Carbon Budget Model Research Articles

Carbon estimation using sampling to correct LiDAR-assisted enhanced forest inventory estimates

Light Detection and Ranging (LiDAR) scanning has been increasingly applied in forest ecosystem surveys. Data from LiDAR describe forest structure and provide attribute information for forest inventory. These attributes can potentially aid in the estimation of biomass and carbon by providing sampling covariates. Therefore, this study explored the accuracy of estimating carbon storage by calibrating LiDAR attributes using list sampling with a ratio estimator. Standing tree carbon and down woody debris carbon were estimated across 10 broad forest types. LiDAR-derived gross total volume was used as a listing factor and big BAF samples to collect field data. Gross total volumes were “corrected” using a ratio estimator. The results show that standing tree carbon was 58.5 Mg C × ha-1 (± 2.9% SE), and dead woody debris carbon 1.8 Mg C × ha-1 (± 7.2% SE). With the exception of one forest type, these estimates were comparable to those derived from the carbon budget model of the Canadian forest sector (CBM-CFS3).

Forest harvesting and the carbon debt in boreal east-central Canada

Conversion of carbon-rich, primary boreal landscapes to managed ones through clearcut-based silviculture has the potential to decrease landscape-level carbon storage and thereby incur a significant carbon debt. We calculated carbon debts and payback periods associated with production of wood pellets to replace coal, oil and natural gas in electricity generation for such landscape conversion in boreal east-central Canada. Local forest inventory information in combination with the Carbon Budget Model (CBM-CFS3) was used to estimate biomass and dead wood carbon stocks after fire or clearcutting, and resulting age- and disturbance-specific carbon stock estimates were used to populate simulated landscapes. Based on empirical information, we investigated a range of fire-return intervals in the primary landscapes (114–262 years), harvest rotation ages (80–100 years) and conversion efficiency factors (0.17–0.71 tonnes fossil fuel carbon eliminated per tonne harvested wood carbon). After a first rotation of harvesting, carbon stocks declined 33–50% relative to stocks in the natural, fire-dominated landscapes and payback periods ranged from 92 to 757 years. The type of fossil fuel had the strongest effect on payback periods: under average efficiencies, ranges were 122–207, 156–268 and 278–481 years for coal, oil and natural gas respectively. These calculations suggest that under a wide range of assumptions, clearcut-based management of boreal primary landscapes to produce wood pellets to replace fossil fuels in electricity generation will result in net emissions of greenhouse gases to the atmosphere for many decades.

Quantifying the interannual litterfall variations in China’s forest ecosystems

Abstract Aims Litterfall is a key parameter in forest biogeochemical cycle and fire risk prediction. However, considerable uncertainty remains regarding the litterfall variations with forest ages. Quantifying the interannual variation of forest litterfall is crucial for reducing uncertainties in large-scale litterfall prediction. Methods Based on the available dataset (N = 318) with continuous multi-year (≥2 years) measurements of litterfall in Chinese planted and secondary forests, coefficient of variation (CV), variation percent (VP), and the ratio of next-year litterfall to current-year litterfall were used as the indexes to quantify the interannual variability in litterfall. Important Findings The interannual variations of litterfall showed a declining trend with increasing age from 1 to 90 years. The litterfall variations were the largest in 1–10 years (mean CV = 23.51% and mean VP = −28.59% to 20.89%), which were mainly from tree growth (mean ratio of next-year to current-year = 1.20). In 11–40 years, the interannual variations of litterfall gradually decreased but still varied widely, mean CV was ~18% and mean VP ranged from −17.69% to 21.19%. In 41–90 years, the interannual variations minimized to 8.98% in mean CV and ~8% in mean VP. As a result, forest litterfall remained relatively low and constant when stand age was larger than 40 years. This result was different from the previous assumptions that forest litterfall reached relatively stable when stand age was larger than 30, 20 or even 15 years. Our findings can improve the knowledge about forest litter ecology and provide the groundwork for carbon budget and biogeochemical cycle models at a large scale.

