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Reindeer husbandry and commercial forestry seek to co-exist in the forests of Northern Sweden. As interwoven as the two industries are, conflicts have arisen. Forest practices have reduced the distribution of lichen, the main winter diet for reindeer. Forest practices have also increased forest density, compromising the animals' ability to pass through forested areas on their migration routes. In an attempt to reduce impacts on reindeer husbandry, we present a spatially explicit harvest scheduling model that includes reindeer corridors with user-defined spatial characteristics. We illustrate the model in a case study and explore the relationship between timber revenues and the selection and maintenance of reindeer corridors. The corridors are not only to include sufficient lichen habitat, but they are also supposed to ensure access for reindeer by connecting lichen areas with linkages that allow unobstructed travel. Since harvest scheduling occurs over a planning horizon, the spatial configuration of corridors can change from one time period to the next in order to accommodate harvesting activities. Our results suggest that maintaining reindeer corridors in harvest scheduling can be done at minimal cost. Also, we conclude that including corridor constraints in the harvest scheduling model is critical to guarantee connectivity of reindeer pastures.

Wildlife corridors are often used to connect critical habitat for species protection. Mixed integer programming models have been used in the past to create wildlife corridors, but they lack the capacity to control corridor geometry. We propose an approach that employs path planning techniques from artificial intelligence to account for and control corridor geometry, such as width and length. By combining path planning with network optimization, our approach allows the user to control and optimize the geometric characteristics of wildlife corridors. We illustrate our approach on two realistic landscapes and present numerical results on several computer-generated landscapes. The computational results indicate that this approach is efficient and can address problems controlling corridor geometry that were previously thought intractable. The approach has potential applications in such areas as the selection of routes or barrier construction problems, an example of which is fire break design.

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This systematic review supports a recommendation for clinicians to perform routine hearing screening in children with CF during and after aminoglycoside exposure based on the high prevalence of SNHL in this population. Future studies should define the optimal timing for hearing screening during and after aminoglycoside therapy in children with CF.

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Spatially explicit harvest scheduling models optimize the layout of harvest treatments to best meet management objectives such as revenue maximization subject to a variety of economic and environmental constraints. A few exceptions aside, the mixed-integer programming core of every exact model in the literature requires one decision variable for every applicable prescription for a management unit. The only alternative to this "bruteforce" method has been a network approach that tracks the management pathways of each unit over time via four sets of binary variables. Named after their linear programming-based aspatial predecessors, Models I and II, along with Model III, which has no spatial implementation, each of these models rely on static volume and revenue coefficients that must be calculated pre-optimization. We propose a fundamentally different approach that defines stand volumes and revenues as variables and uses difference equations and Boolean algebra to transition forest units from one planning period to the next. We show via three sets of computational experiments that the new model is a computationally promising alternative to Models I and II.

No abstract