Permafrost extent sets drainage density in the Arctic.

Amplified warming of high latitudes and rapid thaw of frozen ground threaten permafrost carbon stocks. The presence of permafrost modulates water infiltration and flow, as well as sediment transport, on soil-mantled slopes, influencing the balance of advective fluvial processes to diffusive processes on hillslopes in ways that are different from temperate settings. These processes that shape permafrost landscapes also impact the carbon stored on soil-mantled hillslopes via temperature, saturation, and slope stability such that carbon stocks and landscape morphometry should be closely linked. We studied [Formula: see text]69,000 headwater basins between 25° and 90 °N to determine whether the thermal state of the soil sets the balance between hillslope (diffusive) and fluvial (advective) erosion processes, as evidenced by the density of the channel networks (i.e., drainage density) and the proportion of convex to concave topography (hillslopes and river valleys, respectively). Watersheds within permafrost regions have lower drainage densities than regions without permafrost, regardless of watershed glacial history, mean annual precipitation, and relief. We find evidence that advective fluvial processes are inhibited in permafrost landscapes compared to their temperate counterparts. Frozen soils likely inhibit channel development, and we predict that climate warming will lower incision thresholds to promote growth of the channel network in permafrost landscapes. By demonstrating how the balance of advective versus diffusive processes might shift with future warming, we gain insight into the mechanisms that shift these landscapes from sequestering to exporting carbon.

Global patterns of tree wood density.

Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.

Routine results of an algorithm for managing the production of blood components.

BACKGROUND AND OBJECTIVES: The variability in the number of donations together with a growing demand for platelet concentrates and plasma-derived medicines make us seek solutions aimed at optimizing the processing of blood. Some mathematical models to improve efficiencies in blood banking have been published. The goal of this work is to validate and evaluate an algorithm's impact in the production of blood components in the Blood and Tissues Bank of Aragon (BTBA). MATERIALS AND METHODS: A mathematical algorithm was designed, implemented and validated through simulations with real data. It was incorporated into the fractionation area, which uses the Reveos® fractionation system (Terumo BCT) to split blood into its components. After 9 months of daily routine validation, retrospective activity data from the Blood Bank and Transfusion Services before and during the use of the algorithm were compared. RESULTS: Using the algorithm, the outdating rate of platelet concentrates (PC) decreased by 87.8% in the blood bank. The average shelf life remaining of PC supplied to Transfusion Services increased by almost 1 day. As a consequence, the outdating rate in the Aragon Transfusion Network decreased by 33%. In addition, extra 100 litres of plasma were obtained in 9 months. CONCLUSIONS: The algorithm improves the blood establishment's workflow and facilitates the decision-making process in whole blood processing. It resulted in a decrease in PC outdating rate, increase in PC shelf life and finally an increase in the volume of recovered plasma, leading to significant cost savings.

A Comprehensive Accounting of Construction Materials in Belt and Road Initiative Projects.

The Belt and Road Initiative (BRI) stands as the most ambitious infrastructure project in history, marked by its scale of investment, extensive geographical reach across continents and countries, and a diverse array of projects from roads to digital networks. While the BRI's environmental sustainability has raised concerns, the impacts of construction materials used in these projects have been overlooked, especially in developing countries. Here, we map and account for the materials embodied in the BRI by integrating, for the first time, official governmental project reports, geographical information, and material flow analysis. We pinpoint and analyze the BRI material stocks in each individual project by material types, countries, regions, and sectors. Between 2008 and 2023, 328 million tons of construction materials have accumulated in 540 BRI projects around the world, mostly in Asia and Africa. Aggregates (sand and gravel) constitute the largest share (82%), followed by cement, steel, and other materials. Most of the materials are used in transportation infrastructure. Our work further highlights some limitations in terms of data quality for such sustainability assessments. By shedding light on the significant impact of BRI projects on raw material usage across the globe, this study sets the stage for further investigations into environmental impacts of BRI and material stock-flow-nexus from perspective of an initiative.

Uncovering the Nexus between Urban Heat Islands and Material Stocks of Built Environment in 335 Chinese Cities.

China's unprecedented rapid urbanization has dramatically reshaped the urban built environment, disrupting the thermal balance of cities. This disruption causes the urban heat island (UHI) effect, adversely affecting urban sustainability and public health. Although studies have highlighted the remarkable impacts of the built environment on UHIs, the specific effects of its various structures and components remain unclear. In this study, a multidimensional remote sensing data set was used to quantify the atmospheric UHIs across 335 Chinese cities from 1980 to 2020. In conjunction with stocks of three end-use sectors and three material groups, the impacts of gridded material stocks on UHI variations were analyzed. The findings reveal that building stocks exert a predominant influence in 48% of cities. Additionally, the extensive use of metal and inorganic materials has increased thermal stress in 220 cities, leading to an average UHI increase of 0.54 °C. The effect of organic materials, primarily arising from mobile heat sources, is continuously increasing. Overall, this study elucidates the effect of the functional structure and material composition of urban landscapes on UHIs, highlighting the complexities associated with the influence of the built environment on the urban heat load.