Recommended temperature metrics for carbon budget estimates, model evaluation and climate policy

Recent estimates of the amount of carbon dioxide that can still be emitted while achieving the Paris Agreement temperature goals are larger than previously thought. One potential reason for these larger estimates may be the different temperature metrics used to estimate the observed global mean warming for the historical period, as they affect the size of the remaining carbon budget. Here we explain the reasons behind these remaining carbon budget increases, and discuss how methodological choices of the global mean temperature metric and the reference period influence estimates of the remaining carbon budget. We argue that the choice of the temperature metric should depend on the domain of application. For scientific estimates of total or remaining carbon budgets, globally averaged surface air temperature estimates should be used consistently for the past and the future. However, when used to inform the achievement of the Paris Agreement goal, a temperature metric consistent with the science that was underlying and directly informed the Paris Agreement should be applied. The resulting remaining carbon budgets should be calculated using the appropriate metric or adjusted to reflect these differences among temperature metrics. Transparency and understanding of the implications of such choices are crucial to providing useful information that can bridge the science–policy gap. Different methods for determining global mean temperature change are preferable for different purposes, such as estimating carbon budgets versus consistency with the achievement of the Paris Agreement, argues a Perspective that outlines methodological choices and recommends decision pathways.

Evaluating impacts of climate change on net ecosystem productivity (NEP) of global different forest types based on an individual tree-based model FORCCHN and remote sensing

Abstract Accurately assessing the NEP of global forest ecosystem is indispensable to adjusting the global carbon balance for climate change. In this study, an improved individual-based forest ecosystem carbon budget model (FORCCHN) and remote sensing outputs were applied to investigate the impacts of climate change on the NEP of global different forest types from 1982 to 2011. The contributions of carbon sinks in different forest types to carbon sinks in global forest ecosystems were explored. The global forests were categorized into five ecological types according to their habitats and generic characteristics: deciduous coniferous forest (DCF), evergreen coniferous forest (ECF), evergreen coniferous deciduous broad-leaved mixed forest (ECDBMF), deciduous broad-leaved forest (DBF) and evergreen broad-leaved forest (EBF). The results showed that globally, the forest ecosystems represented a huge carbon sink and that the total carbon uptakes per unit area per year for EBF, ECF, DBF, DCF and ECDBMF forests from 1982 to 2011 were 0.388 kgC m−2·yr−1, 0.116 kgC m−2·yr−1, 0.082 kgC m−2·yr−1, 0.048 kgC m−2·yr−1 and 0.044 kgC m−2·yr−1, respectively. Inter-annual variability in global NEP per unit area per year among different forest types clearly existed. From 1982 to 2011, especially, the NEP increased in the EBF and ECF forests globally, but decreased in DBF forests. Moreover, there were no significant changes in the NEP of DCF and ECDBMF forests. The carbon sink areas varied among the 5 global forest types. For the DCF forest, central Asia, northern Europe and central North America were the main carbon sink regions. Central Asia, northern Europe and central North America were the main carbon sink regions for the ECF forest. For the ECDBMF forest, the carbon sink regions were mainly concentrated in northern and central Asia. The carbon sink regions for the DBF forest were mainly concentrated in southern Asia, southern Europe and mid-eastern North America. The carbon sink regions for the EBF forest were mainly concentrated in northern and central South America, southern Africa and southern Asia. Finally, the individual contributions of the NEP of each of forest type to global forest's NEP were calculated. The contributions of NEP for the EBF, ECF, DBF, DCF and ECDBMF forests to the total NEP of global forests were 57.19%, 17.07%, 12.17%, 7.10% and 6.47%, respectively. Our findings highlight that, over the past three decades, the EBF, ECF and DBF forests have been the main contributors to the increases in net ecosystem productivity of global forests.

