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Geology topics

Bruce D. Maxwell

Publications and source records attributed to Bruce D. Maxwell.

2 recordsLinked to original sources

Towards an urgent yet deliberate conservation strategy: Sustaining social-ecological systems in rangelands of the Northern Great Plains, Montana

Urgency and deliberateness are often at odds when executing conservation projects, especially as the scale and complexity of objectives increases. The pace of environmental degradation supports immediate and measurable action. However, best practices for adaptive governance and building resilient social-ecological systems call for more deliberate efforts and participatory processes, which can be slow. We explore conflicts between urgency and deliberateness and the potential for their reconciliation through a case study of the challenges of conserving native rangelands in North America’s Northern Great Plains, an ecoregion targeted for global conservation initiatives. This region is undergoing a significant social-ecological transition, which underscores a need to rethink conservation strategies in light of the social-ecological system dynamics and potential future trajectories. Based on a structured narrative literature review process and iterative engagement with key regional stakeholders, we identify three interrelated factors critical to the system’s future outcomes that illustrate system complexity as well as trade-offs between urgent and deliberate action and unilateral and multilateral approaches to conservation: (1) influences of land management on biodiversity, (2) economic restructuring and shifting land use priorities, and (3) changing climate and disturbance regimes. We identify key gaps in the literature for each factor and across the factors—an effort that informs our call for research and practice agendas that address uncertainty and complexity at regional scales through more inclusive and future-oriented approaches.

Montana

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis . The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis . However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Environmetrics