Forest harvesting and land-use conversion over two decades in Massachusetts

McDonald, Robert I.; Motzkin, Glenn; Bank, Michael S.; Kittredge, David B.; Burk, John; Foster, David R.

doi:10.1016/j.foreco.2006.02.006

Cited by 64 publications

(61 citation statements)

References 28 publications

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“…Median family income exceeding $49,445 (i.e., the median value of median family income in 2010 [20]) and income from nonfarm sources greater than farming (i.e., negative farm net income) indicated most family dependent on nonfarm income. "Road density", which is highly correlated with population density, was also considered as a proxy or indirect measure of forest parcel size [37]. A threshold value of exceeding 5 km/km 2 was considered as very high road density and that when this level of road density occurs the probability of forest harvesting dramatically declines [38,39].…”

Section: Low Suitabilitymentioning

confidence: 99%

A Spatial Index for Identifying Opportunity Zones for Woody Cellulosic Conversion Facilities

Huang

Perdue

Young

2012

International Journal of Forestry Research

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A challenge in the development of renewable energy is the ability to spatially assess the risk of feedstock supply to conversion facilities. Policy makers and investors need improved methods to identify the interactions associated with landscape features, socioeconomic conditions, and ownership patterns, and the influence these variables have on the geographic location of potential conversion facilities. This study estimated opportunity zones for woody cellulosic feedstocks based on landscape suitability and market competition for the resource. The study covered 13 Southern States which was a segment of a broader study that covered 33 Eastern United States which also included agricultural biomass. All spatial data were organized at the 5-digit zip code tabulation area (ZCTA). A landscape index was developed using factors such as forest land cover area, net forest growth, ownership type, population density, median family income, and farm income. A competition index was developed based on the annual growth-toremoval ratio and capacities of existing woody cellulosic conversion facilities. Combining the indices resulted in the identification of 592 ZCTAs that were considered highly desirable zones for woody cellulosic conversion facilities. These highly desirable zones were located in Central Mississippi, Northern Arkansas, South central Alabama, Southwest Georgia, Southeast Oklahoma, Southwest Kentucky, and Northwest Tennessee.

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Section: Low Suitabilitymentioning

confidence: 99%

A Spatial Index for Identifying Opportunity Zones for Woody Cellulosic Conversion Facilities

Huang

Perdue

Young

2012

International Journal of Forestry Research

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“…and because they include extensive forest harvesting and considerable variation in forest composition and habitat characteristics that could infl uence browse patterns (Table 1, Fig. 1; McDonald et al 2006). Both watersheds are 10 km from a large urban area (Table 1).…”

Section: Field Site Descriptionmentioning

confidence: 99%

“…data). Upland areas harvested since 1984 were identified based on maps filed for all commercial harvests in Massachusetts (McDonald et al 2006). Eight harvested and 8 unharvested sites were randomly selected in each forest type.…”

Section: Plot Selectionmentioning

confidence: 99%

“…Hillshade is derived from an analysis performed with ArcGIS 9.2 to provide a proxy for relative radiation load using winter altitudes and azimuths for the town of Barre, MA (US Naval Observatory 2008). Time since harvest had a maximum value of 22 years because forest-cutting plans were not fi led prior to the 1983 Massachusetts Forest Cutting Practices Act (McDonald et al 2006). Distance to development/major roads was also calculated with ArcGIS, and "developed" land included residential, industrial, commercial, transportation, waste disposal, and recreation sites, but was primarily residential development in our study area.…”

Section: Foraging-intensity Indexmentioning

confidence: 99%

“…With 25-30% of the forest land in central Massachusetts harvested between 1984-2003 and White Pine growing with Red Maple and other hardwoods in many regenerating cut blocks, the current rate of logging could largely determine spatial pattern and extent of Moose impacts to forest composition (McDonald et al 2006). In the boreal zone, landscape-scale fi res and large clearcuts (Delong andTanner 1996, Hunter 1993) produce extensive areas of abundant regeneration that can reduce the impact of even very high Moose densities (Pastor et al 1988, Peterson 1995.…”

Section: Interactions With Forest Harvestingmentioning

confidence: 99%

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Moose Foraging in the Temperate Forests of Southern New England

Faison¹,

Motzkin²,

Foster³

et al. 2010

Northeastern Naturalist

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-Moose have recently re-colonized the temperate forests of southern New England, raising questions about this herbivore's effect on forest dynamics in the region. We quantifi ed Moose foraging selectivity and intensity on tree species in relation to habitat features in central Massachusetts. Acer rubrum (Red Maple) and Tsuga canadensis (Eastern Hemlock) were disproportionately browsed; Pinus strobus (White Pine) was avoided. Foraging intensity correlated positively with elevation, distance to development, and watershed type and negatively with time since forest harvest, explaining 26% of the variation. Moose may interact with forest harvesting to contribute to a decline in Red Maple and Eastern Hemlock and an increase in White Pine in intensively browsed patches. Nonetheless, foraging impacts may diminish over time, as increasing temperatures and sprawling development increasingly restrict suitable Moose habitat.

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Social and biophysical variation in regional timber harvest regimes

Thompson

Canham

Morreale

et al. 2017

Ecological Applications

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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.

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Forest harvesting and land-use conversion over two decades in Massachusetts

Cited by 64 publications

References 28 publications

A Spatial Index for Identifying Opportunity Zones for Woody Cellulosic Conversion Facilities

A Spatial Index for Identifying Opportunity Zones for Woody Cellulosic Conversion Facilities

Moose Foraging in the Temperate Forests of Southern New England

Social and biophysical variation in regional timber harvest regimes

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