![](media/image1.png){width="0.6756944444444445in" height="0.75in"}North
American Carbon Program

**Linking Landscape-scale Carbon Monitoring with Forest Management**

**2007 Progress Report**

(NASA proposal \# CARBON/04-0225-0191)

**Contents**

1\. Project History page 3

2\. Project Description page 4

3\. Progress Report and Plans page 11

4\. Synthesis Activities page 14

5\. Northern Forest Soil Carbon page 15

6\. Proposed Future Work page 16

APPENDIX 1: Field Manual Summary page 17

APPENDIX 2: Data Management Plan page 19

APPENDIX 3: Land Classification page 24

APPENDIX 4: List of Products page 27

**Partial List of Participants in Landscape-scale Carbon Monitoring**

Richard Birdsey, USDA Forest Service

Marie-Louise Smith, USDA Forest Service

Harry Valentine, USDA Forest Service

Michael Ryan, USDA Forest Service

Randall Kolka, USDA Forest Service

Steven McNulty, USDA Forest Service

John Hom, USDA Forest Service

Ken Clark, USDA Forest Service

Yude Pan, USDA Forest Service

Linda Heath, USDA Forest Service

Dave Hollinger,USDA Forest Service

Coeli Hoover, USDA Forest Service

John Bradford, USDA Forest Service

Chris Potter, NASA (Ames Research Center)

Steven Klooster, California State University

Vanessa Genovese, California State University

Michael Lefsky, Colorado State University

Peter Weishampel, University of Minnesota

Scott Ollinger, University of New Hampshire

Michael Gavazzi, North Carolina State University

> **1. Project History**

In 2001 we initiated a series of research studies at NE and NC to
enhance capacity in carbon cycle science. We strengthened our scientific
capability to contribute to the strategic priorities of the USGCRP. We
targeted the CCSP Strategic Plan's "North American Carbon Program"
(NACP) as the highest priority for future research.

In 2002 we proposed to initiate an improved forest carbon observation
and monitoring system to augment existing capability at the Forest
Service network of experimental forests and at intensive research and
monitoring sites such as the LTER and AmeriFlux networks. Three related
activities comprise the improved observation system: (1) development and
deployment of improved field measurement techniques to enhance ongoing
monitoring activities, (2) implementation of an efficient and
cost-effective forest carbon monitoring network based on the Forest
Service experimental forest network, and (3) development of data
analysis and integration methods. Improved estimates of carbon stocks
and flows will provide a strong scientific foundation for development
and deployment of carbon sequestration technology to mitigate greenhouse
gas emissions. Anticipated products include key input data for
predictive models and scenario analysis, comprehensive and timely
analyses and reports that support an increasing interest in forest
carbon management, improved monitoring and estimation methods, and
customized studies of opportunities to protect and enhance America's
forest productivity. Enhancing observations at experimental forests has
additional benefits such as facilitating use of these sites for carbon
management research and demonstration projects, and providing the basis
for an "early warning" capability to detect the initial impacts of
climate change.

A national planning workshop was held in June 2003 to devise a
preliminary sampling strategy and determine the suite of appropriate
measurements. The objective was to develop a common suite of
measurements for application at condition sample sites (tier 3)
associated with the North American Carbon Program (NACP). At this
workshop we identified a list of variables, developed guidelines for
sample site selection, and discussed consistent sampling protocols for
the proposed "tier 3" sites. Two documents were developed: a generic
field manual of recommended field measurements for intensive forest
carbon monitoring, and a recommended sampling design for landscape-scale
monitoring.

Three pilot studies were begun in 2004 in different areas of the U.S. to
test methods and develop a consensus on specific protocols:

-   Northeast pilot at Bartlett, NH with emphasis on remote sensing,
    foliar chemistry, data analysis, and integration methods.
    Marie-Louise Smith (lead), Linda Heath, David Hollinger, Coeli
    Hoover, other FS scientists and University of New Hampshire.

-   North Central pilot at Marcell, MN with emphasis on CO2 and CH4
    fluxes and cooperation with Canada. Randy Kolka (lead), Christian
    Giardina, other FS scientists and University of Minnesota.

-   Rocky Mountain pilot at 3 alpine sites featuring methods for
    mountain terrain and cooperation with Mexico. Mike Ryan (lead),
    other FS scientists and University of Colorado.

**2. Project Description**

**OVERVIEW**

The USDA Global Climate Change Program has recently funded several pilot
projects to examine the potential of sites with intensive ground-based
measurements to aid in the development of landscape level carbon flux
estimates. The sites, termed "Tier 3" sites in the North American Carbon
Program, are intended to tie the spatially extensive, but coarsely
resolved, measurements made through remote sensing and forest inventory
to the spatially intensive and highly resolved measurements made at
AmeriFlux sites. To more fully develop the potential of connecting
intensive and extensive monitoring, and increase our ability to develop
accurate terrestrial carbon budgets for various forest management and
disturbance scenarios, we propose to expand upon this effort by
extending our ground-based measurements across additional levels of
forest management intensity, by adding Lidar measurements, by developing
ecosystem process models at two distinct scales, and by linking
landscape monitoring to carbon management at a scale relevant to land
managers.

Our proposal consists of the following three linked objectives: (1)
develop a consistent set of landscape-scale estimates of carbon stocks
and productivity (NPP, NEP) for stands at various stages of succession
following land management activities and natural disturbances, and
evaluate their uncertainty; (2) develop and validate two compatible
process models to simulate (a) effects of natural disturbances on carbon
stocks and productivity at the ecoregion scale, and (b) effects of
forest management activities on carbon stocks and productivity at the
forest stand scale; and (3) develop and evaluate two decision support
tools for estimating and reporting carbon stocks and changes in carbon
stocks for use by forest carbon managers. Achieving these objectives
will constitute a significant advance in availability of relevant and
useful ecosystem data for broad application by the scientific, policy,
and land management community, and lead the way toward implementation of
landscape monitoring on a much broader scale than currently possible.

A physiologically-based individual tree modeling component (AMORPHYS)
will facilitate using the field data to estimate NPP and NEP for managed
tree stands in various stages of development, and will provide the
ability for land managers to update or project stand-level inventories
of carbon stock for project evaluation and reporting to greenhouse gas
registries. We plan to strengthen our ability to map and characterize
landscapes through remote sensing technologies, primarily MODIS and
Lidar. Finally, this suite of landscape-scale data will be used to
parameterize decision support tools such as CASA-CQUEST for analysis of
carbon cycle impacts of operational forest management and to implement
carbon management programs.

