Massachusetts Project: Effects of habitat, density, and climate on moose and winter tick ecology in the northeast US

Massachusetts Project

Effects of habitat, density, and climate on moose and winter tick ecology in the northeast US

September 2021 - August 2024

Personnel

Participating Agencies

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Moose (Alces alces) populations in the northeastern US have declined by over 50% in the past 15 years. Winter tick (Dermacentor albipictus) infestations are a major driver of moose population trends, negatively affecting both survival and reproduction. We will partner with cooperators in Maine, Massachusetts, New Hampshire, New York, and Vermont to measure winter tick and moose distribution and abundance on a large camera trapping array. We will use our data to evaluate moose-tick dynamics across the full distribution of moose in New England. In doing so we can examine the relative importance of climate, habitat, and moose density in driving damaging epizootic conditions.

Research Publications

Research Publications	Publication Date
Schmidt, J.H., W.L. Thompson, T.L. Wilson, J.H. Reynolds. 2022. Understanding the impacts of the detection process on distance sampling surveys: selecting among approaches and minimizing total error. Wildlife Monographs 210: e1070. https://doi.org/10.1002/wmon.1070 \| Abstract	July 2022	Wildlife population estimators often require formal adjustment for imperfect detection of individuals during surveys. Conventional distance sampling (CDS) and its extensions (mark‐recapture distance sampling [MRDS], temporary emigration distance sampling [TEDS]) are popular approaches for producing unbiased estimators of wildlife abundance. However, despite extensive discussion and development of distance sampling theory in the literature, deciding which of these alternatives is most appropriate for a particular scenario can be confusing. Some of this confusion may stem from an incomplete understanding of how each approach addresses the components of the detection process. Here we describe the proper application of CDS, MRDS, and TEDS approaches and use applied examples to help clarify their differing assumptions with respect to the components of the detection process. To further aid the practitioner, we summarize the differences in a decision tree that can be used to identify cases where a more complex alternative (e.g., MRDS or TEDS) may be appropriate for a given survey application. Although the more complex approaches can account for additional sources of bias, in practical applications one also must consider estimator precision. Therefore, we also review the concept of total estimator error in the context of comparing competing methods for a given application to aid in the selection of the most appropriate distance sampling approach. Finally, we detail how the use of more advanced techniques (i.e., informed priors, open‐population distance sampling models, and integrated modeling approaches) can further reduce total estimator error by leveraging information from existing and ongoing data collection .By synthesizing the existing literature on CDS, MRDS, TEDS and their extensions, in conjunction with the concepts of total estimator error and the components of the detection process, we provide a comprehensive guide that can be used by the practitioner to more efficiently, effectively, and appropriately apply distance sampling in a variety of settings.

Presentations

Presentations	Presentation Date
Wilson, T.L., J.A. Berube, A.P.K. Sirén, 2022, Perfecting the Imperfect Detection of Ticks: Winter Tick Epizootics and Moose Populations in the Northeastern U.S. Moose research in the Northeast U.S. and eastern provinces of Canada: 2022 project updates. 6 July, 2022 on-line,	July 2022
Berube, J., A. P. K. Sirén, C. Frank, L. Clarfeld, B. Simpson, T.M. Donovan, T. L. Wilson. 2022. Perfecting the Imperfect Detection of Ticks: Winter Tick Epizootics and Moose Populations in the Northeastern U.S. Presentation. The Wildlife Society Annual Conference, Spokane, WA. 6-10 November 2022.	November 2022

Cooperative Fish and Wildlife Research Units Program: Massachusetts Education, Research and Technical Assistance for Managing Our Natural Resources