Changes In Forest Carbon Research Articles

Spatial and Temporal Patterns of Forest Biomass Carbon Sink in China from 1990 to 2021

China’s forests act as a large carbon sink and play a vital role in achieving the carbon neutrality goal by the 2060s. To achieve this goal, the magnitude and spatial patterns of forest carbon sinks must be accurately quantified. In this study, we aim to provide the longest estimate of forest biomass carbon storage and sinks in China at a 1 km spatial resolution from 1990 to 2021 by merging long-term observations from optical and microwave remote sensing datasets with a field-validated benchmark map. We explored the spatial characteristics of aboveground biomass (AGB) and belowground biomass (BGB) carbon in China’s forests, as well as variations in AGB carbon sinks. The average AGB and BGB carbon storage from 1990 to 2021 in China’s forests were 8.42 ± 0.96 Pg C and 1.9 ± 0.21 Pg C, respectively. The average annual AGB carbon sink during this period was approximately 0.083 ± 0.023 Pg C yr−1. Forests in the southwest region contributed 31.15% of the forest AGB carbon sink in China and contributed 41.01% of the forest AGB carbon storage. Our study presents an effective tool for assessing changes in forest biomass carbon by leveraging comprehensive multi-source remote sensing data and highlights the importance of obtaining large-scale, high-quality, consistent, and accessible plot survey data to validate the earth observation of biomass.

Forest Restoration Thinning Has Minimal Impacts on Surface Soil Carbon in a Second-Growth Temperate Rainforest

Forest restoration thinning may accelerate the development of structural complexity toward old-growth conditions faster than a natural forest, yet associated changes in forest carbon (C) are poorly understood. Old-growth forests are characterized by high levels of sequestered C in aboveground biomass and soil C pools, yet active management has well-recognized negative impacts on stored C. Effects of forest restoration thinning on forest C can be determined using longitudinal measurements and modeling based on stand conditions and tree growth. At Ellsworth Creek Preserve in Southwest Washington, forest restoration efforts in a second-growth temperate rainforest have been monitored using permanent plots since 2007. Here, we compare repeat measurements from 2020, modeled forest C, and measurements of O-horizon C pools from 2022 to determine C impacts of silvicultural treatments for old-growth restoration. We found good general agreement between empirical measurements and models of forest C using the Forest Vegetation Simulator (FVS). However, treatment alone was not a strong indicator for C conditions; rather, forest age and age–treatment interactions better predicted soil C responses to restoration treatments. These data may indicate that “light” forest restoration thinning can accelerate old-growth development with minimal effects on soil carbon—a win-win conservation strategy for old-growth forests and the climate.

Leveraging climate and remote sensing metrics for predicting forest carbon stock using Bayesian geostatistical modelling under a projected climate warming in Zimbabwe

Climate change, driven by escalating carbon dioxide (CO2) emissions, poses a significant threat to forest ecosystems and the livelihoods of communities reliant on them, especially for the global south countries and regions like the eastern highlands of Zimbabwe. The 2000 land redistribution programme reduced buffer zones between ecologically sensitive forests and land reform beneficiaries near major carbon reservoirs. In light of these challenges, this study aimed to assess the potential effects of climate change on a strategically important plantation forest ecosystem in Zimbabwe's eastern highlands. Using data from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) of the Intergovernmental Panel on Climate Change (IPCC), we modelled and predicted changes in forest carbon (C) stock density under different climate scenarios: current (1970–2000), SSP5–4.5, and SSP5–8.5. Employing a hierarchical Bayesian geostatistical approach, we compared the baseline scenario (1970–2000) with projected scenarios (RCP4.5 and RCP8.5) for 2075 to estimate changes in forest carbon stock distribution. Our results indicated a decline in carbon stock concentration under future climate scenarios, reflecting the adverse impact of greenhouse gas emissions on forest growth. We found that the projected range of forest carbon stock under the RCP8.5 scenario for 2075 is notably lower (2≤MgCha−1≤44.9) than that of the baseline period (1970–2000) (1≤MgCha−1≤97), suggesting a substantial reduction in carbon storage. As the difference in posterior mean C stock (μ̅1−μ̅2), 52.1 MgCha-1 is well above zero, we deduce that the posterior mean C stock distribution of the projected future RCP8.5 2075 climate projection is indeed credibly different from the current (1970–2000) climate scenario. Additionally, there is a high probability (>90%) that forest plantations will be adversely affected by the business-as-usual climate warming projection. Overall, our findings highlight the urgent need for climate change mitigation strategies, such as reforestation programs and careful selection of tree species for plantations, to safeguard forest ecosystems and the communities dependent on them. These insights are crucial for informing effective adaptation measures in the face of future climate uncertainties.

