Ecology

Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/44

The department's teaching and research addresses critical ecological and natural resources issues for Montana, but also tackles fundamental and applied questions around the globe. Undergraduate programs within the department include Fish & Wildlife Management and Ecology, Conservation Biology and Ecology, Organismal Biology, and Biology Teaching. Graduate programs (M.S. and P.hD.) include Fish & Wildlife Management or Biology and Biological Sciences and an intercollege PhD in Ecology and Environmental Sciences.

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Author: search.filters.author.Flesch, Elizabeth P.

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    Evaluating wildlife translocations using genomics: A bighorn sheep case study
    (Wiley, 2020-12) Flesch, Elizabeth P.; Graves, Tabitha A.; Thomson, Jennifer M.; Proffitt, Kelly M.; Stephenson, Thomas R.; Garrott, Robert A.
    Wildlife restoration often involves translocation efforts to reintroduce species and supplement small, fragmented populations. We examined the genomic consequences of bighorn sheep (Ovis canadensis) translocations and population isolation to enhance understanding of evolutionary processes that affect population genetics and inform future restoration strategies. We conducted a population genomic analysis of 511 bighorn sheep from 17 areas, including native and reintroduced populations that received 0–10 translocations. Using the Illumina High Density Ovine array, we generated datasets of 6,155 to 33,289 single nucleotide polymorphisms and completed clustering, population tree, and kinship analyses. Our analyses determined that natural gene flow did not occur between most populations, including two pairs of native herds that had past connectivity. We synthesized genomic evidence across analyses to evaluate 24 different translocation events and detected eight successful reintroductions (i.e., lack of signal for recolonization from nearby populations) and five successful augmentations (i.e., reproductive success of translocated individuals) based on genetic similarity with the source populations. A single native population founded six of the reintroduced herds, suggesting that environmental conditions did not need to match for populations to persist following reintroduction. Augmentations consisting of 18–57 animals including males and females succeeded, whereas augmentations of two males did not result in a detectable genetic signature. Our results provide insight on genomic distinctiveness of native and reintroduced herds, information on the relative success of reintroduction and augmentation efforts and their associated attributes, and guidance to enhance genetic contribution of augmentations and reintroductions to aid in bighorn sheep restoration
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    Comparing citizen science and professional data to evaluate extrapolated mountain goat distribution models
    (2017-02) Flesch, Elizabeth P.; Belt, Jami J.
    Citizen science provides a prime opportunity for wildlife managers to obtain low-cost data recorded by volunteers to evaluate species distribution models and address research objectives. Using mountain goat (Oreamnos americanus) location data collected through aerial surveys by professionals, ground surveys by professionals, and ground surveys by volunteers, we evaluated two mountain goat distribution models extrapolated across Waterton-Glacier International Peace Park. In addition, we compared mountain goat location data by observer and survey type to determine whether there were differences that affected extrapolated model evaluation. We found that all dataset types compared similarly to both mountain goat models. A mountain goat occupancy model developed in the Greater Yellowstone Area (GYA) was the most informative in describing mountain goat locations. We compared Spearman-rank correlations (rs) for occupancy probability bin ranks in the GYA model extrapolation and area-adjusted frequencies of mountain goat locations, and we found that all datasets had a positive correlation, indicating the model had useful predictive ability. Aerial observations had a slightly greater Spearman-rank correlation (rs = 0.964), followed by the professional ground surveys (rs = 0.946), and volunteer ground datasets (rs = 0.898). These results suggest that with effective protocol development and volunteer training, biologists can use mountain goat location data collected by volunteers to evaluate extrapolated models. We recommend that future efforts should apply this approach to other wildlife species and explore development of wildlife distribution models using citizen science.
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