Spatial–temporal variations of carbon storage of the global forest ecosystem under future climate change

Forests play an important role in sequestrating atmospheric carbon dioxide (CO2). Therefore, in order to understand the spatial–temporal variations and controlling mechanisms of global forest carbon (C) storage under future climate change, an improved individual-based forest ecosystem carbon budget model and remote sensing outputs in this study were applied to investigate the spatial–temporal dynamics of global forest (vegetation+soil) C storage in the future climate change scenario. The results showed that in the future RCP4.5 (representative concentration pathways) climate scenario, the total C storage per unit area per year in vegetation and soil of the global forest ecosystem showed a trend of first decreasing and then increasing from 2006 to 2100, with an average of 22.77 kg C m−2 year−1. However, the evolution trends of C storage changes in vegetation and soil were different. Moreover, the average soil C storage per unit area per year was 2.87 times higher than the average vegetation C storage. The impact of climate change on total C storage in vegetation and soil of the global forest ecosystems was positive, showing an obvious increase during 2006–2100. The total C storage varied significantly in spatial distribution. Spatially, the vegetation C storage and the soil organic C storage were projected to decrease significantly in most parts of South America and southern Africa in the Southern Hemisphere and increase in eastern North America, western Asia, and most areas of Europe in the Northern Hemisphere. Especially in the middle and high latitude regions of the Northern Hemisphere, the total forest C stock was projected to increase by 30–90% from 2046 to 2100. In the future, in these areas where forest C reserves were predicted to be reduced, it was suggested to increase afforestation, prohibit deforestation, and develop projects to increase forest C. Sustainable forest managements also offered opportunities for immediate mitigation and adaptation to climate change. Our findings provided not only a projection of C storage of global forest ecosystem responses to future climate change but also a useful methodology for estimating forest C storage at global levels.

Empirical and Predicted Boreal Forest Carbon Pools Following Stem‐Only Harvesting in Quebec, Canada

Core Ideas Total ecosystem carbon recovered to pre‐harvest levels after seven decades. Predicted and observed carbon pools differed most for deadwood and soil. Modified CBM‐CFS3 initialization and default decay parameters may improve accuracy. Climate change and global wood products demand raise concerns about boreal forest ecosystem resilience to natural disturbances and harvesting. A chronosequence experiment located in Forêt Montmorency, Quebec was used to evaluate the effects of harvesting on carbon (C) recovery trajectories at the stand level over a period of 77 years in balsam fir‐white birch stands. Empirical estimates of 19 Forêt Montmorency forest carbon pools were compared with those simulated by the Carbon Budget Model (CBM‐CFS3) to test model assumptions for predicting carbon dynamics in this forest. The model was initialized using forest inventory data, spatially explicit environmental conditions, and disturbance matrices designed to represent historical spruce budworm epidemics in Forêt Montmorency. Over the chronosequence, total ecosystem C increased significantly (p = 0.05) following harvest from 211 Mg in year‐zero to 279 ± 8 Mg C ha−1 in year 67 (mean ± SE), suggesting that FM carbon pools were recovering to pre‐harvest levels after seven decades. The CBM‐CFS3 model predicted total ecosystem C stocks within 10% of the empirical mean at stand maturity; however, several predicted C pools deviated from field observations in both C amounts and trends over time. The greatest differences were in deadwood and soil C pools, suggesting that model initialization of dead organic matter pools did not adequately simulate the 1000‐yr history of C‐pool transfers and stand dynamics leading up to the harvest. Modifications to CBM‐CFS3 initialization assumptions and default decay parameters may more accurately simulate long‐term effects of natural disturbances on C pools for this forest region.

