Aboveground Biomass Carbon Research Articles

Biochar Effects on Carbon Stocks in the Coffee Agroforestry Systems of the Himalayas

Coffee agroforestry is an emerging agricultural practice in the mid hills of Nepal. Smallholder farmers of low-income strata have progressively adopted coffee as a perennial crop over seasonal crops. A multi-year study was conducted to test effects of locally produced biochar derived from coffee wastes, e.g., pulp and husks, on carbon stocks of: i) coffee trees, and, ii) soil organic carbon (SOC) in selected coffee growing pockets. We conducted on-farm experimental trials in three different physiographical locations of the Nepal mid-hills, namely, Chandanpur (Site I at 1475masl), Panchkhal (Site II at 1075masl), and Talamarang (Site III at 821masl) where smallholders grow coffee together with other cereal crops and vegetables. We applied biochar to the soil at a rate of 5 Mgha-1, then, monitored the SOC and biomass growth of the coffee trees in the three treatment plots at sites I, II and III over two years beginning in 2013. The average stocks of aboveground carbon in coffee trees increased from 6.2±4.3 Mgha-1 to 9.1±5.2 Mgha-1 over the trial period of two years in biochar treated plots. The same in control plots increased from 5.6±2.8 Mgha-1 to 6.7±4.7 Mgha-1. In the biochar plots, the average increments of ABG carbon was 0.73 Mgh-1 while in the control it was 0.29 Mgh-1. Analysis of soil organic carbon of the plots indicated overall incremental change in carbon stocks in the coffee farms. During the base year, the average SOC stocks in the top 0-15cm layer of the soil at sites I, II, and III were estimated 74.88 ± 15.93; 63.96 ±16.71 and 33.05 ±4.42 Mgha-1 respectively. Although both the biochar treated and control plot registered incremental change in SOC stocks, the volumes were remarkably higher in the former than the latter. Compared to the baseline data, the changes in SOC stocks in the three biochar treated plots were 19.8, 49.8 and 45.3 Mgha-1, respectively, whereas in the control plots these were 8.3, 29.3 and 11.3 Mgha-1, respectively. The higher incremental rates of C-stocks in all the biochar treated plots in comparison to the corresponding control plots of the coffee agroforestry implies that application of biochar can enhance accumulation of carbon in the form of aboveground biomass and soil organic carbon.

Efecto de la riqueza de especies y la estructura de la vegetación en el almacenamiento de carbono en sistemas agroforestales en la Amazonía sur de Bolivia

Diverse agroforestry systems conciliate food production, biodiversity conservation, and the provision of ecosystem services as atmospheric carbon sequestration. However, the role of floristic richness in the production of biomass in these systems is not clear. This study evaluated the effect of species richness and vegetation structure on aboveground biomass carbon in different agroforestry systems in the Southern Amazon of Bolivia. For that, 25 agroforestry systems and 4 secondary forests were studied in the departments of Santa Cruz and Beni. In each system, a 1 963 m2 circular plot was installed, where the vegetation (trees, shrubs and herbaceous) and necromass (leaf litter, branches and dead trees) were sampled. Linear and logarithmic functions were used to evaluate the effect of vegetation richness and structure on carbon, and the variance partition was used to examine the pure and shared effect of the richness and vegetation structure variables on carbon. Regressions showed a positive strong relationship between species richness and carbon (r2 = 0.74; P < 0.001). The partition of carbon variance showed that richness, structure and variation of the structure explained 85.7 %. Alone the richness explained 12.7 %, the structure 8.8 % and the variation of the structure 4.8 %. These results confirm that carbon in the aboveground biomass increases with species richness and structural variation of the vegetation. Therefore, more biodiverse and stratified agroforestry systems are more efficient in the use of resources and can contribute with climate change mitigation.

Structure and activity of soil microbial communities in three Mediterranean forests

The effect of plant cover on soil microbial community structure and activity was investigated in forest ecosystems dominated by holm oak (Quercus ilex), Turkey oak (Quercus cerris) and beech (Fagus sylvatica), in two seasons (autumn and early summer). Microbial community structure was investigated by phospholipid fatty acid (PLFA) profile and ergosterol determination. Microbial community activity was assessed by fluorescein diacetate hydrolisys, β-glucosidase and cellulase activities. The Turkey oak forest showed the lowest soil microbial biomass, both as total and specific PLFA markers. PLFA profile showed a different microbial community structure among forest soils, mainly between the two oak systems. Enzyme activities were affected by soil organic carbon content, with the lowest values measured in Turkey oak. A seasonal effect both on microbial biomass and on enzyme activity was generally observed. Among the investigated forest systems, the beech forest appeared to store more carbon both in aboveground biomass and in soil.