Component-Level Residential Building Material Stock Characterization Using Computer Vision Techniques.

Residential building material stock constitutes a significant part of the built environment, providing crucial shelter and habitat services. The hypothesis concerning stock mass and composition has garnered considerable attention over the past decade. While previous research has mainly focused on the spatial analysis of building masses, it often neglected the component-level stock analysis or where heavy labor cost for onsite survey is required. This paper presents a novel approach for efficient component-level residential building stock accounting in the United Kingdom, utilizing drive-by street view images and building footprint data. We assessed four major construction materials: brick, stone, mortar, and glass. Compared to traditional approaches that utilize surveyed material intensity data, the developed method employs automatically extracted physical dimensions of building components incorporating predicted material types to calculate material mass. This not only improves efficiency but also enhances accuracy in managing the heterogeneity of building structures. The results revealed error rates of 5 and 22% for mortar and glass mass estimations and 8 and 7% for brick and stone mass estimations, with known wall types. These findings represent significant advancements in building material stock characterization and suggest that our approach has considerable potential for further research and practical applications. Especially, our method establishes a basis for evaluating the potential of component-level material reuse, serving the objectives of a circular economy.

Inorganic carbon is overlooked in global soil carbon research: A bibliometric analysis.

Soils are a major player in the global carbon (C) cycle and climate change by functioning as a sink or a source of atmospheric carbon dioxide (CO2). The largest terrestrial C reservoir in soils comprises two main pools: organic (SOC) and inorganic C (SIC), each having distinct fates and functions but with a large disparity in global research attention. This study quantified global soil C research trends and the proportional focus on SOC and SIC pools based on a bibliometric analysis and raise the importance of SIC pools fully underrepresented in research, applications, and modeling. Studies on soil C pools started in 1905 and has produced over 47,000 publications (>1.7 million citations). Although the global C stocks down to 2 m depth are nearly the same for SOC and SIC, the research has dominantly examined SOC (>96 % of publications and citations) with a minimal share on SIC (<4%). Approximately 40 % of the soil C research was related to climate change. Despite poor coverage and publications, the climate change-related research impact (citations per document) of SIC studies was higher than that of SOC. Mineral associated organic carbon, machine learning, soil health, and biochar were the recent top trend topics for SOC research (2020-2023), whereas digital soil mapping, soil properties, soil acidification, and calcite were recent top trend topics for SIC. SOC research was contributed by 151 countries compared to 88 for SIC. As assessed by publications, soil C research was mainly concentrated in a few countries, with only 9 countries accounting for 70 % of the research. China and the USA were the major producers (45 %), collaborators (37 %), and funders of soil C research. SIC is a long-lived soil C pool with a turnover rate (leaching and recrystallization) of more than 1000 years in natural ecosystems, but intensive agricultural practices have accelerated SIC losses, making SIC an important player in global C cycle and climate change. The lack of attention and investment towards SIC research could jeopardize the ongoing efforts to mitigate climate change impacts to meet the 1.5-2.0 °C targets under the Paris Climate Agreement of 2015. This bibliographic study calls to expand the research focus on SIC and including SIC fluxes in C budgets and models, without which the representation of the global C cycle is incomplete.

Effects of co-application of biochar and nitrogen fertilizer on soil profile carbon and nitrogen stocks and their fractions in wheat field.

Applying biochar to nitrogen (N)-fertilized soils is recognized as an effective technique for enhancing soil carbon (C) accumulation and improving agroecosystem sustainability. However, the impact of co-application of biochar and N fertilizer on soil C and N stocks, as well as their fractions, within the 0-60 cm soil profile remains unclear. This study examined the soil C and N fractions as well as stocks in soil profiles, and the primary influencing factors in wheat field with different rates of biochar (0, 20 and 40 t ha-1; B0, B1 and B2) and N application (0, 180 and 360 kg N ha-1; N0, N1 and N2). The results revealed that compared to B0N0 treatment, biochar plus N application increased soil organic carbon (SOC) and dissolved organic carbon (DOC), while N application alone decreased microbial biomass carbon (MBC). SOC in topsoil (0-10 cm) and DOC in subsoil (40-60 cm) were more susceptible to biochar and N application. The combined application of biochar and N enhanced soil N fractions, with NO3--N having the highest sensitivity than the other N fractions, whereas biochar application alone decreased topsoil inorganic N content. Biochar and N application significantly altered soil C stocks (4.33%-42.20%) and N stocks (-1.24%-20.91%) within the 0-60 cm soil layers, and belowground biomass and SOC were the main influencing factors, respectively. The combination of moderate biochar (42.35 t ha-1) and N (277.78 kg ha-1) application was the most beneficial for soil C accumulation in the 0-60 cm depth. These findings indicate the positive impacts of co-applying of biochar and N in agroecosystems on soil C and N accumulations, and highlight the importance of C and N stabilization in both topsoil and subsoil under management practice.

