United States Department of Agriculture

Forest 

Service

General Technical 

Report NRS-127

Northern 

Research Station January 2014

Past and Prospective Carbon Stocks 

in Forests of Northern Wisconsin

A Report from the Chequamegon-Nicolet National Forest 

Climate Change Response Framework
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Abstract

This report assesses past and prospective carbon stocks for 4.5 million ha of forest land 

in northern Wisconsin, including a baseline assessment and analysis of the impacts 

of disturbance and management on carbon stocks. Carbon density (amount of carbon 

stock per unit area) averages 237 megagrams (Mg) per ha, with the National Forest 

lands having slightly higher carbon density than other ownership classes. Over the last 

decade, carbon stocks of northern Wisconsin forests have been increasing by about one 

teragram (Tg) per year or 0.22 megagrams per ha per year, with most of the increase 

in live biomass. Harvest, wind, and fire have been principal drivers of forest carbon 

dynamics over the last century. For all forest types in northern Wisconsin, there is 

potential to increase stocking on the land by allowing more of the forested area to reach 

older age classes or by increasing productivity. Opportunities to increase afforestation and 

reduce deforestation are limited, but the potential exists for utilizing biomass energy as a 

substitute for fossil fuels. There are several options for private landowners to participate 

in carbon markets or greenhouse gas registries and receive some credit for additional 

actions to reduce emissions or increase sequestration of carbon. The methods used here 

can be adapted for use by other regions or forests to assess carbon stocks and effects of 

management on future carbon stocks. 

Cover photo by Scott Pearson.
Past and Prospective Carbon Stocks in Forests of Northern Wisconsin

A Report from the Chequamegon-Nicolet National Forest 

Climate Change Response Framework

Richard Birdsey, Yude Pan, Maria Janowiak, Susan Stewart, Sarah Hines, 

Linda Parker, Stith Gower, Jeremy Lichstein, Kevin McCullough, 

Fangmin Zhang, Jing Chen, David Mladenoff, Craig Wayson, and Chris Swanston

The Authors

RICHARD BIRDSEY is project leader of the Strategic Foresight 

and Rapid Response research unit with the U.S. Forest Service, 

Northern Research Station, 11 Campus Boulevard, Suite 200, 

Newtown Square, PA 19073, rbirdsey@fs.fed.us

YUDE PAN is a research scientist with the U.S. Forest Service, 

Northern Research Station, 11 Campus Boulevard, Suite 200, 

Newtown Square, PA 19073, ypan@fs.fed.us

MARIA JANOWIAK is a climate change adaptation and carbon 

management scientist with the Northern Institute of Applied 

Climate Science, U.S. Forest Service, 410 MacInnes Drive, 

Houghton, MI 49931, mjanowiak02@fs.fed.us

SUSAN STEWART is a research social scientist (retired) with 

the U.S. Forest Service, Northern Research Station, Evanston, 

IL 60201

SARAH HINES is a science delivery specialist with the U.S. 

Forest Service, Rocky Mountain Research Station, 240 West 

Prospect, Fort Collins, CO, shines@fs.fed.us

LINDA PARKER is a forest ecologist with the U.S. Forest 

Service, Chequamegon-Nicolet National Forest, 500 Hanson 

Lake Road, Rhinelander, WI 54501, lrparker@fs.fed.us

STITH GOWER is a professor with the University of Wisconsin, 

Department of Forest and Wildlife Ecology, Madison, WI 53706, 

stgower@wisc.edu

JEREMY LICHSTEIN is an assistant professor with the 

University of Florida, Department of Biology, Gainesville, FL 

32611, jlichstein@ufl.edu

KEVIN MCCULLOUGH is a geographer with the U.S. Forest 

Service, Northern Research Station, 1 Gifford Pinchot 

Drive, Forest Products Laboratory, Madison, WI 53726, 

kevinmccullough@fs.fed.us

FANGMIN ZHANG is postdoctoral research associate with the 

University of Toronto, Department of Geography, 45 St. George 

Street, Toronto, ON, Canada M5S 2E5, zfmnuist@hotmail.com

JING CHEN is a professor with the University of Toronto, 

Department of Geography, 45 St. George Street, Toronto, ON, 

Canada M5S 2E5, jing.chen@utoronto.ca

DAVID MLADENOFF is a professor with the University of 

Wisconsin, Department of Forest and Wildlife Ecology, 1630 

Linden Drive, Madison, WI 53706, djmladen@wisc.edu 

CRAIG WAYSON is program coordinator with SilvaCarbon, 

Lima, Peru, cwayson.silvacarbon@gmail.com

CHRIS SWANSTON is a research ecologist with the U.S. 

Forest Service, Northern Research Station and director of the 

Northern Institute of Applied Climate Science, 410 MacInnes 

Drive, Houghton, MI 49931, cswanston@fs.fed.us 
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PREFACE

In recognition of the importance of forests in removing carbon dioxide (CO2) from the 

atmosphere, various mechanisms have been introduced to track changes in forest carbon 

stocks and to provide incentives for increasing carbon stocks or sequestration rates on public 

and private lands. At the national scale, annual estimates of carbon stocks in forests and wood 

products are included in the U.S. greenhouse gas inventory submitted by the Environmental 

Protection Agency to the United Nations Framework Convention on Climate Change. Some 

states and regions have established greenhouse gas markets or registries to facilitate greenhouse 

gas reductions that include forestry activities on private lands, and there is an active voluntary 

market where payments may be made to increase carbon stocks or sequestration rates.

For public lands, a series of regulations and policies require tracking and reporting forest 

carbon stocks and assessing the impact of land management on carbon stocks. Executive 

orders, the “National Environmental Policy Act,” the new “U.S. Forest Service Planning Rule,” 

and the “U.S. Department of Agriculture Strategic Plan for 2010-2015” all include measures 

of forest carbon stocks and/or assessments of the main factors influencing forest carbon stocks. 

These regulations have prompted the Forest Service to develop a climate change performance 

scorecard comprised of 10 elements in order to gauge performance in a wide variety of climate 

change-related activities. Element 9 on the performance scorecard focuses on greenhouse gas 

mitigation that seeks to: (1) develop a baseline assessment of carbon stocks on National Forest 

lands, and (2) assess the influence of disturbance and management activities on these carbon 

stocks. This reflects the fact that both forest management and natural factors can influence 

forest carbon sequestration or emissions. 

This report specifically addresses methods to achieve acceptable results for performance 

scorecard element 9, including the required baseline assessment and analysis of the impacts of 

disturbance and management on carbon stocks, using a forested region of the Eastern United 

States as an example. It is designed to illustrate how to apply the best available science to assess 

the effects of land management planning and practice on carbon in forests and wood products. 

Future analyses may also integrate anticipated effects on forests as a result of climate change 

(performance scorecard element 6) (e.g., Swanston et al. 2011) to address the potential viability 

of mitigation options given expected changes in climate, impacts on forest ecosystems, and 

management responses for adaptation.
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Contents

Executive Summary ................................................................................................1

Introduction..............................................................................................................4

Past and Current Carbon Stocks in Forests and Wood Products 

of Northern Wisconsin ........................................................................................8

Past and Current Stocks of Forest Carbon ............................................................8

Carbon in Harvested Wood Products................................................................... 10

Recent Changes in Carbon Stocks of Forests and Wood Products..................... 11

Principal Factors Affecting Carbon Stocks and Fluxes ..................................... 12

Forest Area and Area Change ............................................................................. 12

Productivity of the Land ....................................................................................... 12

Land Management............................................................................................... 14

Age and Condition of the Region’s Forests.......................................................... 17

Effects of Climate, Air Pollution, and Natural Disturbance ................................... 18

Mitigation Options for Northern Wisconsin ........................................................22

Potential Carbon Stocks.......................................................................................22

Increasing Carbon Stocks in Forests and Wood Products ...................................24

Avoiding Loss of Forest Land ..............................................................................30

Increasing Use of Wood for Bioenergy ................................................................35

Climate Change and Other Risk Factors .............................................................37

Potential Pathways to Implementation ................................................................39

Forest Carbon Accounting Issues........................................................................39

Markets and Registries........................................................................................40

Public Policies and Regulations...........................................................................41

Discussion and Conclusions ...............................................................................42

Literature Cited ......................................................................................................43
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1

EXECUTIVE SUMMARY

This pilot study assesses past and prospective carbon stocks for all forest lands in northern 

Wisconsin and includes a baseline assessment and analysis of the impacts of disturbance and 

management on carbon stocks. It is designed to illustrate how to apply the best available science 

to assess the effects of land management planning and activities on carbon in forests and wood 

products. Many different influencing factors and significant uncertainties affect the choices that 

land managers may consider for achieving their goals for managing forests and the impacts of 

management on carbon stocks; therefore, this study illustrates these factors and uncertainties 

but does not provide a roadmap for land management decisions.

Carbon Stocks and Recent Historical Changes in Forests and Wood Products of 

Northern Wisconsin

•	 Carbon stocks—Carbon density (amount of carbon stock per unit area) averages 237 

megagrams (Mg) per ha, with the National Forest lands having slightly higher carbon 

density than the other ownership classes. Total forest carbon stocks are distributed in 

approximate proportion to the area by ownership class. Private owners hold 63 percent 

of the carbon stock, followed by state and local ownership (24 percent) and National 

Forest (14 percent). About 60 percent of the ecosystem carbon is in the soil.

•	 Changes in carbon stocks—Over the last decade, carbon stocks of northern Wisconsin 

forests have been increasing by about one teragram (Tg) per year or 0.22 Mg per ha per 

year, with most of the increase in live biomass. Among ownership groups, the per ha 

increase has been largest on public forest lands. The rate of sequestration is decreasing, 

however, with the rate now slightly less than that of the previous decade.

•	 Causes of change in carbon stocks—Likely causes for the declining sequestration rate 

are continuing high rates of harvesting for wood products, which result in large areas of 

forest recovering from this intensive disturbance, and increasing areas of older forests 

where growth rates are slowing down. Since 1990, carbon in harvested wood products 

has increased by 0.5 Tg per year. The total net carbon sequestration in northern 

Wisconsin forests and wood products since 2000 was approximately 1.5 Tg per year.

Principal Factors Affecting Current and Future Forests 

•	 Forest area and area change—The area of forest land increased by 3 percent in northern 

Wisconsin since 1990. Studies of land-cover change indicate that deforestation claimed 

less than 10,000 ha per year from 1990 to 2001, inferring that more than 15,000 ha per 

year of afforestation would be needed to result in the net forest area increase of 146,000 ha 

since 1990.

•	 Age and condition of the region’s forests—Forests of northern Wisconsin are 

distributed broadly among multiple age classes, with peaks in the middle ages of the 

forest succession. This pattern reflects the history of land clearing for agriculture and 

reversion back to forest followed by periods of intensive timber harvest. The younger 

age classes are well represented among all ownership groups because of continuing 

reversions from agriculture to forest plus active forest management; young and middleaged forests tend to be productive and healthy unless affected by a disturbance.
2

•	 Effects of climate, air pollution, and disturbance—Harvest, wind, and fire have been 

principal drivers of forest carbon dynamics over the last century in the upper Midwest. 

Windstorms, insects, diseases, land use change, and other disturbances also cause tree 

damage and mortality to varying degrees. The effects of these disturbances on forest carbon 

stocks are highly variable and are linked to the spatial extent and severity of a particular 

disturbance as well as the amount of time since disturbance. The long-term trend in 

productivity of northern Wisconsin forests shows the effect of recovery from intensive 

harvesting and fire during the early 20th century, with productivity rising as forests recovered 

from these historical disturbances. Nitrogen deposition has the next largest effect followed 

by minor influences of increasing carbon dioxide (CO2) and climate variability, which has 

had a strong interannual effect but has not been very influential over the long term.

Mitigation Options for Northern Wisconsin

•	 Potential carbon stocks—Land management has long-term effects on carbon stocks, and 

therefore may be modified to reduce emissions or increase sequestration in forest ecosystems 

and harvested wood products. Forests recover lost carbon stocks in predictable patterns after 

reforestation, timber management, or natural disturbance. For all forest types in northern 

Wisconsin, there is the potential to increase stocking on the land by allowing more of 

the forested area to reach older age classes. On average, in northern Wisconsin ecosystem 

carbon could increase at an annual rate of 4.3 million Tg per year over the next 50 years 

in the absence of harvest, compared with the current rate of 1.5 million Tg per year, for a 

potential net additional increase of 2.8 million Tg per year. However, reduced harvest for 

wood products would cause a significant loss of carbon entering the wood products pools, 

and as existing forests age, their net ecosystem production declines.

•	 Increasing carbon stocks in forests and wood products—Afforestation options are 

limited across the northern Wisconsin landscape. Many nonforested areas are open wetlands 

or pine barrens which are highly valued for their ecological functions. There are multiple 

options for using forest management to increase carbon stocks by increasing productivity, 

storage, or both, but their effects are not necessarily large and may be difficult to predict 

because of high variability in management practices and site conditions. Harvest activities 

have a profound influence on regional forest carbon dynamics. The carbon retained in 

harvested forest products has a significant effect on the overall carbon balance of managed 

forests, although changes in ecosystem carbon stocks are about twice as large as changes in 

carbon stocks of harvested wood products.

•	 Avoiding loss of forest land—Forest loss in northern Wisconsin causes significant 

reductions of carbon stocks. In this region, the housing growth rate was 244 percent from 

1940 to 2000, and 128 percent more growth is expected between 2000 and 2030. Reducing 

the rate of forest loss would avoid emissions of stored carbon. The projected baseline and 

the alternative scenarios for future land use predict an increase in rangelands, a major loss 

in pasture, a smaller loss in crops, and major gains in urban land use. Forest land use is not 

projected to increase. While northern Wisconsin currently has extensive forested land, it is 

likely to have less private forest land in the future. Although there will most likely be fairly 

substantial changes in land use, the differences projected by the alternative policy scenarios 

used in this report are relatively small.
3

•	 Increasing use of wood for bioenergy—There are opportunities in northern 

Wisconsin to utilize biomass energy as a substitute for fossil fuels. A recent analysis 

of available forest biomass in Wisconsin estimated that 1.5 million dry tons could be 

sustainably available for energy use annually at a price of $40 per dry ton. The actual 

amount of biomass that is available is likely less than what is potentially available 

because of conflicts with other owner objectives for land management. Several factors 

including concerns about mitigating greenhouse gases and climate change, increasing 

the amount of energy from domestic sources, and strengthening local and rural 

economies are encouraging a greater use of wood for energy in the state. Depending 

on the accounting framework, net forest system carbon balance may be negatively 

correlated with biomass harvested, illustrating the tradeoffs between increased carbon 

uptake by forests and utilization of woody biomass for energy.

•	 Climate change and other risk factors—Many of the stressors that currently affect the 

forests of northern Wisconsin may increase in importance as a result of climate change. 

Temperature increases and altered precipitation regimes are expected to lead to drier 

summer soil conditions which may make drought and associated disturbances (such 

as fire or pest and disease outbreaks) more prevalent. Climate change is also expected 

to increase the frequency and severity of extreme weather events which may lead to 

greater occurrence of catastrophic winds or rain events. Suitable habitat for tree species 

is projected to shift northward as the climate changes. Many of the area’s dominant 

tree species are located at the southern extent of the species’ range, and declines in the 

suitability of habitat may lead to subsequent declines in the ability of those species to 

persist.

Potential Pathways to Implementation

•	 Participation in markets and registries—There are several options for landowners to 

participate in carbon markets or greenhouse gas registries and receive some credit for 

additional actions to reduce emissions or increase sequestration of carbon. A universal 

component to any forest-based carbon project—be it afforestation, reforestation, 

forest management, or reduced deforestation—is dealing with several forest carbon 

accounting issues. The way in which these issues are defined and treated within a 

specific market or registry program affects the program’s credibility, the project 

enrollment process, and the atmospheric and climate benefits of a project.