Operationalizing Blue Carbon in the Mission-Aransas National Estuarine Research Reserve, Texas

Recently, greater interest in the resilience of coastal habitat ecosystem services in the northern Gulf of Mexico has emerged due in part to an expansion of mangroves into areas previously dominated by salt marshes. To operationalize coastal wetland ecosystem services for decision-making, there is a need to clarify how salt marshes and mangroves function in this region. The goal of this research is to operationalize blue carbon (carbon stored in coastal habitats) within the Mission-Aransas National Estuarine Research Reserve, TX by documenting what we know about blue carbon within the study area, identifying data gaps and future research needs, and using available knowledge to inform management and decision-making within the Reserve. Our research shows that there is a lack of data within the Reserve on mangrove aboveground biomass, belowground biomass and soil carbon and on salt marsh soil carbon. There is also a dearth of information on wetland carbon sequestration and emission rates within the Reserve, making it challenging to inform management and develop a market for blue carbon.

Analysis of Carbon Storage and Its Contributing Factors—A Case Study in the Loess Plateau (China)

The Chinese Loess Plateau is an ecologically fragile and sensitive area. The carbon storage dynamics in this region and the contributions from land use/land cover change (LUCC) and carbon density from 2000 to 2010 were analyzed in this paper. Normalized difference vegetation index (NDVI), biomass and soil carbon data in 2000 were used for regression analysis of biomass and soil carbon, and an inversion analysis was used to estimate biomass and soil carbon in 2005 and 2010. Quadrat data, including aboveground biomass and soil organic carbon, were used to calibrate the model output. Carbon storage and sequestration were calculated by the InVEST toolset with four carbon pools, including aboveground biomass, belowground biomass, dead wood and soil carbon. The results showed that carbon storage increased steadily from 2000 to 2010, increasing by 0.260 billion tons, and that woodland area increased and arable land decreased; the overall trend in land cover improved, but the improvement was not pronounced. Carbon storage in the Loess Plateau was correlated with geographical factors. We found that when assuming a constant carbon density, carbon storage decreased, accounting for −1% of the carbon storage dynamics. When assuming no land conversion, carbon storage increased, accounting for 101% of the carbon storage dynamics.

Low blue carbon storage in eelgrass (Zostera marina) meadows on the Pacific Coast of Canada.

Seagrass habitats provide important ecosystem services, including their ability to take up and store substantial amounts of organic carbon, known as ‘blue carbon.’ However, the paucity of geospatial and carbon storage information along the Pacific Coast of Canada hinders the inclusion of blue carbon storage data in conservation planning and policy development in coastal habitats. We assessed the carbon storage and accumulation rates in three eelgrass (Zostera marina) meadows in southern Clayoquot Sound on the Pacific Coast of British Columbia. The intertidal and subtidal portions of each meadow were mapped and sampled to estimate eelgrass density, biomass, and carbon, and sediment cores were analyzed to estimate sediment carbon storage and accumulation rates. Aboveground biomass measurements were consistent with estimates for Z. marina in other regions, with average aboveground carbon biomass estimates of 16.78 g C m-2 and 16.25 g C m-2 in the intertidal and subtidal areas, respectively. However, the estimated aboveground to belowground biomass ratio was an order of magnitude higher than for seagrass species in temperate/tropical areas, largely because belowground biomass was up to 10 times lower than for other Z. marina meadows, averaging 6.17 g C m-2 and 5.03 g C m-2 in the intertidal and subtidal zones, respectively. Sediment carbon concentrations did not exceed 1.30%Corg, and carbon accumulation rates ranged from 2.90–39.61 g Corg m-2 yr-1, decreasing with depth and averaging 10.8 ± 5.2 g Corg m-2 yr-1. While sediment carbon stocks were generally higher in the eelgrass meadows relative to non-vegetated reference sites, carbons stocks averaged 1343 ± 482 g Corg m-2, substantially less than global averages. These carbon results confirm that eelgrass does contribute to carbon storage in Clayoquot Sound but at lower rates than identified for more tropical seagrasses. By improving the quantification of site-specific carbon dynamics, eelgrass’ role in climate change mitigation and conservation planning can be assessed.

