A framework for identifying carbon hotspots and forest management drivers

被引:41
|
作者
Timilsina, Nilesh [1 ]
Escobedo, Francisco J. [1 ]
Cropper, Wendell P., Jr. [1 ]
Abd-Elrahman, Amr [2 ]
Brandeis, Thomas J. [3 ]
Delphin, Sonia [4 ]
Lambert, Samuel [5 ]
机构
[1] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 USA
[2] Univ Florida, Geomat Program, Sch Forest Resources & Conservat, Plant City, FL 33563 USA
[3] US Forest Serv, USDA, SRS FIA, Knoxville, TN 37919 USA
[4] Univ Florida, Sch Forest Resources & Conservat, Gainesville, FL 32611 USA
[5] US Forest Serv, USDA, Spatial Data Serv, Knoxville, TN 37919 USA
基金
美国食品与农业研究所;
关键词
Hotspot analysis; Forest carbon; Florida; Spatial statistics; Ecosystem service drivers; Forest disturbance; SPATIAL ASSOCIATION; ECOSYSTEM SERVICES; BOREAL FOREST; STAND AGE; BIOMASS; STORAGE; CLIMATE; SEQUESTRATION; CONSERVATION; INDICATORS;
D O I
10.1016/j.jenvman.2012.10.020
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Spatial analyses of ecosystem system services that are directly relevant to both forest management decision making and conservation in the subtropics are rare. Also, frameworks that identify and map carbon stocks and corresponding forest management drivers using available regional, national, and international-level forest inventory datasets could provide insights into key forest structural characteristics and management practices that are optimal for carbon storage. To address this need we used publicly available USDA Forest Service Forest Inventory and Analysis data and spatial analyses to develop a framework for mapping "carbon hotspots" (i.e. areas of significantly high tree and understoly aboveground carbon stocks) across a range of forest types using the state of Florida, USA as an example. We also analyzed influential forest management variables (e.g. forest types, fire, hurricanes, tenure, management activities) using generalized linear mixed modeling to identify drivers associated with these hotspots. Most of the hotspots were located in the northern third of the state some in pen-urban areas, and there were no identifiable hotspots in South Florida. Forest silvicultural treatments (e.g. site preparation, thinning, logging, etc) were not significant predictors of hotspots. Forest types, site quality, and stand age were however significant predictors. Higher site quality and stand age increased the probability of forests being classified as a hotspot. Disturbance type and time since disturbance were not significant predictors in our analyses. This framework can use globally available forest inventory datasets to analyze and map ecosystems service provision areas and bioenergy supplies and identify forest management practices that optimize these services in forests. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:293 / 302
页数:10
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