Family Forest Landowner Behavior in the Southeast

Abstract

Forests and forestry have played a significant role in the economic development and psyche of the South. Forests, which pre-settlement occupied nearly all of the land area of the South, now occupy only 55 percent. More important, perhaps, is the change in the structure and composition of these forests. Some of these changes have resulted from harvest for conversion to agriculture, and the subsequent reversion to forest. Other changes have occurred as fiber demand increased and harvested lands were replanted with pines. More recent is the recognition that forests provide amenity and recreational values which may lead to reductions in harvest by family forest owners. With an unprecedented growth in the number of family forest landowners there is an increase in the surge for researchers to investigate the motives of these landowners to manage their land for timber and/or non-timber use. The diversity amongst these owners in terms of their objectives and their forest conditions coupled with the increasing urbanization pressure warrants need for a thorough investigation. This study presents result from investigating the complexities of family forest owner behavior in three separate chapters (2, 3 & 4) which can be read independently and is styled in journal publication format. Chapter 2 explores the impacts of population pressures on forestland use change in Alabama and results suggest initial forest type and population gravity index to be significant correlates to forest type transition and conversion o forest to non-forest use. Measures of anthropogenic influence such as population density and real per capita income had significant impact on conversion of forest to non-forest use. We also found that Nested Logit is a appropriate econometric technique to study the discrete choice behavior of private landowners. Chapter 3 investigates the diversity of motivations of family forest owners in the Southeast and tests the assumption of homogeneity (treating family forest owners as a single homogeneous group) that previous researchers have made. Our study using multivariate cluster analysis procedures suggest that family forest owner ‘group’ is in fact a diverse set of owners who can be grouped into three attitudinal types namely multiple-objective, non-timber and timber. Finally, in Chapter 4 multivariate non-parametric discriminant procedures was used to discriminate the three attitudinal groups (Chapter 3) using bio-physical, socio-economic and demographic variables. Analysis results indicate that 84% of landowners across all landowner groups were correctly classified. With all the variables used to develop the classification scheme in this study known, a-priori, that is before landowners on a Forest Inventory and Analysis (FIA) plot location is contacted for the National Woodland Owner Survey (NWOS), it may be possible to predict membership of a future landowner with known FIA and Census demographic attributes.