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Zhiliang Zhu

Publications and source records attributed to Zhiliang Zhu.

At least 37 records · Page 2Linked to original sources

Critical land change information enhances the understanding of carbon balance in the United States

Large-scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine-scale processes including land use and land cover change into a large-scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1-km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO 2 fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.

Global Change Biology↗

Substantially greater carbon emissions estimated based on annual land-use transition data

Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km 2 , respectively, but developed lands gained 293 km 2 (29 km 2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr −1 ) and agricultural expansion (0.046 Tg C·yr −1 ); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

Delaware, Maryland, Virginia↗

Spatially explicit reconstruction of post-megafire forest recovery through landscape modeling

Megafires are large wildfires that occur under extreme weather conditions and produce mixed burn severities across diverse environmental gradients. Assessing megafire effects requires data covering large spatiotemporal extents, which are difficult to collect from field inventories. Remote sensing provides an alternative but is limited in revealing post-fire recovery trajectories and the underlying processes that drive the recovery. We developed a novel framework to spatially reconstruct the post-fire time-series of forest conditions after the 1987 Black Dragon fire of China by integrating a forest landscape model (LANDIS) with remote sensing and inventory data. We derived pre-fire (1985) forest composition and the megafire perimeter and severity using remote sensing and inventory data. We simulated the megafire and the post-megafire forest recovery from 1985 to 2015 using the LANDIS model. We demonstrated that the framework was effective in reconstructing the post-fire stand dynamics and that it is applicable to other types of disturbances.

Environmental Modelling and Software↗

Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements

Surface soil temperature is the soil temperature from the surface to 10 cm in depth. Surface soil temperature plays a significant role in agricultural drought monitoring, ecosystem energy transfer modeling, and global carbon cycle evaluation. Studies have been proposed to estimate surface soil temperature, but surface soil temperature monitoring within forested areas still poses a significant challenge. In this study, we proposed a surface soil temperature retrieval method using combined satellite observations and in-situ measurements for the Great Dismal Swamp (GDS). The GDS is a U.S. protected area managed and protected by the U.S. Fish and Wildlife Service. It is located along the boundary of Virginia and North Carolina, with maple gum, Atlantic white cedar, and pine pocosin as the main forest cover types. Ground-based surface soil temperature measurements were collected for these forest types from May 2015 to April 2017. Both the Land Remote Sensing Satellite (Landsat) Thermal Infrared Sensor (TIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) carry two thermal infrared (TIR) channels. The TIR channels with similar corresponding wavelengths were first fused using an improved fusing model to generate high resolution TIR measurements. Then the enterprise algorithm was applied to calculate land surface temperature (LST) from the fused TIR bands. An improved soil temperature retrieval method was applied to generate surface soil temperature based on LST and vegetation index (VI) within the study area for the three forest types. In-situ measurements were used to build the surface soil temperature retrieval method, and results were then validated. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were integrated separately as VIs in the model to monitor surface soil temperature. The R 2 for retrieved surface soil temperature through satellite observations was 0.76, and the RMSE was 1.96 ℃ ">℃ ℃ when NDVI was integrated in the model; the R 2 was 0.78, and the RMSE was 1.85 ℃ ">℃ ℃ when EVI was used.

North Carolina, Virginia↗

Estimating burn severity and carbon emissions from a megafire in boreal forests of China

Wildfires, especially those of large size, worsen air quality and alter the carbon cycle through combustion of large quantities of biomass and release of carbon into the atmosphere. The Black Dragon fire, which occurred in 1987 in the boreal forests of China is among the top five of such megafires ever recorded in the world. With over 30 years of accumulation of data and availability of new greenhouse gas emission accounting methods, carbon emissions from this megafire can now be estimated with improved precision and greater spatial resolution. To do this, we combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire. Results of the study showed that 1.30 million hectares burned and 52% of that area burned with high severity. The emitted carbon dioxide equivalents (CO2e), accounted for approximately 10% of total fossil fuel emissions from China in 1987, along with CO (2%–3% of annual anthropogenic CO emissions from China) and non-methane hydrocarbons (NMHC) contributing to the atmospheric pollutants. Our study provides an important basis for carbon emission estimation and understanding the impacts of megafires.