The main products of this research include precise statistical estimates
and maps of carbon stocks and productivity for a variety of forest
landscape conditions; improved process models at ecoregion and stand
scales; and decision-support tools for land managers interested in
carbon management.

**Total budget for 3 years:** \$1,074,716

**Project period:** March 1, 2005 through December 31, 2008

**Landscape research and monitoring sites:**

-   Marcell Experimental Forest, Northern Minnesota

-   Bartlett Experimental Forest, New Hampshire

-   Fraser Experimental Forest, Colorado

-   Niwot Ridge LTER, Colorado

-   Glacier Lakes Ecosystem Experimental Site, Wyoming

-   The Parker Tract (Weyerhauser land), North Carolina

-   Silas Little Experimental Forest, New Jersey (added in 2006)

**"ROADMAP" LINKING DATA, MODELS, AND DECISION SUPPORT**

![](media/image1.pct)We envision a multi-component process to link data
collection and process models with decision support needs (Figure 1).
Our roadmap consists of 3 broad activities as illustrated in Figure 1:
(1) develop a consistent set of landscape-scale estimates of carbon
stocks and productivity (NPP, NEP) for stands at various stages of
succession following land management activities and natural
disturbances, and evaluate their uncertainty; (2) develop and validate
process models to simulate (a) effects of natural disturbances on carbon
stocks and productivity at the ecoregion scale, and (b) effects of
forest management activities on carbon stocks and productivity at the
forest stand scale; and (3) develop and evaluate decision support tools
for estimating and reporting carbon stocks and changes in carbon stocks
for use by forest carbon managers. Achieving these objectives will
constitute a significant advance in availability of relevant and useful
ecosystem data for broad application by the scientific, policy, and land
management community, and lead the way toward implementation of
landscape monitoring on a much broader scale than currently possible.

![](media/image2.pct){width="6.125in" height="4.604166666666667in"}

Six landscape monitoring sites began testing the field protocols in
April 2004; a sixth (New Jersey) began in 2005. The sites were selected
to represent a variety of managed and unmanaged forest conditions in
different physiographic regions, so that the protocols can be thoroughly
tested using a realistic range of applications. Figure 1 shows the
locations of the pilot test landscapes along with a representation of
existing and potential flux tower sites and other intensive monitoring
sites without flux towers. Except for the Southern site, these locations
are on public lands and therefore protected from unanticipated human
disturbances.

![](media/image3.pct){width="5.875694444444444in"
height="4.416666666666667in"}

A summary list of variables is shown in Table 1. Similar to intensive
monitoring, important variables that define the ecosystem "state" such
as vegetation type, foliage nitrogen concentration, and soil C:N ratio
will be measured along with automated measurements of key "driving
variables" such as light, temperature, and precipitation that control
the rate of ecosystem carbon uptake and loss. These state and driving
variables will be measured at different vegetation conditions within
landscapes, allowing estimates of NPP and NEP to be derived as closely
as possible from field measurements, supplemented by models of ecosystem
C exchange that are parameterized for each landscape monitoring
location.

> Table 1. Selected land measurement variables and scale of measurement.

+-----------------------+---------------+-------------+---------------+
| Example               | Extensive     | Landscape   | Intensive     |
|                       | Monitoring    | Monitoring  | Monitoring    |
| Variable              |               |             |               |
+-----------------------+---------------+-------------+---------------+
| Land cover            | X             | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Leaf area             | X             | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Disturbance           | X             | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Live biomass          | X             | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Litterfall            |               | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Soil CO~2~ flux       |               | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Methane flux          |               | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Dissolved Organic C   |               | X           | X             |
+-----------------------+---------------+-------------+---------------+
| Net Ecosystem         |               |             | X             |
| Exchange of CO~2~     |               |             |               |
+-----------------------+---------------+-------------+---------------+

**TASK LIST FROM ORIGINAL PROPOSAL**

**Task 1. Harmonize classifications and definitions** \[PI and CO-PIs\].

> **Task 1a.** Develop crosswalk between Forest Inventory (FIA) forest
> types, MODIS land classes, and CASA land classes.
>
> **Task 1b.** Agree on classification of natural disturbances and
> management activities.
>
> **Task 1c.** Ensure all components adhere to definitions of ecosystem
> carbon pools used in greenhouse gas registries.

**Task 2. Estimate and map carbon stocks and productivity for landscape
sites.**

> **Task 2a. Lidar.** Acquire Lidar imagery for the selected landscape
> monitoring sites -- target is 3x3 km square at each site. Produce maps
> of stand structure scaled up from biometric measurements; explore
> linkages with stand model; determine spatial and temporal
> characteristics of disturbances. \[Co-PI Lefsky\]
>
> **Task 2b. Biometrics.** Continue existing (pre-proposal) biometric
> measurements at the core 1x1 km square at each site. Add (this
> proposal) biometric measurements to parameterize stand model. Add
> (this proposal) biometric measurements at Lidar validation sites in
> the 3x3 km square. \[Co-PIs Kolka, Smith, Ryan, McNulty, Valentine\]
>
> **Task 2c. Data compilation.** Combine intensive data, landscape data,
> and remote sensing to characterize the temporal and spatial variation
> in carbon stocks and productivity estimates. Develop and apply
> consistent forest classifications based on FIA forest types and
> selected natural disturbance and management classes \[Co-PIs Kolka,
> Smith, Ryan, McNulty, Lefsky\]

**Task 3. Link models to multi-scale data sets.**

> **Task 3a. Ecoregion model (CASA).** Use intensive field site tower
> and biometric measurements, of carbon fluxes and storage pools, and
> lidar--based maps, to evaluate the accuracy of our satellite
> data-driven model simulations for NASA-CASA \[Co-PIs Potter, Klooster,
> Genovese\]
>
> **Task 3b. Stand model (AMORPHYS).** Parameterize a process-based
> individual tree model for updating and projecting estimates of carbon
> stocks and NPP, and evaluate the accuracy of estimates using data from
> landscape monitoring sites. \[Co-PI Valentine\]

**Task 4. Apply models and resource inventory data for carbon management
needs.**

> **Task 4a. CQUEST.** Validate model application for mapping natural
> disturbances, and estimating the magnitude of observed changes in
> carbon stocks attributable to natural disturbance events. \[Co-PIs
> Potter, Klooster, Genovese\]
>
> **Task 4b. Entity Greenhouse Gas Inventory.** Demonstrate how entities
> can combine output from models and data from resource inventories to
> estimate and report greenhouse gas inventories (forest sector) to
> State and National registries. \[PI Birdsey\]