Calculating a Land Carbon Accounting Factor in the United States: an Example and Implications

Abstract Companies that produce and use wood for products and energy find it increasingly important to communicate the carbon balance and potential climate effects of these activities. Computing forest carbon stocks and stock changes, and emissions from operations, are often part of institutional reporting for environmental, social, and governance purposes. This article describes an example methodology to assess forest carbon changes associated with the harvesting of wood products and proposes metrics that could be used to allocate harvesting effects to individual organizations for their reporting purposes. We discuss boundaries (types of forests and carbon pools to include), spatially appropriate evaluations given uncertainty, temporal considerations, risk of reversals, and allocation of net sequestration to products sourced from the region. We also discuss the complex nature of the biogenic carbon cycle and warn about the appropriate interpretation of this methodology.

Aboveground live tree carbon stock and change in forests of conterminous United States: influence of stand age

BackgroundSequestration of carbon on forest land is a common and practical component within many climate action plans developed by state or municipal governments. Initial planning often identifies the general magnitude of sequestration expected given the scope of the project. Because age plays a key role in forest carbon dynamics, we summarize both the carbon stock and accumulation rates in live trees by age class and region, allowing managers and policymakers to assess the influence of forest age class structure on forest carbon storage as represented in current inventories. State-level information is provided in supplementary tables.ResultsAverage regional aboveground live tree carbon stocks (represented on a per area basis) range from 11.6 tC/ha in the Great Plains to 130 tC/ha in the Pacific Northwest West (west-side of Cascades) and increase with age in all regions, although in three regions carbon stock declined in the oldest age class. Regional average annual net change in live aboveground tree carbon varies from a low of − 0.18 tC /ha/yr in the Rocky Mountain South region to a high value of 1.74 tC/ha/yr in Pacific Northwest West. In all regions except Rocky Mountain South, accumulation rates are highest in the younger age classes and decline with age, with older age classes in several western regions showing negative rates. In the Southeast and Pacific Northwest West, intermediate age classes exhibit lower rates, likely due to harvesting activity.ConclusionsAboveground live tree carbon stocks increase and rates of average change decrease with age with few exceptions; this pattern holds when examining hardwood and softwood types individually. Because multiple forest management objectives are often considered and tradeoffs need to be assessed, we recommend considering both measures—standing stock and average annual change—of carbon storage. The relative importance of each component depends on management and policy objectives and the time frame related to those objectives. Harvesting and natural disturbance also affect forest carbon stock and change and may need to be considered if developing projections of potential carbon storage. We present forest carbon summaries at a scale and scope to meet information needs of managers and policymakers.

Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years

Abstract. To quantify the ecological consequences of recent nationwide restoration efforts in China, spatially explicit information on forest biomass carbon stock changes over the past 20 years is critical. However, long-term biomass tracking at the national scale remains challenging as it requires continuous and high-resolution monitoring. Here, we characterize the changes in the above- and belowground biomass carbon (AGBC and BGBC) of forests in China between 2002 and 2021 at 1 km spatial resolution by integrating multiple types of remote sensing observations with intensive field measurements through regression and machine learning approaches. On average, 8.6 ± 0.6 and 2.2 ± 0.1 PgC were stored in above- and belowground live forests in China. Over the last 20 years, the total forest biomass carbon pool in China has increased at a rate of 114.5 ± 16.3 TgC yr−1 (approximately 1.1 % yr−1). The most pronounced forest biomass carbon stock gains occurred in central to southern China, including the southern Loess Plateau, Qinling mountains, southwestern karsts and southeastern forests. While the combined use of multi-source remote sensing data provides a powerful tool to assess the forest biomass carbon changes, future research is also needed to explore the drivers of the observed woody biomass trends and to evaluate the degree to which biomass gains will translate into biodiverse, healthy ecosystems that are sustainable. Annual forest above- and belowground biomass maps for China are now available at https://doi.org/10.6084/m9.figshare.21931161.v1 (Chen, 2023).

