National Forest Carbon Monitoring Research Articles

Beyond biomass to carbon fluxes: application and evaluation of a comprehensive forest carbon monitoring system

Accurate quantification of forest carbon stocks and fluxes over regions is needed to monitor forest resources as they respond to changes in climate, disturbance and management, and also to evaluate contributions of forest sector to the regional and global carbon balances. In previous work we introduced a national forest carbon monitoring system (NFCMS) that combines forest inventory data, satellite remote sensing of stand biomass and forest disturbances, and an ecosystem carbon cycle model to assess contemporary forest carbon dynamics at a 30 m resolution. In this study, we evaluate the NFCMS estimates of biomass and carbon fluxes with available data products for the Pacific Northwest (PNW) region, and then analyze the regional carbon balance over the period 1986–2010. The biomass estimates have good agreements with evaluation datasets (eMapR, NBCD2000, and Hagen2005) at regional and forest type levels, and at spatial scales of 1 km2 and larger. Regionwide, PNW forests acted as a stable net sink for atmospheric CO2 (18.5 Tg C yr–1) within forestlands. However, harvesting activities removed significant amounts of carbon, equating to over 75% of annual net carbon sink, though only 25% of this (∼3.5 Tg C yr–1) is emitted to the atmosphere within 50 years. Wildfires contributed modestly to carbon emissions in most years, however, the severe fires of 2002 and 2006 released 16.6 and 7.1 Tg C, respectively. The study demonstrates the potential of the NFCMS framework to serve as a candidate measuring, reporting and verification system, informed by field and remotely sensed inventories, and tracking the carbon balance of the forest sector across the United States.

The Canadian model for peatlands (CaMP): A peatland carbon model for national greenhouse gas reporting

A model framework for national greenhouse gas emission and removal estimation for Canadian peatlands (CaMP v2.0) was developed and tested. It provides a module that can work alongside the upland forest Generic Carbon Budget Model (GCBM) developed to eventually replace the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) as the core model in Canada's National Forest Carbon Monitoring, Accounting and Reporting System. The CaMP (v2.0) provides a simple model foundation that can be applied nationally for 11 different peatland categories. It tracks the growth, turnover and decay in annual time steps of different vegetation components (foliage, branches, stems, and roots of trees, shrubs, sedges and mosses). It uses a Q10 relationship to model peat C pool decomposition as a function of mean annual temperature, and models methane flux response to deviations in annual water table depth. The CaMP takes a simple approach to modeling hydrology for large spatial scales by using the nationally-available Canadian Fire Weather Index Drought Code to predict long-term and annual water table depth. The CaMP (v2.0) provides the framework needed to model disturbances but only includes wildfire in this version. Model behavior and sensitivity were assessed, and evaluated against observed flux data. Results suggest that the CaMP (v2.0) provides an appropriate structure for large spatial- and temporal-scale estimation of emissions, owing to the model behaving as expected relative to shifts in environmental variables, and to reasonably small mean observed to modeled residuals. Methane was overestimated by the model on average by 6 g C ha−1y − 1 (n = 53 years of data across 11 peatland sites), and by 8 g C ha−1y − 1 when weighted by site location (n = 12 sites, ≥ 3 years of data per site). The model overestimated net ecosystem exchange (NEE) by 20 g C ha−1y − 1 (n = 36 years of data across 12 peatland sites), and by 2 g C ha−1y − 1 when weighted by site location (n = 11 sites, ≥ 3 years of data per site), and results demonstrate that inter-site variation is greater than temporal variation across NEE measures. Several aspects were identified as requiring further work to increase explained variation in finer-scale emission estimates. Recommendations include further expanding the existing peatland databases to re-calibrate peat decomposition rates and better parameterize NPP rates by region for certain vegetation layers and peatland types, as well as developing a national annual-scale soil temperature model that could serve to replace the air temperature (Q10) decay relationship currently used in the CaMP (v2.0). Data gaps that were identified include the need for annualized methane flux datasets with appropriate annual-scale meta-data. Future work is required to include permafrost dynamics, as well as additional natural, and anthropogenic disturbances.

Uncertainty of inventory-based estimates of the carbon dynamics of Canada’s managed forest (1990–2014)

Canada’s National Forest Carbon Monitoring Accounting and Reporting System (NFCMARS) quantifies the carbon (C) dynamics and greenhouse gas (GHG) emissions and removals of Canada’s managed forest to fulfill reporting obligations under international climate conventions. Countries are also requested to assess the uncertainty associated with these estimates, which we report here. We used Monte Carlo simulation to quantify uncertainty of carbon stock and flux estimates from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), the core ecosystem model of the NFCMARS. We evaluated the impacts of model algorithms, parameters, and the input data used to describe forest characteristics and disturbance rates. Under our assumptions, 95% confidence interval widths averaged 16.2 Pg C (+8.3 and –7.9 Pg C, or ±15%) for total ecosystem C stock and 32.2 Tg C·year−1 (+16.6 and –15.6 Tg C·year−1) for net biome production relative to an overall simulation median of –0.8 Tg C·year−1 from 1990 to 2014. The largest sources of uncertainty were related to factors determining biomass increment and the parameters used to model soil and dead organic matter C dynamics. Opportunities to reduce uncertainty and associated research challenges were identified.