Planting Density and Site Effects on Stem Dimensions, Stand Productivity, Biomass Partitioning, Carbon Stocks and Soil Nutrient Supply in Hybrid Poplar Plantations

In this study, planting density and site effects on hybrid poplar productivity and stem dimensions were evaluated on the mid-term and longer term (8 and 14 years) in southern Québec (Canada). We also evaluated the effects of planting density and site on biomass accumulation and carbon stocks in different plantation compartments, on biomass partitioning at the stand-level, on soil carbon stocks and on soil nutrient supply rate after 14 years. The experimental design consisted of three replicate poplar stands located along a site fertility gradient. Each stand contained six planting densities (ranging from 494 to 1975 trees/ha) and a single genotype (Populus canadensis × P. maximowiczii hybrid). Planting density had a large effect on stem dimensions, but a minor effect on stand volume, aboveground woody biomass production, and aboveground biomass carbon stocks. Site selection and tree survival were more important factors affecting these variables. At all sites, and independent of planting density, mean annual volume increments were also higher after 14 vs. 8 years. On fertile sites, strong correlations between area per tree at planting and biomass partitioning, carbon allocation belowground, soil nutrient supply rate and soil carbon stocks were observed. Aboveground, higher competition for light with increasing planting density resulted in an increase in the stem to branch ratio. Belowground, higher competition for soil resources with increasing planting density reduced soil macronutrient availability (except for potassium), which likely stimulated carbon allocation belowground and carbon accumulation in the soil. Over the longer-term, higher density plantations of poplars could provide greater benefits in terms of carbon storage belowground (soil and roots).

Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).

Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.

Bamboo based family forests offer opportunities for biomass production and carbon farming in North East India

Although neglected in scientific research and development, bamboo based family forests (BBFF) have traditionally been managed on family farms because of their great socioeconomic value in India and other parts of Asia. Recently, there has been increasing interest in their role in biomass production and climate change mitigation. However, our knowledge of the contribution of BBFF at village and landscape level to biomass production and terrestrial carbon is very limited. Therefore, the objectives of this paper are to (1) quantify occurrence of bamboo resources in BBFF,(2) develop appropriate models for estimation of biomass of thick walled bamboos, and (3) estimate biomass and carbon stock in BBFFs in North East India. Occurrence of bamboo resources in BBFF was quantified through survey of 2850 households selected from 95 villages of Barak valley, North East India. Allometric models for biomass estimation were developed through destructive harvesting of 268 bamboo culms from Bambusa cacharensis, B. vulgaris and B. balcooa. The height-diameter relationships and allometric scaling between above-ground biomass (AGB), culm height (H) and diameter at breast height (D) were examined using various models.Culm height, D and AGB were allometrically related in all the three species, but the exponents were significantly larger than those expected under a geometric and stress similarity growth models. The above-ground biomass carbon density in BBFF was estimated at 16.38 Mg ha−1 for B. cacharensis, 38.42 Mg ha−1 for B. vulgaris and 19.64 Mg ha−1 for B. balcooa. In addition to the various ecosystem services provided by village grown bamboo, total biomass (52.8 Mg ha−1) and carbon (25.8 Mg ha−1) storage in BBFFs can offer an opportunity for carbon farming.

A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

Control of "blue carbon" storage by mangrove ageing: Evidence from a 66-year chronosequence in French Guiana.