Improving a Process-Based Model to Simulate Forest Carbon Allocation under Varied Stand Density

Carbon allocation is an important mechanism through which plants respond to environmental changes. To enhance our understanding of maximizing carbon uptake by controlling planting densities, the carbon allocation module of a process-based model, TRIPLEX-Management, was modified and improved by introducing light, soil water, and soil nitrogen availability factors to quantify the allocation coefficients for different plant organs. The modified TRIPLEX-Management model simulation results were verified against observations from northern Jiangsu Province, China, and then the model was used to simulate dynamic changes in forest carbon under six density scenarios (200, 400, 600, 800, 1000, and 1200 stems ha−1). The mean absolute errors between the predicted and observed variables of the mean diameter at breast height, mean height, and estimated aboveground biomass ranged from 15.0% to 26.6%, and were lower compared with the original model simulated results, which ranged from 24.4% to 60.5%. The normalized root mean square errors ranged from 0.2 to 0.3, and were lower compared with the original model simulated results, which ranged from 0.3 to 0.6. The Willmott index between the predicted and observed variables also varied from 0.5 to 0.8, indicating that the modified TRIPLEX-Management model could accurately simulate the dynamic changes in poplar (Populus spp.) plantations with different densities in northern Jiangsu Province. The density scenario results showed that the leaf and fine root allocation coefficients decreased with the increase in stand density, while the stem allocation increased. Overall, our study showed that the optimum stand density (approximately 400 stems ha−1) could reach the highest aboveground biomass for poplar stands and soil organic carbon storage, leading to higher ecological functions related to carbon sequestration without sacrificing wood production in an economical way in northern Jiangsu Province. Therefore, reasonable density control with different soil and climate conditions should be recommended to maximize carbon sequestration.

Making the US national forest inventory spatially contiguous and temporally consistent

Signatories to the United Nations Framework Convention on Climate Change (UNFCCC) are required to annually report economy-wide greenhouse gas emissions and removals, including the forest sector. National forest inventory (NFI) is considered the main source of data for reporting forest carbon stocks and changes to UNFCCC. However, NFI samples are often collected asynchronously across regions in intervals of 5–10 years or sub-sampled annually, both introducing uncertainties in estimating annual carbon stock changes by missing a wide range of forest disturbance and recovery processes. Here, we integrate satellite observations with forest inventory data across the conterminous United States to improve the spatial and temporal resolution of NFI for estimating annual carbon stocks and changes. We used more than 120 000 permanent plots from the US forest inventory and analysis (FIA) data, surveyed periodically at sampling rate of 15%–20% per year across the US to develop non-parametric remote sensing-based models of aboveground biomass carbon density (AGC) at 1 ha spatial resolution for the years 2005, 2010, 2015, 2016, and 2017. The model provided a relatively unbiased estimation of AGC compared to ground inventory estimates at plot, county, and state scales. The uncertainty of the biomass maps and their contributions to estimates of forest carbon stock changes at county and state levels were quantified. Our results suggest that adding spatial and temporal dimensions to the forest inventory data, will significantly improve the accuracy and precision of carbon stocks and changes at jurisdictional scales.

Rapid remote monitoring reveals spatial and temporal hotspots of carbon loss in Africa\u2019s rainforests

Spatially explicit monitoring of tropical forest aboveground carbon is an important prerequisite for better targeting and assessing forest conservation efforts and more transparent reporting of carbon losses. Here, we combine near-real-time forest disturbance alerts based on all-weather radar data with aboveground carbon stocks to provide carbon loss estimates at high spatial and temporal resolution for the rainforests of Africa. We identified spatial and temporal hotspots of carbon loss for 2019 and 2020 for the 23 countries analyzed, led by different drivers of forest disturbance. We found that 75.7% of total annual carbon loss in the Central African Republic happened within the first three months of 2020, while 89% of the annual carbon loss in Madagascar occurred within the last five months of 2020. Our detailed spatiotemporal mapping of carbon loss creates opportunities for much more transparent, timely, and efficient assessments of forest carbon changes both at the level of specific activities, for national-level GHG reporting, and large area comparative analysis.