Improving carbon monitoring and reporting in forests using spatially-explicit information.

BackgroundUnderstanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere—specifically the process of C removal from the atmosphere, and how this process is changing—is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada.ResultsOur results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year−1) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha−1. Comparisons between our estimates and estimates from Canada’s National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates.ConclusionsBoth estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences between these estimates. This study represents an important first step towards the integration of spatially-explicit information into Canada’s NFCMARS.

Spatially explicit analysis of field inventories for national forest carbon monitoring.

BackgroundTropical forests provide a crucial carbon sink for a sizable portion of annual global CO2 emissions. Policies that incentivize tropical forest conservation by monetizing forest carbon ultimately depend on accurate estimates of national carbon stocks, which are often based on field inventory sampling. As an exercise to understand the limitations of field inventory sampling, we tested whether two common field-plot sampling approaches could accurately estimate carbon stocks across approximately 76 million ha of Perúvian forests. A 1-ha resolution LiDAR-based map of carbon stocks was used as a model of the country’s carbon geography.ResultsBoth field inventory sampling approaches worked well in estimating total national carbon stocks, almost always falling within 10 % of the model national total. However, the sampling approaches were unable to produce accurate spatially-explicit estimates of the carbon geography of Perú, with estimates falling within 10 % of the model carbon geography across no more than 44 % of the country. We did not find any associations between carbon stock errors from the field plot estimates and six different environmental variables.ConclusionsField inventory plot sampling does not provide accurate carbon geography for a tropical country with wide ranging environmental gradients such as Perú. The lack of association between estimated carbon errors and environmental variables suggests field inventory sampling results from other nations would not differ from those reported here. Tropical forest nations should understand the risks associated with primarily field-based sampling approaches, and consider alternatives leading to more effective forest conservation and climate change mitigation.Electronic supplementary materialThe online version of this article (doi:10.1186/s13021-016-0050-0) contains supplementary material, which is available to authorized users.

Land use changes affecting soil organic carbon storage along a mangrove swamp rice chronosequence in the Cacheu and Oio regions (northern Guinea-Bissau)

Guinea-Bissau has the largest area of mangrove swamp rice, an important cropping system that significantly contribute to the food security of the nation. Attempts to reclaim mangrove swamps for rice growing have shown the importance of a greater knowledge on the effects of land use change on soil properties and soil carbon storage. To address this problem, a study was undertaken within Cacheur and Oio regions in Northern Guinea-Bissau, along the following chronosequence: mangrove, rice and abandoned fields. Changes in C/N ratio, δ13C and δ15N values were used to study the dynamics of C3 plant-derived and marine-derived carbon (C) in order to analyze the origin of soil organic matter (SOM) and estimate the impact of marine contribution to SOC. Isotopic signatures within the mangrove swamp rice soils suggested the inwelling of marine derived C. SOC stock was estimated in 0–10, 0–20, 0–40 and 0–80cm soil layers using fixed soil depth (FD) and fixed soil mass (FM) approaches. The significantly highest values were found in mangrove soils and the lowest in the abandoned fields for both sites, while no significant differences were recorded for the topsoil (0–10cm) between mangrove and rice fields. The results of this study revealed that conversion of mangrove to rice cropping has technical potential of SOC sequestration in the upper part of the soil (0–40cm). On the other hand, the abandonment of the fields caused decreases in carbon storage along the whole soil depth. These findings may have important implications for national forest carbon monitoring systems and regional level reducing emission from deforestation and forest degradation (REDD+) strategies.

Integrating forest fuels and land cover data for improved estimation of fuel consumption and carbon emissions from boreal fires

Estimating carbon emissions from wildland fires is complicated by the large variation in both forest fuels and burning conditions across Canada’s boreal forest. The potential for using spatial fuel maps to improve wildland fire carbon emission estimates in Canada’s National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) was evaluated for select wildfires (representing a transect across western Canada) occurring in 2003 and 2004 at four study areas in western Canada. Area-normalised emission rates and total emissions differed by fuels data source, mainly as a function of the treatment of open fuels in the higher resolution spatial fuel models. The use of spatial data to refine the selection of stand types that probably burned and the use of fire weather conditions specific to the fire increased the precision of total carbon emission estimates, relative to computational procedures used by Canada’s NFCMARS. Estimates of total emissions from the NFCMARS were consistent with the regional and national data sources following the spatial approach, suggesting the two approaches had equivalent accuracies. Though it cannot be said with certainty that the inclusion of this detailed information improved accuracy, the spatial approach offers the promise or potential for more accurate results, pending more consistent fuel maps, especially at finer scales.

