Land Ownership and Land‐Cover Change in the Southern Appalachian Highlands and the Olympic Peninsula

Abstract

Social and economic considerations are among the most important drivers of landscape change, yet few studies have addressed economic and environmental influences on landscape structure, and how land ownership may affect landscape dynamics. Watersheds in the Olympic Peninsula, Washington, and the southern Appalachian highlands of western North Carolina were studied to address two questions: (1) Does landscape pattern vary among federal, state, and private lands? (2) Do land‐cover changes differ among owners, and if so, what variables explain the propensity of land to undergo change on federal, state, and private lands? Landscape changes were studied between 1975 and 1991 by using spatial databases and a time series of remotely sensed imagery. Differences in landscape pattern were observed between the two study regions and between different categories of land ownership. The proportion of the landscape in forest cover was greatest in the southern Appalachians for both U.S. National Forest and private lands, compared to any land‐ownership category on the Olympic Peninsula. Greater variability in landscape structure through time and between ownership categories was observed on the Olympic Peninsula. On the Olympic Peninsula, landscape patterns did not differ substantially between commercial forest and state Department of Natural Resources lands, both of which are managed for timber, but differed between U.S. National Forest and noncommercial private land ownerships. In both regions, private lands contained less forest cover but a greater number of small forest patches than did public lands. Analyses of land‐cover change based on multinomial logit models revealed differences in land‐cover transitions through time, between ownerships, and between the two study regions. Differences in land‐cover transitions between time intervals suggested that additional factors (e.g., changes in wood products or agricultural prices, or changes in laws or policies) cause individuals or institutions to change land management. The importance of independent variables (slope, elevation, distance to roads and markets, and population density) in explaining land‐cover change varied between ownerships. This methodology for analyzing land‐cover dynamics across land units that encompass multiple owner types should be widely applicable to other landscapes.

Historical framework to explain long-term coupled human and natural system feedbacks: application to a multiple-ownership forest landscape in the northern Great Lakes region, USA

“…Investigators have employed ownership class as a variable to examine human influence on forest landscape pattern , Turner et al 1996, Spies et al 2007). Different ownership classes may implement varying management practices (e.g., Fischer and Charnley 2012), in turn influencing landscape structure.…”

Plant Diversity and Vegetation Structures in the Understory of Mixed Boreal Forests under Different Management Regimes

“…In addition, more focus has been placed on changing the way forests are managed and addressing habitat fragmentation caused by the change of land use and forest ownership [40][41][42][43]. However, with the increase of forestry work intensity and frequency, this human pressure disturbed plant diversity and vegetation structure [27].…”

Cities and Satellites: Spatial Effects and Unobserved Heterogeneity in the Modeling of Urban Growth

“…The grid pattern across the satellite scene was such that roughly 1.2 kilometers separated each pixel from their nearest neighbors. Systematic sampling is a commonly applied technique to handle spatial correlation of unobserved variables that affect the probability of conversion (Turner, Wear, and Flamm 1996;Kline, Moses, and Alig 2001;Cropper, Puri, and Griffiths 2001). A major source of spatial autocorrelation arises from multiple observations falling under common landowners (Kline, Moses, and Alig 2001).…”

“…An early example of such work in the U.S. context is Turner, Wear, and Flamm's (1996) multinomial logit analysis using a time series of satellite imagery to study the effect of socioeconomic, ecological, and locational factors on landscape changes in North Carolina and Washington. Other issues explored in this literature include the 5 role of GIS-created spatial pattern metrics as determinants of property values (Geoghegan, Wainger, and Bockstael 1997), the joint influence of urban population growth and urban proximity on land use change (Kline, Moses, and Alig 2001), and the causes of fragmented development patterns among residential land parcels on the rural-urban interface (Irwin and Bockstael 2002).…”