•	 Public policies and regulations—Federal and state policy guidance regarding the role 

that public lands may play in carbon markets is not well developed. Leading standards 

in the voluntary market may preclude public land participation. Within the federal 

government, there are several executive orders and planning regulations that require 

tracking of carbon stocks and assessments of future potential; however, these do not 

specify that a goal of land management necessarily includes increasing carbon stocks.
4

INTRODUCTION

Measuring and monitoring carbon and carbon dioxide 

(CO2) on the land, oceans, and in the atmosphere 

has taken place for many decades. The global carbon 

budget is generally well understood, but uncertainties 

involving CO2 exchanges between the land and the 

atmosphere still exist (Le Quéré et al. 2009). There 

are many variables that affect the land-atmosphere 

exchange at different temporal and geographic scales, 

such as interannual climate variability, periodic natural 

disturbances, a wide range of land management practices, 

and spatially variable emissions from burning fossil fuels.

About half of global fossil fuel emissions is absorbed by 

the oceans and land (carbon sinks), while the other half 

stays in the atmosphere contributing to the increasing 

concentration of CO2 (Pan et al. 2011a), which is now 

about 400 parts per million or 30 percent higher than 

100 years ago (National Oceanographic and Atmospheric 

Administration 2013). There is emerging evidence that 

the oceans and land may become saturated with added 

carbon, implying that an increasing proportion of the 

emitted CO2 would stay in the atmosphere (Canadell et 

al. 2007).

The United States emits approximately 1.5 billion tons 

of CO2 per year or about 17 percent of global emissions. 

About 12 percent of CO2 emissions from burning fossil 

fuel is sequestered in forests and wood products each year 

(U.S. Environmental Protection Agency 2009); however, 

the effects of recent sharp increases in wildfire and insect 

disturbances (Man 2010, Marlon et al. 2012, Turner 

2010) on forest carbon stocks are not yet fully reflected 

in the national-scale estimates of forest inventories.

According to some estimates, it may be possible to 

significantly increase the rate of carbon sequestration 

by forests in the United States (Lewandrowski et al. 

2004, U.S. Environmental Protection Agency 2005). 

Key factors determining rates of sequestration are the 

biological potential of the land to absorb more CO2, the 

economic potential as determined by the future price 

of CO2 in the market, and the policies implemented at 

national, regional, state, and local levels.

The United States has a strong program for inventorying 

and monitoring emissions and sequestration in the 

forest sector (Heath et al. 2011), though there are 

some significant gaps in specific areas (Birdsey 2004). 

For example, the remoteness of Alaska has precluded 

systematic monitoring. Additionally, soil carbon is not 

adequately monitored except in some specific research 

areas even though it could be subject to significant 

changes given the vulnerability of this sequestered carbon 

to changes in climate and natural disturbance.

At smaller geographic scales, such as that of states 

or individual landowners, technology is available to 

measure, monitor, and verify carbon emissions and 

sequestration from individual activities or projects for 

the purpose of reporting to greenhouse gas registries or 

obtaining market credits. A variety of “carbon tools” 

(U.S. Forest Service 2013b) are available to support land 

managers and policy makers in making decisions, and 

methods are available to measure, monitor, and verify 

actions that are intended to reduce emissions or increase 

sequestration. Although these actions take place on the 

small scale of individual projects, there is a need for 

verification at larger scales (region, country, or global) to 

ensure that, collectively, the actions taken individually 

are having a detectable effect and that the measured 

effect is not reduced by reactions outside of the project 

boundaries (i.e., “leakage”).

This report describes current carbon stocks in forests and 

wood products of northern Wisconsin, recent trends, and 

potential impacts of several greenhouse gas mitigation 

options that have been discussed by public and private 

entities in the region. Three general categories of 

mitigation options were analyzed for this report: (1) 

increase carbon stocks in forests and wood products; 

(2) reduce the loss of forest land; and (3) increase the 

use of wood for bioenergy. The report also describes 

opportunities and issues regarding implementation of a 

mitigation strategy such as engagement in greenhouse 

gas markets and registries. Estimates of carbon stocks 

and stock changes by forest ownership were derived 

using U.S. Forest Service Forest Inventory and Analysis 

(FIA) data, and models were used to assess the impacts of 

disturbance, climate, and land management scenarios.
5

This report follows the international reporting 

requirements established under the umbrella of 

the Intergovernmental Panel on Climate Change 

(IPCC) as implemented for the forestry sector of 

the U.S. greenhouse gas inventory compiled by the 

Environmental Protection Agency (U.S. Environmental 

Protection Agency 2009). The seven main forest sector 

carbon pools generally defined by IPCC and adapted for 

reporting in the United States are: 

•	 Live trees—Live trees with diameter at breast 

height (d.b.h.) of at least 2.5 cm (1 inch), 

including carbon mass of coarse roots (diameter 

greater than a minimum size that ranges from 

0.2 to 0.5 cm), stems, branches, and foliage.

•	 Standing dead trees—Standing dead trees with 

d.b.h. of at least 2.5 cm, including carbon mass 

of coarse roots, stems, and branches.

•	 Understory vegetation—Live vegetation that 

includes the roots, stems, branches, and foliage 

of seedlings (trees less than 2.5 cm d.b.h.), 

shrubs, and bushes.

•	 Down dead wood—Woody material that 

includes logging residue and other coarse dead 

wood on the ground that is larger than 7.5 cm 

in diameter, and stumps and coarse roots of 

stumps.

•	 Forest floor—Organic material on the floor of 

the forest that includes fine woody debris up 

to 7.5 cm in diameter, tree litter, humus, and 

fine roots in the organic forest floor layer above 

mineral soil.

•	 Soil organic carbon—Belowground carbon 

without coarse roots, but including fine roots 

and all other organic carbon not included in 

other pools, to a depth of 1 meter.

•	 Carbon in harvested wood—Carbon contained 

in products in use and in landfills. Products 

in use include end-use products that have not 

been discarded or otherwise destroyed such as 

residential and nonresidential construction, 

wooden containers, and paper products. 

Products in landfills include discarded wood and 

paper placed in landfills where most carbon is 

stored long-term and only a small portion of the 

material is assumed to degrade at a slow rate.

Carbon is transferred among these seven pools and the 

atmosphere (Fig. 1). The amount of carbon in each pool 

is commonly called a stock, and the transfers may be 

Figure 1.—Forest sector carbon pools and flows (Heath et al. 2003).
6

called fluxes or changes in carbon stocks. These terms 

and some of the other common terminology used in this 

report are highlighted in Box 1.

The scope of analysis is the portion of Wisconsin 

occurring within Ecological Province 212: Laurentian 

Mixed Forest (Fig. 2) (McNab and Avers 1994, McNab 

et al. 2007). This area includes three major forest 

ownership groups that were used for this assessment: 

National Forest, other public lands, and private lands 

which include land owned by tribes. Northern Wisconsin 

is the most heavily forested region of the state, containing 

4.6 million ha, or about two-thirds of the state’s total 

forest land (Perry et al. 2008, Swanston et al. 2011). 

The percentage of land with forest cover increases from 

south to north until almost all of the land area is forest. 

The region’s forests represent the transition from the 

more southerly broadleaf deciduous forest to the more 

northerly boreal forest. Deciduous hardwoods such as 

maples, ashes, and yellow birch tend to occupy high 

quality sites, while conifers such as pine, tamarack, and 

spruce occupy the less productive sites (Perry et al. 2008).

Figure 2.—Forest types of Wisconsin (Perry et al. 2008). Ecoregion Province 212 includes the northern 

half of the State.

Ecoregion 

Province 212

White/red/jack pine

Spruce/fir

Oak/hickory

Elm/ash/cottonwood

Maple/beech/birch

Aspen/birch

Nonforest

Water

Chequamegon-Nicolet National Forest
7

Box 1—Common forest carbon terminology and reporting units used in this report

Afforestation—The establishment of forest or forest stands on lands where the preceding vegetation or land 

use was not forest.

Carbon pool—A reservoir that stores carbon. Examples include forest biomass, wood products, soils, and 

the atmosphere.

Deforestation—Land that changes from forest to nonforest use including a significant removal of tree cover. 

Areas temporarily treeless from harvesting are not included if regeneration occurs.

Flux—The transfer of carbon from one carbon pool to another.

Flux tower—A tower that extends above the forest canopy, instrumented to measure the exchange of water, 

energy, and carbon dioxide (CO2) between the forest and the atmosphere using a statistical technique known 

as eddy covariance.

Forest land—Land that is at least 10 percent stocked by forest trees of any size or formerly having such tree 

cover and not currently developed for nonforest uses.

Mitigation—Actions to decrease the amount of CO2 in the atmosphere in order to reduce the effects of 

global warming.

Reforestation—The reestablishment of forest cover, naturally or artificially, after a previous stand or forest 

was removed or lost.

Sequestration—The direct removal of CO2 from the atmosphere through biologic processes such as forest 

growth.

Sink—Any process, activity, or mechanism that removes CO2 from the atmosphere.

Stock—The quantity of carbon stored in biological and physical systems, including live and dead trees and 

tree roots, products of harvested trees, other live vegetation, woody debris, litter, and soils.

Carbon Units—

Megagram (Mg): 1,000 kilograms (2,204.6 pounds) = 1 tonne

Teragram (Tg): 1,000,000 tonnes
8

PAST AND CURRENT CARBON 

STOCKS IN FORESTS AND WOOD 

PRODUCTS OF NORTHERN 

WISCONSIN

In this section we examine data from past periodic and 

recent annual inventories to develop estimates of current 

carbon stocks and recent trends. To the extent allowed 

by existing data and analyses, we identify the main causes 

of observed changes in carbon stocks. This information 

is useful both to understand the current forest situation 

for developing mitigation options and to establish the 

historical baseline for comparing with projections of 

changes in carbon stocks under different management 

and policy scenarios.

Past and Current Stocks of Forest 

Carbon

We used the Forest Service “Carbon Calculation 

Tool” (CCT) and queries of publicly available Forest 

Inventory and Analysis (FIA) online data sets to develop 

the estimates of past and current carbon stocks in this 

section (Smith et al. 2007). CCT is designed to estimate 

annual carbon stocks and changes in carbon stocks for 

forests at the state level for the forestry statistics of the 

U.S. greenhouse gas inventory (U.S. Environmental 

Protection Agency 2009). CCT uses FIA data from older 

periodic inventories, newer annual inventories, and the 

carbon conversion factors as described in Heath et al. 

(2011) to estimate annual stocks of carbon in each of the 

major ecosystem carbon pools since 1990. Because the 

standard CCT output is at the State level, we developed 

an historical FIA data set for Ecoregion 212 of northern 

Wisconsin for input to CCT so that the results pertained 

specifically to this region. Note that although CCT 

produces estimates of carbon stocks in soils at different 

time periods, the estimates are not sufficiently accurate to 

report the estimated changes in soil carbon stocks, which 

are generally thought to be small relative to changes in 

the other carbon pools.

About 64 percent of northern Wisconsin forest land 

is in private ownership (Table 1). Despite increasing 

development pressures, the area of forest land has 

been increasing slowly over the last decades, primarily 

because the rate of increase in abandoned agricultural 

land exceeds the losses from conversion to nonforest 

use. Geographically, the percentage of land classified as 

forest increases from south to north, with the highest 

forest cover occurring in the most northern counties and 

averaging more than 80 percent of the land area (Fig. 3).

Table 1.—Area of forest land by ownership class and 

year, Wisconsin Ecoregion 212

Year

Ownership class 1990 2000 2009

Thousand ha

National Forest 570.5 573.6 571.0 

State and local 984.3 1,020.3 1,068.0 

Private 2,815.0 2,861.8 2,877.1 

All owners 4,369.8 4,455.7 4,516.0 

Figure 3.—Area of forest land 

by county, Wisconsin, 2004 

(Perry et al. 2008).

Projection: Wisconsin Transverse Mercator, NAD83/91. 

Sources: U.S. Forest Service, Forest Inventory and 

Analysis Program, 2004 data. Geographic base data are 

provided by the National Atlas of the http://fiatools.fs.fed.us. 

Cartography: C.H. Perry. October 2007.

Relative Forest Cover

More than 80

61 - 80

41 - 60

21 - 40

Less than 21

Projection: Wisconsin Transverse Mercator, NAD83/91.

Sources: U.S. Forest Service, Forest Inventory and Analysis Program,

2004 data. Geographic base data are provided by the National Atlas of the

USA. FIA data and mapping tools are available online at

http://fiatools.fs.fed.us.

Cartography: C.H. Perry. October, 2007.

(percent of county land area)

0 50

Miles

Relative Forest Cover
9

Table 2.—Area of forest land by ownership class, year, and selected major 

forest types, Wisconsin Ecoregion 212

Year/Ownership class

Forest typea

WRJ SF OH EAC MBB AB

Thousand ha

1996

National Forest 55.6 87.9 11.2 34.3 222.8 155.7

State and Local 92.6 121.2 83.1 75.8 287.1 326.9

Private 147.9 313.7 216.4 276.7 1148.7 722.8

All owners 296.1 522.7 310.8 386.8 1658.6 1205.5

2007

National Forest 52.5 95.5 28.4 19.2 213.9 146.6

State and local 105.5 139.8 118.0 47.7 255.0 322.2

Private 198.6 290.8 540.2 133.0 916.1 661.5

All owners 356.7 526.1 686.6 199.9 1385.1 1130.3

a

White-red-jack pine (WRJ), Spruce-fir (SF), Oak-hickory (OH), Elm-ash-cottonwood (EAC), 

Maple-beech-birch (MBB), Aspen-birch (AB).

Table 3.—Forest carbon density for 2009 by ownership 

class and carbon pool, Wisconsin Ecoregion 212

Carbon pool

Ownership class Biomass

Dead 

wood

Forest 

floor Soil Total

MgC ha-1

National Forest 74.4 10.6 21.4 155.1 261.4

State and local 59.8 9.5 17.1 149.1 235.4

Private 65.5 9.9 16.9 140.0 232.3

All owners 65.3 9.9 17.5 144.1 236.7

Table 4.—Forest carbon stocks for 2009 by ownership 

class and carbon pool, Wisconsin Ecoregion 212

Carbon pool

Ownership class Biomass

Dead 

wood

Forest 

floor Soil Total

TgC

National Forest 42.5 6.1 12.2 88.5 149.3

State and local 63.8 10.2 18.2 159.2 251.5

Private 188.5 28.4 48.6 402.9 668.3

All owners 294.8 44.6 79.0 650.6 1069.1

Significant changes in forest composition have occurred 

recently. Over the last decade, the area of oak-hickory 

forest has increased as the area of other hardwood forest 

types has declined (Table 2). These composition changes 

are most pronounced on private lands 

Carbon density (amount of carbon stock per unit area) 

is high, averaging 237 megagrams (Mg) per ha, with the 

National Forest ownership class having a slightly higher 

density than the other ownership classes (Table 3). Total 

carbon stocks are distributed in approximate proportion 

to area of ownership class (Table 4). About 60 percent of 

the ecosystem carbon is in the soil.

Over the last decade, carbon stocks of northern 

Wisconsin forests have been increasing by about one Tg 

per year or 0.22 Mg per ha per year, a little less than the 

previous decade (Table 5). Most of the increase has been 

in live biomass. Among ownership groups, the per ha 

increase has been largest on public forest lands.

In summary, the forests of northern Wisconsin have been 

net carbon sinks for at least the last two decades, though 

the rate of sequestration has been declining. Public lands 

sequester more carbon, on average, than private lands. 