Carbon stocks and changes in tropical secondary forests of southern Mexico

The role of tropical secondary forests in carbon accumulation has been widely acknowledged, but the rates of changes in carbon stocks still remain uncertain. The aim of this study was to analyze the changes in carbon pool sizes and accumulation rates associated with growth, recruitment and mortality of trees at different ages of forest succession in semi-evergreen tropical forests and relate these to the age of the secondary vegetation and prior land use intensity. The study was carried out in a chronosequence of secondary and mature forests around Calakmul Biosphere Reserve in southern Yucatan Peninsula, Mexico. Permanent monitoring plots were established and measured in 2011 and 2012 to account all carbon stocks and changes due to tree increments, establishment of new trees and tree mortality in different age classes of secondary forests.We found that carbon stocks in living tree biomass increased rapidly in the early stages and decreased in the older secondary forests. The annual carbon dynamics of trees were higher in younger secondary forest compared to older forests due to higher tree growth and recruitment. Growth functions predict that the secondary forests recover live aboveground biomass carbon stocks to pre-disturbance levels (99.56MgCha−1) at the age of about 125 years or more, while the basal area (33.2m2ha−1) regains this level at the age of about 85 years. The longer carbon recovery time can be explained by the fact that mature forests are dominated by hardwood species whereas secondary forests are composed of softwood species and that species composition turnover during succession is relatively slow. Secondary forests of 35 years look similar to mature forests in terms of basal area, but this is located in large number of small and medium sized trees, whereas in mature forests, most of the basal area is in trees of >20cm diameter. In addition, the intensity of slash and burn agriculture can negatively alter the velocity of carbon accumulation. These findings have important implications for national forest carbon monitoring systems, greenhouse gas emission inventories and regional level REDD+ strategies.

Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada's National Forest Inventory

Assessing the uncertainties in the estimates obtained from forest carbon budget models used for national and international reporting is essential, but model evaluations are rarely conducted mainly because of lack of appropriate, independent ground plot data sets. Ecosystem carbon stock estimates for 696 ground plots from Canada's new National Forest Inventory enabled the assessment of carbon stocks predicted by the Carbon Budget Model of the Canadian Forest Sector 3 (CBM-CFS3). This model uses country-specific parameters, incorporates all five ecosystem carbon pools, and uses a simulation-based approach to predict ecosystem C stocks from forest inventory data to implement a Tier-3 (most complex) approach of the Intergovernmental Panel on Climate Change Good Practice Guidance for Land Use, Land-Use Change and Forestry (IPCC-GPG). The model is at the core of Canada's National Forest Carbon Monitoring, Accounting, and Reporting System (NFCMARS). The set of ground plots meets the IPCC-GPG standard for model evaluation as it is entirely independent of the model, but similar in type to that required for IPCC Tier-3 inventory-based C stock estimation. Model simulations for each ground plot used only the type of input data available to the NFCMARS for the national inventory report in 2010 and none of the model's default parameters were altered. Ecosystem total C stocks estimated by CBM-CFS3 were unbiased (mean difference=1.9Mgha−1, p=0.397), and significantly correlated (r=0.54, p=0.000) with ground plot-based estimates. Contribution to ecosystem total C stocks error from soil was large, and from deadwood and aboveground biomass small. Results for percent error in the aboveground biomass (7.5%) and IPCC defined deadwood (30.8%) pools compared favourably to the IPCC-GPG standards of 8% and 30%, respectively. Thus, we concluded that the CBM-CFS3 is reliable for reporting of C stocks in Canada's national greenhouse gas inventories. However, available standards for judging model reliability are few, and here we provide recommendations for the development of practical standards. Analyses by leading species (n=16) showed that error could often be attributed to a small subset of species and/or pools, allowing us to identify where improvements of input data and/or the model would most contribute to reducing uncertainties. This C stock comparison is one of the first ever to follow the evaluation process recommended by the IPCC-GPG for a Tier-3 model, and is a first step towards verification of greenhouse gas emission and removal estimates based on C stock changes.

