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USGS2022

Ungulate migrations of the western United States, volume 3

Ungulates (hooved mammals) have a broad distribution across the western United States and play an important role in maintaining predator-prey dynamics, affecting vegetation communities, and providing economic benefits to regional communities through tourism and hunting. Throughout the diverse landscapes they occupy, many ungulate populations undertake seasonal migrations to exploit spatially and temporally variable resources and to avoid predation or other threats. As the human footprint continues to expand across the western United States, ungulates increasingly face more obstacles on their migratory journeys. These obstacles threaten the long-term persistence of existing migrations. As a result, wildlife management agencies across the western United States have worked to identify and protect (or enhance) ungulate migration corridors and seasonal ranges identified from global positioning system (GPS) collar data. These efforts garnered additional support through the U.S. Department of the Interior Secretarial Order (SO) 3362, which was initiated in 2018 and provided Federal support for enhancing habitat quality of big-game winter ranges and migration corridors across the western states. Further, SO 3362 prompted the U.S. Geological Survey (USGS) to establish the Corridor Mapping Team (CMT): a collaboration between USGS and participating State and Federal wildlife management agencies, as well as numerous Tribal Nations. The CMT works collaboratively to map ungulate migrations and seasonal ranges throughout the western United States within the Ungulate Migrations of the Western United States report series. Volume 1 of the series was published in 2020 and contained migrations and winter ranges from 42 herds across 5 states. Volume 2 was published in 2022 and contained migrations and seasonal ranges from an additional 65 herds. This report, Volume 3 in the series, details migrations and seasonal ranges from an additional 45 herds throughout most western states. In aggregate, the report series has detailed and mapped the migrations and seasonal ranges of 152 ungulate herds and serves as a map-based inventory of the documented ungulate migrations across the western United States. The data layers for most of the herds included in the report series are also available to the public by the USGS. In addition to the included herd maps, this volume provides an overview of the many ways the mapping efforts associated with the CMT are being integrated into local conservation, management, and policy throughout the western United States.

Arizona, California, Idaho, Nevada, New Mexico, Or↗

USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