**Task 5.** **Evaluate methods, data, and approach.**

> **Task 5a.** Sponsor independent statistical review of network design,
> landscape monitoring protocols, sampling methods and data. \[PI
> Birdsey -- subcontract\]
>
> **Task 5b.** Certify that estimates meet greenhouse gas registry
> requirements for content and precision. \[PI Birdsey\]

A preliminary timeline linked to the project tasks of this proposal, and
also showing the associated pilot study (funded separately), is shown in
the following table:

  ------------------ ---------------- --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- ---
  Fiscal Year:       2003                         2004               2005               2006               2007               2008           

  Quarter:           1                2   3   4   1      2   3   4   1      2   3   4   1      2   3   4   1      2   3   4   1      2   3   4

  *Task - pilot      Ongoing                                                                                                                 
  study:*            biometrics pilot                                                                                                        
                     study and                                                                                                               
                     implementation                                                                                                          

  Workshop                                x                                                                                                  

  Field manual                            x   x   x      x                      x   x                                                        

  Pilot study                                            x   x   x   x      x   x   x                                                        

  Implementation                                                                        x      x   x   x   x      x   x   x   x      x   x   x

  *Task -- this      Remote sensing,                                                                                                         
  proposal:*         modeling, and                                                                                                           
                     applications                                                                                                            

  1.Classification                                                   x      x   x   x                                                        

  2a. Lidar                                                          x      x   x   x   x      x   x   x   x      x   x   x                  

  2b. Biometrics                                                                x   x   x      x   x   x   x      x   x   x                  

  2c. Data comp.                                                                        x      x   x   x   x      x   x   x   x      x       

  3\. Model dev.                                                     x      x   x   x   x      x   x   x   x      x   x   x   x      x       

  4\. Applications                                                                                         x      x   x   x   x      x       

  5\. Evaluation                                                                                                              x      x   x   x
  ------------------ ---------------- --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- --- ------ --- --- ---

**3. Progress Report and Plans**

**Task 1. Harmonize classifications and definitions.** We have developed
a crosswalk between Forest Inventory (FIA) forest types, MODIS land
classes, and CASA land classes. We continue to address this issue
through cross-site comparison studies, and it is embedded into our data
management strategy which requires consistent definitions and units, and
compatible calculation procedures.

**Task 2. Estimate and map carbon stocks and productivity for landscape
sites.**

-   **Lidar imagery** acquired and processed for each site. Supporting
    biometric measurements made on schedule for each site, and analysis
    of data has begun. Integration of biometric data and Lidar imagery
    is underway.

-   **Frazer, Niwot Ridge, and Glacier Lakes** -- During FY06 we
    maintained the existing set of plots at 3 the Fraser Experimental
    Forest, the Glacier Lakes Ecosystem Experiment Station and the Niwot
    Ridge Ameriflux site. This maintenance included measurement of soil
    respiration twice during the winter and monthly during the summer,
    as well as collection of litterfall in spring and fall. We installed
    branchfall traps in summer 2006 in all plots.

-   **Marcell** -- We have collected all of our samples that required a
    one time sampling (e.g. soil and leaf samples). Some of those
    samples still need to processed and analyzed. We have begun to
    analyze and present our data as noted by the presentations listed
    below. We continue to take our periodic gas measurement fluxes on
    our plots. Our eddy covariance system starting collecting data on
    June 2, 2006 in an open (non-forested) peatland. We hope to compare
    several years with our data with data collected in the early 1990s
    for NEE and gaseous fluxes of carbon dioxide and methane.

-   **Bartlett** -- Coordinated Hyperion imaging spectrometer data
    collection at NJ NACP sites. Collection of images pending; field
    sampling deferred until successful image acquisition. Coordinated
    and carried out foliar chemistry sampling in conjunction with
    Hyperion image acquisition at Bartlett and Marcel Experimental
    Forests. Continued plot-level measurements of C stocks and fluxes at
    Bartlett Experimental forest. Five (5) manuscripts submitted or in
    press. Worked up and shared plot level productivity data with C.
    Potter for use in CASA modelling.

-   **Parker Tract** -- Data collection for most aboveground carbon
    pools have been completed through 2006, with plans to complete
    remaining data collection and analysis by May 2007. Two years of
    branchfall data should be analyzed by summer 2007, once we have
    obtained carbon estimates from samples collected in 2006 and 2007.
    Data collection for a more complete estimate of belowground carbon
    (60 + cm) will be conducted when the water table is lower.

-   **Silas Little** - We have made extensive measurements of forest
    structure and fuel loading at a total of ca. 150 sites thoughout
    upland forests in the Pine Barrens. In conjunction with LIDAR
    measurements, these data are used to estimate aboveground biomass
    and C pools across the Pinelands. We have started to collaborate
    with Dr. Yude Pan to parameterize PnET CN specifically for our 3
    eddy flux sites, in conjunction with Tier 3 activities. To date we
    have provided formatted meterological files and forest structure
    data.

**Task 3. Link models to multi-scale data sets.** Completed several
tasks with CASA: U.S. C sequestration inventory using MODIS; historical
reconstruction of U.S. C pool baselines from 20 years of AVHRR;
completed U.S. analysis of soil C changes from land use change. For the
stand model (AMORPHYS): Post-doc hired and has begun calibrating the
model for carbon change estimation at the field sites.

**Task 4. Apply models and resource inventory data for carbon management
needs.** Not scheduled until 2007.

**Task 5. Evaluate methods, data, and approach. Not scheduled until
2008.**

FY 2007 Plans

**Task 1. Harmonize classifications and definitions.** This activity
will continue as we develop cross-site synthesis products and a
prototype data base for landscape-scale carbon monitoring.

**Task 2. Estimate and map carbon stocks and productivity for landscape
sites.**

-   **Lidar imagery** will be processed and preliminary maps developed.
    Scheduled biometric measurements will be continued.

-   **Frazer, Niwot Ridge, and Glacier Lakes** - For FY07 we intend to
    continue maintaining the plots at these three sites and begin
    measuring some experiments that were installed previously. In summer
    2005, we installed both root ingrowth bags and litter decomposition
    bags. We plan to harvest and analyze the root ingrowth bags and one
    set of the litter bags in late summer 2007.

-   **Marcell** - Over the next year we will continue to sample/measure
    the necessary variables for the pilot project and will be spending
    much more time analyzing data, developing outputs and publications.
    Need to develop data compilation standards and data management plan.

