Carbon stocks on forestland of the United States, with emphasis on USDA Forest Service ownership

Heath, Linda S.; Smith, James E.; Woodall, Christopher W.; Azuma, David L.; Waddell, Karen L.

doi:10.1890/es10-00126.1

Cited by 54 publications

(37 citation statements)

References 14 publications

(17 reference statements)

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“…In this set, tree carbon estimates correspond to current methods (U.S. EPA ), whereas the remaining forest ecosystem pools either predate or correspond with those of U.S. EPA () and Heath et al. (). Exact methodological details for each pool at each time are well documented (U.S. EPA , , Heath et al.…”

Section: Methodsmentioning

confidence: 99%

“…A second set of carbon conversion factors applied to a specific inventory at a somewhat similar scope (as this report) is the summary of Forest Service forest lands of Heath et al. (), which also corresponds to forest carbon as reported in U.S. EPA (). The third set of estimates is from fields currently populated in the tree and forest condition tables of the FIADB, which represents a mix of both current and older carbon conversions.…”

Section: Methodsmentioning

confidence: 99%

“…These forest carbon estimates are similarly applied to other national reports (USDA ) or regional analyses (Heath et al. , Ogle et al. , Hoover and Smith ).…”

Section: Introductionmentioning

confidence: 99%

“…One result of these updates is that on average over 98% of ecosystem carbon on forest plots is estimated according to different conversion factors or models today (U.S. EPA ) relative to similar scope summaries from almost a decade ago (U.S. EPA , Heath et al. ). However, all such estimates and changes are documented, and incremental differences, or step changes, in stand level carbon stocks are generally small (Heath , Smith et al.…”

Section: Introductionmentioning

confidence: 99%

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Carbon stocks and stock change on federal forest lands of the United States

et al. 2019

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Forest land in the United States offsets more than 11% of total domestic greenhouse gas emissions each year through growth of live woody biomass and accumulation of carbon in trees, dead organic matter, and harvested wood products. Forest lands owned and managed by various agencies of the U.S. government cover 77 million hectares, which is 29% of U.S. forest land and an estimated 33%, or 17.2 Pg C, of forest carbon stocks. Here, we summarize forest inventory‐based estimates of forest carbon stocks and indications of carbon stock change on forest lands managed by agencies within the U.S. federal government. Within the conterminous USA, the proportion of forest land that is federally owned is higher in the West representing two‐thirds of forest carbon stocks; in the East, federal lands represent 9% of forest carbon. The majority of federal forests and forest carbon are managed by the U.S. Forest Service (13.8 Pg C), but 20% of federal forest carbon stocks, or 3.5 Pg C, are managed by other federal agencies (e.g., National Park Service, Bureau of Land Management). We also briefly review some broad characteristics of the forest inventory that affect forest carbon reported for the USA as included in greenhouse gas inventories such as for United Nations Framework Convention on Climate Change reporting.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…These forest carbon estimates are similarly applied to other national reports (USDA ) or regional analyses (Heath et al. , Ogle et al. , Hoover and Smith ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Carbon stocks and stock change on federal forest lands of the United States

et al. 2019

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“…These inventory systems generally consist of permanent plots from which tree and other ancillary stand data are collected periodically. Most recently, these available plot-level data are also being used to estimate landscape and regional-level forest ecosystem services, such as aboveground, understory and below-ground carbon stocks [4].…”

Section: Introductionmentioning

confidence: 99%

Predicting Understory Species Richness from Stand and Management Characteristics Using Regression Trees

Timilsina

Cropper

Escobedo

et al. 2013

Forests

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Abstract:Managing forests for multiple ecosystem services such as timber, carbon, and biodiversity requires information on ecosystem structure and management characteristics. National forest inventory data are increasingly being used to quantify ecosystem services, but they mostly provide timber management and overstory data, while data on understory shrub and herbaceous diversity are limited. We obtained species richness and stand management data from relevant literature to develop a regression tree model that can be used to predict understory species richness from forest inventory data. Our model explained 57% of the variation in herbaceous species richness in the coastal plain pine forests of the southeastern USA. Results were verified using field data, and important predictors of herbaceous richness included stand age, forest type, time since fire, and time since herbicide-fertilizer application. This approach can make use of available forest inventories to rapidly and cost-effectively estimate understory species richness for subtropical pine forests.

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A Systems Engineering Approach to Estimating Uncertainty in Above‐Ground Biomass (AGB) Derived from Remote‐Sensing Data

Weisbin

Lincoln

Saatchi

2013

Systems Engineering

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We integrate systems of measurement and modeling to improve estimation of uncertainties in aboveground biomass (AGB) derived from remote sensing. The outcome provides a unified starting point for the climate-change carbon community to assess uncertainty and sensitivity data and methodologies, and ultimately supports decision-making about which missions and instruments to develop for a desired cost/benefit ratio. Initial results include fusion of remote-sensing techniques (e.g., radar and lidar), uncertainties associated with measurement and modeling, and the impact of potential uncertainty correlations across aggregated unit areas. Biomass uncertainty estimates are presented at the single-hectare level for the forestlands of California. Using a forest biomass map of California, we calculate changes in variance (e.g., 2 orders of magnitude) as a function of uncertainty correlation assumptions, with correlations extending to spatial scales up to 100 km. Using a variogram formalism to derive the correlation shape and magnitude, we show that the estimated variance for California above-ground biomass is between 1% and 2% (1 standard deviation) for our current best estimate of the correlation range at 5-10 km-i.e., we bound the standard deviation by a factor of 2. This contrasts with 0.025% (1 standard deviation) if one does not include the correlation term.

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Carbon stocks on forestland of the United States, with emphasis on USDA Forest Service ownership

Cited by 54 publications

References 14 publications

Carbon stocks and stock change on federal forest lands of the United States

Carbon stocks and stock change on federal forest lands of the United States

Predicting Understory Species Richness from Stand and Management Characteristics Using Regression Trees

A Systems Engineering Approach to Estimating Uncertainty in Above‐Ground Biomass (AGB) Derived from Remote‐Sensing Data

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