scholarly journals Current aboveground live tree carbon stocks and annual net change in forests of conterminous United States

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Coeli M. Hoover ◽  
James E. Smith
Keyword(s):  
Pacific Northwest ◽  
Unit Area ◽  
Forest Type ◽  
Standing Stock ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Annual Change ◽  
Rates Of Change ◽  
Average Annual Change ◽  
Live Tree

Abstract Background With the introduction of the Trillion Trees Initiative and similar programs, forests’ ability to absorb carbon dioxide is increasingly in the spotlight. Many states have mandates to develop climate action plans, of which forest carbon is an important component, and planners need current information on forest carbon stocks and rates of change at relevant spatial scales. To this end, we examine rates of average annual change in live aboveground tree carbon in different forest type groups and provide state-wide and regional summaries of current live tree carbon stock and rates of change for the forests of the conterminous United States. Forest carbon summaries are presented in a format designed to meet the needs of managers, policymakers, and others requiring current estimates of aboveground live tree carbon at state and regional scales. Results Regional average aboveground live tree carbon stocks (represented on a per area basis) are generally between 40 and 75 tC/ha but range from 12.8 tC/ha in the Great Plains to 130 tC/ha in the Pacific Northwest West (west-side of Cascades). Regional average annual change in live aboveground tree carbon varies from a low of − 0.18 mtC/ha/y in the Rocky Mountain South to a high value of 1.74 mtC/ha/y in Pacific Northwest West. For individual states, carbon per unit area varies widely, from a low of 11.9 tC/ha in Nevada to a high of 96.4 tC/ha in Washington, with half the states falling between 50 and 75 tC/ha. Rates of average annual change in live aboveground tree carbon vary from a high of 1.82 tC/ha/y in Mississippi to a low of − 0.47 tC/ha/y in Colorado. Conclusions Aboveground live tree carbon stocks and rates of average annual change vary by forest type within regions. While softwood forest types currently exhibit a higher rate of increase in the amount of carbon in aboveground live tree biomass, the current standing stock of carbon per unit area does not consistently follow this pattern. For this reason, we recommend computing and considering both measures -standing stock and average annual change—of carbon storage. The relative importance of each component will depend on management and policy objectives and the time frame related to those objectives. Harvesting and natural disturbance also affect forest carbon stock and change and may need to be considered if developing projections of potential carbon storage.

scholarly journals A 100-year conservation experiment: Impacts on forest carbon stocks and fluxes

2013 ◽  
Vol 310 ◽  
pp. 242-255 ◽  
Author(s):  
Tara Sharma ◽  
Werner A. Kurz ◽  
Graham Stinson ◽  
Marlow G. Pellatt ◽  
Qinglin Li
Keyword(s):  
Carbon Stocks ◽  
Forest Carbon

scholarly journals Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

2016 ◽  
Vol 13 (5) ◽  
pp. 1571-1585 ◽  
Author(s):  
Pierre Ploton ◽  
Nicolas Barbier ◽  
Stéphane Takoudjou Momo ◽  
Maxime Réjou-Méchain ◽  
Faustin Boyemba Bosela ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Reference Model ◽  
Original Data ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Biomass Estimation ◽  
Systematic Bias ◽  
Data Set ◽  
Allometric Models ◽  
Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees  ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

Examining High-Resolution PiSAR-L2 Textures for Estimating Tropical Forest Carbon Stocks

2016 ◽  
Vol 9 (7) ◽  
pp. 3202-3209 ◽  
Author(s):  
Rajesh Bahadur Thapa ◽  
Manabu Watanabe ◽  
Masanobu Shimada ◽  
Takeshi Motohka
Keyword(s):  
High Resolution ◽  
Tropical Forest ◽  
Carbon Stocks ◽  
Forest Carbon

scholarly journals Forest Type Definitions by Cluster Analysis

2001 ◽  
Vol 16 (3) ◽  
pp. 101-105 ◽  
Author(s):  
Willem W.S. van Hees ◽  
Kevin Dobelbower ◽  
Kenneth Winterberger
Keyword(s):  
Cluster Analysis ◽  
Pacific Northwest ◽  
Forest Inventory ◽  
Forest Type ◽  
Research Station ◽  
Inventory Data ◽  
Southeast Alaska ◽  
Cluster Development ◽  
Forest Inventory Data

Abstract A method is presented to develop forest type definitions by using cluster analysis of forest inventory data collected in southeast Alaska from 1995 through 1998. Species stocking levels were used as variables for cluster development. Pacific Northwest Research Station forest inventory staff could not compute forest type for some forested conditions in southeast Alaska using then existing forest type definitions. Forest type definitions developed by cluster analysis improved computed assignment of forest type. West. J. Appl. For. 16(3):101–105.

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