-   **Bartlett** - Ongoing activities field activities during
    fall (2006) and winter (2007) including litterfall collection,
    re-measurement (mid-Oct.) of stem DBH on all subplots. Early FY2007
    will be devoted to summarization of FY2006 field measurements, and
    integration of field measurements with remote sensing (Hyperion,
    MODIS) and flux tower data.

-   **Parker Tract** -- will continue collecting data on the "tier-3"
    sampling grid; add measurements of tree height and dbh from a
    variety of stand structures within the Lidar footprint; and begin
    compiling data and comparing estimates with other sites.

-   **Silas Little** -- we will complete the collection of basic
    biometric data on the "tier 3" sampling grid; continue collecting
    data at the 3 tower sites; compile estimates of NPP, NEP, biomass,
    and age at multiple scales; and compare and analyze the results
    across spatial and temporal scales.

**Task 3.** **Link models to multi-scale data sets.** Generate CASA
model products for NPP annual carbon flux and above-ground carbon pools
at high spatial resolution for each study site. Integrate CERES
satellite products into CASA model results for ecosystem carbon budgets
and begin benchmarking. Compare top-down CASA model predictions with
bottom-up estimates on approximately 50 x 50 km2 areas around the field
sites.

**Task 4. Apply models and resource inventory data for carbon management
needs.**

We are beginning to integrate the intensive biometric data with the FIA
data sets surrounding each of the field sites. Once we have harmonized
the data (e.g., definitions, consistent estimates of NEP, accounting
standards) we will evaluate whether the estimates are rigorous enough to
comply with the standards set for greenhouse gas registries.

**Task 5. Evaluate methods, data, and approach.**

*Not scheduled until 2008.*

**4. Synthesis Activities**

**DRAFT Common Products Table (11/20/06)**

  ------------------- -------------------- -------------------------------
  *Short title*       ***Lead** and        *Brief description*
                      contributors\**      

  \(1\) Network       **Cole, Birdsey**,   Prepare metadata form for each
  database (*see 2006 all others           PI to fill out; design and
  progress report for                      populate a common summary
  details*)                                database; ensure archiving by
                                           each PI

  \(2\) Spatial       **Bradford**, others Characterize spatial
  variability and                          variability in stand structure,
  sampling design                          carbon stocks, and carbon
  (*outline                                fluxes; assess influence on
  available*)                              plot layout and sample size.

  \(3\) Importance of **Bradford**, others Quantify C in CWD and FF;
  CWD and forest                           determine if amount of C is
  floor in carbon                          related to components that can
  dynamics (*outline                       be measured remotely; determine
  available*)                              relationship with age.

  \(4\) Belowground   **Ryan**, others     Use C balance approach and
  carbon allocation                        compare to above-ground C
                                           across and within sites.

  \(5\) LIDAR         **Lefsky**, Hom,     Above-ground stand structure
  comparison with     others               maps and biomass estimates
  plot data                                (maps, statistics)

  \(6\) Biomass and   **Potter**, others   Compare each site with CASA
  soil respiration                         predictions
  comparison                               

  \(7\) Woody biomass ?                    Tree cores available at some
  increment                                sites. May need additional data
                                           collection to get recent years.
                                           Use AMORPHYS?? (see #12).

  \(8\) Accuracy      **Birdsey**, Potter, Prepare maps of stand age,
  assessment --       Van Tuyl, Pan,       biomass, NPP, and NEP for each
  compare top-down &  others               site at scales of 1 km^2^, 9
  bottom up estimates                      km^2^, and 2500 km^2^. Compare
                                           with CASA and other model
                                           predictions.

  \(9\) Comparison of **Hom**, others with 
  flux measurements   flux towers          

  \(10\) Use of       **Smith**, others    
  canopy N and LAI                         
  for scaling up                           

  \(11\)              **?**                
  Landscape-scale                          
  modeling: linking                        
  above- and                               
  below-ground                             
  processes                                

  \(12\) AMORPHYS     **Valentine,**       Calibrate model with site data
  stand dynamics      Ducey, Henning       and LIDAR; estimate
  model                                    above-ground C and compare with
                                           other estimates. Link to
                                           below-ground??? (see item 11)

  \(13\) Standardized **Potter,** others   For each site (3 x 3 km area
  land cover                               plus 50 x 50 km surrounding
  classifications                          area for selected maps): land
                                           use/land cover; land cover
                                           change; present vegetation
                                           composition; derived products
                                           (e.g., biomass, NPP, NEP,
                                           etc.).

  \(14\) Field manual **Hoover,** others   This is a methods manual for
                                           landscape monitoring sites,
                                           based on initial workshop and
                                           modified with field experience.

  \(15\) Do we need a **Birdsey**, others  These are final reports to NASA
  network of                               describing the effectiveness of
  landscape-scale                          the project for decision
  monitoring sites                         support.
  for decision                             
  support?                                 
  ------------------- -------------------- -------------------------------

\* "others" means that contributions will be made from someone at each
site

**5. NGCP Soil Carbon Initiative**

**NOTE: these are related studies under the NACP umbrella program. They
were begun in the summer of 2006. We will begin reporting progress in
the fall of 2007.**

**Objective:** To improve accuracy and precision of soil carbon
estimates, and estimates of the effects of management and disturbance on
soil carbon, for regional and project analyses in the Northeastern and
North Central U.S.

**Key questions:**

1\. What are regional estimates of soil C, especially with respect to
land use and land cover change?

2\. How do we improve regional C estimates?

3\. What are the driving factors (now and the future) at regional scales
(e.g., soil texture, landscape position, temperature, moisture, land
use, land cover, natural disturbance, vegetation cover, atmospheric
chemistry, management / utilization, invasive species).

4\. How will expected changes in driving variables (Temperature,
Moisture, Land-use, Natural disturbance, Vegetation cover, Atmospheric
chemistry, Management / Utilization) affect C storage, and our ability
to predict over these changes?.