Global sensitivities of forest carbon changes to environmental conditions.

The responses of forest carbon dynamics to fluctuations in environmental conditions at a global scale remain elusive. Despite the understanding that favourable environmental conditions promote forest growth, these responses have been challenging to observe across different ecosystems and climate gradients. Based on a global annual time series of aboveground biomass (AGB) estimated from radar satellites between 1992 and 2018, we present forest carbon changes and provide insights on their sensitivities to environmental conditions across scales. Our findings indicate differences in forest carbon changes across AGB classes, with regions with carbon stocks of 50-125MgC ha-1 depict the highest forest carbon gains and losses, while regions with 125-150MgC ha-1 have the lowest forest carbon gains and losses in absolute terms. Net forest carbon change estimates show that the arc-of-deforestation and the Congo Basin were the main hotspots of forest carbon loss, while a substantial part of European forest gained carbon during the last three decades. Furthermore, we observe that changes in forest carbon stocks were systematically positively correlated with changes in forest cover fraction. At the same time, it was not necessarily the case with other environmental variables, such as air temperature and water availability at the bivariate level. We also used a model attribution method to demonstrate that atmospheric conditions were the dominant control of forest carbon changes (56% of the total study area) followed by water-related (29% of the total study area) and vegetation (15% of the total study area) conditions. Regionally, we find evidence that carbon gains from long-term forest growth covary with long-term carbon sinks inferred from atmospheric inversions. Our results describe the contributions from the atmosphere, water-related and vegetation conditions to forest carbon changes and provide new insights into the underlying mechanisms of the coupling between forest growth and the global carbon cycle.

Spatially explicit changes in forest biomass carbon of China over the past 4 decades: Coupling long-term inventory and remote sensing data

Quantification of the spatial pattern of forest carbon (C) sinks in high resolution is helpful to reveal the factors that affect the C cycle and provides valuable information for developing sustainable forest management policies. Here we developed a method using the data of long-term forest inventories (1977–2018) and spatially-explicit remotely sensed information from land-use maps and the Normalized Difference Vegetation Index (NDVI) datasets, to estimate the spatial and temporal variation of forest biomass C in China. At first, we calculated forest biomass C stocks using the refined Continuous Biomass Expansion Factor (CBEF) model with parameters for each forest type based on eight national forest inventories. Secondly, based on multi-temporal land-use remote sensing and national forest inventory datasets, we obtained forest coverage datasets with high resolution (1 km*1 km). Thirdly, we downscaled the forest biomass C density using the calibrated forest coverage maps and the maximum NDVI values derived from GIMMS-NDVI3g imagery. Our results showed that China's forest functioned as a C sink of 3777.73 Tg C, and the C density of forest stands increased from 35.41 Mg C ha−1 during 1977–1981 to 43.95 Mg C ha−1 during 2014–2018. In addition, the validation results for most of the provinces based on published inventory estimates during the eight periods showed that the forest area at the pixel scale was successfully calibrated. From this, we produced the maps with a finer resolution for a series of spatially continuous forest biomass carbon density distribution and carbon sinks. Notably eight major forest projects have accounted for 44%–51% of the forest C stocks added in China from 1977 to 2018. Our research provides new insights for understanding and monitoring the spatiotemporal variations in of forest biomass and key information to support the development of new afforestation policies moving forward.