Modeling organic carbon loss from a rapidly eroding freshwater coastal wetland

Shoreline erosion can transition freshwater coastal wetlands from carbon sinks to carbon sources. No studies have explored the impacts of coastal geomorphic processes on freshwater wetland carbon budgets. To do so, we modified a saltmarsh carbon budget model for application in freshwater coastal wetlands. We validated the model with data from a shoreline wetland in the Laurentian Great Lakes. The model generates the carbon budget by differencing carbon export and carbon storage. The inputs for carbon storage are the carbon inventory and maximum wetland age. Inputs for carbon export include erosion rates and overwash extent. The model demonstrates that the wetland examined in this study transitioned to a source of carbon during periods of erosion. In fact, the net carbon export between 2015 and 2018 was 8.1% of the wetland’s original carbon stock. This study indicates that geomorphic change can dictate whether and how freshwater coastal wetlands serve as sources or sinks for terrestrial carbon, and that carbon stocks can fluctuate on a geologically rapid timescale. We recommend that such geomorphic processes be considered when developing carbon budgets for these marginal environments. Furthermore, the carbon budget model refined in this study can be used to prioritize wetlands in land management and conservation efforts.

Forestry carbon budget models to improve biogenic carbon accounting in life cycle assessment

Currently, wood and wood construction materials have limitations in how carbon fluxes are accounted for in life cycle assessments. The biogenic carbon balance of wood is often considered to be neutral, meaning that the carbon sequestered by biomass through photosynthesis is considered equal to the carbon feedstock in wood that is eventually released throughout its life cycle. Several publications have recently shown that this assumption could lead to accounting errors. This research work aims to improve the biogenic carbon accounting of the forestry phase of the life cycle of softwood products. This involved specifically modelling carbon fluxes as a function of tree species, growing conditions and forest management practices, from Canadian managed forests. A baseline natural forest scenario was run for 1000 years until the carbon stocks were assumed to reach an approximate steady-state, followed immediately by a harvest scenario that was simulated for another 100 years. The ecosystem carbon costs of the harvest activity were calculated for 117 species and region forest landscapes across Canada and expressed per cubic meter of harvested wood. Most landscapes showed net sequestration after 100 years of harvest history. Exceptions to this included outlier landscapes characterized by low average annual temperatures and precipitation where slightly positive values (net emissions) were found. The mean time to ecosystem cost neutrality for each species ranged from 16 to 60 years. Knowing the time since forest management has started on a particular forest landscape now enables managers to obtain an estimate of ecosystem carbon cost per cubic meter of wood harvested for most of Canada's forests and commercial tree species. These ecosystem carbon costs can be used to generate regionalized cradle-to-gate life cycle inventories for harvested wood products across Canada.

Potential use of hyperspectral data to classify forest tree species

BackgroundRemote sensing techniques and data are becoming increasingly popular in forest management, e.g. for change detection and health condition analysis. Tree species recognition is a fundamental issue in taking forest inventories, especially in carbon budget modelling. Hyperspectral imagery provides an accurate classification results for large areas based on a relatively small amount of training data.ResultsA hyperspectral image of a forest stand in north-eastern Poland taken using an AISA (Airborne Imaging Spectrometer for Application) Eagle camera was transformed to extract the most valuable spectral differences and was classified into seven tree types (birch, European beech, oak, hornbeam, European larch, Scots pine, and Norway spruce) using nine classification algorithms. The highest overall accuracy and kappa coefficient were 90.3% and 0.9 respectively using three minimum noise fraction bands and maximum likelihood classifier.ConclusionsHyperspectral imaging of forests can be used to classify major forest tree species with a good degree of accuracy. It is time-efficient and user-friendly; however, the data and software required means that this approach is still expensive at present.

A carbon budget model to predict branch carbohydrate deficiencies as a function of water stress and crop load in pistachio (Pistacia veraL.)

A carbon budget model to predict branch carbohydrate deficiencies as a function of water stress and crop load in pistachio (<i>Pistacia vera</i>L.)