The role of mangroves in the blue carbon stock is critical and requires special focus. Mangroves are carbon-rich forests that are not in steady-state equilibrium at the decadal time scale. Over the last decades, the structure and zonation of mangroves have been largely disturbed by coastal changes and land use conversions. The amount of time since the last disturbance is a key parameter determining forest structure, but it has so far been overlooked in mangrove carbon stock projections. In particular, the carbon sequestration rates among mangrove successional ages after (re)establishment are poorly quantified and not used in large-scale estimations of the blue carbon stock. Here, it is hypothesized that ecosystem age structure significantly modulates mangrove carbon stocks. We analysed a 66-year chronosequence of the aboveground and belowground biomass and soil carbon stock of mangroves in French Guiana, and we found that in the year after forest establishment on newly formed mud banks, the aboveground, belowground and soil carbon stocks averaged 23.56±7.71, 13.04±3.37 and 84.26±64.14 (to a depth of 1m) Mg C/ha, respectively. The mean annual increment (MAI) in the aboveground and belowground reservoirs was 23.56×Age-0.52 and 13.20×Age-0.64 Mg Cha-1 year-1 , respectively, and the MAI in the soil carbon reservoir was 3.00±1.80Mg Cha-1 year-1 . Our results show that the plant carbon sink capacity declines with ecosystem age, while the soil carbon sequestration rate remains constant over many years. We suggest that global projections of the above- and belowground reservoirs of the carbon stock need to account for mangrove age structures, which result from historical changes in coastal morphology. Our work anticipates joint international efforts to globally quantify the multidecadal mangrove carbon balance based on the combined use of age-based parametric equations and time series of mangrove age maps at regional scales.

Assessing the sensitivity of urban ecosystem service maps to input spatial data resolution and method choice

Ecosystem service (ES) mapping frequently uses secondary data and value-transfer methods to map services over broad extents at coarse resolutions, possibly causing poor prediction accuracy. Although ES map quality has received some recent attention in the literature, little is known about the accuracy of these maps in urban contexts or about the factors that influence this accuracy. To address this issue, we quantitatively compared and validated ES maps in a heterogeneous urban landscape to generate insight into ES map accuracy in these environments. Using aboveground biomass carbon storage as an example, we examined how input data resolution and assessment method affect the accuracy of urban ES maps. Two mapping methods were employed: (1) maps based on ecosystem components involved in carbon storage (trees and lawns) and (2) maps based on land-cover proxies and data at coarse and fine spatial resolutions. We compared carbon storage predicted by these methods to that estimated by using field-collected data to examine the accuracy of predictions and spatial variation therein. Different methods and data produced similar study area-wide estimates; however, the spatial distribution of estimates varied among methods. Estimates using ecosystem components agreed with the actual observations better than the proxy-based estimates, although map accuracy was improved by using higher resolution land-cover data. Thus, when study area-wide estimates suffice for decision making, proxy-based methods and coarse-resolution data should provide adequate assessments. Detailed ecosystem structure and composition data are needed when fine-resolution, spatially-explicit estimates are required.

Modeling carbon storage across a heterogeneous mixed temperate forest: the influence of forest type specificity on regional-scale carbon storage estimates

Accurately assessing forest carbon storage on a landscape scale is critical to understanding global carbon cycles and the effects of land cover changes on ecological processes. Calculations of regional-scale forest carbon storage that rely on maps of land cover typically reflect only coarse forest classes. How differences in carbon stored by different tree species may affect such assessments is largely unexplored. We examined a range of forest carbon storage models to understand the effects of forest type specificity on carbon storage estimates in the northeastern United States. Models estimated forest carbon in total aboveground and coarse root biomass based on three levels of forest classification specificity: (1) relative basal area by species, (2) species associations, and (3) broad forest types per IPCC (in: IPCC guidelines for national greenhouse gas inventories, IPCC, Japan, 2006) guidelines. The specificity of forest type classifications influenced results with generally lower carbon storage estimates resulting from higher-specificity forest classifications. The two most specific models, with mean carbon storage estimates of 103–107 Mg/ha, were most accurate compared to field validation points. These estimates are greater than 2013 field-based U.S. Forest Service estimates (84–90 Mg/ha). There are many sources of uncertainty in landscape-scale carbon storage assessments. Here we show that improving detail in one of these sources, forest stand composition, increases the accuracy of these assessments, and better reflects carbon storage patterns across heterogeneous landscapes. While more work is needed, particularly to improve stand age maps, this information can inform the interpretation of current carbon storage estimates and improve future estimates in heterogeneous forests.

