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288 result(s) for "704/158/1145"
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Mangrove reforestation provides greater blue carbon benefit than afforestation for mitigating global climate change
Significant efforts have been invested to restore mangrove forests worldwide through reforestation and afforestation. However, blue carbon benefit has not been compared between these two silvicultural pathways at the global scale. Here, we integrated results from direct field measurements of over 370 restoration sites around the world to show that mangrove reforestation (reestablishing mangroves where they previously colonized) had a greater carbon storage potential per hectare than afforestation (establishing mangroves where not previously mangrove). Greater carbon accumulation was mainly attributed to favorable intertidal positioning, higher nitrogen availability, and lower salinity at most reforestation sites. Reforestation of all physically feasible areas in the deforested mangrove regions of the world could promote the uptake of 671.5–688.8 Tg CO 2 -eq globally over a 40-year period, 60% more than afforesting the same global area on tidal flats (more marginal sites). Along with avoiding conflicts of habitat conversion, mangrove reforestation should be given priority when designing nature-based solutions for mitigating global climate change. Blue carbon benefit has not been compared among mangrove reforestation and afforestation pathways at the global scale. This study shows that mangrove reforestation could perform a greater carbon storage potential per hectare than afforestation as its higher nitrogen availability and lower salinity.
Forest expansion dominates China’s land carbon sink since 1980
Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China’s reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting. The impact of land-use and cover-change (LUCC) on ecosystem carbon stock in China is poorly known due to large biases in existing databases. Here the authors develop a new LUCC database with corrected false signals and reveal that forest expansion is the dominant driver of China’s recent carbon sink.
The effectiveness of global protected areas for climate change mitigation
Forests play a critical role in stabilizing Earth’s climate. Establishing protected areas (PAs) represents one approach to forest conservation, but PAs were rarely created to mitigate climate change. The global impact of PAs on the carbon cycle has not previously been quantified due to a lack of accurate global-scale carbon stock maps. Here we used ~412 million lidar samples from NASA’s GEDI mission to estimate a total PA aboveground carbon (C) stock of 61.43 Gt (+/− 0.31), 26% of all mapped terrestrial woody C. Of this total, 9.65 + /− 0.88 Gt of additional carbon was attributed to PA status. These higher C stocks are primarily from avoided emissions from deforestation and degradation in PAs compared to unprotected forests. This total is roughly equivalent to one year of annual global fossil fuel emissions. These results underscore the importance of conservation of high biomass forests for avoiding carbon emissions and preserving future sequestration. Protected areas are important for climate change mitigation. Here, the authors use satellite data and statistical matching to show that terrestrial protected areas have higher C stocks than non-protected areas, roughly equivalent to one year of annual global fossil fuel emissions.
Soil organic carbon is a key determinant of CH4 sink in global forest soils
Soil organic carbon (SOC) is a primary regulator of the forest–climate feedback. However, its indicative capability for the soil CH 4 sink is poorly understood due to the incomplete knowledge of the underlying mechanisms. Therefore, SOC is not explicitly included in the current model estimation of the global forest CH 4 sink. Here, using in-situ observations, global meta-analysis, and process-based modeling, we provide evidence that SOC constitutes an important variable that governs the forest CH 4 sink. We find that a CH 4 sink is enhanced with increasing SOC content on regional and global scales. The revised model with SOC function better reproduces the field observation and estimates a 39% larger global forest CH 4 sink (24.27 Tg CH 4 yr −1 ) than the model without considering SOC effects (17.46 Tg CH 4 yr −1 ). This study highlights the role of SOC in the forest CH 4 sink, which shall be factored into future global CH 4 budget quantification. Soil organic carbon has a positive effect on the removal of methane in forest soils. Global forests are found to be larger sinks of methane than previously estimated when the influence of SOC is considered.
Carbon storage through China’s planted forest expansion
China’s extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China’s planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China’s planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China’s planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr −1 . The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China’s Carbon Neutrality Target for 2060. The dynamics of planted forests in China over the past three decades have contributed ~1198tg of above-ground carbon storage.
More than one quarter of Africa’s tree cover is found outside areas previously classified as forest
The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = −6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.
Global patterns and climatic controls of forest structural complexity
The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes. Forest structure depends both on extrinsic factors such as climate and on intrinsic properties such as community composition and diversity. Here, the authors use a dataset of stand structural complexity based on LiDAR measurements to build a global map of structural complexity for primary forests, and find that precipitation variables best explain global patterns of forest structural complexity.
Maximizing carbon sequestration potential in Chinese forests through optimal management
Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1–3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement. The authors show China’s forests can sequester 172.3 million tons of carbon per year in biomass by 2100, with an additional 28.1 million tons from improved management practices, but neglecting wood harvest impacts will distort long-term future projections.
Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms
Forest aboveground biomass (AGB) plays an important role in the study of the carbon cycle and climate change in the global terrestrial ecosystem. AGB estimation based on remote sensing is an effective method for regional scale. In this study, Landsat 8 Operational Land Imager and Sentinel-1A data and China’s National Forest Continuous Inventory data in combination with three algorithms, either the linear regression (LR), random forest (RF), or the extreme gradient boosting (XGBoost), were used to estimate biomass of the subtropical forests in Hunan Province, China. XGBoost is a scalable tree boosting system that is widely used by data scientists and provides state-of-the-art results for many problems. It can process an entire dataset with billions of examples using a minimal amount of computational resources through the particular way of cache access patterns, data compression, and data fragmentation. The results include: (1) The combination of Landsat 8 and Sentinel-1A images as predictor variables in the XGBoost model provided the best AGB estimation. (2) In contrast to the LR method, the F-test results indicated that a significant improvement in AGB estimation was achieved with the RF and XGBoost algorithms. (3) The effect of parameter optimization was found to be more significant on XGBoost than on RF. (4) The XGBoost model is an effective method for AGB estimation and can reduce the problems of overestimation and underestimation. This research provides a new way of estimating AGB for the subtropical forest based on remote sensing through the synergy of different sensors datasets and modeling algorithms.
Systematic assessment of the achieved emission reductions of carbon crediting projects
Carbon markets play an important role in firms’ and governments’ climate strategies. Carbon crediting mechanisms allow project developers to earn carbon credits through mitigation projects. Several studies have raised concerns about environmental integrity, though a systematic evaluation is missing. We synthesized studies relying on experimental or rigorous observational methods, covering 14 studies on 2346 carbon mitigation projects and 51 studies investigating similar field interventions implemented without issuing carbon credits. The analysis covers one-fifth of the credit volume issued to date, almost 1 billion tons of CO 2 e. We estimate that less than 16% of the carbon credits issued to the investigated projects constitute real emission reductions, with 11% for cookstoves, 16% for SF 6 destruction, 25% for avoided deforestation, 68% for HFC-23 abatement, and no statistically significant emission reductions from wind power and improved forest management projects. Carbon crediting mechanisms need to be reformed fundamentally to meaningfully contribute to climate change mitigation. Carbon markets are key in climate strategies, but only 16% of carbon credits represent real emission reductions, based on a study of 2,346 projects. Reforms are needed to improve the effectiveness of carbon crediting mechanisms in addressing climate change.