Likely causes for the declining rate of sequestration are 

increased harvesting for wood products, aging forests, 

and increasing natural disturbances. These driving factors 

are considered in more depth later in this report.
10

Carbon in Harvested Wood Products

Change in the stock of carbon in harvested wood 

products is estimated as the difference between the input 

of carbon to wood products in use or in landfills and the 

emissions from these two pools. The U.S. Department of 

Agriculture greenhouse gas inventory (Smith and Heath 

2008) estimates that harvested timber from Wisconsin 

forests are responsible for a net transfer of about 0.7 Tg 

carbon each year from live pools to wood products and 

landfills. The estimate of transfer to these two pools by 

White et al. (2005) was similar at about 0.8 Tg carbon 

each year.

Industrial roundwood production in Wisconsin has been 

relatively stable over the last two decades at about 10 

million cubic meters per year (Perry et al. 2008). About 

two-thirds of this harvest is from northern Wisconsin—

an average of 7 million cubic meters per year since 1996 

(Table 6). Roundwood removals were lower overall in 

2001, but the trends were different among ownership 

groups. Roundwood removals from National Forest 

lands declined significantly since 1996, while removals 

from both private and other public owner classes 

declined and then increased significantly in the most 

recent statistics (Table 6).

Table 5.—Average annual change in forest carbon stock by ownership 

class and carbon pool, 1990-1999 and 2000-2009

Carbon pool

Years/Ownership class Biomass

Dead 

wood

Forest 

floor Total

Average 

(MgC/ha)

TgC yr-1

1990-1999

National Forest 0.279 0.019 0.068 0.367 0.64 

State and local 0.320 0.026 0.102 0.448 0.44 

Private 0.644 0.012 0.045 0.701 0.25 

All owners 1.244 0.057 0.215 1.516 0.34 

2000-2009

National Forest 0.192 0.008 0.080 0.279 0.49 

State and Local 0.267 0.041 0.161 0.469 0.44 

Private 0.370 -0.014 -0.125 0.230 0.08 

All owners 0.829 0.035 0.115 0.979 0.22 

Table 6.—Average annual volume of roundwood 

removals, counties of Ecoregion 212 in northern 

Wisconsina

Year

Owner/species group 1996 2001 2006

1000 ft3

National Forest

Softwood 4,827 3,568 5,872

Hardwood 14,706 12,761 5,612

Total 19,534 16,329 11,483

Other Public

Softwood 13,848 11,851 9,996

Hardwood 45,706 41,616 46,150

Total 59,554 53,467 56,146

Private

Softwood 37,725 35,594 39,035

Hardwood 138,583 136,417 151,735

Total 176,308 172,011 190,770

All Owners

Softwood 56,400 51,013 54,903

Hardwood 198,995 190,794 203,497

Total 255,396 241,807 258,399

a

Data retrieved from the Forest Inventory and Analysis timber 

products output database available at http://srsfia2.fs.fed.us/php/

tpo_2009/tpo_rpa_int1.php. 1 ft3

 = 0.028317 m3.
11

We followed the standard methodology for estimating 

gains and losses of carbon in harvested wood products 

(Skog 2008, Smith et al. 2006). The amount of harvested 

carbon remaining in the different carbon pools is 

encoded in a new harvested wood product calculator 

named PRESTO (U.S. Forest Service 2013d) which 

accepts input from the FIA timber products output 

database. We then used a simple spreadsheet model to 

estimate the carbon remaining in the products in use 

and landfill categories from 1950 to 2010. The period 

1950 to 1990 was used to initiate variables in the model 

so that the decay pattern of losses from historical input 

to these durable wood pools was stable for the reporting 

period from 1990 to 2010 (Fig. 4). Results showed that 

since 1990, carbon in harvested wood products has been 

increasing by 0.5 Tg per year from timber removals in 

northern Wisconsin, with a reduced rate of increase in 

2000 because of temporarily reduced harvest. About 

Figure 4.—Change in C stocks of 

harvested wood products (products in 

use and landfills) by ownership class, 

northern Wisconsin, 1990 to 2010.

Figure 5.—Change in C stocks of 

forest ecosystems and harvested 

wood products (products in use and 

landfills) by ownership class, northern 

Wisconsin, 1990-2000 and 2000-2010.

three-fourths of the carbon in harvested wood carbon 

pools comes from private lands.

Recent Changes in Carbon Stocks 

of Forests and Wood Products

The total net carbon sequestration in northern Wisconsin 

forests and wood products was 2.0 Tg per year from 

1990 to 2000 and 1.5 Tg per year from 2000 to 

2010 (Fig. 5). National Forest and private landowner 

groups exhibited reductions in carbon accumulations 

rates in ecosystems, while state and local ownership 

groups showed a small increase in the rate of carbon 

accumulation in forest ecosystems. There was also a 

significant drop in additions to the harvested wood 

product carbon pool for National Forests and an increase 

in additions to the harvested wood product carbon pool 

for the private ownership group.

0

0.1

0.2

0.3

0.4

0.5

0.6

1990 1995 2000 2005 2010

National Forest

Other Public

Private

All Owners

TgC yr-1

0

0.5

1

1.5

2

2.5

National Forest Other Public Private All Owners

1990-2000

TgC

2000-2010

yr-1
12

PRINCIPAL FACTORS AFFECTING 

CARBON STOCKS AND FLUXES

In this section we review the main factors affecting 

carbon stocks and fluxes in the forests of northern 

Wisconsin, which will help reveal the opportunities for 

increasing carbon stocks in the future. We highlight 

stand- and landscape-level productivity estimates and 

their relationship to management, natural disturbance, 

age distribution, and current condition of the region’s 

forests. In section 3 we use this information and that of 

the previous section to support analyses of management 

actions that could potentially be applied in the region as 

part of a climate mitigation strategy.

Forest Area and Area Change

The area of forest is a principal determinant of the stock 

of carbon and the rate of change in a landscape. Since 

1990, forest land area increased by 3 percent in northern 

Wisconsin (Table 1). This means that losses of forest 

land to development and other nonforest land uses 

were less than additions to forest from other land uses 

such as cropland or pasture. About half of the counties 

in northern Wisconsin had either significant gains or 

significant losses in the total area of forest (Perry et al. 

2008). Although the forest inventory does not separately 

report the magnitudes of gains and losses of forest area 

but rather the net change, studies of land cover change 

indicate that deforestation claimed less than 10,000 ha 

per year from 1990 to 2001, inferring that more than 

15,000 ha per year of afforestation would be needed to 

result in a net forest area increase of 146,000 ha from 

1990 to 2009. Even with increasing forest area, it is 

possible that the carbon stock declines. This is because 

deforestation can remove a large quantity of existing 

carbon stock in a very short time, whereas afforestation 

is a slower process of regrowth and accumulation of new 

carbon stocks.

Productivity of the Land

Productivity estimates can be derived from different 

kinds of observations, and these estimates may not be 

equivalent (Box 2). Northern Wisconsin has a dense 

network of 13 CO2 observation sites with flux towers 

(see Box 1) in the region, all having similar vegetation 

and climate and collectively providing approximately 70 

data years (Table 7). The network has discovered a range 

of carbon sequestration rates from very strong sinks to 

weak or moderate sources. Some sites switch between 

sinks and sources depending on year. A more detailed 

summary (not including net ecosystem production 

[NEP] rates) of the flux towers in the region can be 

found in Desai et al. (2008). Detailed data are readily 

available to the public and can be downloaded from the 

AmeriFlux Web site (http://public.ornl.gov/ameriflux/) 

or the respective project Web sites.

Table 7.—Carbon sink strength at flux tower sites in Wisconsin. Negative numbers represent ecosystems 

that are sources of CO2

Site name Status Vegetation type

Net ecosystem production

(Mg C ha-1)

Lost Creek Active Closed shrublands 0.63 to 1.02

Park Falls Active Mixed forest -1.07 to -0.23

Sylvania Wilderness Inactive Mixed-forest (old-growth) -1.17 to 1.47

Willow Creek Inactive Deciduous broadleaf forest 4.45 to 5.05

Wisconsin Clearcut Red Pine Inactive Open shrublands 1.67

Wisconsin Clearcut Young Hardwood Inactive Deciduous broadleaf forest -0.99

Wisconsin Intermediate Hardwoods Inactive Deciduous broadleaf forest 1.11

Wisconsin Intermediate Red Pine Inactive Evergreen needleleaf forest 8.67

Wisconsin Mature Red Pine Inactive Evergreen needleleaf forest 8.53 to 9.55

Wisconsin Mixed Young Jack Pine Inactive Evergreen needleleaf forest 5.73

Wisconsin Pine Barrens Inactive Open shrublands 2.72

Wisconsin Young Jack Pine Inactive Evergreen needleleaf forest 2.72 to 3.24

Wisconsin Young Red Pine Inactive Evergreen needleleaf forest 4.74
13

Using data from a very tall tower (much taller than the 

flux towers reported in Table 7) representing a large 

heterogeneous landscape, Davis et al. (2003) found 

that the ecosystems in the region were, on average, 

carbon neutral. The tall tower represents a landscape 

that includes aspen, northern hardwood, and coniferous 

stands, and about 30 percent of the area is shrub or 

forested wetland. The average stand age is 51 for uplands 

and 69 for wetlands (Davis et al. 2003).

A tower in the Sylvania Wilderness Area documented 

a small carbon sink (Desai et al. 2005), consistent with 

most other older forest sites in the Fluxnet network 

which have shown small to moderate carbon sinks 

(Griffis et al. 2003, Hollinger et al. 1994, Knohl et al. 

2003). However, the carbon sequestration value (net 

ecosystem exchange, NEE) for Sylvania was only 11 

percent of that for Willow Creek; the mature forest at 

Willow Creek was a much stronger carbon sink.

Additional towers were located in several forest types 

on the Washburn District of the ChequamegonNicolet National Forest (CNNF) including young 

red pine, mature red pine, young hardwood clearcut, 

mature hardwood, and pine barrens. Age, not species 

composition, appeared to be the more important factor 

in this study. Mature red pine and mature hardwoods 

had nearly equal values (6.48 and 6.55 Mg C per ha 

per year, respectively) although this study only took 

observations during the growing season, making them 

significantly higher than if the observations were made 

year round (Noormets et al. 2007).

Land use history, species composition, age, and soil 

characteristics are possible reasons for the differences 

in the productivity estimates for these sites (Cook et al. 

2004). Broadleaf trees typically have higher maximum 

rates of CO2 uptake than conifers, but because conifers 

are usually evergreen, their uptake rates over the whole 

year can be similar (Malmsheimer et al. 2008).

Bradford and Kastendick (2010) used a chronosequence 

approach to study carbon storage in pine and aspenbirch systems in nearby Minnesota. They found that 

total carbon storage, along with structural complexity, 

increased with stand age. However, in these previously 

harvested systems (which were depleted of course woody 

debris, and thus had lower rates of decomposition), 

the young stands had the highest rates of carbon 

sequestration. This highlights some of the possible 

Box 2—Forest processes affected by natural disturbances and management practices

Timber harvesting, fire, weather events, and many other disturbances affect a variety of processes that 

determine the net carbon balance of an ecosystem and how that balance changes over time. Some types of 

ecosystem models simulate the responses of these processes and predict how different ecosystem carbon 

pools may change after disturbances.

•	 Gross Primary Production (GPP)—ecosystem-level gain of CO2 from photosynthesis, a process by 

which green plants utilize the energy of sunlight to manufacture carbohydrates from carbon dioxide 

and water in the presence of chlorophyll.

•	 Autotrophic Respiration (Ra)—Oxidation of specific organic molecules by photosynthetic plants with 

a subsequent release of CO2.

•	 Net Primary Production (NPP)—GPP minus Ra.

•	 Heterotrophic Respiration (Rh)—Release of CO2 by nonphotosynthetic organisms that obtain 

nourishment from the ingestion and breakdown of organic matter.

•	 Net Ecosystem Production (NEP)—NPP minus Rh.

•	 Net Ecosystem Carbon Balance (NECB)—NEP minus carbon losses to disturbances or other 

transfers from the ecosystem (e.g., ecosystem carbon removed by fire or forest management).

•	 Net Biome Production (NBP)—NECB integrated over time and space.
14

tradeoffs managers will face in deciding whether to favor 

younger or older forests. Interestingly, this study also 

found that older aspen stands continued to accumulate 

carbon well beyond the current recommended 

management rotation of 30 to 60 years.

Using plot-based techniques, aboveground net primary 

production (NPP) for mixed hardwood stands in the 

region has been estimated at 3.75 Mg carbon per ha per 

year using data collected from 1998 to 2000 (Burrows

et al. 2003) and 3.30 Mg carbon per ha per year using 

data collected from 1993 to 1994 (Fassnacht and Gower 

1997). Wang et al. (2009) used a model approach and 

estimated ecosystem NPP to be 7.30 Mg carbon per ha 

per year for a mixed hardwood forest. Combining flux 

towers and remotely sensed data to produce a landscape 

level estimate of NEP, Cook et al. (2009) found a 

sequestration rate of 3.84 Mg carbon per ha per year. 

Peckham et al. (2012) estimated an average net biome 

production (NBP) of 2.3 Mg carbon per ha per year 

using the model Biome-BGC, which showed a range of 

1.6 to 3.0 across the landscape.

Land Management

Effects of Forest Management on Carbon Stocks 

and Fluxes

Forest management strategies can be designed to 

manipulate carbon stocks and rate of carbon uptake by 

forest systems. The impact of a selected management 

strategy will depend on the type of the management 

practices (e.g., thinning, prescribed burning), how 

these practices transfer carbon between the different 

carbon pools, the time period between disturbances or 

management practices, and the area of forests under 

management. Several basic ecosystem processes (Box 

2) are affected by management practices, and together 

these processes determine the overall carbon balance 

(Harmon 2001, Harmon and Marks 2002, Pregitzer and 

Euskirchen 2004).

Time since disturbance, whether natural or humancaused, largely determines whether a forest system is a 

net source or sink of carbon. In general, forest stands 

recovering from disturbance are sources of carbon until 

uptake from growth becomes greater than losses due to 

respiration, usually within 10 years (Amiro et al. 2006).

When forests are clearcut, carbon is removed for wood 

products, and residual carbon stocks, such as woody 

debris and litter, decompose. It typically takes several 

decades for the ecosystem carbon stocks to recover to 

the preharvest level. The time it takes to recover is highly 

variable, depending on site productivity, regeneration 

success, species, climate, and other factors, but the forest 

will eventually recover the emitted carbon unless the 

soil, climate, or other environmental conditions have 

changed.

The conversion of mature forests into young, intensively 

managed stands may change a landscape from a sink to 

a source because of increased emissions from harvesting 

and because reduced leaf area of the regenerating stand 

leads to lower photosynthesis and NEP (Janisch and 

Harmon 2002, Schulze et al. 2000). However, carbon 

losses after timber harvest can be reduced by efficient 

utilization of harvested wood and maintaining a certain 

level of leaf area of the residual stand (Chen et al. 

2004). Generally, reducing the harvest of live trees from 

complete removal to 20 percent removal could increase 

carbon stocks by 20 to 50 percent, depending on the 

harvest interval (Ryan et al. 2010).

Smith et al. (2006) developed forest ecosystem carbon 

yield tables using Forest Inventory and Analysis (FIA) 

data, conversion factors, and forest growth-yield models 

to represent stand-level merchantable volume and 

carbon pools as a function of stand age for 51 forest 

types within 10 regions of the United States. Separate 

tables were developed for afforestation and reforestation. 

Calculations of carbon sequestered in harvested wood 

products were also included. Estimates in Smith et al. 

(2006) represent average values for forest types within 

large regions containing substantial site variability; 

therefore, the uncertainty of the estimates if applied 

to a specific forest stand may be high relative to other 

techniques that use site- or project-specific data. The 

estimates showing the average response of forest carbon 

pools to management and disturbance may be used 

for strategic analysis and in some cases, estimating and 
15

reporting actual changes in carbon stocks from forestry 

activities (e.g., Birdsey 2006).