Forest carbon stocks in Newfoundland boreal forests of harvest and natural disturbance origin II: model evaluation

The Intergovernmental Panel on Climate Change recommends that countries that use advanced (Tier 3) models to meet their international reporting obligations on forest greenhouse gas emissions and removals evaluate model predictions against independent field data. Unfortunately, estimates of total ecosystem C stocks and stock changes are scarce and consequently the recommended evaluations are rarely completed. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is the core model of Canada’s National Forest Carbon Monitoring, Accounting, and Reporting System that implements an Intergovernmental Panel on Climate Change Tier 3 approach. It accounts for biomass, dead organic matter, and soil C pools as affected by natural and anthropogenic disturbances. We used data from a recent study of total ecosystem C stocks for black spruce ( Picea mariana (Mill.) BSP) and balsam fir ( Abies balsamea (L.) Mill.) boreal forest chronosequences of different disturbance origins in Newfoundland, Canada, to evaluate C stock and stock change predictions from the CBM-CFS3. Results indicated that the accuracy of the CBM-CFS3 is high for landscape-scale estimation of C stocks. Comparison of estimates stratified by lead species or disturbance type indicated that model accuracy could be improved at finer scales by increasing specific model parameters such as the snag fall rate and woody debris decay rates relative to default parameters.

Comparing measured and modelled forest carbon stocks in high-boreal forests of harvest and natural-disturbance origin in Labrador, Canada

Understanding the effects of disturbance regimes on carbon (C) stocks and stock changes is a prerequisite to estimating forest C stocks and fluxes. Live-tree, dead-tree, woody debris (WD), stump, buried wood, organic layer, and mineral soil C stock data were collected from high-boreal black spruce ( Picea mariana (Mill.) B.S.P.) stands of harvest and fire origin and compared to values predicted by the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3); the core model of Canada's National Forest Carbon Monitoring, Accounting and Reporting System. Data comparing the effect of natural and anthropogenic disturbance history on forest C stocks are limited, but needed to evaluate models such as the CBM-CFS3. Results showed that adjustments to the CBM-CFS3 volume-to-biomass conversion and partitioning parameters were required for the non-merchantable and branch C pools to accurately capture live-tree C stocks in the studied black spruce ecosystems. Accuracy of the CBM-CFS3 modelled estimates of dead organic matter and soil C pools was improved relative to regional default parameters by increased snag fall and >10 cm WD base decay rates. The model evaluation process also highlighted the importance of developing a bryophyte module to account for bryophyte C dynamics and the physical burial of woody debris by bryophytes. Modelled mineral soil C estimates were improved by applying a preliminary belowground slow C pool base decay rate optimized for the soil type of the studied sites, Humo-Ferric Podzols.

Estimating direct carbon emissions from Canadian wildland fires

In support of Canada’s National Forest Carbon Monitoring, Accounting and Reporting System, a project was initiated to develop and test procedures for estimating direct carbon emissions from fires. The Canadian Wildland Fire Information System (CWFIS) provides the infrastructure for these procedures. Area burned and daily fire spread estimates are derived from satellite products. Spatially and temporally explicit indices of burning conditions for each fire are calculated by CWFIS using fire weather data. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) provides detailed forest type and leading species information, as well as pre-fire fuel load data. The Boreal Fire Effects Model calculates fuel consumption for different live biomass and dead organic matter pools in each burned cell according to fuel type, fuel load, burning conditions, and resulting fire behaviour. Carbon emissions are calculated from fuel consumption. CWFIS summarises the data in the form of disturbance matrices and provides spatially explicit estimates of area burned for national reporting. CBM-CFS3 integrates, at the national scale, these fire data with data on forest management and other disturbances. The methodology for estimating fire emissions was tested using a large-fire pilot study. A framework to implement the procedures at the national scale is described.

Developing Canada's National Forest Carbon Monitoring, Accounting and Reporting System to Meet the Reporting Requirements of the Kyoto Protocol

The rate of carbon accumulation in the atmosphere can be reduced by decreasing emissions from the burning of fossil fuels and by increasing the net uptake (or reducing the net loss) of carbon in terrestrial (and aquatic) ecosystems. The Kyoto Protocol addresses both the release and uptake of carbon. Canada is developing a National Forest Carbon Monitoring, Accounting and Reporting System in support of its international obligations to report greenhouse gas sources and sinks. This system employs forest-inventory data, growth and yield information, and statistics on natural disturbances, management actions and land-use change to estimate forest carbon stocks, changes in carbon stocks, and emissions of non-CO2 greenhouse gases. A key component of the system is the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS). The model is undergoing extensive revisions to enable analyses at four spatial scales (national, provincial, forest management unit and stand) and in annual time steps. The model and the supporting databases can be used to assess carbon-stock changes between 1990 and the present, and to predict future carbon-stock changes based on scenarios of future disturbance rates and management actions.