Evaluating spatially explicit viability of a declining ruffed grouse population

Species associated with early successional habitats have experienced dramatic declines in the eastern United States as a result of land use changes and human disruption of natural disturbance regimes. Consequently, active management is required to create early successional habitat and promote plant and animal communities that depend on periodic forest disturbance. Ruffed grouse (Bonasa umbellus) depend on recently disturbed forest habitat, and have experienced dramatic declines over the last half-century. Although ruffed grouse are extensively studied, little effort has been made to link population dynamics with habitat management at landscape scales. We used stochastic, spatially explicit population models that combined landscape conditions derived from a Geographic Information System with demographic data, and applied the model to a declining ruffed grouse population in Rhode Island, USA. We identified vital rates that influence ruffed grouse population dynamics using baseline models constructed with current demographic rates and landscape conditions, and assessed the effect of landscape-scale forest management alternatives on population persistence by running multiple management simulations. Baseline models typically predicted population decline, and we concluded that vital rates (survival and recruitment) had a greater influence on population persistence than did dispersal capability, carrying capacity, or initial population size. Management simulations predicted greater population persistence under a scenario where high-quality habitat was provided in fewer large blocks as opposed to many small blocks, and the rate at which we allowed ruffed grouse to colonize newly created habitat had a substantial impact on management success. Populations of ruffed grouse in the eastern United States are likely to continue to decline given current disturbance regimes, and our work provides a link between ruffed grouse demography and landscape-scale habitat conditions to support management decisions. © 2011 The Wildlife Society.     

Forest and Landscape Structure as Predictors of Capercaillie Occurrence

ABSTRACT Capercaillie (Tetrao urogallus) is a large, endangered forest grouse species with narrow habitat preferences and large spatial requirements that make it susceptible to habitat changes at different spatial scales. Our aim was to evaluate the relative power of variables relating to forest versus landscape structure in predicting capercaillie occurrence at different spatial scales. We investigated capercaillie-habitat relationships at the scales of forest stand and forest-stand mosaic in 2 Swiss regions. We assessed forest structure from aerial photographs in 52 study plots each 5 km². We classified plots into one of 3 categories denoting the observed local population trend (stable, declining, extinct), and we compared forest structure between categories. At the stand scale, we used presence-absence data for grid cells within the plots to build predictive habitat models based on logistic regression. At this scale, habitat models that included only variables relating to forest structure explained the occurrence of capercaillie only in part, whereas variables selected by the models differed between regions. Including variables relating to landscape features improved the models significantly. At the scale of stand mosaic, variables describing forest structure (e.g., mean canopy cover, proportion of open forest, and proportion of multistoried forest) differed between plot categories. We conclude that small-scale forest structure has limited power to predict capercaillie occurrence at the stand scale, but that it explains well at the scale of the stand mosaic. Including variables for landscape structure improves predictions at the forest-stand scale. Habitat models built with data from one region cannot be expected to predict the species occurrence in other regions well. Thus, multiscale approaches are necessary to better understand species-habitat relationships. Our results can help regional authorities and forest-management planners to identify areas where suitable habitat for capercaillie is not available in the required proportion and, thus, where management actions are needed to improve habitat suitability.