Aboveground biomass of the alpine shrub ecosystems in Three-River Source Region of the Tibetan Plateau

Though aboveground biomass (AGB) has an important contribution to the global carbon cycle, the information about storage and climatic effects of AGB is scare in Three-River Source Region (TRSR) shrub ecosystems. This study investigated AGB storage and its climatic controls in the TRSR alpine shrub ecosystems using data collected from 23 sites on the Tibetan Plateau from 2011 to 2013. We estimated the AGB storage (both shrub layer biomass and grass layer biomass) in the alpine shrubs as 37.49 Tg, with an average density of 1447.31 g m-2. Biomass was primarily accumulated in the shrub layer, which accounted for 92% of AGB, while the grass layer accounted for only 8%. AGB significantly increased with the mean annual temperature (P < 0.05). The effects of the mean annual precipitation on AGB were not significant. These results suggest that temperature, rather than precipitation, has significantly effects on of aboveground vegetation growth in the TRSR alpine shrub ecosystems. The actual and potential increase in AGB density was different due to global warming varies among different regions of the TRSR. We conclude that long-term monitoring of dynamic changes is necessary to improve the accuracy estimations of potential AGB carbon sequestration across the TRSR alpine shrub ecosystems.

Carbon stocks in aboveground biomass for Colombian mangroves with associated uncertainties

Decision-making process, as well as the implementation of future climate change mitigation strategies for mangrove ecosystems, need the availability of reliable base information and tools to estimate the carbon stocks at regional and national levels. We estimated carbon (C) stocks in aboveground biomass (AGB) for mangroves in the Caribbean and Pacific coasts of Colombia. Using available data on AGB density and mangrove area for the whole country (excluding islands) and each coast independently, we estimated a national carbon stock in AGB for Colombian mangroves as 14.95 ± 2.72 TgC (mean ± SE), with 2.20 ± 0.86 TgC in the Caribbean coast and 9.61 ± 2.78 TgC in the Pacific coast. Uncertainty for total carbon in AGB in Colombian mangroves, reported as SE/mean in percentage, was 18% at the national level, 39% in the Caribbean coast, and 29% in the Pacific coast. This uncertainty was more influenced by uncertainties associated with the estimation of mangrove area for the Caribbean coast, while for the Pacific coast it was more influenced by the uncertainties associated with AGB density. This difference is the result of a contrasting availability of AGB density data for both coasts. Comparison between observed AGB density data and predictions from large-scale models showed that these models underestimate AGB density for Colombian mangroves. We reparameterized these models with our data, but found poor goodness-of-fit statistics for these model structures. We propose therefore three new statistical models to predict AGB density in Colombian mangroves based on climatic and vegetation data. In all cases, the best models included the enhanced vegetation index (EVI) and the mean temperature of driest quarter (BIO9).

Pilot study on the effects of elevated air temperature and CO2 on artificially defoliated silver birch saplings

The impacts of elevated temperature and CO2 on young silver birch (Betula pendula Roth) saplings after 0, 25, 50 or 75% artificial defoliation were assessed by measuring plant height and dry mass of aboveground compartments and roots and various morphological and physiological variables. Defoliation either increased or decreased plant growth depending on the severity of damage and the climatic treatment. At 21 °C and 400 mg L−1 CO2, defoliated plants were not able to compensate for the lost foliage, but growth compensation and adaptation to the changed conditions were greater; growth of young defoliated silver birch saplings increased, which led to increased height and a tendency to enhance final aboveground and root biomass and leaf nitrogen and carbon content compared to the nondefoliated controls. Nevertheless, the short-term effect of the different climatic conditions did not result in a significant overgrowth of defoliated plants. A slight increase in temperature and CO2 were the most acceptable conditions for defoliated plants; however, a 4 °C increase with correspondingly higher CO2 was more stressful as shown by less growth in height and biomass allocation to leaves, stems and roots. The findings from the pilot experiment are more applicable to young birch trees, but stress on young trees may be reflected in future tree growth.

Increased vegetation growth and carbon stock in China karst via ecological engineering

Afforestation and reforestation projects in the karst regions of southwest China aim to combat desertification and improve the ecological environment. However, it remains unclear at what scale conservation efforts have impacted on carbon stocks and if vegetation regrowth occurs at a large spatial scale as intended. Here we use satellite time series data and show a widespread increase in leaf area index (a proxy for green vegetation cover), and aboveground biomass carbon, which contrasted negative trends found in the absence of anthropogenic influence as simulated by an ecosystem model. In spite of drought conditions, aboveground biomass carbon increased by 9% (+0.05 Pg C y−1), mainly in areas of high conservation effort. We conclude that large scale conservation projects can contribute to a greening Earth with positive effects on carbon sequestration to mitigate climate change. At the regional scale, such ecological engineering projects may reduce risks of desertification by increasing the vegetation cover and reducing the ecosystem sensitivity to climate perturbations. Since 2000, China has attempted to vegetate huge portions of eroded landscape in its south west, bordering Vietman, Laos, and Myanmar. This study finds that this ecological engineering is combating desertification as vegetation regrows and stores carbon.