Variation in trunk taper of buttressed trees within and among five lowland tropical forests

AbstractAccurately projecting global carbon dynamics requires understanding controls over temporal and spatial tropical forest biomass variation. Changes in tropical forest aboveground biomass per area are most commonly estimated using repeat forest plot censuses, but errors in these estimates can be relatively large, limiting our ability to detect real changes in forest carbon. One source of error is nonstandard heights of diameter measurement, which are common in tropical forests because buttressed trees are usually measured above buttresses. Nonstandard and temporally variable measurement heights affect biomass change estimates because tree trunks taper—higher measurements result in smaller diameters and, thus, smaller estimated biomass. Modeling trunk taper is a potential way to correct for biases associated with nonstandard and changing measurement heights. We measured trunk taper for 260 buttressed trees in five lowland tropical forests to assess variation in taper within and among sites. Trunks taper more slowly in trees with larger diameters above buttress, taller buttresses, and higher wood density; these variables together explain 29% of taper variation. We also used plot data to quantify the distribution of measurement heights—and potential for bias in biomass estimates. We found significant variation in measurement heights among plots, and over time within plots. At the site level, our general taper model (taper predicted from diameter above buttress, buttress height, and wood density) produced site‐level biomass estimates within 3.4%, on average, of estimates from measured taper. We recommend using this model to reduce bias from nonstandard measurement heights in studies of tropical forest biomass variation.Abstract in Spanish is available with online material.

Current aboveground live tree carbon stocks and annual net change in forests of conterminous United States

BackgroundWith the introduction of the Trillion Trees Initiative and similar programs, forests’ ability to absorb carbon dioxide is increasingly in the spotlight. Many states have mandates to develop climate action plans, of which forest carbon is an important component, and planners need current information on forest carbon stocks and rates of change at relevant spatial scales. To this end, we examine rates of average annual change in live aboveground tree carbon in different forest type groups and provide state-wide and regional summaries of current live tree carbon stock and rates of change for the forests of the conterminous United States. Forest carbon summaries are presented in a format designed to meet the needs of managers, policymakers, and others requiring current estimates of aboveground live tree carbon at state and regional scales.ResultsRegional average aboveground live tree carbon stocks (represented on a per area basis) are generally between 40 and 75 tC/ha but range from 12.8 tC/ha in the Great Plains to 130 tC/ha in the Pacific Northwest West (west-side of Cascades). Regional average annual change in live aboveground tree carbon varies from a low of − 0.18 mtC/ha/y in the Rocky Mountain South to a high value of 1.74 mtC/ha/y in Pacific Northwest West. For individual states, carbon per unit area varies widely, from a low of 11.9 tC/ha in Nevada to a high of 96.4 tC/ha in Washington, with half the states falling between 50 and 75 tC/ha. Rates of average annual change in live aboveground tree carbon vary from a high of 1.82 tC/ha/y in Mississippi to a low of − 0.47 tC/ha/y in Colorado.ConclusionsAboveground live tree carbon stocks and rates of average annual change vary by forest type within regions. While softwood forest types currently exhibit a higher rate of increase in the amount of carbon in aboveground live tree biomass, the current standing stock of carbon per unit area does not consistently follow this pattern. For this reason, we recommend computing and considering both measures -standing stock and average annual change—of carbon storage. The relative importance of each component will depend on management and policy objectives and the time frame related to those objectives. Harvesting and natural disturbance also affect forest carbon stock and change and may need to be considered if developing projections of potential carbon storage.

Reducing Global Environmental Uncertainties in Reports of Tropical Forest Carbon Fluxes to REDD+ and the Paris Agreement Global Stocktake

