USAID-CIFOR-ICRAF Project Assessing the Implications of Climate Change for USAID Forestry Programs...

USAID-CIFOR-ICRAF ProjectAssessing the Implications of Climate Change for USAID Forestry Programs (2009)

Carbon accounting: Monitoring

Topic 4, Section F

Learning outcomes

In this presentation you will

learn about various

monitoring methods for

carbon accounting.

Topic 4, Section F, slide 2 of 29

Outline1. USAID project monitoring for performance

• Data needed for Forest Carbon Calculator

2. Detailed project monitoring• Monitoring plans• Sampling• Collecting and analyzing data

3. General concepts and guidance

4. National monitoring systems• Forest carbon inventory of India• Australian national carbon accounting system• US Forest Service carbon inventory


USAID’s standard climate change indicator

USAID’s standard climate change CO2 indicator:

“Quantity of greenhouse gas emissions, measured in metric tons of CO2 equivalent, reduced or sequestered as a result of USG assistance in natural resources management, agriculture, and/or biodiversity sectors.”

This indicator can be used at the project level with USAID’s Forest Carbon Calculator

If the project is to influence national level policy, the USAID indicator, will be a policy indicator, not CO2

If USAID engages in large-scale attempts to change a country’s emissions trajectory, then national GHG inventory done with host government provides CO2 impact measures


Data needed for project monitoring with USAID’s Forest Carbon Calculator

Locations of projects according to administrative unit, such as state or district

How many hectares are affected by the activity, such as area of forest protected, reforested, regenerated, or under agroforestry

Measure of project effectiveness: • % reduction in deforestation, • % of trees that survive at end of the year, • % of logging stopped or % of logging that is being done with

reduced impact

Documentation of how you estimated project effectiveness measures


Detailed project monitoring

More site-specific monitoring may be desired for project performance or required for carbon finance

Requires a monitoring plan and approach Monitoring that seeks to measure actual carbon

accumulation in soils may be outside the timescale of USAID funding, so measures of activity adoption may be more practical


Manuals and guidebooks

MacDicken (1997)

IPCC GPG (2003)

Pearson et al. (2005)

GOFC-GOLD (2008)


What to monitor?


How to proceed?Define monitoring boundaries (national, project, etc.)

Stratify the area to be monitored

Decide which carbon pools to measure (5 pools)

Determine type, number and location of measurement plots

Determine measurement/monitoring frequency


Measuring and monitoring plan for a project-based activity

Source: IPCC GPG 2003:


General approach to monitoring Monitoring carried out through sampling and using existing forest

inventory and other data sources

Monitoring should produce estimates of carbon stocks that are both precise and accurate

These will affect the monitoring costs

It is important to design a monitoring system (using stratification, etc.) that produces the desired precision and accuracy with minimal costs

(A) Accurate but not precise

(B) Precise but not accurate

(C) Precise and accurate


Sample size

Calculate the sample size n (number of plots) – based on pre-sampling

Where

• n = number of plots to be measured

• Syx = estimation error

• t = Studet t value

• S = variance

• X = mean value


Stratification

Allows researchers obtain precise estimates at a lower cost than without stratification

Steps:

• Divide heterogeneous population into homogenous groups

• Apply monitoring (sampling and calculations) to each strata and compile results at the end


Field plotsThis schematic diagram represents a three-nest sampling plot in both circular and rectangular forms

Source: Pearson et al. 2006


Frequency of monitoring

For carbon accumulation, the frequency of measurements should be defined in accordance with the rate of change of the carbon stock• Forest processes are generally measured over periods of

five-year intervals

• Carbon pools that respond more slowly, such as soil, are measured every 10 or even every 20 years

See the graph in the next slide

Source: IPCC GPG 2003; Pearson et al. 2005


Detecting the difference Two means (time 1 and time 2) RME = Reliable Minimum Estimate When number of observations (plots) increases -> variability of the

data (standard deviation) decreases

A data set with a mean of 50 (shown in blue) and a standard deviation (σ) of 20.