NEP was calculated for three different forest types 

typical of northern Wisconsin using the estimates from 

Smith et al. (2006). The rate of carbon sequestration 

after clearcut harvest is zero or negative for about 

a decade due to decomposition of residual carbon 

primarily from the forest floor and woody debris pools 

(Fig. 6a). It then increased to a maximum rate at 20 

to 35 years of age, followed by a long period of slow 

reduction in rate of uptake. The results are slightly 

different for afforestation, here defined as reversion of 

cropland back to forest (Fig. 6b). In this case there is no 

loss of stored carbon because the forest floor and woody 

debris pools are absent at age zero, and the maximum 

rate of NEP is a little higher in the early decades 

because of buildup of soil carbon after depletion from 

cultivation.

Carbon in Harvested Wood Products

Carbon stocks that are transferred by harvest from 

ecosystem carbon pools to wood products retain some 

portion of carbon removed from the forest over the long 

term (Skog 2008, Smith et al. 2006). It is important 

to keep track of the carbon sequestered in harvested 

wood products until it returns to the atmosphere. How 

long the carbon is retained is determined by the kind 

of products produced (e.g., lumber, pulpwood) and 

how these products are disposed of (e.g., landfilled, 

combusted). Figure 7 shows a typical retention pattern 

for carbon in harvested hardwood of the Lake States. If 

all of the harvested hardwood were used for sawn timber 

rather than pulpwood, 37 percent of the carbon removed 

from the forest would still be in use or in a landfill after 

65 years.

-1

0

1

2

3

0 10 20 30 40 60 80 100

MgC ha-1 yr-1 

Age

Red pine

Oak-hickory

Hard maple

-1

0

1

2

3

0 10 20 30 40 60 80 100

MgC ha-1 yr-1 

Age

Red pine

Oak-hickory

Hard maple

Figure 6.—Net ecosystem production of selected forest types 

(a) after clearcut harvest, and (b) after afforestation. Estimates 

are from Carbon OnLine Estimator (COLE), data retrieved 

April 12, 2010. 

(a)

(b)

Figure 7.—Disposition of carbon in 

harvested hardwood over 100 years 

in the Lake States. In use refers to 

wood products still in use. Landfill

refers to wood that has been 

disposed of, yet the carbon is still 

sequestered in a landfill. Energy

refers to the amount of harvested 

wood burned for energy. The 

remainder is Emitted. From Smith 

et al. (2006).
16

A common question is whether harvesting and 

regeneration on a repeated rotation sequesters more 

carbon than leaving a forest to grow without harvest 

(assuming no natural disturbance). The answer often 

depends on the time horizon. For a short period of 

time of several decades or so (actual timing depends on 

growth rates and other factors), leaving a forest intact will 

sequester more carbon than harvesting and regenerating. 

Over a longer time period, repeated harvesting and 

regeneration can provide more total carbon storage in the 

ecosystem plus wood products if substitution of wood for 

other materials is part of the accounting system (Fig. 8). 

This conclusion is based on data showing that there may 

be substantial energy savings if wood is used instead of 

other products that consume more energy in production.

Landscape-scale Considerations

In a landscape that contains forests with different 

disturbance histories and age classes, some stands are likely 

to be carbon sources (releasing carbon to the atmosphere), 

others are likely to be carbon sinks (removing carbon from 

the atmosphere), and some may be close to a balanced state 

(Harmon 2001, Jarvis et al. 2005). Adding together all 

of the individual stand-level estimates determines overall 

landscape-level carbon stocks and fluxes (Fig. 9). A single 

stand shows the typical dynamics of recovering carbon 

stocks following a disturbance, but when carbon stocks of 

multiple stands are averaged together, the line flattens as 

the aggregate values represent the entire landscape.

Whether a landscape is a carbon sink or source reflects 

its site quality, species composition (forest type), 

management history, and time since last disturbance or 

age-class structure. The average carbon stock of a large 

number of stands is determined by the interval and 

severity of disturbances over the landscape. With more 

frequent and severe disturbances, the average carbon stock 

(including stock in harvested wood products) becomes 

lower. Practices designed to enhance carbon sequestration 

at the landscape scale must replace ecosystems having 

lower carbon densities with ones having higher densities. 

Examples of these practices include: reducing the severity 

of disturbances, increasing the time interval between 

disturbances, emphasizing long-lived forest products, or 

reducing decomposability of dead material.

Figure 8.—Comparison of changes in 

carbon stocks for no harvest and multiple 

rotation scenarios. From Ingerson (2007).

Figure 9.—Carbon storage over time of a single stand 

and averaged over multiple stands (McKinley et al. 2011).

Adapted from Wilson 2006, data from Perez-Garcia et al. 2005
17

Age and Condition of the Region’s 

Forests

Young, rapidly growing forests, once established, have 

higher rates of carbon sequestration but lower levels of 

stored carbon compared with older forests. In contrast, 

older forests have higher levels of stored carbon, but 

lower rates of net sequestration due to greater mortality 

and respiration (Harmon 2001, Malmsheimer et al. 

2008). Late successional and old growth forests may 

capture less or perhaps even no new carbon from the 

atmosphere, but they can store large masses of carbon 

in biomass and soils for long time periods (Harmon 

2001). At any time, the balance between production, 

decomposition, and horizontal or vertical transfers into 

and out of a forest stand determines whether the forest 

is a net source or a net sink of carbon; however, over 

the long term, the average amount of carbon stored on 

a landscape is a more stable indicator of the impacts of 

management.

The forests of northern Wisconsin have a distribution of 

age classes that peaks in the middle ages of a forest life 

cycle, a pattern typical of northern U.S. forests (Fig. 10) 

(Pan et al. 2011b). Generally, this pattern reflects the 

history of land clearing for agriculture and reversion back 

to forest and periods of intensive timber harvest during 

the last century. Because of continuing reversions plus 

active industrial forest management, the younger age 

classes are well represented among all ownership groups. 

The oldest forests sampled by FIA in the region are about 

200 years old. There is a slightly higher proportion of 

older-aged forests on Federal lands. Young and middleaged forests tend to be productive and healthy unless 

affected by a disturbance.

Distributions of age classes by forest type show 

distinctively different patterns (Fig. 11). The white-redjack pine and aspen-birch forest type groups tend to 

be younger on average, reflecting plantation and earlysuccessional management, respectively, for industrial 

wood products. Spruce-fir, oak-hickory, and maplebeech-birch all show the typical northeastern pattern of 

higher proportions of middle-aged forests.

0

50,000

100,000

150,000

200,000

250,000

Histogram of 2007 Age Distribution 

for Forest Service Lands 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

Histogram of 2007 Age Distribution

for State & Local Government Lands0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

Histogram of 2007 Age Distribution

for Private Lands 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

Figure 10.—Area of forest in 2007 by age class and 

ownership class, northern Wisconsin.

The age-class distribution over a landscape, which 

reflects the legacy of past harvest, natural disturbance, 

and abandonment of agriculture, is a useful indicator of 

potential for additional carbon storage. If the landscape 

is dominated by young forests, there is significant 

potential to increase carbon stocks, whereas an area with 

mostly old forests will not likely increase carbon stocks 

significantly in the future.
18

Effects of Climate, Air Pollution, and 

Natural Disturbance

Harvest and fire have been principal drivers of forest 

carbon dynamics over the last century in the upper 

Midwest (Gough et al. 2007). Windstorms, insects, 

diseases, and other disturbances such as land use change 

also strongly affect the natural systems of northern 

Wisconsin and cause tree damage and mortality to 

varying degrees (Mladenoff et al. 2008). Wind and 

fire have historically been the most destructive natural 

disturbances. Although fires during settlement times, 

often as a result of land clearing, had substantial effects 

on the landscape, wind appears to have had significantly 

greater effects than fire on Wisconsin’s forests over long 

periods of time (Mladenoff et al. 2008, Schulte and 

Mladenoff 2005). The effects that these disturbances 

have on forest carbon budgets are highly variable and 

linked to the type of disturbance, the spatial extent and 

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

Histogram of 2007 Age Distribution 

for White-red-jack pine 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

50,000

100,000

150,000

200,000

250,000

Histogram of 2007 Age Distribution

for Spruce-fir 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

Histogram of 2007 Age Distribution

for Oak-hickory 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

Histogram of 2007 Age Distribution

for Maple-beech-birch 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

Histogram of 2007 Age Distribution

for Aspen-birch 0 Yrs

1-10 Yrs

21-30 Yrs

31-40 Yrs

41-50 Yrs

41-50 Yrs

51-60 Yrs

61-70 Yrs

71-80 Yrs

81-90 Yrs

91-100 Yrs

101-125 

Yrs

(Using ECOSUBCD 212 from the FIA data.)

Figure 11.—Area of forest in 2007 by age class and 

forest type, northern Wisconsin.
19

severity of a particular disturbance, and the amount of 

time since disturbance (Gower 2003). Collectively, past 

disturbances have long-lasting effects on the ability of 

forests to sequester carbon (Gough et al. 2008).

Atmospheric pollutants also have wide-ranging effects 

on forest carbon. Ozone is a well-known damaging air 

pollutant that has adverse effects on forest productivity 

(Gower 2003). Ozone damage is a threat in areas of 

higher concentration, though northern Wisconsin forests 

are relatively free of damaging exposure (Perry et al. 

2008). Nitrogen deposition and CO2 fertilization have 

complex effects on forest productivity and may increase 

productivity in some instances, while causing negative 

(for nitrogen) or neutral (for CO2) impacts on forest 

carbon in others (Gower 2003).

We used the Integrated Terrestrial Ecosystem Carbon 

Cycle Model (InTEC) to quantify the historical effects 

of disturbance factors (harvesting, fire, insect infestation) 

and nondisturbance factors (CO2 concentration, N 

deposition, climate variability) on productivity and 

carbon stocks of the continental United States, including 

northern Wisconsin (Chen et al. 2000a, 2000b; Zhang 

et al. 2012). The InTEC model is process-based, 

closely calibrated to FIA and other observational data, 

and validated at the regional scale (Box 3) (Zhang et 

al. 2012). For northern Wisconsin we used a simple 

downscaling approach by extracting results based on the 

geographic boundary of Ecoregion 212 (Fig. 12).

The long-term trend for forest productivity in northern 

Wisconsin shows the effect of forest recovery from 

intensive harvesting and fire of the early 20th century, 

with productivity rising as forests recovered from these 

disturbances (Fig. 13). The model results suggest that 

vegetation recovered first, followed by an increase in 

soil carbon that may now be approaching the rate of 

increase in aboveground carbon. Overlaid on these 

long-term trends is the strong effect of interannual 

climate variability, which results in substantial yearto-year changes in productivity across much of the 

historical reconstruction (Fig. 13). The effect of climate 

variability is more pronounced on vegetation than soil, 

Box 3—Description of the Integrated Terrestrial Carbon Cycle Model (InTEC), from 

Zhang et al. (2012)

The carbon balance of a forest ecosystem is the sum of changes in vegetation (living biomass) and soil 

carbon pools, which in turn result from net primary production (NPP) over a specified period of time (Chen et 

al. 2000a). Since NPP changes with climate, atmospheric composition, soil conditions, and disturbances, the 

carbon balance of a forest region is a function of these external forcing factors (Chen et al. 2000b). The model 

includes five core processes:

1. Simulation of gross primary production (GPP) using a two-leaf canopy photosynthesis model based 

on Farquhar’s leaf-level biochemical model (Chen et al. 2000a), and spatial distributions of GPP as 

well as NPP in a recent reference year (NPPref) are modeled using spatial datasets of leaf area index 

(LAI), clumping index, land cover, soil texture, and hourly meteorology.

2. Based on the NPP distribution in NPPref, annual historical NPP is reconstructed retrospectively based 

on past climate data.

3. Normalized NPP-age relationships derived from the FIA data are used to determine patterns of forest 

regrowth after disturbances (He et al. 2012).

4. A three-dimensional distributed hydrological model is used to simulate soil moisture and temperature 

(Ju and Chen 2005).

5. A modified CENTURY model (Parton et al. 1987) and the net N mineralization model of Townsend et 

al. (1996) are employed to simulate soil carbon and N cycles.
20

Figure 12.—Downscaling with InTEC: spatial distribution of change in carbon stocks, northern Wisconsin and Chequamegon-Nicolet National Forest, 1994-2003. Negative values indicate net emissions to the atmosphere. 
21

though there is a noticeable lagged response. Some 

of the years with high reductions of productivity 

appear to correspond with El Nino climate events 

which are known to alter precipitation and will likely 

result in higher than normal rainfall in the Lake States 

(Holmgren et al. 2001).

Among the main factors affecting cumulative 

productivity, the regrowth and disturbances cycle has 

by far the largest effect, accounting for about twothirds of the total (Fig. 14). Nitrogen deposition has 

the next largest effect, followed by the minor influences 

of increasing CO2 and climate variability which causes 

a strong interannual effect that has not been very 

influential over the long term.

-100

-50

0

50

100

150

200

250

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001

gC m-2 yr-1 

Total NBP

Vegetation

Soils

Figure 13.—Net biome productivity (NBP) of vegetation and soils in forests of northern Wisconsin, 1901-

2010 (Zhang et al. 2012). Negative values indicate net emissions to the atmosphere. Land use change is not 

accounted for in these estimates.

Figure 14.—Cumulative net biome production (NBP) for 

northern United States attributed to principle driving factors 

(Zhang et al. 2012).
22

MITIGATION OPTIONS FOR 

NORTHERN WISCONSIN

Northern U.S. forests are highly diverse ecosystems 

with different patterns of land use history. Forest 

management has adapted locally to this diversity and to 

various federal and state regulations. Because carbon is 

not often the main goal of land ownership, mitigation 

is generally considered in the context of multiple goals 

and objectives. Broad categories of forestry activities that 

can contribute to increasing carbon stocks or reducing 

emissions include: 

•	 increasing carbon stocks in forests and 

wood products including reducing loss from 

disturbances

•	 avoiding loss and fragmentation of forest land

•	 increasing the use of wood for bioenergy

These activities can be consistent with many common 

landowner objectives such as timber production, provision 

of wildlife habitat, and watershed protection. At the same 

time, there may also be tradeoffs. For example, greater 

amounts of carbon can be stored in trees and long-lived 

wood products when forests are allowed to mature, but 

the transition to older forests may reduce early successional 

habitat for some common wildlife species.

McKinley et al. (2011) summarized current knowledge 

about forests and carbon storage in the United States 

and described forest management strategies that can 

increase forest carbon, prevent its loss, and/or reduce 

fossil fuel consumption. Each strategy has tradeoffs, risks, 

and uncertainties which are vital considerations for any 

effort to promote forest carbon storage, especially with 

the uncertainty of forest growth and disturbance under 

future climate. The effectiveness of each strategy depends 

on many factors including time horizon of analysis, 

geographic location, forest type, and specific practices 

applied. A literature review of many specific studies in 

the United States is also available (Hines et al. 2010). See 

Box 4 for a summary of mitigation activities, examples of 

tradeoffs, and a description of some issues for managers 

to consider.

Potential Carbon Stocks

Historical data for northern Wisconsin show that 

significantly higher biomass existed in prelogging forests 

compared to today, which illustrates that it is 

theoretically possible to restore large areas of forest to 

historically higher levels of carbon stock (Rhemtulla et al. 

