. This data aids decision-making and management within the Park. Given the rapid and ease of accumulating data from these units, maintaining a high standard of data integrity is paramount to ensure future data interoperability and sharing. WildTrax is an online platform developed by the Alberta Biodiversity Monitoring Institute (ABMI) for users of environmental sensors to help addresses these big data challenges by providing solutions to standardize, harmonize, and share data.
The objectives of this report are to:
- Describe the data management and processing procedures for the acoustic data collected from 2018 to 2023;
- Utilize traditional human tagging, visual scanning and automated recognition techniques to detect and count species and individuals heard on recordings;
- Define straightforward methods for evaluating species presence, species richness, and species occupancy over time at various locations; * Offer recommendations for ongoing monitoring approaches to contribute to the assessment of ecological integrity in forest ecosystems;
- Facilitate data publication to the public, resource managers, academic institutions, and any other relevant agencies
Methods
Data were collected during the spring and summer seasons from 2014 to 2023. A total of 91 locations were surveyed over the five-year period:
Locations were surveyed on rotation with 6 locations (WBNP-HWY-2, WBNP-HWY-3, WBNP-HWY-4, WBNP-PAD-1-14, WBNP-PAD-1-16, WBNP-PAD-1-8) surveyed each year. A detailed list of all survey years can be found in Table 1 (?@tbl-loc-summary) and illustrated in Figure 1 (Figure 1). ARUs were deployed at the beginning of the breeding season in April-May, and rotated locations until their final retrieval in July-August. The ARUs were set to record for []. On average, each ARU recorded for
Data collection and management
Community data processing
The principal goal for data processing was to describe the acoustic community of species heard at locations while choosing a large enough subset of recordings for analyses. To ensure balanced replication, for each location and year surveyed, four randomly selected recordings were processed for 3-minutes between the hours of 4:00 AM - 7:59 AM ideally on four separate dates (see ?@tbl-loc-repl), and four recordings during the dusk hours (19:00 - 23:00) for nocturnal vocalizing species. Four recordings will ensure that we have the minimum number of samples for a simple occupancy analysis (Darryl I. MacKenzie et al. (2002) and Darryl I. MacKenzie et al. (2003)). Tags are made using count-removal (see Farnsworth et al. (2002), Sólymos et al. (2018)) where tags are only made at the time of first detection of each individual heard on the recordings. In case a species was overly abundant a TMTT (‘too many to tag’) flag was used (see ?@tbl-tmtt). 3% of the total tags were TMTT but were subsequently converted to numeric using wildRtrax::wt_replace_tmtt. We also verified that all tags that were created were checked by a second observer (n = 1.42) to ensure accuracy of detections (see ?@tbl-verified). Amphibian abundance was estimated at the time of first detection using the North American Amphibian Monitoring Program with abundance of species being estimated on the scale of “calling intensity index” (CI) of 1 - 3. Mammals such as Red Squirrel, were also noted on the recordings. After the data are processed in WildTrax, the wildRtrax package is use to download the data into a standard format prepared for analysis. The wt_download_report function downloads the data directly to a R framework for easy manipulation (see wildRtrax APIs).
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Results
Species richness
A total of 168 species were found across the five years. Figure 2 describes the relationship of species richness across each location and survey year with Figure 3 showing the relationship between species richness and survey effort.
| species_common_name | habitat_nesting |
|---|---|
| Alder Flycatcher | TSS |
| American Redstart | MW |
| Baltimore Oriole | OW |
| Bay-breasted Warbler | CW |
| Black-and-white Warbler | MW |
| Black-backed Woodpecker | CW |
| Black-throated Blue Warbler | MW |
| Black-throated Green Warbler | CW |
| Blackburnian Warbler | CW |
| Blackpoll Warbler | CW |
| Blue Jay | OW |
| Blue-headed Vireo | MW |
| Boreal Chickadee | CW |
| Brown Creeper | CW |
| Canada Jay | CW |
| Canada Warbler | MW |
| Cape May Warbler | CW |
| Chestnut-sided Warbler | MW |
| Chipping Sparrow | OW |
| Common Nighthawk | OW |
| Dark-eyed Junco | CW |
| Downy Woodpecker | MW |
| Eastern Wood-Pewee | OW |
| Fox Sparrow | OW |
| Golden-crowned Kinglet | CW |
| Gray Catbird | MW |
| Hairy Woodpecker | MW |
| Hermit Thrush | CW |
| Lincoln's Sparrow | TSS |
| Magnolia Warbler | MW |
| Mountain Bluebird | OW |
| Mourning Warbler | MW |
| Northern Flicker | MW |
| Northern Parula | OW |
| Orange-crowned Warbler | OW |
| Philadelphia Vireo | MW |
| Pileated Woodpecker | MW |
| Pine Warbler | CW |
| Red-eyed Vireo | MW |
| Ruby-crowned Kinglet | CW |
| Ruffed Grouse | MW |
| Rusty Blackbird | TSS |
| Swainson's Thrush | MW |
| Veery | MW |
| Warbling Vireo | MW |
| Western Wood-Pewee | OW |
| Yellow-bellied Sapsucker | MW |
| Yellow-rumped Warbler | CW |
Species diversity
Shannon’s diversity was stable based on results. (see Figure 5.)
Species occupancy
We selected `` species to represent the forest songbird community into 4 separate habitat nesting guilds (see Table 1): conifer (?@fig-spp-occ-conifer), deciduous (?@fig-spp-occ-decid), treed / shrubby (?@fig-spp-occ-tss) and open (?@fig-spp-occ-open). Analysis of species occupancy revealed diverse and varied changes across these species. Analytically, many models were singular, and a few exhibited overdispersion (indicated by c-hat in ?@tbl-c-hat), likely due to low detections or a limited sample size of spatial locations. Ubiquitous species such as [], demonstrated stable site occupancy across the years. Generalist species or those capable of capitalizing on utilizing mixed habitats, exemplified by [], also maintained consistent occupancy levels. The occurrence of [2023 fire] led to notable breakpoints in the occupancy of certain species: RESULTS