Social and biophysical variation in regional timber harvest regimes.

Abstract

In terms of adult tree mortality, harvesting is the most prevalent disturbance in northeastern United States forests. Previous studies have demonstrated that stand structure and tree species composition are important predictors of harvest. We extend this work to investigate how social factors further influence harvest regimes. By coupling the Forest Inventory and Analysis database to U.S. Census and National Woodland Owner Survey (NWOS) data, we quantify social and biophysical variation in the frequency and intensity of harvesting throughout a 20-state region in the northeastern United States. Among social factors, ownership class is most predictive of harvest frequency and intensity. The annual probability of a harvest event within privately owned forest (3%/yr) is twice as high as within publicly owned forests (1.5%/yr). Among private owner classes, the annual harvest probability on corporate-owned forests (3.6%/yr) is 25% higher than on private woodlands (2.9%/yr). Among public owner classes, the annual probability of harvest is highest on municipally owned forests (2.4%/ yr), followed by state-owned forests (1.6%/yr), and is lowest on federal forests (1%/yr). In contrast, corporate, state, and municipal forests all have similar distributions of harvest intensity; the median percentage of basal area removed during harvest events is approximately 40% in these three owner groups. Federal forests are similar to private woodlands with median harvest intensities of 23% and 20%, respectively. Social context variables, including local home prices, population density and the distance to a road, help explain the intensity, but not the frequency, of harvesting. Private woodlands constitute the majority of forest area; however, demographic data about their owners (e.g., their age, educational attainment, length of land tenure, retired status) show little relationship to aggregate harvest behavior. Instead, significant predictors for harvesting on private woodlands include live-tree basal area, forest type, and distance from roads. Just as with natural disturbance regimes, harvest regimes are predictable in terms of their frequency, intensity, and dispersion; and like their natural counterparts, these variables are determined by several important dimensions of environmental context. But in contrast to natural disturbance regimes, the important dimensions of context for harvesting include a combination of social and biophysical variables.