2009). For all forest types in northern Wisconsin, there 

is potential to increase stocking by allowing more of the 

forest area to reach older age classes. However, the 

reduction in harvesting for wood products would cause a 

significant decline of carbon entering the wood products 

pools, and as existing forests age, their net ecosystem 

production declines as shown in Figure 6. Nonetheless, 

with annual change in carbon stocks (excluding soil C) 

averaging 0.22 MgC/ha (Table 5), there should be 

identifiable opportunities 

to increase carbon 

sequestration by 

following some of the 

management practices 

described in the 

literature.

Rhemtulla et al. 

(2009) estimated that 

aboveground carbon 

density in Wisconsin’s 

forests could be doubled 

if existing forests were 

allowed to grow to old 

age and all suitable 

agricultural land were 

converted to forest and 

allowed to fully regrow. 

Most of the existing 

forest recovery would 

take place in northern 

Wisconsin, but only 

about a third of the 

potential reversion of 

agricultural land would 

occur there (Fig. 15). 

These estimates assume 

that the effects of CO2

Figure 15.—Potential increases 

in aboveground carbon density if 

existing forests were allowed to 

grow to old age and all suitable 

agricultural land were converted to 

forest and allowed to fully re-grow. 

(From Rhemtulla et al. 2009, used 

with permission).
23

fertilization, air pollution, and natural disturbances 

are the same as in the recent past. Because only live 

aboveground carbon was estimated in this study, 

estimated potential gains are likely lower than what is 

actually possible. However, because of industrial wood 

use in the region and continued need for agricultural 

products, it is unlikely that the maximum potential gains 

in ecosystem carbon will be realized.

For this report, the magnitude of potential increases 

in carbon stocks was calculated by examining the ageclass distribution of current forests, matching ages with 

productivity estimates from standard carbon yields for 

the region (Smith et al. 2006), and calculating carbon 

gains as if all existing forests were allowed to grow 

without natural disturbances or harvesting. This is not 

a recommended management scenario, but it is useful 

to put an upper bound on how much additional carbon 

could be sequestered in the future. Table 8 shows the 

results of the simulation over 50 years for the five most 

common forest types in northern Wisconsin. For all 

forest types combined, ecosystem carbon could increase 

at an annual rate of 4.3 Tg per year in the absence of 

harvest compared with the current rate of 1.5 Tg per year

(Fig. 5), for a potential net additional increase of 2.8 Tg 

per year.

Box 4—Strategies for increasing or maintaining carbon stocks in forests and wood 

products (McKinley et al. 2011)

Current knowledge and forest management strategies for increasing forest carbon:

•	 Avoiding deforestation retains forest carbon and has many co-benefits and few risks.

•	 Afforestation increases forest carbon but can decrease stream flow and biodiversity, depending on 

where and how afforestation occurs.

•	 Decreasing harvests can increase species and structural diversity but may cause harvesting 

elsewhere and the risk of carbon loss from disturbance.

•	 Intensive silviculture can increase both forest carbon storage and wood production; however, 

practices can –reduce stream flow and biodiversity.

•	 Use of biomass energy from forests can reduce carbon emissions but would require more intensive 

forest management over broader areas.

•	 Substituting wood products for concrete or steel building materials can reduce fossil fuel emissions, 

but the potential carbon savings for the U.S. is not well known.

•	 Urban forestry has a small role in sequestering carbon and may improve energy efficiency of 

structures.

•	 Fuel treatments lower forest biomass to reduce wildfire risk and intensity, trading current carbon 

stocks in forests for the potential of avoiding larger carbon losses from future wildfire.

•	 Forest health treatments reduce susceptibility to drought, insects, and disease.

Some issues to consider when assessing mitigation options:

•	 What are the boundaries of the analysis—geographic, temporal, ownership, accounting, etc.? 

•	 What are some likely strategies to increase carbon sequestration and reduce carbon emissions? 

•	 What may be an optimum mix of mitigation options for a particular region, ownership, or parcel? 

•	 What tradeoffs need to be considered between carbon management and management for other 

ecosystem benefits and services?

•	 How can this information be integrated into forest planning?
24

Increasing Carbon Stocks in Forests 

and Wood Products

Increasing carbon stocks may involve several approaches 

including changing forest management practices, 

managing wood products, and increasing the area of 

forests. An overview of literature describing each of 

these strategies is presented here. Each of these strategies 

has potential benefits, tradeoffs, and risks, and may 

be an effective strategy if regional circumstances are 

appropriate.

Afforestation

An increase in forested land results in additional carbon 

sequestration over a landscape or region if new areas are 

converted or restored at a higher rate than deforestation 

(Sedjo 2001), though the timing and magnitude of 

impacts from the two activities means that carbon 

losses from deforestation (particularly aboveground 

biomass) occur much more rapidly than carbon gains 

from afforestation or reforestation (Intergovernmental 

Panel on Climate Change 2000). The recent rate of 

reforestation and afforestation in the United States may 

be as high as 700,000 ha per year (Masek et al. 2011), 

which is similar to the rate over the entire 20th century 

(Birdsey and Lewis 2003). These large increases are 

responsible for a relatively stable area (about 304 million 

ha) of U.S. forests over the last century after accounting 

for deforestation (Smith et al. 2009). Many Midwestern 

states had increases in the area of forest land over the 

last decade, including Wisconsin with an increase of 9 

percent since 1977.

The appeal of increasing forest area as a mitigation 

strategy is evident in that 83 percent of the forestry 

projects reported to the U.S. Department of Energy’s 

1605(b) program involved tree planting (Energy 

Information Administration 2006). To qualify for credit 

from tree planting projects, the carbon sequestered must 

be an additional amount to what would have been there 

without the afforestation/reforestation project. This is 

usually easy to document since the alternative nonforest 

land uses typically store much less carbon per unit land 

area (McKinley et al. 2011).

A meta-analysis of the effects of land use change on 

soil carbon concluded that conversion of native forest 

to cropland decreased soil carbon by 42 percent on 

average (Guo and Gifford 2002). However, reversion of 

cropland to secondary forest may reverse this historical 

loss. Post et al. (2004) indicate that the average rate of 

soil carbon accumulation for afforestation and grassland 

establishment ranges from 10 to 40 g per m2

 per year 

(equivalent to between 0.1 and 0.5 percent per year), 

with the highest rates in more humid regions.

Midwestern states have significant nonforest areas that 

can be afforested if the value of carbon rises sufficiently, 

according to macro-economic analyses (Lewandrowski 

et al. 2004, U.S. Environmental Protection Agency 

2005). Among different mitigation options, afforestation 

becomes a dominant strategy at prices ranging from 

$30 to $50 per ton of CO2, with the Lake States and 

Corn Belt figuring prominently among U.S. regions 

with significant areas of marginal cropland and pasture 

available.

A study of afforestation opportunities in the Midwest 

(not including Wisconsin) by Niu and Duiker (2006) 

showed significant potential in Michigan, especially in 

Table 8.—Mitigation potential of northern Wisconsin forests, 50-year no harvest simulation, by forest type

Forest type

Estimate

White-redjack pine Spruce-fir Oak-hickoryMaple-beechbirch Aspen-birch Total

Total C 2007 (TgC) 82.57 198.56 143.39 363.81 234.25 1022.58

Total C 2057 (TgC) 106.48 219.06 186.69 439.29 287.77 1239.29

Annual change C (TgCyr-1) 0.48 0.41 0.87 1.51 1.07 4.33

Annual products C (TgCyr-1) 0.50

Net annual change C (TgCyr-1) 3.83
25

the northern Lower Peninsula. They estimated that 24 

percent of the agricultural land identified as marginally 

productive for crops could be available. Rhemtulla et 

al. (2009) came to a similar conclusion for the state of 

Wisconsin where there is a potential for increases in 

the area of forest land on marginal cropland in central 

northern Wisconsin.

Areas of marginal cropland and pasture that could 

be converted to forest are more likely to be found in 

those counties with 21 to 80 percent forest cover in 

the transitional area between northern and southern 

Wisconsin. Afforestation options are much more limited 

farther north because that area is already primarily 

forested, and nonforested areas include many open 

wetlands and pine barrens. Both of these ecosystems are 

highly valued ecologically, so afforestation efforts here 

may compete with other land management goals. To 

summarize, available land for afforestation is mainly on 

limited areas of private lands in northern Wisconsin. 

The Chequamegon-Nicolet National Forest (CNNF) 

is already 94 percent forested, and there is currently no 

significant backlog of needed reforestation.

Changing Forest Management Practices

There is a great deal of interest aimed at forest 

management and its potential for climate mitigation 

(Birdsey et al. 2006, Ruddell et al. 2007, Sedjo 2001). 

Management practices may affect the amount and 

structure of tree stems and crowns, the microclimate 

above and below ground, and the structure and chemical 

composition of the forest floor and soil (Jarvis et al. 

2005). Since harvesting is usually involved, management 

also affects the amount of carbon stored in harvested 

wood products. Full accounting should include both 

changes in ecosystem carbon storage and harvested wood 

products. This section addresses management strategies 

or practices that may increase carbon stocks in forests 

and wood products of northern Wisconsin.

In general, increasing the interval between harvests in 

aggrading forests can lead to an increase in overall carbon 

storage; the greater the increase in the harvest interval, 

the higher the percentage increase in carbon storage 

(Ryan et al. 2010). Euskirchen et al. (2002) modeled 

nine different Great Lakes landscapes ranging in average 

age from 12 to 50 years with disturbance intervals 

ranging from 25 to 100 years. Results indicated the 

ecosystem with the longest rotation length of 100 years 

and oldest average age of 58.2 years was the strongest net 

carbon sink. The youngest ecosystem (with an average 

age of 15 years and managed on 25-year rotations) was 

the only ecosystem to act as a net ecosystem source, 

releasing carbon to the atmosphere. However, when 

the rotation age for this young ecosystem was increased 

to 50 years, it became a net carbon sink with a carbon 

biomass increase of more than 100 percent. This study 

did not include estimates of carbon stored in harvested 

wood products, which would have reduced the size of the 

estimated additional carbon from lengthening rotations.

Nunnery and Keeton (2010) looked at the effects of both 

harvesting intensity and postharvest retention on forest 

carbon storage in the Northeast United States. They 

found a clear gradient of increasing carbon sequestration 

(total carbon stocks) as forest management intensity 

ranged from high (clearcut) to low (individual tree 

selection or no management). The no-management 

scenario had significantly higher mean carbon stocks 

than all other scenarios. Among active management 

scenarios, individual tree selection with high structural 

retention sequestered the greatest amount of carbon. 

Postharvest structural retention significantly affected 

carbon sequestration, but longer rotations still resulted in 

the largest carbon stocks.

In a study on the Missouri Ozark Experimental Forest, 

Li et al. (2007) compared three silvicultural treatments 

eight years after treatment: no harvest management 

(control); single-tree, uneven-aged management; and 

clearcut even-aged management. The no harvest control 

had the highest total carbon (all carbon pools combined) 

with 182 Mg per ha, compared with 170 Mg per ha 

for single-tree harvest and 130 Mg per ha for clearcut 

harvest. This study did not estimate carbon in the 

harvested wood products.

Peckham et al. (2012, 2013) used an ecosystem process 

model, Biome-BGC, and life cycle inventory data 

for wood and paper products to explore the effects of 
26

different harvest scenarios on net biome production 

(NBP) and wood product carbon for the Midwestern 

region including northern Wisconsin. Biome-BGC 

produces a similar reconstruction of historical patterns 

of productivity as the InTEC model described earlier 

(Fig. 16). Seven harvest scenarios were simulated by 

varying the amount of harvest residue retained, the total 

harvest area, and the harvest type (clearcut and selective) 

to assess the potential impacts on NBP, net primary 

production (NPP), and total vegetation carbon (Fig. 17). 

The seven harvest scenarios removed from 11 to 38 

TgC per year, with five scenarios resulting in increases 

of vegetation carbon of at least 12 percent, and the two 

most intensive harvest scenarios showing decreases of 

more than 8 percent (Fig. 18a). All harvest scenarios 

resulted in decreased NPP for the region (Fig. 18b). 

NBP was positive (i.e., carbon sink) but decreased in 

magnitude over the 50-year simulation period (Fig. 18c). 

More intensive management scenarios decreased average 

NBP by a maximum of 58 percent and vegetation carbon 

by a maximum of 29 percent compared to the current 

harvest regime (base scenario), while less intensive harvest 

scenarios increased NBP.

gure 16

BIOME-BGC

Figure 16.—Simulated net biome production (NBP) for the 

Chequamegon-Nicolet National Forest (CNNF) from Biome-BGC. 

Positive values indicate a C sink relative to the atmosphere. Grey 

bars show total harvest area.

Figure 17.—Seven harvest scenarios for northern 

Wisconsin (Peckham et al. 2013): base = 25 percent 

clearcut and 75 percent selective cut over 1.7 percent 

of area per year (B); base + low residue retention 

(BRL); base + high residue retention (BRH); 100 

percent selective cut (SH); 50 percent clearcut and 50 

percent selective cut (CH); doubled area harvested 

(AH); half area harvested (AL).

The results from Peckham et al. (2013) suggest that a 

reduction in the harvest area and the proportion of area 

harvested by clearcutting would increase vegetation 

carbon and NBP, and that decreasing the amount of 

residue removed could also increase NBP. However, 

these results are regional averages and may not be 

applicable to smaller areas or individual stands with 

different age structure and disturbance history.

Peckham et al. (2012) reported that for the CNNF, a 

slight increase in harvest area would maximize carbon 

sequestration over a 100-year period (Fig. 19). Simulated 

total NBP (i.e., cumulative carbon sequestered) ranged 

from 1.1 to 2.0 MgC per ha per year for annual harvest 

rates of 0 to 5 percent of the total CNNF area. Current 

percentages of clearcut and selective harvests in CNNF 

(20 and 80 percent, respectively) were held constant 
27

throughout the simulation. The 1 percent harvest area 

scenario represents approximately 50 percent of the 

allowable sale quantity set by the CNNF Land and 

Resource Management Plan (U.S. Forest Service 2013a). 

Increasing harvest intensity temporarily decreased NBP, 

but increased NBP in the long term because a greater 

proportion of the forest area was of optimal age for 

maximum NPP. Maximizing net carbon uptake over the 

100-year simulation period increased NBP by 22 percent 

or 0.33 MgC per ha per yearrelative to the 1 percent 

harvest area scenario when harvest intensity in each time 

period was allowed to vary between 0 and 2 percent 

(within the limits of the CNNF plan).

Fissore et al. (2010) asked a different forest management 

question for the Upper Midwest. What is the potential 

effect of increasing the stocking of understocked forests? 

Understocked forests are forests with poor stocking 

primarily because of poor site conditions or pests. Their 

findings for Wisconsin, based on a rate of increased 

stocking of 29 Mg C per ha per year, resulted in a 

maximum potential of 3.2 TgC per year of increased 

sequestration, which is more than the current rate of 

1.5 TgC per year of carbon sequestration in northern 

Wisconsin, but not likely achievable in a realistic 

scenario.

The previous analyses did not include effects of harvest 

on soil carbon. Soil contains the largest carbon pool in 

forest ecosystems (Pan et al. 2011a, Post et al. 1990), 

so changes in soil carbon should be considered when 

estimating carbon fluxes. For the North Central region, 

Figure 18.—Model results of (a) vegetation C (VegC); (b) net primary 

production (NPP); and (c) net biome production (NBP) for the forests 

of the northern Wisconsin region (Peckham et al. 2013). Harvest 

scenarios are the same as shown in Figure 17. Results of the different 

management scenarios are denoted with different line types.

Figure 19.—Potential net C uptake for the Chequamegon-Nicolet 

National Forest (CNNF) in the next 100 years (Peckham et al. 