**Selected Pre-proposals:**

**Modeling soil carbon at the landscape level by linking NRCS and FIA
data**

Charles Perry, Linda Heath, and Richard Pouyat (FS)

Jim Thompson (WVU)

**Models of Northern forest C dynamics at a range of spatial scales**

Paul Bolstad (U. MN)

R. Pouyat (FS)

R. Scheller (U. Wisc.)

M. Carreiro (U. Louisville)

**Management effects on forest soil carbon: literature synthesis,
meta-analysis, and assessment of implications for carbon management and
accounting**

Peter Curtis (Ohio State)

Alex Friend (FS)

Eric Vance (NCASI)

**Soil carbon storage and accumulation in forests of Western New England
and the Northern Great Lakes States**

Art Johnson and Fred Scatena (U. Penn)

Coeli Hoover, Erik Lilleskov, Yude Pan, and Richard Pouyat (FS)

Paul Bolstad (U. MN)

**6. Proposed Future Work**

Landscape-scale monitoring provides a critical element for evaluating
the causes and impacts of natural and human-induced disturbances (e.g.
fire, harvesting), climate variability and atmospheric chemistry on
forest carbon dynamics in the temperate and boreal forest zones of North
America. Two areas of research are fundamental to realize this
opportunity:

1.  Develop a forest-age distribution map that reflects the history of
    disturbances

2.  Link ecosystem process models with landscape disturbance models to
    quantify the relative effects of different factors (climate,
    atmospheric chemistry, and disturbance) on forest carbon cycling

The work involves integrating satellite data, inventory data, and other
statistical data sets across space and time; and strategic enhancement
of modeling capability so that the unique characteristics of different
regions can be effectively represented.

An example of a forest-age distribution map for Canada illustrates one
of the main products of this proposed work.

![](media/image4.wmf){width="4.992361111111111in"
height="3.7527777777777778in"}

**APPENDIX 1: Field Measurements for Forest Carbon Monitoring at
Research Sites (Manual in Review)**

I. Overview --

> A. Brief outline of North American Carbon Program

B. Objectives for land measurements and models

C. Heirarchical approach to biophysical measurements

D. Tier 3: Carbon process monitoring at medium-intensity sites

II\. Proposed Tier 3 Network

A. Goals and objectives of network

1\. Augment coverage of the land surface by Tier 4 sites

a\. Natural disturbances and management

b\. Edges/fragmented landscapes

c\. Mountain terrain

2\. Scaling from intensive sites to landscapes

3.Model parameterization or validation

B. Site Selection Criteria

1\. Need for comprehensive representation of North America's forests

2\. Stratification and other general design issues

3\. Choosing representative sites

4\. Linkages with sites from other tiers (scaling)

C. Choosing Sample Plot Locations

1\. Random sampling, grids, and clusters

2\. Tradeoffs : cost/precision; consistency/flexibility

3\. Statistical rigor : power and independence; avoiding bias

4\. Management and disturbance effects: chronosequences, experimental
plots

5\. Other factors (ownership, access, security, safety, georeferencing,
etc.)

D. Plot design considerations

1\. Need to facilitate cross comparisons w/other Tiers and sites,
Canada, Mexico

2\. Need consistency and flexibility -- use core + added design

3\. Statistical rigor

4\. Practicality and efficiency

III\. Overview of Recommended Variables

A. What guided choices

B. Recommendations for core, added

C. Tables for each variable group, listing variable, frequency, use, ?

IV\. Site Description --

A. Site history

1\. Management

2\. Natural disturbances

B. Stand ages, including appropriate indicator for mixed age stands

C. Other general stand description variables -- geology, etc.

V. Meteorological Variables --

A. Air temperature

B. Soil temperature

C. Precipitation

D. Relative humidity

E. Soil moisture (litter moisture?)

F. Photon Flux Density

G. Net radiation

VI\. Aboveground Pools and Properties-

A. Pools-

1\. Aboveground biomass

2\. Woody shrub biomass

3\. CWD by size class

4\. Forest floor mass

B. Properties --

1\. Vegetation height

2\. LAI

3\. % canopy cover

4\. Foliar N

5\. Litter C:N ratio?

VII\. Aboveground Fluxes --

A. Litterfall

B. Branchfall

C. Litter decomposition

D. Dead wood decomposition

1\. Decomposition rates

2\. Specific gravity -- by species or decay class? How to define decay
classes?

VIII\. Belowground Pools and Properties --

A. Pools

1\. Soil C stocks (including concentration, bulk density, and
calculation of Content)

2\. Coarse root biomass

a\. Total roots: live and dead

b\. Discussion of root allometry

c\. Explanation of why fine roots are not included

B. Properties

1\. Soil C:N ratio

2\. Soil C turnover rates (14C incubations)

IX\. Belowground Fluxes --

A. CO~2~

B. CH~4~

C. N~2~O

4\. DOC

5\. Suspended sediment

X. Synthesis

A. Use the variables to:

1\. Estimate ANPP

2\. Estimate NEP

3\. Validate remote sensing imagery

B. Integrating Tier 3 measurements with flux tower data

C. Management and disturbance effects

D. Cross comparing and integrating with Canada and Mexico

E. Adapting design, measurements, and protocols to other land cover
types: grasslands, etc.

**APPENDIX 2: Data Management Plan (DRAFT -- 02/23/06)**

[Purpose of Plan]{.underline}

This plan outlines a data management policy and plan for the landscape
monitoring component of the North American Carbon Program (NACP). The
main objectives are to (1) document data collection procedures and
QA/QC, (2) define standard data products, (3) state a policy for data
sharing both internally and externally, and (4) plan for data archiving.
This plan follows the general guidance on data management developed for
the NACP, and is consistent with the guidelines in the U.S. Government's
Data Quality Act. For additional information about data and information
management for the NACP, see the NACP Science Implementation Strategy
at: http://www.nacarbon.org/nacp/documents.html

[NACP Data Policy (from Science Implementation Strategy
document)]{.underline}

A data policy for NACP needs to be developed and approved by the
international partners based on data sharing and cooperation in support
of the scientific goals of NACP. The NACP data policy should treat the
following issues:

• Definition of the data that falls within the purview of the NACP data
policy (e.g., primary observations, monitoring data compiled by U.S.,
Canadian, and Mexican agencies, site characterization, remotely sensed
data, and ancillary data required by NACP);

• Timely release of data to NACP participants (e.g., no period of
restricted access, within 6 months of collection, or other period);

• Timely release of data and documentation to the public (e.g., within
0, 1, or 2 years of collection);

• Timely documentation of data products;

• Protecting the intellectual property rights of data originators

\- Data users should contact data originators before publishing data,

> \- Credit is given to data originators, through co-authorship,
> citation, or acknowledgement;

• Protecting the rights of students

> \- Some institutions require that key data cannot be published prior
> to submitting dissertation;

• Acknowledging NACP and its sponsors;

• Establishing a process and timeline for archiving key NACP data; and

• Resolving conflicts over data and the data policy.

[Data Collection]{.underline}

1.  **Field methods manual:** draft nearly complete, will be circulated
    to all investigators for review.