Seasonal differences in drivers of species richness of waders in inland wetlands of La Mancha Húmeda Biosphere Reserve

This study forms part of the doctoral thesis of M. S. S. G., supported by a grant from Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil. This study was jointly supported by the Ministry of Economy and Competitiveness of the Government of Spain (MINECO) and Competitiveness and the European Regional Development Fund (FEDER) ‘One way to make Europe’, through the projects: ‘CLIMAWET’ – Climate change mitigation and adaptation in the main types of Iberian Mediterranean wetlands: carbon budget and response models of species and habitats (CGL2015‐69557‐R); and ‘ECOLAKE’ – Ecological patterns in endorheic lakes: keys to their conservation (CGL2012‐38909).

Climate change mitigation in Canada\u2019s forest sector: a spatially explicit case study for two regions

BackgroundWe determine the potential of forests and the forest sector to mitigate greenhouse gas (GHG) emissions by changes in management practices and wood use for two regions within Canada’s managed forest from 2018 to 2050. Our modeling frameworks include the Carbon Budget Model of the Canadian Forest Sector, a framework for harvested wood products that estimates emissions based on product half-life decay times, and an account of marginal emission substitution benefits from the changes in use of wood products and bioenergy. Using a spatially explicit forest inventory with 16 ha pixels, we examine mitigation scenarios relating to forest management and wood use: increased harvesting efficiency; residue management for bioenergy; reduced harvest; reduced slashburning, and more longer-lived wood products. The primary reason for the spatially explicit approach at this coarse resolution was to estimate transportation distances associated with delivering harvest residues for heat and/or electricity production for local communities.ResultsResults demonstrated large differences among alternative scenarios, and from alternative assumptions about substitution benefits for fossil fuel-based energy and products which changed scenario rankings. Combining forest management activities with a wood-use scenario that generated more longer-lived products had the highest mitigation potential.ConclusionsThe use of harvest residues to meet local energy demands in place of burning fossil fuels was found to be an effective scenario to reduce GHG emissions, along with scenarios that increased the utilization level for harvest, and increased the longevity of wood products. Substitution benefits from avoiding fossil fuels or emissions-intensive products were dependent on local circumstances for energy demand and fuel mix, and the assumed wood use for products. As projected future demand for biomass use in national GHG mitigation strategies could exceed sustainable biomass supply, analyses such as this can help identify biomass sources that achieve the greatest mitigation benefits.

Warming enhances sedimentation and decomposition of organic carbon in shallow macrophyte-dominated systems with zero net effect on carbon burial.

Temperatures have been rising throughout recent decades and are predicted to rise further in the coming century. Global warming affects carbon cycling in freshwater ecosystems, which both emit and bury substantial amounts of carbon on a global scale. Currently, most studies focus on the effect of warming on overall carbon emissions from freshwater ecosystems, while net effects on carbon budgets may strongly depend on burial in sediments. Here, we tested whether year-round warming increases the production, sedimentation, or decomposition of particulate organic carbon and eventually alters the carbon burial in a typical shallow freshwater system. We performed an indoor experiment in eight mesocosms dominated by the common submerged aquatic plant Myriophyllum spicatum testing two temperature treatments: a temperate seasonal temperature control and a warmed (+4°C) treatment (n=4). During a full experimental year, the carbon stock in plant biomass, dissolved organic carbon in the water column, sedimented organic matter, and decomposition of plant detritus were measured. Our results showed that year-round warming nearly doubled the final carbon stock in plant biomass from 6.9±1.1g C in the control treatment to 12.8±0.6g C (mean±SE), mainly due to a prolonged growing season in autumn. DOC concentrations did not differ between the treatments, but organic carbon sedimentation increased by 60% from 96±9.6 to 152±16gCm-2 yaer-1 (mean±SE) from control to warm treatments. Enhanced decomposition of plant detritus in the warm treatment, however, compensated for the increased sedimentation. As a result, net carbon burial was 40±5.7gCm-2 year-1 in both temperature treatments when fluxes were combined into a carbon budget model. These results indicate that warming can increase the turnover of organic carbon in shallow macrophyte-dominated systems, while not necessarily affecting net carbon burial on a system scale.