2012a). The x-axis is the percentage of the total area of the CNNF 

harvested yearly, held constant in every year. The y-axis is the 

time horizon, or number of 10-year increments. The red line 

shows net biome production (NBP) when annual harvest is held 

constant at 1 percent of the CNNF area.
28

Heath et al. (2003) estimated that 60 percent of the total 

carbon in forests was in the mineral soil and about 8 

percent in the forest floor in the year 1997. Grigal and 

Ohmann (1992) found that most terrestrial carbon in 

the Lake States is stored in the upper meter of mineral 

soil (55 percent) and the forest floor (9 percent). Powers 

et al. (2005) reported some carbon and nitrogen loss 

in the top 20 cm of soil in the first 10 years following 

harvest, but only when the entire forest floor was 

removed. Mixing the forest floor with the mineral soil, 

such as when disking to prepare a site for planting, may 

accelerate decomposition and mineralization of the 

organic layers (Jarvis et al. 2005, Pritchett and Fisher 

1987). However, Alban and Perala (1989) found that 

heavy disking for natural regeneration of paper birch 

did not change total soil carbon over a 7 year period. 

Comprehensive literature reviews reveal that the results 

of harvesting and soil mixing are highly variable, though 

many studies suggest that harvesting has a significant 

effect on the forest floor but not mineral soil (Johnson 

and Curtis 2001, Nave et al. 2010). Thus, operations 

that minimize soil disturbance may or may not increase 

the net strength of the carbon sink, probably depending 

on local factors such as climate and nature of the forest 

operation.

Peckham and Gower (2011) used the ecosystem process 

model Biome-BGC to simulate the effects of harvest 

and residue removal management scenarios on soil 

carbon, available soil nitrogen, NPP, and net ecosystem 

production (NEP) in jack pine (Pinus banksiana Lamb.) 

and sugar maple (Acer saccharum Marsh.) ecosystems in 

northern Wisconsin. All the harvest scenarios decreased 

mineral soil carbon and available mineral soil N content 

relative to the no harvest scenario for jack pine and sugar 

maple. These studies all suggest that harvest effects on 

soil carbon could be important when evaluating the 

effects of harvest on ecosystem carbon stocks.

In summary, changing forest management practices 

has complex and long-lasting effects on the stocks and 

fluxes of carbon, and it is not always possible to predict 

the results from a given project, although the results of 

many projects may have a positive effect over a large 

landscape, on average. It is difficult to recommend 

specific management practices, though there seems to 

be some consensus in the literature relevant to northern 

Wisconsin that: (1) lengthening harvest rotations will 

increase carbon stocks if other disturbances do not occur; 

(2) there is an optimal harvesting rate that maximizes 

annual carbon sequestration (but not necessarily carbon 

stocks); (3) low-intensity harvesting (selective harvest) 

appears to result in both higher carbon stocks and 

higher carbon sequestration compared with no harvest 

and minimizes disturbance to the forest floor and soil; 

and (4) if biologically feasible, increasing the stocking 

on poorly-stocked forest land will increase both carbon 

stocks and sequestration. In all of the cases involving 

harvesting, accounting for the carbon in harvested wood 

products increased the overall carbon stocks but not 

enough to fully offset the reduced carbon stocks on the 

land. These conclusions illustrate that there appears to 

be multiple solutions to managing for carbon, either 

through increasing productivity, storage, or both.

Fire and Fuels Management

Fire plays an important role in global and regional 

carbon budgets. It is a primary mechanism for the loss 

of stored terrestrial carbon and can emit large quantities 

of carbon dioxide to the atmosphere. On a regional 

and global scale, fires have been shown to account for 

a large portion of annual variation of CO2 emissions to 

the atmosphere (Randerson et al. 2005, Schultz et al. 

2008). In the Lake States, fire has had less impact on 

forests in recent years compared with other regions of 

the United States (Birdsey and Lewis 2003, Zheng et 

al. 2011). This was not always the case. In the North 

Central region, wildfire was much more significant in 

the late 19th century and early 20th century, a period of 

rapidly increasing logging before fire control programs 

were established (Sterns 1997). Before the advent of 

intensive logging, fire return intervals ranged from about 

50 years for jack pine to more than 1000 years for some 

hardwood forests (Frelich 1995).

Fuel treatments, such as reducing tree density by 

thinning, may reduce the intensity and extent of future 

wildfires (Finney 2001). Because moderate to heavy 

thinning lowers the carbon stored in the forest and, in 

some cases, removes an amount of carbon comparable to 
29

a stand replacing wildfire (Mitchell et al. 2009, Stephens 

et al. 2009), it is important that such activities fully 

consider the probability of a stand replacing wildfire 

(Ryan et al. 2010). In the Lake States, prescribed burning 

may reduce ecosystem respiration and preserve carbon 

stocks. Noormets et al. (2007) studied carbon flux on the 

Moquah Barrens, an extensive pine barrens restoration 

area on the CNNF, and found that the fire-maintained 

pine barrens had lower ecosystem respiration rates than 

the young, harvest-generated hardwood and red pine 

stands which had high amounts of logging residue.

Gough et al. (2007) examined the effects of clearcut and 

slash burning on carbon storage in a mixed deciduous 

forest in the northern Lower Peninsula of Michigan. 

Although stands that were repeatedly disturbed 

reverted to sinks within 6 years of disturbance, repeated 

disturbances (a second harvest and burn) reduced site 

quality and resulted in annual carbon storage that was 45 

percent lower than that in the reference stand receiving 

a single harvest and burn disturbance. Maximum annual 

carbon storage was 26 percent lower than that in the 

reference stand over a 62-year period. Another study 

by Gough et al. (2008) measured annual forest carbon 

storage from 1999 to 2005 in a mixed deciduous forest 

in Michigan’s northern Lower Peninsula, dominated by 

aspen and subjected to harvest and fire, and found lower 

annual carbon sequestration and lower carbon stocks 

in forests having more frequent disturbances. These 

reductions, from roughly 2 to 1 MgC per ha per year, 

were attributed to reduced soil fertility.

In summary, the effectiveness of using fire-related 

mitigation options to increase carbon stocks over the 

long term is highly uncertain. Reducing fuels through 

mechanical treatment or biomass harvesting may result 

in reduced emissions if frequency of future wildfires is 

reduced. One viable option may be to maximize utilization 

of woody material before conducting prescribed burns, 

but the studies referenced above did not include 

estimates of carbon stored in harvested wood products.

Managing the Industrial Forest Carbon Cycle: 

Harvest, Transportation, Processing, and Final 

Fate

Carbon emissions occur during harvest and processing of 

timber, and carbon stored in wood products is gradually 

released through decomposition and combustion. Since 

not all of the harvested carbon is released immediately 

to the atmosphere, the amount remaining in products 

is temporarily stored. In addition, forest products may 

require less energy to produce than materials such as 

concrete and metal, resulting in a net reduction of 

carbon emissions that can be substantial according to 

some estimates, as illustrated in Figure 8 (Krankina and 

Harmon 2006, Lippke et al 2004, Perez-Garcia et al 

2005). However, very few studies have quantified the full 

effects, including substitution, of using wood products 

on the carbon cycle, since the data requirements are 

extensive and the accounting rules for substitution effects 

are not very well established. Box 5 summarizes some 

potential mitigation options involving the industrial 

wood carbon cycle.

Box 5—Summary of industrial carbon cycle mitigation options

•	 Consider total fuel consumption when planning hauls roads and skidding/forwarding patterns.

•	 Incorporate fuel consumption considerations when planning thinning regimes in even-aged 

management systems.

•	 Substitute wood for cement or steel which uses more energy to extract and process.

•	 Increase lifespan of wood products in order to retain carbon in long-lived wood products.

•	 Increase energy efficiency in mill processing, which will substantially decrease carbon emissions.

•	 Reduce the distance that raw material is transported (e.g., to mills) in order to decrease carbon 

emissions from transportation. 

•	 Buy local wood fiber thereby avoiding extremely long transportation chain emissions.
30

White et al. (2005) analyzed the industrial and biological 

effects of timber production on the carbon cycle for 

northern Wisconsin forests. Their wood products analysis 

included fossil fuel used in harvesting, transport, and 

manufacturing processes, but did not include the effects 

of substituting wood for other products. They found that 

emissions from harvesting for the CNNF were -0.10 

MgC per ha per year, a small carbon emission source. 

The nonindustrial private forests had emissions of -0.11 

MgC per ha per year, and the state forests were the 

highest emission source at -0.18 MgC per ha per year. 

Coupling these results with the biological carbon cycle, 

however, indicates that the CO2 emissions associated 

with the industrial carbon cycle are more than offset by 

the net CO2 uptake of the forest (Gower and Ahl 2006; 

Peckham et al. 2012).

Substituting wood products for nonwood products 

that require more energy to produce, such as steel and 

concrete, may reduce net C emissions (Hennigar et 

al. 2008). While some studies have calculated avoided 

emissions (Lippke et al. 2004, Perez-Garcia et al. 2005), 

obtaining such estimates is not straightforward and 

involves a number of assumptions and uncertainties 

(Miner and Perez-Garcia 2007). Even lacking precise 

data, it is nonetheless important to consider the 

potentially significant effects of product substitution 

because the estimated net reduction in emissions 

from wood substitution can be significant (Sathre and 

O’Connor 2008). Opportunities for substitution in the 

United States are largely in nonresidential buildings 

(McKeever et al. 2006, Upton et al. 2008) because most 

residential housing units are already built with wood.

Avoiding Loss of Forest Land

Loss of forests causes significant carbon emissions. 

Forest conversion not only releases CO2 but significantly 

decreases the capacity of a site to sequester additional 

carbon in the future (Ingerson 2007). Deforestation 

in the United States has recently affected about 

355,000 ha per year (Masek et al. 2011). Estimated 

carbon losses from deforestation in the United States 

are approximately 23 TgC per year based on analysis 

from1987 to 1997 (Birdsey and Lewis 2002) and equate 

to more than 10 percent of the net increase in carbon 

stocks on existing forest land. Zheng et al. (2011) 

estimated that for all of Wisconsin, loss of carbon stocks 

from deforestation was 1.3 TgC per year from 1992 to 

2001 based on a loss of forest area of about 16,000 ha 

annually. Generally, more than half of the forest area loss 

in the Lake States is to urban or suburban development 

and other developed uses (Birdsey and Lewis 2002).

Because the area of Wisconsin forests increased from 

1983 to 1996 and has been stable since then (Perry 

et al. 2008), deforestation may not be perceived as a 

significant problem in the state. However, these are net 

change statistics and do not clearly reflect losses of forest 

area and carbon stocks to deforestation, which have been 

more than offset by afforestation of marginal cropland. 

Over the long term, patterns of housing density change 

suggest that deforestation is both a significant issue 

and an opportunity for action to reduce emissions of 

greenhouse gases. However, reducing the loss of forest 

land to developed uses is challenging because of the 

strong leakage effect—it is very difficult to ensure that 

preserving one area from forest loss will not simply result 

in forest clearing in another area (Murray et al. 2004).

Northern Wisconsin is an amenity migration destination, 

so-called because its natural beauty and outdoor recreation 

opportunities attract residents (Stewart 2002). Amenity 

migrants are primarily retirees, sometimes converting 

their summer home to a year-round or two-season 

home. The social outcomes of migration are mixed; 

new residents are new property taxpayers in these rural 

communities, and often bring with them a stream of 

income originating outside the area that represents new 

economic activity for the rural economy. The addition of 

year-round residents helps to even out the seasonal cycles 

that characterize tourism-based economies, which in turn 

supports more year-round employment that can provide 

young workers the opportunity to stay in their home 

community (Johnson and Stewart 2007).

The most significant impact of amenity migration is 

that it creates demand for housing. Areas like northern 

Wisconsin have experienced decades of housing growth 

(Hammer et al 2004, Radeloff et al. 2005a). Housing 

development occurred first around lakes and in small 
31

towns then pushed into the forests and the countryside 

in recent decades when lakeshores were unavailable or 

unaffordable (Gonzalez-Abraham et al. 2007, Hammer et 

al. 2009). Both patterns of growth expand the wildlandurban interface (WUI) where homes are near or within 

forests and other areas with wildland vegetation (Radeloff 

et al. 2005b).

The impacts of housing are numerous. Trees are cut 

to make space for homes, removing biomass from the 

forest. The built surfaces that replace trees have higher 

reflectance and most are impermeable. Houses create 

openings and edge habitat, support predation and 

harassment of wildlife, and influence invasion of exotic 

plants into the forest. New roads accompany housing 

growth and have similar extensive and well-documented 

effects (Hawbaker et al. 2005, 2006). While few of these 

impacts are catastrophic or abrupt, they are persistent 

and widespread, raising concern about effects that 

accumulate over space and time.

The Land Cover Impacts of Housing Growth

To examine in detail when and where housing growth 

has occurred and is likely to occur in the future, we used 

Census housing data to estimate historic patterns and 

project future housing at a subcounty scale (see Hammer 

et al. 2004 and Hammer et al. 2009 for methods). These 

data show where housing growth was fastest between 

1940 and 2000 and where the most growth is expected 

in coming decades from 2000-2030 (Fig. 20). The high 

growth areas represent the neighborhoods (partial block 

groups or PBGs) with the top 25 percent of housing 

density increases. These high-growth PBGs contain 86 

percent of all the new housing units added between 1940 

and 2000 and 82 percent of the new units expected by 

2030. The map in Figure 21 shows the top quartiles of 

the two growth periods, with PBGs in the top growth 

Figure 20.—Regions of (a) fastest housing growth between 1940 and 2000, and (b) projected fastest housing growth 

between 2000-2030.

(a) (b)

Figure 21.—Changing patterns of housing growth, northern 

Wisconsin.
32

category during both periods shown in yellow. The 

housing growth rate was 244 percent between 1940 and 

2000, and we expect 128 percent more growth between 

2000 and 2030.

The carbon consequences of housing growth depend 

in part on what type of vegetation is affected by 

development. To assess this, we overlaid maps of historic 

and future high housing growth on the 2001 National 

Land Cover Database (NLCD) (Homer et al. 2007) and 

summarized the areas in these PBGs by land cover type. 

Note that housing development is unlikely to affect the 

entire PBG; this analysis simply indicates the land cover 

characteristics of the neighborhoods experiencing the 

most growth. It is also important to note that the land 

cover that was displaced by initial development (e.g., in 

1940 and subsequent decades) may have been different 

than the vegetation present now; without detailed and 

extensive land cover data from the 1940s, we cannot 

know the extent of differences. Figure 22 shows the land 

Figure 22.—Land cover proportion by housing growth category, northern Wisconsin.

open water

barren

urban-high intensity

urban-med intensity

urban-low intensity

urban-open space

cropland

pasture

herbaceous wetlands

woody wetlands

shrub/scrub

grassland

mixed forest

coniferous forest

deciduous forest

1940_only

2030_only

both_1940_and_2030

neither_1940_or_2030

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

cover types represented in the four groups of PBGs: 

those that grew from 1940-2000; areas forecast to grow 

between 2000 and 2030; areas in the top quartile of 

growth in both periods; and those with no fast growth 

in either period. All reflect the character of northern 

Wisconsin’s landscape, with forests and other wildlands 

covering over half the area.

Reducing the Projected Impacts of Housing 

Growth

The land use projections described here are based 

on an econometric model that simulates changes in 

land use as a function of the changing profitability of 

various land uses, and the costs of making a change 

in land use (Radeloff et al. 2012). Profitability, or 

net returns, is determined by the productivity of the 

land, its location, and the production costs associated 

with its use, including those needed to change its use. 

In other words, the model assumes that landowners 

make decisions about land use based on the relative 
33

profitability of different land uses. In this way, the model 

uses observations of previous landowner decisions to 

estimate the probabilities of future decisions in terms of 

the land use categories gaining or losing area. Both taxes 

and subsidies are policy instruments that aim to alter 

land use outcomes either by encouraging transition into 

a particular land use, or by discouraging transition out of 

a favored use. The scenarios tested here are examples of 

such policies.