2.  **Remote sensing specifications:** for "standard" products such as
    Landsat-TM, refer to original documentation. For LIDAR and
    hyperspectral products specific to this study, investigators should
    provide documentation or links to documentation.

3.  **QA/QC plans** for each site: responsibility of each PI.

[Data Processing and Products]{.underline}

1.  **Standards for data processing** (how computations are done):
    synthesis products (cross-site comparisons) should include
    evaluation of computation methods to ensure consistency among sites.

2.  **Central vs. distributed processing.** All data processing is
    distributed to individual PIs unless separate agreement made to
    share processing.

3.  **Summary data base** of compiled field observations and basic
    calculations: For general use (internal and external), all PIs are
    expected to contribute data to a data base using a standard format
    and variable definitions. PIs will agree on these data base
    attributes. Example attached from Delaware River Basin study.

4.  **Remote sensing data sets:** responsible PIs will ensure that
    common remote sensing data products are available and that
    sufficient information about processing methods and data standards
    are documented.

5.  **"Value-added" data products** (e.g. estimates derived from
    models): if value-added data products are critical components of a
    research paper, then these data sets should be documented and
    archived in the same manner as primary data sets.

6.  **Meta-data requirements** following NACP protocols: specific
    requirements for NACP are not yet available. Meanwhile, follow the
    meta-data protocol used by the DAAC for biogeochemical dynamics:
    http://www.daac.ornl.gov/PI/pi_info.html

7.  **QA/QC plans** for each data processor including error analysis:
    responsibility of each PI.

[Data Sharing]{.underline}

1.  **Sharing preliminary data** among project scientists: open policy,
    data should be available for sharing as soon as QA/QC performed.

2.  **Making data publicly available:** follow guidelines for NACP (yet
    to be determined).

3.  **Protecting the rights** of project scientists and students: follow
    guidelines for NACP (yet to be determined). Meanwhile, use
    reasonable judgment to ensure the rights of everyone involved in
    this projects.

[Data Maintenance and Archiving]{.underline}

1.  **What data sets to archive:**

    a.  all primary data sets

    b.  secondary data sets used for cross-site studies (including the
        summary data base)

    c.  value-added data sets if basis for research or policy paper

2.  **When and where to store and archive data:** will follow NACP
    protocols, which are not yet available. A Task Force recommended a
    central data index linked to thematic data centers, but this is not
    yet implemented. Meanwhile, we will follow a model that involves
    central archiving of meta-data and selected key data sets that are
    common among most sites, with all other data sets managed in a
    distributed way.

3.  **Monitoring data use and citations:** until data is made publicly
    available, appropriate acknowledgement among PIs and students
    involved in this project is required common courtesy. For public
    release we will follow NACP guidelines when available.

[ACTION ITEMS (03/02/06)]{.underline}

1.  **Resources:** NGCP will make staff time available for initiating
    central data archive for this project. Interim location will be NGCP
    computing lab in Newtown Square; other options being explored
    according to FS and NCAP developments.

2.  **Incentives for good data management:**

    a.  Resources needed by anyone?

    b.  Will review data management status before allocating FY 2007
        funds.

3.  **Summary data base:** will develop draft and circulate for review
    (example from another project attached).

4.  **Field methods manual:** will be circulated for review.

5.  **Identify critical common data sets:** draft will be circulated for
    review (see next section)

**\
**

**Plan for Developing a Common Data Base for Landscape-scale Monitoring
in the NACP**

**Purpose:** to develop a common framework for organizing, archiving,
and retrieving the various kinds of measured biometric data and derived
variables at landscape-scale research sites of the NACP.

**Kinds of data:** data sets include both measured variables and derived
variables relevant to estimating carbon stocks and fluxes for above- and
below-ground ecosystem components. In-situ, remote sensing, and modeled
estimates are included. Data sets will include primary measurements
(such as tree dbh); carbon stock and flux estimates of different
ecosystem carbon pools (such as aboveground live biomass); and ancillary
variables (such as time since disturbance) that help explain
observations. Attached is a prioritized list of the kinds of relevant
variables compiled during a workshop held in 2002 to identify key
variables and data sets.

**Approach:** request each landscape monitoring site to compile a list
of key variables including name, description, and reporting units.
Attached is a second list of specific plot- and subplot-level variables
compiled by Mike Ryan and John Bradford to link their site-level data
with LIDAR data. This is a suggested format for the tables that should
be developed for each landscape site. These lists will be sent to Jason
Cole (<jcole@fs.fed.us>) who will sort and combine the lists into a
first draft of a framework. This draft will be circulated back out, and
then we will convene a conference call to discuss the progress and
determine if there needs to be a small workshop to finish the process.
We also need to consider data formats, data base requirements, where to
store the data, and when to make it available for general use.

EXAMPLE DATA BASE: Biometric Measurements Only

  ---------------- ------------------------------------------- -----------
  **Variable       **Description**                             **Units**
  Name**                                                       

  Site             Site: F, G, or N                            

  Plot             Plot: 1 - 16                                

  Subplt           Subplot within the plot (1-4)               

  pla_sum          Sum of leaf area from trees                 m2

  hght_mean        mean tree height                            m

  BincMgCha        mean biomass increment for 1994 - 2003      MgC/ha/yr

  ba_m2ha          basal area of all trees                     m2/ha

  baLP_m2ha        lodgepole basal area                        m2/ha

  baSF_m2ha        subalpine fir basal area                    m2/ha

  baES_m2ha        engelman spruce basal area                  m2/ha

  baTA_m2ha        aspen basal area                            m2/ha

  baLM_m2ha        limber pine basal area                      m2/ha

  treesha          tree density                                trees/ha

  agemean          mean age                                    years

  agemax           maximum age                                 years

  treeagl_MgCha    tree aboveground live biomass               MgC/ha

  treebgl_MgCha    tree belowground live biomass               MgC/ha

  treeagd_MgCha    tree aboveground dead biomass (standing     MgC/ha
                   snags)                                      

  treebgd_MgCha    tree belowground biomass (from snags and    MgC/ha
                   stumps)                                     

  pla_sum_sap      sum of sapling leaf area                    m2

  sapba_m2ha       sapling basal area                          m2/ha

  saps/ha          sapling density                             saps/ha

  sapbio_Mg/ha     sapling (2.5-10cm dbh) total biomass        MgC/ha

  sapagMgC/ha      sapling aboveground biomass                 MgC/ha

  sapbgMgC/ha      sapling belowground biomass                 MgC/ha

  pla_sum_seed     sum of seedling leaf area                   m2

  seeds/ha         seedling density                            seeds/ha

  seedbio_Mg/ha    seedling total biomass                      MgC/ha

  seedagMgC/ha     seedling aboveground biomass                MgC/ha

  seedbgMgC/ha     seedling belowground biomass                MgC/ha

  stumpnum         number of stumps/plot                       sumpts

  stump_MgC/ha     aboveground stump biomass                   MgC/ha

  cwd_MgCha        coarse woody debris biomass                 MgC/ha

  ffMgCha          forest floor biomass                        MgC/ha

  soilcmassMgCha   soil carbon (top 10 cm)                     MgC/ha

  LF_MgChayr       litterfall (only 1 year)                    MgC/ha/yr

  veg_MgCha        understory productivity                     MgC/ha/yr
  ---------------- ------------------------------------------- -----------