Changes in soil organic carbon stocks and its physical fractions along an elevation in a subtropical mountain forest.

Soil microorganisms are the drivers of soil organic carbon (SOC) mineralization, and the activities of these microorganisms are considered to play a key role in SOC dynamics. However, studies of the relationship between soil microbial carbon metabolism and SOC stocks are rare, especially in different physical fractions (e.g., particulate organic carbon (POC) fraction and mineral-associated organic carbon (MAOC) fraction). In this study, we investigated the changing patterns of SOC stocks, POC stocks, MAOC stocks and microbial carbon metabolism (e.g., microbial growth, carbon use efficiency and biomass turnover time) at 0-20 cm along an elevational gradient in a subtropical mountain forest ecosystem. Our results showed that SOC and POC stocks increased but MAOC stocks remained stable along the elevational gradient. Soil microbial growth increased while microbial turnover time decreased with elevation. Using structural equation modeling, we found that heightened microbial growth is associated with elevated POC stocks. Moreover, MAOC stocks positively correlate with microbial growth but show negative associations with both POC stocks and soil pH. Overall, the increase in SOC stocks along the elevational gradient is primarily driven by changes in POC stocks rather than MAOC stocks. These findings underscore the importance of considering diverse soil carbon fractions and microbial activities in predicting SOC responses to elevation, offering insights into potential climate change feedbacks.

Impacts of deforestation and land use/land cover change on carbon stock dynamics in Jomoro District, Ghana.

Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above- and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to five different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations) on a total of 72 plots. Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 35% and 85% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems.

Impact of Climate Policy Uncertainty (CPU) and global Energy Uncertainty (EU) news on U.S. sectors: The moderating role of CPU on the EU and U.S. sectoral stock nexus.

This article accounts for the impact of positive and negative shocks of the news-related Climate Policy Uncertainty (CPU) and the novel Economist Intelligence Unit's report-based global Energy Uncertainty (EU) on the U.S. sectoral stock returns by using the ARDL and NARDL approaches with dynamic multiplier simulations. We also utilize both the DCC-GARCH and ADCC-GARCH approaches to extract the symmetric and asymmetric dynamic conditional correlations between the EU and the U.S. sectoral stock returns and then regress these conditional correlation series on the CPU through series of quantile regressions. Overall, the findings suggest that only the positive CPU shocks negatively impact the U.S. sectoral stock returns of Consumer Services, Financials, Industries, Telecommunication and Utilities in the long-term, whereas the negative CPU shocks insignificantly predict the U.S. sectoral returns. The findings also report that only the negative EU shocks increase the U.S. sectoral stock returns of Consumer Services, Financials, Health Care, Industries, Moreover, the positive (negative) EU shocks cause the U.S. sectoral returns of Materials and Technology to decrease (increase) in the long-term. Portfolio managers may consider diversifying their portfolios to include sectors least susceptible to negative impacts from the CPU and EU shocks such as Health Care and Oil & Gas. Our findings also show that CPU shocks moderate the dynamic conditional correlations between the EU and the U.S. sectoral returns of Consumer Services, Materials, Health Care, Telecommunication, Oil and Gas and Utility. Fund managers should contemplate augmenting the allocations to the Financials, Industrials, and Technology sectors owing to their diminished interconnectivity with the EU during periods of heightened CPU.

Concurrent and legacy effects of sheep trampling on soil organic carbon stocks in a typical steppe, China.