Impacts of permafrost on above- and belowground biomass on the northern Qinghai-Tibetan Plateau

ABSTRACT Because permafrost is extremely sensitive to climate change, it is of great importance to understand the relationship between permafrost and vegetation biomass. This study aims to reveal the impacts of permafrost on above- and belowground vegetation biomass on the northern Qinghai-Tibetan Plateau. Soil temperature, moisture, active-layer thickness, vegetation coverage, aboveground biomass (AGB), belowground biomass (BGB), and soil organic carbon were investigated in the growing seasons during 2014–2016. The average AGB and BGB in the growing seasons were 0.036 and 0.83 g cm−2, respectively. The AGB was significantly positively correlated with BGB, soil moisture, and soil organic carbon content, but was significantly negatively correlated with mean annual ground temperature and active-layer thickness, suggesting that permafrost degradation can potentially decrease vegetation growth. The BGB was positively correlated with active-layer thickness and was negatively correlated with soil moisture. This study suggests that permafrost degradation can decrease the soil moisture on the northern Qinghai-Tibetan Plateau and thus decrease AGB. The decreased soil moisture can also lead to lower BGB, while the vegetation in drier soils tends to have higher BGB to access more water resources for plant growth.

Responses of aboveground biomass and soil organic carbon to projected future climate change in Inner Mongolian grasslands

Understanding the impacts of future climate change on the grassland ecosystems of Inner Mongolia is important for adaptation of natural resource planning, livestock industries and livelihoods. The CENTURY model was validated against observed climate data from 1981 to 2010 for 16 sites. It simulated grass productivity and soil fertility with acceptable agreement, with the coefficient of the root-mean-square error calculated as 41.0% for biomass and 19.5% for soil organic carbon. The model was then used to assess changes to 2100 in aboveground biomass and soil organic carbon under two different climate-change scenarios that were developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The first scenario, RCP4.5 is an intermediate scenario for climate change, incorporating policies and technologies that stabilise growth in greenhouse-gas emissions. The second, RCP8.5, assumes continuing, high demand for energy and increasing greenhouse-gas emissions. Aboveground biomass of meadow and desert steppes responded positively to both scenarios, whereas the typical steppe showed a negative response to RCP4.5 but a positive response to RCP 8.5. Soil organic carbon showed a negative response for all steppe types. The simulations indicated that aboveground biomass and soil organic carbon of Inner Mongolian steppes were sensitive to projected emission scenarios. The CENTURY model predicted aboveground biomass to be 8.5% higher in the longer term (2081–2100) than baseline (1986–2005) under RCP4.5, and 24.3% higher under RCP8.5. Soil organic carbon was predicted to undergo small but significant decreases on average across all sites (1.2% for RCP4.5. 2.9% for RCP8.5). Our results could help decision makers to appreciate the consequences of climate change and plan adaptation strategies.

Greenhouse gas emissions and carbon sequestration by agroforestry systems in southeastern Brazil

Agrosilvopastoral and silvopastoral systems can increase carbon sequestration, offset greenhouse gas (GHG) emissions and reduce the carbon footprint generated by animal production. The objective of this study was to estimate GHG emissions, the tree and grass aboveground biomass production and carbon storage in different agrosilvopastoral and silvopastoral systems in southeastern Brazil. The number of trees required to offset these emissions were also estimated. The GHG emissions were calculated based on pre-farm (e.g. agrochemical production, storage, and transportation), and on-farm activities (e.g. fertilization and machinery operation). Aboveground tree grass biomass and carbon storage in all systems was estimated with allometric equations. GHG emissions from the agroforestry systems ranged from 2.81 to 7.98 t CO2e ha−1. Carbon storage in the aboveground trees and grass biomass were 54.6, 11.4, 25.7 and 5.9 t C ha−1, and 3.3, 3.6, 3.8 and 3.3 t C ha−1 for systems 1, 2, 3 and 4, respectively. The number of trees necessary to offset the emissions ranged from 17 to 44 trees ha−1, which was lower than the total planted in the systems. Agroforestry systems sequester CO2 from the atmosphere and can help the GHG emission-reduction policy of the Brazilian government.