**APPENDIX 3: Land Classification**

# **PRESENT LAND USE/LAND COVER**

Current land use/cover should be recorded or mapped for each area using
a national inventory protocol such as FIA or NRI, or a standard land
cover classification such as NLCD 2001 (specify which classification
schemes are used). Recommended major land use/land cover categories and
sub-categories include:

Water

Developed:

Residential

Industrial

Forest

Cropland

Grass/field

Wetland

Advanced land-use features that indicate management intensity may
include:

Agricultural management:

no-till

> fertilizer use
>
> irrigation
>
> herbicides

Forest management:

clearcut

partial cutting

thinning

site preparation

regeneration

fuels management

fertilization

Hydrologic management:

dams

reservoirs

canals

Suggested web sites:

FIA <http://fia.fs.fed.us/>

NRI http://www.nrcs.usda.gov/technical/NRI/

USGS Eros Data Center http://edc.usgs.gov/products/landcover.html

**LAND COVER CHANGE**

All major historical land use changes and disturbances should be
discussed in terms of their geographical distribution, the size of the
area occupied by each, and the impact on land cover. The dates of the
changes or disturbances should be recorded.

Basic land cover change features should be characterized for all study
sites, withprecise dating of events if possible.

Natural disturbances:

wildfire

drought

flood

weather damage (ice, wind)

pest outbreaks

Human disturbances:

fire

deforestation and/or afforestation

timber harvest

stand treatments (see "forest management" above)

grazing

agricultural treatments (see "agricultural management" above)

introduced species

Advanced land cover change features that may be characterized include
tree ring chronologies, carbon dating, and isotope characterization.

Suggested web sites:

http://landcover.usgs.gov/landcovertrends.asp

# **PRESENT VEGETATION COMPOSITION**

A good characterization of vegetation composition is required for using
site data in models, and for extrapolating results from individual sites
or landscapes to larger or similar geographic areas. Major species
and/or species groups, using a common classification system or systems,
should be recorded in terms of geographical distribution and the size of
the area occupied by each. In this section we present a few of the more
common vegetation classification systems. Sometime it is necessary to
have the site classified according to more than one system, or to at
least be aware of how to crosswalk from one system to another.

Forest Inventory and Analysis (FIA) -- the FIA program uses a forest
type classification that is relevant to land management. The system is
based on a set of rules that determine

forest type from the dominance or co-dominance of different tree
species. There is a two-level hierarchy comprised of forest type groups
and forest types. Details are available in the FIA field manual (see web
site below).

Food and Agriculture Organization (FAO) -- the United Nations FAO has
developed a classification system that is commonly used for the world's
forests, and is the basis for reporting global forest statistics in
periodic Forest Resource Assessments. The FAO classification system is
primarily designed to determine how "natural" forests are by determining
whether trees are planted or natural, and if natural, whether the forest
is "primary" (or mostly undisturbed) or "secondary" (recovering from
disturbance).

National Land Cover Data (NLCD) -- National land cover data is derived
from Landsat satellite imagery and is classified by vegetation types
that are more detailed than the basic land cover classes. Since this is
a common product for mapping vegetation, it may be necessary to classify
sites according to this scheme.

International Geosphere/Biosphere Program (IGBP) -- MODIS and other
satellite data products use the IGBP vegetation classification system,
which includes 11 vegetation classes.

Advanced vegetation cover features that may be characterized include
detailed descriptions of species including understory vegetation, which
may also be used to construct biodiversity indices.

Suggested web sites:

FIA <http://fia.fs.fed.us/>

FAO <http://www.fao.org/forestry/index.jsp>

NLCD <http://landcover.usgs.gov/index.asp>

IGBP http://edcdaac.usgs.gov/main.asp

Table 1 Forest cover types, regrouped forest types, and MODIS
classifications (from Pan et al. 2006)

  -------------------- ----------- -------------- ---------- ------------ -----------
  Forest Cover Types   Percent of  Regrouped      Percent of MODIS Class  Percent of
                       forest area Types for      forest                  forest area
                                   PnET-CN        area                    

  Maple-beech-birch    29          N. Hardwoods   29         Deciduous    82

  Elm-Ash -cottonwood  \*                                                 

  Oak-Hickory          53          Oak-hickory    53                      

  Spruce-fir           1           Spruce-fir     1          Coniferous   9

  White-red-jack pine  3           Pine Forests   8                       

  Loblolly-shortleaf   5                                                  
  pine                                                                    

  Long-leaf-Slash Pine \*                                                 

  Oak-Pine             8           Oak-Pine       9          Mixed        9

  Oak-gum-cypress      1                                                  
  -------------------- ----------- -------------- ---------- ------------ -----------

\* Less than 1 percent

**APPENDIX 4: LIST OF PRODUCTS**

[Publications]{.underline}

Birdsey, R., R. Kolka, M.L. Smith, M. Ryan, D. Hollinger, L. Heath, and
C. Hoover. 2004. Landscape carbon monitoring and analysis at the
experimental forest network. Proceedings of the 3rd Annual Conference on
Carbon Sequestration. (electronic only) Alexandria, VA May 2004

Birdsey, Richard; Pregitzer, Kurt; Lucier, Alan. 2006. Forest carbon
management in the United States 1600-2100. Journal of Environmental
Quality. 35: 1461-1469.

Birdsey, Richard A. 2006. Carbon accounting rules and guidelines for the
United States forest sector. Journal of Environmental Quality. 35:
1518-1524.

DeForest, J., G. Sun, A. Noormets, J. Chen, S. McNulty, M. Gavazzi, D.
Amatya, R. Skaggs. 2006. Carbon and water fluxes in a drained coastal
clearcut and a pine plantation in eastern North Carolina. In: Williams,
Thomas, eds. Hydrology and Management of Forested Wetlands: Proceedings
of the International Conference, St. Joseph, MI: ASABE: 587-597.