Land use transition data was from the Natural Resources 

Inventory (NRI) for 1992 and 1997 (Natural Resources 

Conservation Service 2009) in which field surveys of a 

nationwide sample of plots on non-Federal lands from 

the 2 years were compared. Note that the NRI uses a 

different sampling scheme for all lands than the Forest 

Inventory and Analysis (FIA) program uses for forest 

lands, so in some regions there are differences in the 

resulting estimates of the area of forest. Land use was 

derived from the 2001 NLCD dataset (NLCD 2001) 

(Homer et al. 2007) aggregated to 1 ha pixels, and 

classifications were grouped into five categories: urban, 

forest, crops, range, and pasture. The Protected Areas 

Database (PAD) (U.S. Geological Survey 2013) was used 

to identify public lands, and these remain unchanged 

in future projections. Land capability, a measure of 

potential productivity, was based on the USDA National 

Resources Conservation Service Soil Survey Geographic 

Database (Natural Resources Conservation Service 

2011) classified into four nonirrigated classes. We tested 

three scenarios (two that retain forest, one that retains 

forest and rangeland) and compared them to a baseline 

scenario (Baseline). A forest tax and subsidy (Forest1) 

provided a $100/acre subsidy for land entering forest use, 

and a $100/acre tax for land leaving forest use. A forest 

tax only (Forest2) imposed a tax of $100/acre for land 

transitioning from forest use. Both Forest1 and Forest2

were afforestation scenarios intended to retain or move 

more land into forest use. Finally, the native scenario 

(Native) imposed a $100/acre tax for land leaving forest 

or rangeland. Its intent was to retain land in natural 

land uses (forest or range) versus intensively humandominated land uses, in an effort to preserve natural 

habitats.

Land use change is simulated stochastically for 50 years 

(Lewis and Plantinga 2007). Each NRI plot is assigned 

a transition probability based on observed changes in 

its land use, location, potential productivity, and other 

factors representing its profitability for each land use 

as well as costs of changing land use. Transitions into 

or out of land uses are simulated by comparing each 

plot’s transition probabilities for all possible land use 

changes with a random number between zero and 

one, to determine which will occur (e.g., given a 40 

percent probability of remaining forest and a 60 percent 

probability of becoming urban, will it become urban or 

not?). This simulation is iterated 500 times to account for 

the stochastic variability of outcomes in the real world, 

and results are aggregated to the subprovince level.

Thus we create a probability-based estimate of projected 

land use, one which is based on observed landowner 

behavior in response to market prices. The baseline 

scenario results show expected patterns of land use if 

the policy environment does not change. Comparing 

the four sets of scenario-specific projections illustrates 

the different outcomes predicted under various tax and 

subsidy policies.

In northern Wisconsin, the baseline and the alternative 

scenarios for future land use predict an increase in 

range, a major loss in pasture, a smaller loss in crops, 

and major gains in urban land use (Fig. 23) (Table 9). 

These outcomes are unsurprising in that the profitability 

of urban land use is so much higher than that of other 

land uses that the taxes and subsidies tested here do little 

to discourage urban conversions. The inverse is true of 

pasture and crop lands; both are lower-return land uses 

that are unsupported by the taxes and subsidies we tested. 

Relative to forests (or in the native scenario, forests plus 

range lands), the returns associated with pasture and crop 

uses are decreased by these policies, making transition 

to other land uses more likely. Forest land use increases 

only under the forest tax and subsidy scenario. In terms 

of the relative changes this model predicts, the increase 

in urban use and decrease in pasture use are most notable 

and consistent across all policy scenarios.
34

-60.00

-40.00

-20.00

0.00

20.00

40.00

60.00

80.00

100.00

Base_%Change

For1_%Change

For2_%Change

Native_%Change Crops Pasture

Forest Urban Range

Table 9.—Land use by scenario

NLCD 2001a Baseline 2051 Forest1 2051 Forest2 2051 Native 2051

Area (ha)

Crops 1,261,998 1,251,977 1,031,876 1,215,542 1,206,290

Pasture 601,102 379,364 341,071 368,504 346,351

Forest 3,839,139 3,750,043 4,028,903 3,787,738 3,776,719

Urban 393,062 668,155 683,534 711,742 707,987

Range 186,950 232,712 196,867 198,725 244,904

Raw area change (ha)

Crops 0 -10,021 -230,122 -46,456 -55,708

Pasture 0 -221,738 -260,031 -232,598 -254,751

Forest 0 -89,096 189,764 -51,401 -62,420

Urban 0 275,093 290,472 318,680 314,925

Range 0 45,762 9,917 11,775 57,954

Percent change in area

Crops 0 -0.79 -18.23 -3.68 -4.41

Pasture 0 -36.89 -43.26 -38.70 -42.38

Forest 0 -2.32 4.94 -1.34 -1.63

Urban 0 69.99 73.90 81.08 80.12

Range 0 24.48 5.30 6.30 31.00

a See text for a description of each scenario.

Figure 23.—Projected percentage change in future land use calculated as the percent change in the National Land 

Cover Database 2001 land area in northern Wisconsin, by future land use scenarios: a baseline projection (Base), 

a forest tax and subsidy scenario (For1), a forest tax only subsidy (For2), and a tax incentive to preserve native 

vegetation (Native).
35

Effectiveness of Policies to reduce Housing 

Growth

Our results show that while there will most likely be 

fairly substantial changes in land use, the differences 

in future outcomes under alternative policy scenarios 

were relatively small. Policy scenarios within a region 

like northern Wisconsin will be most effective when 

two conditions are met: (1) land prices across land use 

categories must be similar, and (2) land that can change 

uses must be available (i.e., unrestricted by public 

ownership, not too costly to convert, and of comparable 

value to target land uses).

If land uses are similar in profitability so that a small 

change in price can alter which category is the highest 

and best use for land, then taxes and subsidies set 

at modest levels can be effective. If there is a major 

difference in profitability such that one land use 

generates a much higher return on investment, taxes 

and subsidies must be set at higher levels to change the 

relative profitability across land uses. Urban compared 

to nonurban land uses illustrate a wide disparity in 

profitability. Urban land use generates so much higher 

returns that policy changes have to be dramatic to 

overcome the large price difference to the next highestreturn category.

Land availability matters, especially within a small 

region. If a policy increases the profitability associated 

with forested land, afforestation will only result if there 

is also land available that can support additional forest 

growth. In northern Wisconsin, the limited response 

to afforestation scenarios (Forest1 and Forest2) is due 

in part to the relative scarcity of privately owned land 

not already forested. It would be cost prohibitive to 

bring remaining private lands into productive forestry 

use. Hence the model shows little change in expected 

forest trends; urban land use will increase under all four 

scenarios, regardless of policy changes intended to favor 

forest land use.

Because of its dominance in the baseline and all of the 

tax and subsidy scenarios, it is worth examining urban 

land use more closely. The urban land use category is 

unique in that it describes the dominant use of the land, 

but is not precise about its cover, particularly in an area 

like northern Wisconsin where most urban development 

is construction of homes driven by amenity migrants 

wanting a summer retreat or retirement home in the 

woods. Homeowners usually retain trees for privacy and 

aesthetics.

Once land becomes urban, it does not change use. The 

NRI data do not record any transitions out of urban use. 

This is not surprising given the relative permanence of 

the built environment and the time period of these data 

from the early 1990s, when housing growth was reaching 

all-time high rates. The practice of removing housing 

from urban lands is still unusual, though occurring more 

widely after the housing bust of 2008. Hence projections 

under all scenarios show only growth in urban land use.

In summary, the effectiveness of policies intended to 

alter land use change outcomes by imposing taxes and 

subsidies depends on the relative profitability of land 

uses and the availability of land that can undergo land 

use change. While northern Wisconsin currently has 

extensive forested land, it is likely to have less private 

land in forest cover in the future, and taxes and subsidies 

at the moderate levels tested here can do little to retain 

or increase forest land cover. Therefore, we conclude 

that the policies considered here are not likely to have 

any significant effect on the expected continued loss of 

carbon in forests as development occurs, estimated at 1.3 

TgC per year for the whole State of Wisconsin.

Increasing Use of Wood for 

Bioenergy

Forest-based bioenergy is increasingly being examined 

as an option for greenhouse gas mitigation. Some 

studies show that in comparison to fossil fuels, biomass 

results in lower emissions when used to create heat, 

electricity, and transportation fuels (Keoleian and Volk 

2005, Malmsheimer et al. 2008, U.S. Environmental 

Protection Agency 2007). Other studies, however, are 

skeptical of the carbon benefits, citing uncertainties 

in the estimates and lack of full accounting for factors 

that may reduce the expected benefits. Woody biomass 
36

from sustainably managed forests is often considered 

“carbon neutral”, meaning that emissions are simply 

not counted. However, some net emissions may occur 

during the biomass production life cycle, and there 

could be some significant secondary effects such as offsite changes in land management (Cherubini et al. 2011, 

Wise et al. 2009). Bird et al. (2012) demonstrated that 

the current Intergovernmental Panel on Climate Change 

(IPCC) accounting approach provides an incentive to 

use biofuel but does not adequately account for the 

reduction of carbon stock on the land. Searchinger et 

al. (2009) estimate that diverting U.S. corn from food 

to biofuel production actually increased net emissions 

to the atmosphere due to leakage effects on land use 

change.

There is substantial woody biomass available in the 

United States. The U.S. Department of Energy (2011) 

estimates that if prices are high there could be a billion 

tons of dry biomass available from all sources, with 12 

percent coming from forests. The main sources of forest 

biomass in addition to what is currently used for biofuel 

are wood residues (logging residues and thinnings) and 

urban wood wastes followed by pulpwood and mill 

residues. Significant quantities of wood biomass are 

available in the Lake States (Goerndt et al. 2012, U.S. 

Department of Energy 2011). One important constraint 

on the carbon benefits of using wood for biofuel is that 

the emissions from transportation may offset some or all 

of the potential benefit if the distance to transport the 

biomass from the forest to the facility is too long.

The potential to use a forest-based resource for energy 

production and greenhouse gas mitigation is relevant to 

the northern region of Wisconsin, which is more than 

50 percent forested and contains more than two-thirds 

of the forests in the state (Wisconsin Department of 

Natural Resources 2002). Wisconsin already has a strong 

forest products industry, which employs nearly 100,000 

people statewide and generates $30.8 billion in forest 

products related industrial output annually (Mace et al. 

2004). Wood and wood waste is the most widely used 

renewable fuel in Wisconsin and makes up 4.6 percent 

of state energy consumption (Energy Information 

Administration 2009). This is higher than the national 

average of 2.5 percent of energy consumption from wood 

and wood waste.

Several factors are encouraging a greater use of wood for 

energy in the state, including concerns about mitigating 

greenhouse gases and climate change, increasing 

the amount of energy from domestic sources, and 

strengthening local and rural economies. Additionally, 

both national- and state-level policies are encouraging 

a greater use of renewable energy. Nationally, the 

Renewable Fuel Standard of the Energy Policy Act 

of 2005 and the Energy Independence and Security 

Act of 2007 mandated an increase in the amount of 

renewable transportation fuels through 2022, with 

significant increases in the amount of cellulosic ethanol 

produced nationally. Statewide, Wisconsin has enacted 

a Renewable Portfolio Standard which requires that by 

2015 utilities produce 10 percent of their electricity 

from renewable energy sources, with biomass being one 

possible source. The Governor’s Task Force on Global 

Warming (2008) recommended a number of additional 

policies to encourage utilization of biomass from forest 

and agricultural sources for the purpose of greenhouse 

gas mitigation.

While the regional forest products industry has declined 

in recent years due to global economic factors, growth in 

the bioenergy economy in Wisconsin could significantly 

increase demand for biomass (Becker et al. 2009). A 

recent analysis of available forest biomass for energy 

uses in Wisconsin estimated that 1.7 million dry tons 

per year of forest biomass could be available when no 

financial constraints are considered, and 1.5 million 

dry tons per year could be available at a price of $40 

per dry ton at roadside (Becker et al. 2009). The results 

of this analysis are similar to national-level estimates 

of biomass availability, which ranged from 0.6 to 2.3 

million dry tons per year in Wisconsin (Willyard and 

Tikalsky 2006). While the existing demand for biomass 

for energy production was estimated to be 579,000 

dry tons per year, a number of bioenergy projects 

have been announced that could nearly triple biomass 

demand statewide if all of the announced facilities are 

developed. The use of short-rotation woody crops, such 

as high-productivity plantations composed of aspen or 
37

willow species, could also provide a substantial source of 

biomass in the future.

Peckham and Gower (2012) used an ecosystem process 

model, Biome-BGC, combined with a collection of 

greenhouse gas life cycle inventory models to estimate 

availability of woody biomass feedstock from temperate 

forests in the Upper Midwest. Seven forest harvest 

scenarios in the biological ecosystem and three biofuel 

production scenarios in the industrial system were 

simulated for 50 years. The seven harvest scenarios 

produced a 3.5-fold difference in woody biofuel 

feedstock, ranging from 9 TgC for a reduced area harvest 

to 33 TgC for the increased area harvest scenario. The 

net system carbon balance for current management and 

product production was positive (i.e., carbon sink) and 

averaged 1.2 MgC per ha per year for the simulation 

period. The net system carbon balance was positive 

for most scenarios, but model results were sensitive 

to both the harvest scenario and the life cycle model 

emission factors for individual forest products. Net forest 

system carbon balance was significantly and negatively 

correlated (R2

 = 0.67) to biomass harvested, which 

illustrates the tradeoffs between increased carbon uptake 

by forests and utilization of woody biomass for biofuel 

feedstock.

The biomass described above is potentially available, 

meaning that it is present in the forest or at a facility 

and could theoretically be used for energy. However, 

the actual amount of biomass that is available will likely 

be less than what is potentially available. Constraints 

on availability include market conditions and prices, 

operational constraints, landowner willingness to 

harvest, and ecological considerations (Becker et al. 

2009). A set of biomass harvesting guidelines developed 

for Wisconsin to help forest owners and managers 

address concerns related to forest sustainability (Herrick 

et al. 2009) encourages retaining woody biomass on 

some sites to minimize environmental impacts from 

biomass harvesting. Biofuels are currently uneconomical 

compared with fossil fuels, in the absence of incentives. 

Rosberg and Miranowski (2011) concluded that 

cellulosic ethanol production is not sustainable without 

significant incentives or sustained high oil prices in the 

range of $135-$170 per barrel. Thus at present, some 

form of incentive payment would be needed to increase 

biofuel use in the absence of other policy measures. A 

greenhouse gas price for biofuel offsets could serve as 

an economic incentive, but it has been estimated that 

the price of CO2 would need to be at least $30 per 

ton for biofuel offsets to become competitive (U.S. 

Environmental Protection Agency 2005). Finally, 

as mentioned above, accounting for greenhouse gas 

emissions from using woody biomass is also controversial 

and could affect its implementation as a mitigation 

option.

Climate Change and Other Risk 

Factors

Many of the current stressors that act upon the forests of 

northern Wisconsin are expected to increase as a result 

of climate change. Swanston et al. (2011) synthesized 

the available information on projected climatic change 

in northern Wisconsin and potential effects on forest 

ecosystems in order to assess the vulnerability of these 

forests to climate change. Temperature increases and 

altered precipitation regimes are expected to lead to 

drier summer soil conditions which may make drought 

and associated disturbances (such as pest and disease 

outbreaks and fire) more prevalent. Climate change 

is also expected to increase the frequency and severity 

of extreme weather events, which may lead to greater 

occurrence of catastrophic wind and rain events 

(Campbell et al. 2009, Dale et al. 2001, Swanston et al. 