Long-term time series of annual ecosystem production (1985–2010) derived from tree rings in Douglas-fir stands on Vancouver Island, Canada using a hybrid biometric-modelling approach

We used a hybrid-biometric modelling approach that combines tree-ring based stand reconstruction and the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate past magnitude and inter-annual variation of net primary production (NPP), net ecosystem production (NEP), and heterotrophic respiration (Rh) in plots located within the footprint of an eddy-covariance (EC) installation in a Douglas-fir stand of 1949 origin (DF49 or AmeriFlux CA-Ca1). Stand reconstruction estimated NEP showed excellent correspondence with EC-estimated NEP over the period 1998–2010 (r2 = 0.79, mean difference 24 gC m−2 year−1). Estimates of carbon use efficiency, aboveground NPP, and post-disturbance C dynamics following the harvest of DF49 in 2011 showed discrepancies between modelled estimates and independent data, which were attributed to underestimates of coarse litterfall in previous field studies and to uncertainty in the production, turnover, and post-mortality decay of non merchantable woody biomass in the CBM-CFS3. Despite these issues, the results provide further evidence of the potential use of tree-ring data to expand the availability of long-term estimates of annual ecosystem production and their ability to increase our understanding of forest C dynamics.

The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3): customization of the Archive Index Database for European Union countries

Key messageThe purpose of this report is to increase the transparency of applications of the CBM-CFS3 model by climate-related policy-makers and researchers. The report provides explicit information on the parametrization of a new Archive Index Database used with this model to simulate forest carbon dynamics in 26 EU countries. The database can be accessed athttps://data.europa.eu/89h/jrc-cbm-eu-aidb, primary metadata are available in Kull et al. (2017), and additional metadata are available athttps://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/df48155b-973f-4169-a722-100bb6bfc76c.The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) has been adapted, tested, and applied to forests of 26 EU countries over the last 7 years for EU policy making and scientific research. The overall purpose of this exercise is to increase the transparency of how the EU Archive Index Database (EU-AIDB) was parameterized while supporting both the policy making and research communities interested in applying the CBM-CFS3 with ecological parameters specific to the EU context. In addition to preparing model input data reflecting various management and disturbance scenarios for CBM-CFS3 projects, an essential step was to update the original AIDB with information specific to the EU context and create an EU-AIDB. The AIDB is the Microsoft Access database behind the CBM-CFS3 that stores default ecological information and parameters pertaining to the forest ecosystems of a country, among other functions. The EU-AIDB incorporates 1034 spatial units resulting from the intersection of 204 European administrative regions and ecological boundaries representing 35 climatic units. It also contains updated parameters for 192 of the main tree species reported by the National Forest Inventories of each EU country. The release of this database allows CBM-33 CFS3 users in the EU to apply European administrative and ecological units and tree species in forest carbon modeling projects.

Applying a systems approach to assess carbon emission reductions from climate change mitigation in Mexico’s forest sector

The Paris Agreement of the United Nation Framework Convention on Climate Change calls for a balance of anthropogenic greenhouse emissions and removals in the latter part of this century. Mexico indicated in its Intended Nationally Determined Contribution and its Climate Change Mid-Century Strategy that the land sector will contribute to meeting GHG emission reduction goals. Since 2012, the Mexican government through its National Forestry Commission, with international financial and technical support, has been developing carbon dynamics models to explore climate change mitigation options in the forest sector. Following a systems approach, here we assess the biophysical mitigation potential of forest ecosystems, harvested wood products and their substitution benefits (i.e. the change in emissions resulting from substitution of wood for more emissions-intensive products and fossil fuels), for policy alternatives considered by the Mexican government, such as a net zero deforestation rate and sustainable forest management. We used available analytical frameworks (Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model), parameterized with local input data in two contrasting Mexican states. Using information from the National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data), we demonstrate that activities aimed at reaching a net-zero deforestation rate can yield significant CO2e mitigation benefits by 2030 and 2050 relative to a baseline scenario (‘business as usual’), but if combined with increasing forest harvest to produce long-lived products and substitute more energy-intensive materials, emissions reductions could also provide other co-benefits (e.g. jobs, illegal logging reduction). We concluded that the relative impact of mitigation activities is locally dependent, suggesting that mitigation strategies should be designed and implemented at sub-national scales. We were also encouraged about the ability of the modeling framework to effectively use Mexico’s data, and showed the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation.