Ollinger, Scott V.; Smith, Mary-Louise. 2005. Net primary production and
canopy nitrogen in a temperate forest landscape: an analysis using
imaging spectroscopy, modeling and field data. Ecosystems. 8: 760-778.

Pan, Yude; Birdsey, Richard; Hom, John; McCullough, Kevin; Clark,
Kenneth. 2005. Improved estimates of net primary productivity from MODIS
satellite data at regional and local scales. Ecological Applications.
16(1): 125-132.

Ryan MG and BE Law. 2005. Interpreting, measuring and modeling soil
respiration. Biogeochemistry 73: 3-27

Potter, C., S. Klooster, S. Hiatt, M. Fladeland, V. Genovese, and P.
Gross, 2006,

Satellite-derived estimates of potential carbon sequestration though
afforestation of

agricultural lands in the United States, Climatic Change (In Press).

Potter, C., S. Klooster, R. Nemani, V. Genovese, S. Hiatt, M. Fladeland
and P. Gross, 2006, Estimating Carbon Budgets for U.S. Ecosystems, Eos
Transactions American Geophysical Union, 87(8), 85-96.

[Presentations, posters]{.underline}

Birdsey, R., M. Ryan, M.L. Smith, R. Kolka, S. McNulty, J. Hom, C.
Potter, M. Lefsky, J. Bradford, and P. Weishampel. 2006. Linking
landscape-scale carbon monitoring with forest management. NASA Carbon
Cycle and Ecosystems Joint Workshop on Biodiversity, Terrestrial Ecology
and Related Applied Science. Adelphi, MD.

Birdsey, Richard A. Biometric measurement pilot study for North American
Carbon Program. AmeriFlux Annual Meeting, Boulder, CO. Oct. 19, 2005.

Bolstad, P.V., R. Anderson, B.D. Cook, J. Tang, N.Z. Saliendra, P.
Weishampel, R.K. Kolka, J.G. Martin, and K.J. Davis. 2006. Landscape
estimates of carbon pools and fluxes via LIDAR and high resolution
spectral data. American Geophysical Union Annual Conference, San
Franciso, CA.

Bradford, John and Mike Ryan. 2005. Generating large-scale forest NEP
estimates: Can we escape site history? Oral Presentation, Ecological
Society of America Annual Meeting. Montreal, QC. August 2005

Bradford, J. B., Schimel D. S., Monson, R., Sacks, B., Ryan, M.G., and
L.E Scott-Denton. (2006) Biometric versus eddy covariance estimates of
net ecosystem carbon balance: a comparison in the subalpine Rocky
Mountains. Poster Presentation: Integrated Land-Ecosystem-Atmosphere
Processes meeting, Boulder, CO.

Bradford, J.B. (2005) Biometric ecosystem production measurements for
comparison with eddy covariance measurements. Oral Presentation:
Ameriflux annual meeting, Boulder, CO.

Bradford, J.B. and M. G. Ryan (2006) Forest Carbon Dynamics:
consequences of spatial variability for landscape-scale estimation. Oral
Presentation: Ecological Society of America Meetings, Memphis, TN.

Gavazzi, M., S. McNulty, G. Sun, J. Chen, A. Noormets, J. DeForest, S.
Strickland, J. Boggs. 2006. Comparing carbon, water and energy fluxes in
two coastal plain loblolly pine plantations. Critical Processes and
Properties Regulating Carbon Cycling in Southern Forests, Asheville, NC.

Kolka, R. and D. Olson. 2006. Introduction to the Marcell eddy
covariance system. USCCC Meeting, Beijing, China.

Kolka, R.K. and P. Weishampel. 2006. Tier 3 measurements in the
upscaling approach at the Chequamegon Ecosystem-Atmosphere Study
(ChEAS). Annual ChEAS Meeting. Woodruff, WI.

McNulty, Steve. Estimating evapotransiration in threee contrasting
forest ecosystems using eddy covariance, sapflow and soil water balance
methods. American Geophysical Union Fall Meeting. December 5-9, 2005,
San Fransisco, CA

McNulty, Steve. Water cycles in a drained coastal clearcut and pine
plantation in coastal North Carolina. ASABE International Conference on
Hydrology and Management of Forested Wetlands. April 8-12, 2006, New
Bern, NC

Christopher Potter and Matthew Fladeland, NASA Ames Research Center;
Steven Klooster, Vanessa Genovese, Peggy Gross, Seth Hiatt, California
State University. AGU 2005 and updated for NASA ecosystems and carbon
meeting 2006: Terrestrial Carbon Sinks for the United States Predicted
from MODIS Satellite Data and Ecosystem Modeling

Potter, Chris. Past Impacts and Future Scenarios of Climate on Ecosystem
Carbon Balance for the Western United States. Invited Poster Presented
at the Second Annual Conference on Climate Change in the Western States,
Sacramento, CA, September, 2005.

[Saliendra](http://apps.isiknowledge.com/WoS/CIW.cgi?SID=E2mE7ci91Lc9FPbP1J9&Func=OneClickSearch&field=AU&val=Richardson+AD&curr_doc=5/9&Form=FullRecordPage&doc=5/9)
N.Z., M.E. Kubiske, R. Teclaw, R. Kolka, K. Davis, K. Cherrey, A. Desai,
D. Ricciuto, B. Cook, F.A. Heinsch , and P. Bolstad. 2006. Testing the
flux tower upscaling hypothesis in a complex landscape in northern
Wisconsin. Annual AmeriFlux Meeting, Boulder, CO.

Valentine, HT and Annikki Makela. Bridging process-based and empirical
approaches to modeling tree growth. Colloquium and workshop on modeling
wood quality. Montreal May 2005

Valentine, HT and Annikki Makela. Cross-sectional area growth versus
crown length: deductions from theory. Meeting of the Northeastern
Mensurationists' Organization. Freeport, Maine. Nov. 2005

Weishampel, P, J. King, and R. Kolka. 2006. Scaling soil CO~2~ and CH~4~
fluxes in heterogeneous northern forest landscapes. NASA Carbon Cycle
and Ecosystems Joint Workshop on Biodiversity, Terrestrial Ecology and
Related Applied Science. Adelphi, MD.

Weishampel, P, J. King, and R. Kolka. 2006. Methane fluxes in forests
and wetlands of northern Wisconsin and Minnesota. American Geophysical
Union Annual Conference, San Francisco, CA