The magnitude of net carbon dioxide emissions resulting from global forest carbon change, and hence the contribution of forests to global climate change, is highly uncertain, owing to the lack of direct measurement by Earth observation and ground data collection. This paper uses a new method to evaluate this uncertainty with greater precision than before. Sources of uncertainty are divided into conceptualization and measurement categories and distributed between the spatial, vertical and temporal dimensions of Earth observation. The method is applied to Forest Reference Emission Level (FREL) reports and National Greenhouse Gas Inventories (NGGIs) submitted to the UN Framework Convention on Climate Change (UNFCCC) by 12 countries containing half of tropical forest area. The two sets of estimates are typical of those to be submitted to the Reducing Emissions from Deforestation and Degradation (REDD+) mechanism of the UNFCCC and the 2023 Global Stocktake of its Paris Agreement, respectively. Assembling the Uncertainty Fingerprint of each estimate shows that Uncertainty Scores are between 10 and 14 for the NGGIs and 5 and 10 for the FREL reports, and so both exceed the threshold of 2 when it is advisable to evaluate uncertainty by standard statistical methods. Conceptualization uncertainties account for 60% of all uncertainties in the NGGIs and 47% in the FREL reports, e.g., there is incomplete coverage of forest carbon fluxes, and limited disaggregation of fluxes between different ecosystem types and forest carbon pools. Of the measurement uncertainties, all FREL reports base forest area estimates on at least medium resolution satellite data, compared with only 3 NGGIs; after REDD+ Readiness schemes, mean area mapping frequency has fallen to 2.3 years in Latin America and 3.0 years in Asia, but only 8.3 years in Africa; and carbon density estimates are based on national forest inventory data in all FREL reports but only 4 NGGIs. The effectiveness of the Global Stocktake and REDD+ monitoring will therefore be constrained by considerable uncertainties, and to reduce these requires a new phase of REDD+ Readiness to ensure more frequent national forest inventories and forest carbon mapping.

Comparación de modelos de altura de la vegetación para estimación de biomasa en un bosque de manglar en el Caribe Colombiano

Este trabajo integra satélite-LIDAR para comparar la evaluación de stock de carbono en alta resolución en un bosque de manglar (Rincón Mosquito) en la zona costera del mar Caribe. Se comparó la altura de vegetación resultante de la extracción de un modelo de altura de la vegetación satelital EROS-B y un LIDAR aerotransportado vs datos en campo. Los satélites ofrecen una oportunidad de monitorear cambios en el carbono forestal causados por la deforestación y la degradación, igual que nuevos métodos aéreos, especialmente el método LIDAR, ofrecen una forma de estimar la densidad del carbono forestal, lo cual ayuda en el desarrollo de líneas base para inventarios de carbono. Luego de calcular la biomasa total desde los datos de satélite y LIDAR, se comparó la medida de biomasa tomada en campo. En términos de escalas detalladas se puede concluir que el sensor con mayor precisión es el LIDAR al tener un nivel de resolución espacial que permite gran detalle de la masa arbórea., El uso de estéreo pares satelitales es viable en grandes extensiones y no en pequeñas áreas, donde particularmente en los últimos años, los datos tomados con vehículos aéreos no tripulados parecen ser una alternativa más viable en disponibilidad y costo.

Analysis of broad leaved forest carbon sinks changes and forest economics and management in China

The international community is paying more and more attention to the role of forests in CO2 absorption. This study aims the broad leaved forest carbon sinks in China, on the basis of research on coniferous forest carbon sinks in 1981 and 2014, the paper analyses the changes in broad leaved forest carbon sinks and the relations between the changes and the forest economics and management from 1981 to 2015 using the forest stock volume conversion method. The paper selects the common indexes of forest economics and management such as investment in forestry-fixed assets in silviculture and afforestation, the annual gross domestic product (GDP) values for the forestry sector, and management level improvement. The paper first of all establishes carbon sink estimates, and then analyses recent carbon sink trends of the dominant species of broad leaved forest which is based on six times inventories of China's forest resources. The inventory data cover the four dominant broad-leaved species which are named as Oak, Betula, Populus, and others, such as Eucalyptus, Camphor, and Linden. The paper shows that a significant effect has been made by the forest carbon sinks of these species and investment in forestry-fixed assets in silviculture and afforestation, management level improvement etc. though with a lag of 4-7years, and there raises a lot of discussions of various problems regarding forest carbon sinks and forest management and economic development. This study has important implications for forest resource management and climate change mitigation.