Integrating continuous stocks and flows into state‐and‐transition simulation models of landscape change

Abstract State‐and‐transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land‐use/land‐cover (LULC) change. The STSM method divides a landscape into spatially referenced cells and then simulates the state of each cell forward in time, as a discrete‐time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete. Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a STSM with stocks and flows (STSM‐SF). The STSM–SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete‐time stochastic process. The method differs from the traditional systems dynamics approach to stock‐flow modelling in that the stocks and flows can be spatially explicit, and the flows can be expressed as a function of the STSM states and transitions. We demonstrate the STSM‐SF method by integrating a spatially explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, whereas the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years. The new STSM‐SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.

Changes in mass, carbon, nitrogen, and phosphorus in logs decomposing for 30 years in three Rocky Mountain coniferous forests

Estimates of decomposition rates of coarse woody debris (CWD) and fluxes of nutrients therein are essential components of carbon (C) and nutrient budget models. In a 30-year field experiment, we periodically measured mass remaining and nutrient concentrations in log segments of pine, spruce, and fir in natural, mature coniferous forests in Alberta, Canada. The predicted turnover times (t95; years) were 43–44 years for pine, 42–60 years for spruce, and 38–46 years for fir. Extrapolating from best-fit models, we predict that decomposition of these logs would be complete within 50–60 years. The ratio of carbon to nitrogen (C:N) declined for most of the decomposition period, and ratios of the three species converged at &lt;200 at 90% mass loss. Net release of N occurred only after logs had lost 90% of their original C and C:N had declined to &lt;200. The ratio of carbon to phosphorus (C:P) declined and converged at 500–1000 at 90% mass loss. There was no evidence of net P release from logs even at 90% mass loss. It may be possible to estimate the amounts of N and P that will be incorporated into decaying logs based on the extent to which their initial C:N differs from 200 and their initial C:P differs from 500.

Constraining the organic matter decay parameters in the CBM-CFS3 using Canadian National Forest Inventory data and a Bayesian inversion technique

Forests are an important component of the global carbon (C) cycle: they can capture and retain large amounts of C annually, depending on stand characteristics, climate, and disturbance regimes. With climate and disturbance regimes shifting, it is important to be able to accurately represent the corresponding changes in forest C dynamics with well-calibrated models. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a widely used model for simulating C dynamics in managed forests at stand, regional, and national levels. Here, we use a Bayesian Markov Chain Monte Carlo (MCMC) technique to calibrate the parameters in the CBM-CFS3 by assimilating C stocks of six deadwood and soil pools estimated from data collected from 635 plots within the Canadian National Forest Inventory. Calibration led to most improvement in the simulation of C stocks in small and fine woody debris, reducing RMSE by 54.3%, followed by the snag stems (RMSE reduced by 23.2%), and coarse woody debris (13%). The calibrated parameters resulted in increased rates of C cycling in fine and coarse woody debris and the soil organic layer, distinct C dynamics in hardwood and softwood dominated stands, and increased temperature sensitivity of the C contained in the mineral soil. While parameter calibration considerably improved the simulation of the small and fine woody debris and snags stem pools, model representation of the branch snag, coarse woody debris, soil organic layer, and mineral soil pools were not substantially improved. Lack of substantial improvements in the calibrated model performance indicated the need for including additional processes in C dynamics simulation or a change in the modelling paradigm. We illustrate the potential need to include a lignin effect on deadwood decay and suggest further exploration of the effects of tree species, soil types, and mosses on performance of the CBM-CFS3.