2011). Overall, shifting patterns among disturbances and 

stressors are expected to strongly influence ecosystem 

drivers, which will have follow-on effects on forest 

productivity and carbon sequestration.

Northern Wisconsin’s location at the intersection 

of three major biomes may make forests particularly 

susceptible to climatic changes. Suitable habitat for tree 

species is expected to shift northward as the climate 

changes. Many of the area’s dominant tree species are 

located at the southern extent of the species’ range, 

and declines in the suitability of habitat may lead to 

subsequent declines in the ability of those species to 

persist in the region over time. Suitable habitat may 
38

become available for other species, although there 

may be lags before new species and forests are able 

to establish. Changes in productivity are possible in 

response to changing atmospheric conditions and 

weather and interactions with disturbances. Ecosystems 

that are dominated by boreal species, have low-diversity, 

are less resilient to changing conditions, or feature 

species that are already at risk or in decline may be the 

most vulnerable, while species and ecosystems that 

have contrasting characteristics may be better able 

to accommodate change and maintain productivity 

(Swanston et al. 2011).
39

POTENTIAL PATHWAYS TO 

IMPLEMENTATION

To the extent that land management creates additional 

carbon storage either on the land or in products, there 

may be opportunities for engagement in several different 

markets or registries, some of which give credit for 

offsetting emissions (see Box 6). However, there are 

multiple prerequisites to market participation, and these 

opportunities may be further constrained by economic, 

legal/policy, or other logistical considerations or barriers. 

This section outlines universal forest carbon accounting 

issues then describes participation options within the 

current policy landscape, highlighting opportunities and 

constraints specific to three carbon protocols and the 

developing national policy landscape. Finally, public 

policy with respect to land management mandates and 

potential for participation in market opportunities is 

considered.

Forest Carbon Accounting Issues

A universal component to any forest-based carbon 

project—be it afforestation, reforestation, improved 

forest management, or avoided deforestation and 

degradation—is dealing with several forest carbon 

accounting issues. The way in which these issues are 

defined and treated within a project protocol affects 

protocol credibility, the project enrollment process, 

and ultimately helps to define the atmospheric/climate 

benefits of a project.

Some of the most significant accounting issues for 

market participation are:

•	 Additionality—a project is considered 

additional if it would not have occurred absent 

the added incentives provided by the carbon 

market. This applies to both the economic and 

biological aspects of additionality.

•	 Baselines—the expected sequestration (or 

emissions) that would occur without the project 

(i.e., the “business as usual” scenario).

•	 Leakage—a shift in emissions reductions from 

a project to a location (or sector) outside of 

the project boundary. In the case of forestry, 

preserving one tract of forest may put added 

development pressure on an adjacent tract.

•	 Permanence/Reversal Risk—the potential 

that additional sequestration achieved may be 

reversed either intentionally or unintentionally 

(through human actions, fire, insects, disease, or 

weather).

Perhaps the most significant analysis and estimation 

issue involves establishing the boundaries of analysis for 

mitigation options or projects, especially for comparing 

among different alternatives including comparison of 

an action with a baseline. For example, if a no harvest 

scenario was considered the baseline, then the estimated 

additional effect of multiple-rotation harvesting 

Box 6—What is an offset?

A greenhouse gas (GHG) offset is generated by the reduction, avoidance, or sequestration of GHG emissions 

from a specific project. Offsets are so named because they counteract or offset greenhouse gases that are 

emitted into the atmosphere; they are a compensating equivalent for reductions made at a specific source of 

emissions. Forest-based offsets are a specific kind of offset, and can take several forms:

•	 Afforestation—creation of new forests on land that has been unforested for a certain amount of 

time, typically ten or more years.

•	 Reforestation—restoration of forests on lands that were recently forested.

•	 Active/Sustainable/Improved Forest Management—activities that enhance carbon storage on a 

forested landscape or in wood products.

•	 Reduced Emissions from Deforestation and Degradation (REDD)—avoided emissions from 

protecting standing forest carbon stocks. This term is most often used to refer to international/tropical 

forest protection; in the United States, the relevant term is often “avoided conversion.”
40

compared with the baseline would be positive or negative 

depending on whether or not the substitution of wood 

products for other materials was included in the analysis 

(see Fig. 8). Including leakage or not is another example 

of a boundary issue. Searchinger et al. (2009) highlighted 

the significance of this issue with respect to bioenergy. 

They showed how allocating additional land to bioenergy 

production would have significant effects on carbon 

emissions from conversion of intact forests to bioenergy 

plantations, thus disproving the common assumption 

that using renewable bioenergy is “carbon neutral”. 

Indeed, the decision to include the secondary or tertiary 

effects of a project or action is among the most critical 

steps of an analysis.

It is important to note that any activity that increases 

carbon sequestration or storage by reducing harvest 

levels can result in increased harvesting elsewhere to 

compensate for the reduced forest products (another 

example of leakage). Similarly, the utilization of 

harvested materials, for biomass fuel or long-lived forest 

products, can affect the carbon storage benefit of forest 

management practices.

Markets and Registries

Within the past several years, various protocols 

and registries have emerged to define the “Over the 

Counter” (OTC) voluntary carbon market. In addition, 

California’s Assembly Bill 32 (AB32), the Global 

Warming Solutions Act of 2006, went into effect in 

2012 and currently allows for the creation of offsets from 

U.S.-based forest carbon projects. Here we highlight the 

two most popular protocols/registries in the voluntary 

markets, as well as California’s Compliance Offset 

Protocol, to provide some context for how a forest 

carbon project might be developed within the United 

States. Because the voluntary carbon market is still 

evolving, we have not included specifics of each entity’s 

methodologies here, but more information can be found 

on their Web sites.

•	 Verified Carbon Standard (VCS)—The 

Verified Carbon Standard (2013) is one of 

many standards available in the decentralized 

OTC market. The VCS is a third-party project 

standard that markets itself as providing a 

“robust quality assurance standard that projects 

can use to quantify greenhouse gas emissions and 

issue credits in voluntary markets.” The VCS 

provides both protocol standards and a registry 

system for generating and tracking carbon 

offsets. The VCS was developed by the Climate 

Group, the International Emissions Trading 

Association, and the World Economic Forum 

in 2005 and has released several versions of its 

offset project protocols. The VCS has established 

methodologies for a variety of agriculture, 

forestry, and land use-related projects involving 

improved forest management and avoided 

conversion. These methodologies, as well as all 

Clean Development Mechanism (CDM) and 

Climate Action Reserve (CAR) methodologies 

(except for CAR’s Forest Protocol) may be used 

to develop and register projects on the VCS 

registry. Once registered, eligible projects can 

generate Verified Carbon Units (VCUs) that can 

be transacted in the OTC marketplace.

•	 Climate Action Reserve (CAR)—The Climate 

Action Reserve (2013) is a voluntary project 

standard that evolved from the California 

Climate Action Registry (CCAR), a Californiaspecific market registry that was created by 

California law (AB) 32. The Climate Action 

Reserve project protocols are intended for 

national use, but are not accepted by all registries 

(e.g. VCS). CAR also provides its own registry 

system (the Climate Action Registry Reporting 

Tool—CARROT) to register Climate Reserve 

Tonnes (CRTs)—each representative of one 

metric ton of carbon dioxide equivalent—that 

are generated by projects. Forest-related projects 

may include reforestation, improved forest 

management, and avoided conversion.

•	 California’s Cap-and-Trade Program: 

Compliance Offset Protocol—California’s 

Global Warming Solutions Act of 2006, also 

known as Assembly Bill 32, required the creation 

of market mechanisms to reduce greenhouse 
41

gas emissions. California’s Air Resources Board 

(ARB) is responsible for implementing the bill 

and adopted a cap-and-trade program in 2010 

(California Environmental Protection Agency 

2013). The program had a soft launch in 2012, 

and mandatory compliance will be required 

in 2013. The ARB has specified four offset 

protocols, of which forestry is one, that can be 

used to generate compliance offset credits. This 

protocol allows for reforestation, improved forest 

management, and avoided conversion forestry 

projects from throughout the United States.

Public Policies and Regulations

In the past, the U.S. Forest Service has engaged in a 

variety of pilot carbon credit projects, at least one of 

which (Midewin Tallgrass Prairie Restoration Project) 

generated credits on the now-defunct Chicago Climate 

Exchange. However, leading standards in the voluntary 

market – including VCS and CAR – may preclude 

public land participation either explicitly or as a result 

of their multi-criteria additionality requirements, while 

requirements related to permanence/risk of reversal 

that are associated with these standards may conflict 

with legal issues related to placing encumbrances on 

carbon flowing from public lands. Also, because public 

lands in the Midwest and Northeast are typically better 

stocked than private lands, opportunities for generating 

additional emissions reductions or sequestration may be 

less significant.

In general, the state, local, and private forest lands that 

surround and border National Forests may be better 

able to engage in voluntary or other carbon markets. An 

emphasis on multiple uses and overall ecosystem integrity 

rather than carbon maximization guides planning on 

National Forest System lands. However, experimental 

or research areas within National Forests may be used 

to develop or demonstrate management practices that 

can yield additional carbon storage, or may be used as 

benchmark or reference sites to validate measurements, 

approaches, or models.

There is policy guidance for assessing carbon stocks on 

public lands. Executive Order 13514 requires periodic 

reporting of net carbon stock changes on forest land 

as related to land management techniques. Under the 

National Environmental Policy Act, supplemental draft 

guidance for Federal agencies asks whether the impacts 

on carbon sequestration and greenhouse gas emissions 

are being considered in land management decisions. 

The Forest Service Planning Rule of 2012 includes a 

provision to identify and evaluate existing information 

relevant to the plan area for a baseline assessment of 

carbon stocks. The USDA Strategic Plan for 2010-2015 

has an objective to lead efforts to mitigate and adapt to 

climate change. These regulations prompted the Forest 

Service to develop a climate change scorecard (U.S. 

Forest Service 2013c) comprised of 10 elements designed 

to gauge performance in a wide variety of climate change 

activities, including element 9 to: (1) develop a baseline 

assessment of C stocks, and (2) assess the influence of 

disturbance and management activities on C stocks. 

This scorecard element reflects the fact that both forest 

management and natural factors can influence CO2

removal rates or emissions from forests.
42

DISCUSSION AND CONCLUSIONS

This technical report provides an in-depth example of 

using currently available monitoring data and estimation 

methods to assess past and prospective carbon stocks for 

all lands in a forested region of the Eastern United States. 

Future analyses may also integrate anticipated effects 

on forests as a result of climate change to address the 

potential viability of mitigation options given expected 

changes in climate, impacts on forest ecosystems, and 

management responses for adaptation.

Private landowners hold 63 percent of the forest carbon 

stock in northern Wisconsin, followed by state and local 

ownership (24 percent), and National Forest ownership 

(14 percent). Over the last decade, carbon stocks of 

northern Wisconsin forests have been increasing by 

about one million metric tons per year, a little less than 

the previous decade. This reduction compared with 

the previous decade was likely caused by aging forests 

growing more slowly and, in other forested areas, 

continued or increasing use of wood for industrial 

products, which transfers a portion of carbon that is 

removed from the ecosystem to the wood product carbon 

pools. Since 1990, carbon in harvested wood products 

has been increasing by 0.5 million metric tons per year; 

thus in total, the net carbon sequestration in northern 

Wisconsin forests and wood products since 2000 was 

approximately 1.5 million metric tons per year.

Given the currently healthy status of forests of northern 

Wisconsin and a broad distribution among age classes, 

it is likely this level of carbon sequestration along 

with intensive use for industrial wood products can be 

sustained unless climate change or natural disturbances 

increase significantly. In the upper Midwest, harvest 

and fire have been the principal drivers of forest carbon 

dynamics over the last century with windstorms, insects, 

diseases, land use change, and other disturbances 

impacting natural systems as well. The region’s forests 

and carbon stocks have been sustained despite these 

agents causing tree damage and mortality to varying 

degrees. Many of the current stressors that act upon the 

forests of northern Wisconsin are expected to increase 

as a result of climate change, which poses a significant 

threat for sustained ecosystem production in this region.

There is potential to increase stocking on the land by 

allowing more of the forest area to reach older age classes. 

However, net ecosystem production declines as forests 

age, so even though such an increase could be substantial, 

it would be limited over the long term. Reduced harvest 

or lengthening of harvest rotations would increase 

carbon stocks but also cause a substantial loss of carbon 

being sequestered in wood products or providing 

bioenergy to substitute for fossil fuels, illustrating the 

tradeoffs between increased carbon uptake by forests 

and utilization of wood for wood products or bioenergy. 

There will most likely continue to be substantial changes 

in land use causing some loss of forest land, and the 

ability to change this trajectory under alternative policy 

scenarios appears to be relatively small.

Private entities have emerging opportunities to change 

land management practices to increase carbon stocks 

in forests and wood products, as well as to participate 

in markets for ecosystem services that include carbon 

sequestration. Public lands contain large stocks of carbon 

and function as carbon sinks, though are unlikely to 

participate in carbon markets or registries. Although 

specific carbon targets are not driving land management 

decisions, the effects of land management decisions 

on carbon stocks are beginning to be estimated and 

reported.

The estimates in this report rely heavily on data from 

the Nation’s Forest Inventory and Analysis (FIA) 

program. FIA forms a solid foundation of information, 

consistently available over time and for all of the United 

States. We augmented the information from FIA with 

remote-sensing based analyses and ecosystem models 

because many of the carbon pools of interest are difficult 

to observe directly and well-validated models will provide 

valuable information about future forest conditions 

under various management, disturbance, and policy 

scenarios. As models improve and newer data becomes 

available, this analysis can be easily updated. 
43

This project was a pilot study to assess how to improve 

the availability of quantitative carbon information and 

assessment for public and private lands. The methods 

used here can be adapted for use by other regions or 

forests to assess carbon stocks and effects of management 

on future carbon stocks. Methods will improve over time 

to provide more comprehensive and timely information 

that will support science-based policy and management 

decisions.

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Printed on Recycled Paper

Birdsey, Richard; Pan, Yude; Janowiak, Maria; Stewart, Susan; Hines, Sarah; Parker, 

Linda; Gower, Stith; Lichstein, Jeremy; McCullough, Kevin; Zhang, Fangmin; Chen, Jing; 

Mladenoff, David; Wayson, Craig; Swanston, Chris. 2014. Past and prospective carbon 

stocks in forests of northern Wisconsin: a report from the Chequamegon-Nicolet 

National Forest Climate Change Response Framework. Gen. Tech. Rep. NRS-127. 

Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research 

Station. 52 p.

This report assesses past and prospective carbon stocks for 4.5 million ha of forest land 

in northern Wisconsin, including a baseline assessment and analysis of the impacts of 

disturbance and management on carbon stocks. Carbon density (amount of carbon stock 

per unit area) averages 237 megagrams (Mg) per ha, with the National Forest lands having 

slightly higher carbon density than other ownership classes. Over the last decade, carbon 

stocks of northern Wisconsin forests have been increasing by about one teragram (Tg) per 

year or 0.22 megagrams per ha per year, with most of the increase in live biomass. Harvest, 

wind, and fire have been principal drivers of forest carbon dynamics over the last century. For 

all forest types in northern Wisconsin, there is potential to increase stocking on the land by 

allowing more of the forested area to reach older age classes or by increasing productivity. 

Opportunities to increase afforestation and reduce deforestation are limited, but the potential 

exists for utilizing biomass energy as a substitute for fossil fuels. There are several options 

for private landowners to participate in carbon markets or greenhouse gas registries and 

receive some credit for additional actions to reduce emissions or increase sequestration of 

carbon. The methods used here can be adapted for use by other regions or forests to assess 

carbon stocks and effects of management on future carbon stocks.

KEY WORDS: Carbon stocks, forest management, climate change, mitigation, inventory, 

monitoring

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