Science of the Total Environment↗

Evaluating k-nearest neighbor (kNN) imputation models for species-level aboveground forest biomass mapping in northeast China

Quantifying spatially explicit or pixel-level aboveground forest biomass (AFB) across large regions is critical for measuring forest carbon sequestration capacity, assessing forest carbon balance, and revealing changes in the structure and function of forest ecosystems. When AFB is measured at the species level using widely available remote sensing data, regional changes in forest composition can readily be monitored. In this study, wall-to-wall maps of species-level AFB were generated for forests in Northeast China by integrating forest inventory data with Moderate Resolution Imaging Spectroradiometer (MODIS) images and environmental variables through applying the optimal k -nearest neighbor ( k NN) imputation model. By comparing the prediction accuracy of 630 k NN models, we found that the models with random forest (RF) as the distance metric showed the highest accuracy. Compared to the use of single-month MODIS data for September, there was no appreciable improvement for the estimation accuracy of species-level AFB by using multi-month MODIS data. When k > 7, the accuracy improvement of the RF-based k NN models using the single MODIS predictors for September was essentially negligible. Therefore, the k NN model using the RF distance metric, single-month (September) MODIS predictors and k = 7 was the optimal model to impute the species-level AFB for entire Northeast China. Our imputation results showed that average AFB of all species over Northeast China was 101.98 Mg/ha around 2000. Among 17 widespread species, larch was most dominant, with the largest AFB (20.88 Mg/ha), followed by white birch (13.84 Mg/ha). Amur corktree and willow had low AFB (0.91 and 0.96 Mg/ha, respectively). Environmental variables (e.g., climate and topography) had strong relationships with species-level AFB. By integrating forest inventory data and remote sensing data with complete spatial coverage using the optimal k NN model, we successfully mapped the AFB distribution of the 17 tree species over Northeast China. We also evaluated the accuracy of AFB at different spatial scales. The AFB estimation accuracy significantly improved from stand level up to the ecotype level, indicating that the AFB maps generated from this study are more suitable to apply to forest ecosystem models (e.g., LINKAGES) which require species-level attributes at the ecotype scale.

Remote Sensing↗

Carbon dioxide emissions and methane flux from forested wetland soils of the Great Dismal Swamp, USA

The Great Dismal Swamp, a freshwater forested peatland, has accumulated massive amounts of soil carbon since the postglacial period. Logging and draining have severely altered the hydrology and forest composition, leading to drier soils, accelerated oxidation, and vulnerability to disturbance. The once dominant Atlantic white cedar, cypress, and pocosin forest types are now fragmented, resulting in maple-gum forest communities replacing over half the remaining area. In order to determine the effect of environmental variabes on carbon emissions, this study observes 2 years of CO2 and CH4 soil flux, which will also help inform future management decisions. Soil emissions were measured using opaque, non-permanent chambers set into the soil. As soil moisture increased by 1 unit of soil moisture content, CH4 flux increased by 457 μg CH4–C/m2/h. As soil temperature increased by 1 °C, CO2 emissions increased by 5109 μg CO2–C/m2/h. The area of Atlantic white cedar in the study boundary has an average yearly flux of 8.6 metric tons (t) of carbon from CH4 and 3270 t of carbon from CO2; maple-gum has an average yearly flux of 923 t of carbon from CH4 and 59,843 t of carbon from CO2; pocosin has an average yearly flux of 431 t of carbon from CH4 and 15,899 t of carbon from CO2. Total Cha−1year−1 ranged from 1845 kg of Cha−1year−1 in maple-gum to 2024 kg Cha−1year−1 for Atlantic white cedar. These results show that soil carbon gas flux depends on soil moisture, temperature and forest type, which are affected by anthropogenic activities.

North Carolina, Virginia↗

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗

Assessing historical and projected carbon balance of Alaska: A synthesis of results and policy/management implications

