Browsing by Author "Edwards, Margaret"
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Item Hierarchical abundance modeling to inform oak savanna restoration within the Anoka Sand Plain of Minnesota(2019-02) Edwards, MargaretSand Dunes State Forest in Minnesota’s Anoka Sand Plan contains high quality remnants of oak savanna, a habitat that is imperiled across its entire range. To inform local restoration and management, we used hierarchical abundance models to describe relationships between habitat characteristics and rare wildlife species that utilize oak savanna. We found that predicted abundance and occupancy probability of Lark sparrow (Chondestes grammacus), Eastern towhee (Pipilo erythrophthalmus), Leonard’s skipper (Hesperia leonardus leonardus), and northern barrens tiger beetle (Cicindela patruela patruela) were affected by habitat features and management disturbance. It was noteworthy that some variables (e.g. canopy closure, recent disturbance) had disparate effects between species. These results highlight the importance of careful planning when undertaking habitat restoration. Plans should consider the habitat needs of individual species and their respective expected responses to active habitat management to achieve balance between maintenance of local populations and habitat restoration on a landscape scale.Item R Code and Output Supporting: Computational reproducibility in The Wildlife Society's flagship journals(2019-06-05) ArchMiller, Althea A; Johnson, Andrew D; Nolan, Jane; Edwards, Margaret; Elliot, Lisa H; Ferguson, Jake M; Iannarilli, Fabiola; Velez, Juliana; Vitense, Kelsey; Johnson, Douglas H; Fieberg, John R; ALTHEA.ARCHMILLER@GMAIL.COM; ArchMiller, Althea AThe goal of this study was to gauge the level of computational reproducibility, which is the ability to reach the same results using the same data and analysis methods, in the field of wildlife sciences. We randomly selected 80 papers published in the Journal of Wildlife Management and Wildlife Society Bulletin between 1 June 2016 and 1 June 2018. Of those for which we could obtain data, we attempted to reproduce their quantitative results using the original methods and data. The dataset shared in this repository is the de-identified results of our review, and the code provided here produces the results and figures in our published manuscript.