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Browsing by Author "Wear, David N."

Now showing 1 - 3 of 3
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    Investigating the Cooperative Behavior of Nonindustrial Private Forest Landowners when Stands are Spatially Interdependent
    Vokoun, Melinda M. (Virginia Tech, 2005-03-07)
    This research examines how the harvesting behavior of nonindustrial private forest landowners, and their use of forestland for non-timber amenities, is affected by adjacent landowner behavior. The uncertainty an individual landowner has regarding adjacent landowners' preferences, and how the production of non-timber amenities on their own stands relies on the condition of adjacent stocks, is specifically addressed. Economic characterizations of substitutes and complements are employed to investigate the differences in optimal stock levels at the steady state in the production of amenities under various levels of cooperation among landowners. It is shown that there are externalities present when landowners do not coordinate management actions when parcels are spatially interdependent. The effects of spatial interdependencies on landowner behavior are further explored using data from a survey of forest landowners in Central Virginia. Findings suggest that forest landowners are willing to coordinate activities, and such decisions are determined by similar characteristics that function in predicting landowner behavior regarding timber harvesting. Further, landowners' decisions to use own and adjacent parcels were correlated, hinting at the spatial interdependencies of stocks in amenity valuations. Both the theoretical and empirical analyses suggest that the lack of coordination among landowners and its effects on stock management would be best addressed through the use of incentives to drive spatially efficient outcomes.
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    Targeting Nonindustrial Private Forest Landowner Groups for Timber Market Entry
    Conway, M. Christine (Virginia Tech, 2002-08-30)
    This study models the timber market entry decisions of nonindustrial private landowners. It involves examining reservation prices both for harvesting timber from existing forest land and for afforestation of marginal agricultural and abandoned land. An important conclusion drawn from these models is that financial returns are not the only drivers of these decisions. Preferences for amenities derived from forests and farmland are also important. An empirical model follows which characterizes willingness to accept for various landowner groups in Virginia and Mississippi. We identify preferences and characteristics of landowners and features of forest sites that are important to the unobserved price specific to each landowner. Estimation results are also used to assess the size of payments needed to encourage harvesting or conversion from agricultural to forest uses with 50% probability. The determination of reservation prices for landowners in different regions aids in forecasting potential timber supplies from NIPF lands that are either actively managed for timber production or are not, as well as from marginal land not yet in forests, under different policy and pricing scenarios. Furthermore, it gives insight into evolving land use patterns.
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    Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns
    Brooks, Evan B.; Coulston, John W.; Riitters, Kurt H.; Wear, David N. (2020-10-15)
    Future land use projections are needed to inform long-term planning and policy. However, most projections require downscaling into spatially explicit projection rasters for ecosystem service analyses. Empirical demand-allocation algorithms input coarse-level transition quotas and convert cells across the raster, based on a modeled probability surface. Such algorithms typically employ contagious and/or random allocation approaches. We present a hybrid seeding approach designed to generate a stochastic collection of spatial realizations for distributional analysis, by 1) randomly selecting a seed cell from a sample ofncells, then 2) converting patches of neighboring cells based on transition probability and distance to the seed. We generated a collection of realizations from 2001-2011 for the conterminous USA at 90m resolution based on varying the value ofn, then computed forest area by fragmentation class and compared the results with observed 2011 forest area by fragmentation class. We found that realizations based on values ofn <= 256 generally covered observed forest fragmentation at regional scales, for approximately 70% of assessed cases. We also demonstrate the potential of the seeding algorithm for distributional analysis by generating 20 trajectories of realizations from 2020-2070 from a single example scenario. Generating a library of such trajectories from across multiple scenarios will enable analysis of projected patterns and downstream ecosystem services, as well as their variation.