We summarize the results of a recent interagency assessment of land carbon dynamics in Alaska, in which carbon dynamics were estimated for all major terrestrial and aquatic ecosystems for the historical period (1950–2009) and a projection period (2010–2099). Between 1950 and 2009, upland and wetland (i.e., terrestrial) ecosystems of the state gained 0.4 Tg C/yr (0.1% of net primary production, NPP), resulting in a cumulative greenhouse gas radiative forcing of 1.68 × 10 −3 W/m 2 . The change in carbon storage is spatially variable with the region of the Northwest Boreal Landscape Conservation Cooperative (LCC) losing carbon because of fire disturbance. The combined carbon transport via various pathways through inland aquatic ecosystems of Alaska was estimated to be 41.3 Tg C/yr (17% of terrestrial NPP). During the projection period (2010–2099), carbon storage of terrestrial ecosystems of Alaska was projected to increase (22.5–70.0 Tg C/yr), primarily because of NPP increases of 10–30% associated with responses to rising atmospheric CO 2 , increased nitrogen cycling, and longer growing seasons. Although carbon emissions to the atmosphere from wildfire and wetland CH 4 were projected to increase for all of the climate projections, the increases in NPP more than compensated for those losses at the statewide level. Carbon dynamics of terrestrial ecosystems continue to warm the climate for four of the six future projections and cool the climate for only one of the projections. The attribution analyses we conducted indicated that the response of NPP in terrestrial ecosystems to rising atmospheric CO 2 (~5% per 100 ppmv CO 2 ) saturates as CO 2 increases (between approximately +150 and +450 ppmv among projections). This response, along with the expectation that permafrost thaw would be much greater and release large quantities of permafrost carbon after 2100, suggests that projected carbon gains in terrestrial ecosystems of Alaska may not be sustained. From a national perspective, inclusion of all of Alaska in greenhouse gas inventory reports would ensure better accounting of the overall greenhouse gas balance of the nation and provide a foundation for considering mitigation activities in areas that are accessible enough to support substantive deployment.

Alaska↗

Long-term effects of fire and harvest on carbon stocks of boreal forests in northeastern China

Context Boreal forests represent about one third of forest area and one third of forest carbon stocks on the Earth. Carbon stocks of boreal forests are sensitive to climate change, natural disturbances, and human activities. Aims The objectives of this study were to evaluate the effects of fire, harvest, and their spatial interactions on boreal forest carbon stocks of northeastern China. Methods We used a coupled forest landscape model (LANDIS PRO) and a forest ecosystem model (LINKAGES) framework to simulate the landscape-level effects of fire, harvest, and their spatial interactions over 150 years. Results Our simulation suggested that aboveground carbon and soil organic carbon are significantly reduced by fire and harvest over the whole simulation period. The long-term effects of fire and harvest on carbon stocks were greater than the short-term effects. The combined effects of fire and harvest on carbon stocks are less than the sum of the separate effects of fire and harvest. The response of carbon stocks was impacted by the spatial variability of fire and harvest regimes. Conclusion These results emphasize that the spatial interactions of fire and harvest play an important role in regulating boreal forest carbon stocks.

Annals of Forest Science↗

The role of environmental driving factors in historical and projected carbon dynamics of wetland ecosystems in Alaska

Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km 2 , an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO 2 ) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1‐km resolution for the historical period (1950–2009) and future projection period (2010–2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO 2 and biogenic methane (CH 4 ) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO 2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO 2 fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH 4 emissions among the simulations (~15% per °C increase). Ecosystem CO 2 sequestration offset the increase in CH 4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO 2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO 2 , (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH 4 emissions to increases in soil temperature.

Alaska↗

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km 2 of developed lands, an average rate of 3282 km 2 yr −1 . On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr −1 . In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr −1 ). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Environmental Research Letters↗

Modeling wildfire-induced permafrost deformation in an Alaskan boreal forest using InSAR observations

The discontinuous permafrost zone is one of the world’s most sensitive areas to climate change. Alaskan boreal forest is underlain by discontinuous permafrost, and wildfires are one of the most influential agents negatively impacting the condition of permafrost in the arctic region. Using interferometric synthetic aperture radar (InSAR) of Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) images, we mapped extensive permafrost degradation over interior Alaskan boreal forest in Yukon Flats, induced by the 2009 Big Creek wildfire. Our analyses showed that fire-induced permafrost degradation in the second post-fire thawing season contributed up to 20 cm of ground surface subsidence. We generated post-fire deformation time series and introduced a model that exploited the deformation time series to estimate fire-induced permafrost degradation and changes in active layer thickness. The model showed a wildfire-induced increase of up to 80 cm in active layer thickness in the second post-fire year due to pore-ice permafrost thawing. The model also showed up to 15 cm of permafrost degradation due to excess-ice thawing with little or no increase in active layer thickness. The uncertainties of the estimated change in active layer thickness and the thickness of thawed excess ice permafrost are 27.77 and 1.50 cm, respectively. Our results demonstrate that InSAR-derived deformation measurements along with physics models are capable of quantifying fire-induced permafrost degradation in Alaskan boreal forests underlain by discontinuous permafrost. Our results also have illustrated that fire-induced increase of active layer thickness and excess ice thawing contributed to ground surface subsidence.