Projected social costs of CO2 emissions from forest losses far exceed the sequestration benefits of forest gains under global change

Forest cover gains and losses occur in response to complex environmental and anthropogenic pressures. Yet the impact of forest gains and losses on the provision of ecosystem services differs markedly. Here we investigate the social costs of potential forest carbon change in Australia’s intensive agricultural region from 2015 to 2050 using spatial forest cover change and forest carbon models combined with climate and socioeconomic projections. More than 24,000 possible scenarios were used to identify the trend and lower and upper bounds of forest cover/carbon change. Net deforestation (3.5 million hectares, Mha) under the lower bound forest cover (LBFC) projection was around one-third less than net reforestation (4.8 Mha) under the upper bound forest cover (UBFC) projection by 2030. However, the CO2 emissions (1.3 Gigatons of CO2, GtCO2) from deforestation were more than double the sequestration (0.5 GtCO2) from reforestation. The social costs (up to 134 billion dollars) of the LBFC were almost five times the benefits of the UBFC (up to 28 billion dollars). The asymmetry decreased over time but persisted to 2050. This shows the markedly different social costs of potential forest carbon losses and gains under global change, evidence which can be useful to policymakers, stakeholders, and practitioners.

Comment on "Tropical forests are a net carbon source based on aboveground measurements of gain and loss".

Baccini et al (Reports, 13 October 2017, p. 230) report MODIS-derived pantropical forest carbon change, with spatial patterns of carbon loss that do not correspond to higher-resolution Landsat-derived tree cover loss. The assumption that map results are unbiased and free of commission and omission errors is not supported. The application of passive moderate-resolution optical data to monitor forest carbon change overstates our current capabilities.

Forest Carbon Gain and Loss in Protected Areas of Uganda: Implications to Carbon Benefits of Conservation

Uganda designated 16% of its land as Protected Area (PA). The original goal was natural resources, habitat and biodiversity conservation. However, PAs also offer great potential for carbon conservation in the context of climate change mitigation. Drawing on a wall-to-wall map of forest carbon change for the entire Uganda, that was developed using two Digital Elevation Model (DEM) datasets for the period 2000–2012, we (1) quantified forest carbon gain and loss within 713 PAs and their external buffer zones, (2) tested variations in forest carbon change among management categories, and (3) evaluated the effectiveness of PAs and the prevalence of local leakage in terms of forest carbon. The net annual forest carbon gain in PAs of Uganda was 0.22 ± 1.36 t/ha, but a significant proportion (63%) of the PAs exhibited a net carbon loss. Further, carbon gain and loss varied significantly among management categories. About 37% of the PAs were “effective”, i.e., gained or at least maintained forest carbon during the period. Nevertheless, carbon losses in the external buffer zones of those effective PAs significantly contrast with carbon gains inside of the PA boundaries, providing evidence of leakage and thus, isolation. The combined carbon losses inside the boundaries of a large number of PAs, together with leakage in external buffer zones suggest that PAs, regardless of the management categories, are threatened by deforestation and forest degradation. If Uganda will have to benefit from carbon conservation from its large number of PAs through climate change mitigation mechanisms such as REDD+, there is an urgent need to look into some of the current PA management approaches, and design protection strategies that account for the surrounding landscapes and communities outside of the PAs.

Divergent temporal trends of net biomass change in western Canadian boreal forests

Abstract Forests play a strong role in the global carbon cycle by absorbing atmospheric carbon dioxide through increasing forest biomass. Understanding temporal trends of forest net above‐ground biomass change (ΔAGB) can help infer how forest carbon sequestration responds to ongoing climate changes. Despite wide spatial variation in the long‐term average of climate moisture availability (CMIaverage) across forest ecosystems, temporal trends of ΔAGB associated with CMIaverage remain unclear. We tested the hypothesis that the negative impacts of climate change on ΔAGB would decrease with CMIaverage using the data from permanent sample plots, monitored from 1958 to 2011, with stand ages varying from 17 to 210 years, in western boreal forests of Canada. We found that ΔAGB on average increased with CMIaverage. Temporally, ΔAGB declined sharply between 1958 and 2011 in plots with low CMIaverage owing to increased biomass loss from mortality accompanied by little growth gain, whereas ΔAGB changed little in plots with high CMIaverage. The temporal decrease of ΔAGB in drier areas was attributable to its negative responses to warming‐induced temporal decreases in climate moisture availability. Synthesis. Our results indicate that large‐scale changes in forest carbon functioning associated with climate change depend on the long‐term average of climate moisture availability. Our finding suggests a possible retreat of boreal biome at the drier distribution limits with predicted declines in water availability in the 21st century.