PMID- 28054427
OWN - NLM
STAT- MEDLINE
DCOM- 20190718
LR  - 20190718
IS  - 1051-0761 (Print)
IS  - 1051-0761 (Linking)
VI  - 27
IP  - 3
DP  - 2017 Apr
TI  - Social and biophysical variation in regional timber harvest regimes.
PG  - 942-955
LID - 10.1002/eap.1497 [doi]
AB  - 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.
CI  - (c) 2017 by the Ecological Society of America.
FAU - Thompson, Jonathan R
AU  - Thompson JR
AD  - Harvard Forest, Harvard University, Petersham, Massachusetts, 01366, USA.
FAU - Canham, Charles D
AU  - Canham CD
AD  - Cary Institute of Ecosystem Studies, Millbrook, New York, 12545, USA.
FAU - Morreale, Luca
AU  - Morreale L
AD  - Harvard Forest, Harvard University, Petersham, Massachusetts, 01366, USA.
FAU - Kittredge, David B
AU  - Kittredge DB
AD  - Harvard Forest, Harvard University, Petersham, Massachusetts, 01366, USA.
AD  - Department of Environmental Conservation, University of Massachusetts, Amherst, 
      Massachusetts, 01003, USA.
FAU - Butler, Brett
AU  - Butler B
AD  - Northern Research Station, USDA Forest Service, Amherst, Massachusetts, 01003, 
      USA.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20170316
PL  - United States
TA  - Ecol Appl
JT  - Ecological applications : a publication of the Ecological Society of America
JID - 9889808
SB  - IM
MH  - Conservation of Natural Resources/*methods
MH  - Forestry/*methods
MH  - Forests
MH  - Geography
MH  - Models, Statistical
MH  - Ownership
MH  - Time Factors
MH  - United States
OTO - NOTNLM
OT  - Forest Inventory and Analysis Plots
OT  - National Woodland Owner Survey
OT  - coupled human and natural systems
OT  - disturbance ecology
OT  - land use
OT  - maximum-likelihood estimation
OT  - temperate forests
OT  - timber harvest regimes
EDAT- 2017/01/06 06:00
MHDA- 2019/07/19 06:00
CRDT- 2017/01/06 06:00
PHST- 2015/12/22 00:00 [received]
PHST- 2016/10/17 00:00 [revised]
PHST- 2016/12/20 00:00 [accepted]
PHST- 2017/01/06 06:00 [pubmed]
PHST- 2019/07/19 06:00 [medline]
PHST- 2017/01/06 06:00 [entrez]
AID - 10.1002/eap.1497 [doi]
PST - ppublish
SO  - Ecol Appl. 2017 Apr;27(3):942-955. doi: 10.1002/eap.1497. Epub 2017 Mar 16.