Group-size-mediated habitat selection and group fusion-fission dynamics of bison under predation risk

For gregarious animals the cost-benefit trade-offs that drive habitat selection may vary dynamically with group size, which plays an important role in foraging and predator avoidance strategies. We examined how habitat selection by bison (Bison bison) varied as a function of group size and interpreted these patterns by testing whether habitat selection was more strongly driven by the competing demands of forage intake vs. predator avoidance behavior. We developed an analytical framework that integrated group size into resource selection functions (RSFs). These group-size-dependent RSFs were based on a matched casecontrol design and were estimated using conditional logistic regression (mixed and populationaveraged models). Fitting RSF models to bison revealed that bison groups responded to multiple aspects of landscape heterogeneity and that selection varied seasonally and as a function of group size. For example, roads were selected in summer, but not in winter. Bison groups avoided areas of high snow water equivalent in winter. They selected areas composed of a large proportion of meadow area within a 700-m radius, and within those areas, bison selected meadows. Importantly, the strength of selection for meadows varied as a function of group size, with stronger selection being observed in larger groups. Hence the bison-habitat relationship depended in part on the dynamics of group formation and division. Group formation was most likely in meadows. In contrast, risk of group fission increased when bison moved into the forest and was higher during the time of day when movements are generally longer and more variable among individuals. We also found that stronger selection for meadows by large rather than small bison groups was caused by longer residence time in individual meadows by larger groups and that departure from meadows appears unlikely to result from a depression in food intake rate. These group-size-dependent patterns were consistent with the hypothesis that avoidance of predation risk is the strongest driver of habitat selection

Mécanismes de connectivité fonctionnelle : un exemple avec le bison des plaines en milieu forestier

La connectivité de l'habitat est un déterminant important de la répartition spatiale des animaux. Cette connectivité dépend de leurs comportements face aux diverses composantes de l'habitat. Notre étude évalue les mécanismes de connectivité fonctionnelle chez les bisons sauvages. Nous avons déterminé que la sélection du prochain pré visité était influencée par ses caractéristiques intrinsèques (p. ex. disponibilité des plantes) et son accessibilité (p. ex. distance). Les bisons atteignaient le prochain pré sous l'influence de la persistance directionnelle et en orientant leurs déplacements vers les trouées forestières et le pré d'arrivée. De plus, la connectivité fonctionnelle variait durant l'année. Par exemple, ils préféraient des prés offrant davantage de biomasse végétale en hiver. Notre approche permet de quantifier la probabilité d'utilisation des prés et d'établir le chemin probable pour les atteindre. Ceci permet, en retour, de définir la connectivité fonctionnelle des prés, une étape nécessaire pour mieux comprendre la connectivité du paysage

Appendix B. Temporal variations in median distance moved during a three-hour interval by female plains bison in Prince Albert National Park, Saskatchewan, Canada.

Temporal variations in median distance moved during a three-hour interval by female plains bison in Prince Albert National Park, Saskatchewan, Canada

Appendix A. List of candidate resource selection functions for groups associated with female plains bison in Prince Albert National Park, Saskatchewan, Canada.

List of candidate resource selection functions for groups associated with female plains bison in Prince Albert National Park, Saskatchewan, Canada

The Montérégie Connection: Understanding How Ecosystems Can Provide Resilience to the Risk of Ecosystem Service Change

International audienceThe Montérégie Connection project aimed to help the community of this agricultural region just southeast of Montreal to improve management of multiple ecosystem services by developing and empirically testing a modeling framework that quantitatively linked landscape connectivity, biodiversity, and ecosystem services in this region. We will use this framework to build scenarios and other practical decision support tools with communities to help them grapple with the challenges of environmental management in the face of local, regional, and global change. We focused especially on how forest connectivity and forest corridors might help the local landscape maintain biodiversity and provide the desired ES in the face of these changes

The montérégie connection: Linking landscapes, biodiversity, and ecosystem services to improve decision making

To maximize specific ecosystem services (ES) such as food production, people alter landscape structure, i.e., the types of ecosystems present, their relative proportions, and their spatial arrangement across landscapes. This can have significant, and sometimes unexpected, effects on biodiversity and ES. Communities need information about how land-use activities and changes to landscape structure are likely to affect biodiversity and ES, but current scientific understanding of these effects is incomplete. The Montérégie Connection (MC) project has used the rapidly suburbanizing agricultural Montérégien landscape just east of Montreal, Québec, Canada, to investigate how current and historic landscape structure influences ES provision. Our results highlight the importance of forest connectivity and functional diversity on ES provision, and show that ES provision can vary significantly even within single land-use types in response to changes in landscape structure. Our historical analysis reveals that levels of ES provision, as well as relationships among individual ES, can change dramatically through time. We are using these results to build quantitative ES-landscape structure models to assess four future landscape scenarios for the region: Periurban Development, Demand for Energy, Whole-System Crisis, and Green Development. These scenarios integrate empirical and historical data on ES provision with local stakeholder input about global and local social and ecological drivers to explore how land-use decisions could affect ES provision and human well-being across the region to the year 2045. By integrating empirical data, quantitative models, and scenarios we have achieved the central goals of the MC project: (1) increasing understanding of the effects of landscape structure on biodiversity and ES provision, (2) effectively linking this knowledge to decision making to better manage for biodiversity and ES, and (3) creating a vision for a more sustainable social-ecological system in the region