Alaska↗

Executive summary. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report

Central to life on Earth, carbon is essential to the molecular makeup of all living things and plays a key role in regulating global climate. To understand carbon’s role in these processes, researchers measure and evaluate carbon stocks and fluxes. A stock is the quantity of carbon contained in a pool or reservoir in the Earth system (e.g., carbon in forest trees), and a flux is the direction and rate of carbon’s transfer between pools (e.g., the movement of carbon from the atmosphere into forest trees during photosynthesis). This document, the Second State of the Carbon Cycle Report (SOCCR2), examines the patterns of carbon stocks and fluxes—collectively called the “carbon cycle.” Emphasis is given to these patterns in specific sectors (e.g., agriculture and energy) and ecosystems (e.g., forests and coastal waters) and to the response of the carbon cycle to human activity. The purpose of SOCCR2 is to assess the current state of the North American carbon cycle and to present recent advances in understanding the factors that influence it. Concentrating on North America—Canada, the United States, and Mexico—the report describes carbon cycling for air, land, inland waters (streams, rivers, lakes, and reservoirs), and coastal waters (see Figure ES.1, p. 23). The questions framing the publication A U.S. Carbon Cycle Science Plan (Michalak et al., 2011) inspired development of three slightly modified questions that guide SOCCR2’s content and focus on North America in a global context: How have natural processes and human actions affected the global carbon cycle on land, in the atmosphere, in the ocean and other aquatic systems, and at ecosystem interfaces (e.g., coastal, wetland, and urban-rural)? How have socioeconomic trends affected atmospheric levels of the primary carbon-containing gases, carbon dioxide (CO2) and methane (CH4)? How have species, ecosystems, natural resources, and human systems been impacted by increasing greenhouse gas (GHG) concentrations, associated changes in climate, and carbon management decisions and practices? SOCCR2 synthesizes the most recent understanding of carbon cycling in North America, assessing new carbon cycle findings and information, the state of knowledge regarding core methods used to study the carbon cycle, and future research needed to best inform carbon management and policy options. Focusing on scientific developments in the decade since the First State of the Carbon Cycle Report (SOCCR1; CCSP 2007), SOCCR2 summarizes the past, current, and projected state of carbon sources, sinks, and natural processes, as well as contributions by human activities. In addition to CO2 and CH4, the report sometimes discusses nitrous oxide (N2O), a GHG associated with activities and processes that affect fluxes of carbon gases.1 SOCCR2 also describes improvements in analysis tools; developments in decision support; and new insights into ecosystem carbon cycling, human causes of changes in the carbon cycle, and social science perspectives on carbon. Since publication of SOCCR1, coordinated research from agencies in the three North American countries has enabled innovative observational, analytical, and modeling capabilities to further advance understanding of the North American carbon cycle (see Appendix D: Carbon Measurement Approaches and Accounting Frameworks, p. 834). Some of the report’s main conclusions, based on the Key Findings of each chapter, are highlighted in Box ES.1, Main Findings of SOCCR2, p. 24.

Report↗

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km 2 ), are influencing and will influence state‐wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO 2 ), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950–2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (−6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010–2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO 2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO 2 , we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO 2 increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO 2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO 2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.

Alaska↗

A carbon balance model for the great dismal swamp ecosystem

Background Carbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting. Results We modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985–2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus. Conclusions Natural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha −1 /year −1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.

North Carolina, Virginia↗

Human footprint affects US carbon balance more than climate change

The MC2 model projects an overall increase in carbon capture in conterminous United States during the 21st century while also simulating a rise in fire causing much carbon loss. Carbon sequestration in soils is critical to prevent carbon losses from future disturbances, and we show that natural ecosystems store more carbon belowground than managed systems do. Natural and human-caused disturbances affect soil processes that shape ecosystem recovery and competitive interactions between native, exotics, and climate refugees. Tomorrow's carbon budgets will depend on how land use, natural disturbances, and climate variability will interact and affect the balance between carbon capture and release.

Book chapter↗

Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010

Background: Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results: Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha−1 yr−1, while agricultural ecosystems sequestered 0.03 Mg C ha−1 yr−1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr−1. Conclusions: Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger. Keywords: Land-use change, Carbon change, Piedmont ecoregion, IBIS model

Carbon Balance and Management↗