Picture This: Wildlife Habitat Suitability Across a Chronosequence of Wildfire-Origin Stands at a Jack Pine Barrens
Meghan Bargabos, Zachary Hart, Dr. Mark Lesser, Dr. Danielle Garneau
SUNY Plattsburgh, Center for Earth and Environmental Science
Introduction
In the northeastern United States, pine barrens ecosystems are often relatively small landscape patches nested within a matrix of northern hardwood forest with low burn frequency. Thus, pine barrens not only represent a unique habitat type for wildlife at the landscape scale, but also may contain varied forest patches of differing stand age and structure based on their disturbance history. Wildlife may, in turn, respond in their use of this habitat mosaic that is experiencing patch-level successional differences in forest structure and composition since that has been shaped by time since the wildfire disturbance. The objective of this study is to quantify wildlife habitat suitability across a fire-dependent jack pine (Pinus banksiana) sandstone pavement barrens in northeastern New York.
Methods
The Altona Flat Rock is an ~2000 ha pine barrens dominated by jack pine interspersed with, and surrounded by, northern hardwood forest. Over the past century areas of the Flat Rock have experienced wildfire in 1919, 1940, 1957, and most recently 2018, resulting in a chronosequence of stand-origin ages. Beginning in September 2022, we established a network of twenty 1km2 grid cells spanning the Flat Rock and surrounding hardwood forest. We positioned a camera trap in the center of each grid cell to continuously monitor wildlife.
Additionally, we randomly selected three locations within each grid cell to determine forest structural attributes. We quantified understory composition using a 1x1 m quadrat, canopy cover using a densiometer, determined tree heights using a clinometer, characterized forest composition using prisms and DBH tape, and counted downed woody debris. Statistics for each grid cell were calculated form the Kriged surfaces using the extract by mask spatial analyst tool and the zonal statistics as table spatial analyst tool to get means and standard deviations of data in each grid (see "Structural Diversity" tab for more information).
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We also chose three jack pine at each forest structure site to core in order to more accurately age the stands across the Flat Rock. A more in-depth approach will be established in the summer and fall where we will randomly select more forest structure sites within each grid cell.
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iButtons are installed at each camera site to collect temperature and humidity data every four hours. This will allow us to have a better understanding of how seasonality might be influencing habitat use.
Preliminary Results
Overall occurrences/day across all camera sites.
Occurrences/day at each camera site.
Relative occurrences/day at each camera site.
Deer were the most abundant species found across all camera sites, followed by coyote, snowshoe hare, and red squirrel.
Occurrences/day by stand type.
The medium density jack pine showed the highest species diversity and richness. However, deer did not prefer this habitat type.
What's next?
We will begin collecting temperature/humidity data, continue collecting game camera data throughout 2023, and we will continue forest structure data collection in order to better age the stands and conduct in order more in-depth forest structure analysis to be able to include that in occupancy models, and eventually we’ll be able to answer how wildlife are responding to different-aged forests and see the seasonal influences on wildlife presence.
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Occupancy modeling assists with accounting for imperfect detection of species, and we are able to include forest structure data in the model to better understand where species occur, what influences where a species is found, and the different elements of a habitat that influence the presence or absence of a species. So, ultimately, we are able to see how different landscape characteristics, such as the varying structural attributes, may influence species distribution.
Acknowledgements
Thank you to my advisors, Dr. Lesser and Dr. Garneau, for their continued support throughout this project.
Thank you to those who have helped with the field work, analysis, or both: Zachary Hart, Caley Doell, James Wholey, Madelyn Lehman, Casey Halloran, and Liam Rascoe.
And finally, thank you to SUNY Plattsburgh, the Center for Earth and Environmental Science, and the Miner Institute for funding this project.