Standard deviation explained


Source: IPCC GPG 2003

RME 1 is smaller than RME 2

Tons/cell = (tons/ha)*0.0001*(30^2)

Noel Kempff Project (Bolivia): 625 permanent sample plots were measured in 640,000 ha

Vegetation classes Tons of carbon/cell


Noel Kempff (Bolivia) carbon inventoryResults based on 625 permanent plots

Source: Brown et al., 2000


Leakage (displacement)

Carbon leakage takes place when interventions to reduce emissions in one geographical area lead to an increase in emissions in another area• Example: if curbing agricultural encroachment into forests in one

region results in conversion of forests to agriculture in another region

In the context of REDD, leakage is also referred to as ‘emissions displacement’

In the Noel Kempff project:• Leakage for the stop-logging component was thoroughly screened

and found to be in the 2 to 42% range• Deforestation in local communities actually increased initially, which

was hoped to be transitory, related to the creation of new land-use systems


Quality assurance and quality control

QA/QC elements: Reliable field measurements

• Re-check measurements with independent crew (10 to 20% of plots re-measured)

Verify laboratory procedures

• Re-analyse 10 to 20% of samples

Verify data entry and analysis techniques

• Check 10 to15% of the data entries

Adequate data maintenance and archiving

• Make sure that data (including computer files, imagery etc.) is adequately achieved


National forest carbon inventory of India

Stratification• The country is stratified into 14

physiographic zones• In each strata, districts are considered

first sampling units, 10% of districts are being inventoried every year

Field measurements• National grid and sub-grids are marked as the center of the plot at which

a square sample plot of 0.1 hectare is laid out to conduct field inventory of trees

• Soil, litter, and humus samples are collected in sub-plots

Carbon calculation• Based on stem volumes obtained in forest inventory• Using expansion factors for conversion from volumes to carbon


Australian National Carbon Accounting System (NCAS) Components:

Remotely sensed land cover change (including mapped information from thousands of satellite images)

Land-use and management data

Climate and soil data Greenhouse gas accounting

tools Spatial and temporal

ecosystem modeling


US Forest Service Carbon Inventory

USDA Forest Inventory and Analysis (FIA) inventory data coupled with a modeling approach

Data from many field plots, collected by FIA beginning in 1950s

Area data from remote sensing

Where FIA data are limited models, such as equations to estimate non-tree carbon are used

System (model) can track carbon through harvested wood products


Large-scale field inventories include remote sensing for area estimation

Sample points are

located systematically

over the effective area

and land cover is

determined at the point


USDA Forest Inventory Program Evolution

In the recent past, FIA periodically (5-14 years) measured all plots in a state in a 1-2 year timeframe

FIA recently adopted annual inventory, with a subset of plots measured throughout the state each year (5-7 years)

Soil and litter layer carbon measured on subset of plots in new system


US National GHG reporting to UNFCCC Annual Greenhouse Gas Emissions and Sinks Inventories

(1990-present) US Environmental Protection Agency


Discussion

How should a USAID project set up its monitoring? What fits within its timescale and funding?

Is the accuracy of good measures worth the cost?


References Brown, S. 1997 Estimating biomass and biomass change of tropical forests: a primer. FAO Forestry

Paper no. 134. Brown, S. 2002 Measuring carbon in forests: current status and futurechallenges Environ. Pollut.

116:363-72. Brown, S. and Gaston, G. 1995 Use of forest inventories and geographic information systems to

estimate biomass density of tropical forests: applications to tropical Africa. Environ. Monit. Assess. 38:157-68.

Brown, S., Hall, M., Andrasko, K., Ruiz, F., Marzoli, W., Guerrero, G., Masera, O., Dushku, A., de Jong, B. and Cornell, J. 2007 Baselines for land-use change in the tropics: application to avoided deforestation projects. Mitigation and Adaptation Strategies for Global Change 12:1001-26.

Brown, S., Burnham, M., Delaney, M., Vaca, R., Powell, M. and Moreno, A. 2000. Issues and challenges for forest-based carbon offset projects: A case study of the Noel Kempff climate action project in Bolivia. Mitigation and Adaptation Strategies for Global Change 5:99-121.

GOFC-GOLD. 2009. Reducing greenhouse gas emissions from deforestation and 46 degradation in developing countries: a sourcebook of methods and procedures 47 for monitoring, measuring and reporting, GOFC-GOLD Report version COP14-2, 48 (GOFC-GOLD Project Office, Natural Resources Canada, Alberta, Canada)

MacDicken, K. G. 1997 A Guide to Monitoring Carbon Storage in Forestry and Agroforestry Projects. Winrock International.

Pearson, T., Walker, S. and Brown, S. 2005 Sourcebook for land use, land-use change and forestry projects. Winrock International and the BioCarbon Fund of the World Bank. 57p.

Penman, J. et al. 2003 Good practice guidance for land use, land-use change and forestry. IPCC National Greenhouse Gas Inventories Program and Institute for Global Environmental Strategies, Kanagawa, Japan. http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf.htm


http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf.htm

Thank you for your attention

USAID-CIFOR-ICRAF Project Assessing the Implications of Climate Change for USAID Forestry Programs...

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