Grazing plays a key role in ecosystem biogeochemistry, particularly soil carbon (C) pools. The non-trophic interactions between herbivores and soil processes through herbivore trampling have recently attracted extensive attention. However, their concurrent and legacy effects on the ecosystem properties and processes are still not clear, due to their effects being hard to separate via field experiments. In this study, we conducted a 2-year simulated-sheep-trampling experiment with four trampling intensity treatments (i.e., T0, T40, T80, and T120 for 0, 40, 80, and 120 hoofprints m-2, respectively) in a typical steppe to explore the concurrent and legacy effects of trampling on grassland ecosystem properties and processing. In 2017 (trampling treatment year), we found that trampling decreased aboveground biomass (AGB) of plant community and community-weighted mean shoot C concentration (CWM C), soil available nitrogen (N) and available phosphorus (P), but did not affect plant species diversity and belowground biomass (BGB). We show that compared with T0, trampling increased soil bulk density (BD) at T80, and decreased soil organic carbon (SOC) stocks. After the cessation of trampling for two years (i.e., in 2019), previous trampling increased plant diversity and BGB, reaching the highest values at T80, but decreased soil available N and available P. Compared with T0, previous trampling significantly increased soil BD at T120, while significantly decreased CWM C at T80 and T120, and reduced SOC stocks at T80. Compared with 2017, the trampling negative legacy effects amplified at T80 but weakened at T40 and T120. We also show that trampling-induced decreases in soil available N, AGB of Fabaceae and CWM C were the main predictors of decreasing SOC stocks in 2017, while previous trampling-induced legacy effects on soil available P, AGB of Poaceae and CWM C contributed to the variations of SOC stocks in 2019. Taken together, short-term trampling with low intensity could maintain most plant functions, while previous trampling with low intensity was beneficial to most plant and soil functions. The results of this study show that T40 caused by sheep managed at a stocking rate of 2.7 sheep ha-1 is most suitable for grassland adaptive management in the typical steppe. The ecosystem functions can be maintained under a high stocking rate through the process of providing enough time to rebuild sufficient vegetation cover and restore soil through measures such as regional rotational grazing and seasonal grazing.

Edaphic influences on soil organic carbon in the forest systems of southern Western Ghats, India.

Spatial distribution and edaphic influences on soil organic carbon (SOC) are key determinants of carbon sequestration potential, and analysis of aggregate-protected SOC gives an in-depth understanding of the stability of carbon stored in soils. The present study evaluated the edaphic effects on the SOC in four different forest types-tropical evergreen forest, tropical moist deciduous forest, tropical dry deciduous forest and shola forest-in the southern high hills agro-ecological zone of Western Ghats, India. SOC stocks at depths of up to 1 m varied significantly across forest types, with the highest levels observed in the shola forest type (441.08 Mg C/ha) and the lowest in the dry deciduous forest (138.17 Mg C/ha). Around 70% of SOC was found in upper layers (0-30 cm) in all the studied forest types. Evaluation by a fixed-effect model showed that forest type, soil depth and aggregate size significantly affected SOC storage in these systems. An assessment of the relative importance and effect of 14 edaphic factors on SOC content in different forest types using the random forest model showed that the algorithm could explain 93.68%, 41.72%, 45.53% and 75.2% variability of SOC concentration across shola, dry deciduous, moist deciduous and evergreen systems, respectively. Across all forest types, except for dry deciduous forests, soil texture was found to be the primary factor influencing SOC, surpassing all other edaphic parameters. Ionic interactions by way of metal oxides like Ca2+, Al3+, Fe3+, Mg and H+ influenced the SOC in tropical forest systems. The insights into SOC dynamics and the edaphic factors regulating them offer valuable guidance for forest management in tropical regions, particularly regarding climate change mitigation.

Carbon accumulation features in different functional zones of cities in the steppe zone.

This article presents findings on the study of content, profile distribution, and reserves of various carbon forms (organic carbon (TOC) and inorganic carbon (IC)) in Urbic Technosols and Ekranic Technosols within the residential zone of the city, alongside zonal Calcic Chernozems in the recreational zone of Rostov-on-Don, Aksai, and Bataysk. It was revealed that the TOC content in the upper horizons of Urbic Technosols is significantly lower than in the chernozem horizons of fallow areas, registering at 2.59 ± 0.79% and 3.25 ± 0.94%, respectively. IC exhibits an inverse trend, with maximum content observed in the upper horizons of Ekranic Technosols. Down the soil profile, disparities in TOC and IC contents are mitigated. This specificity in TOC accumulation and profile distribution signifies a "bipartite" profile alteration in buried chernozems, affecting solely the upper stratum rather than the entire soil profile. The presence of woody vegetation in the dry-steppe zone positively influences TOC accumulation. Calcic Chernozems beneath woody vegetation showcase the highest TOC reserves within the 30-cm layer (10.61 ± 1.45 kg/m2). Calcic Chernozems of fallow areas under natural steppe vegetation contain 8.94 ± 1.75 kg/m2, Technosols of the residential zone 8.44 ± 2.47 kg/m2. For Technosols of the residential zone, a weakening of the dependence of TOC and IC content on the depth of the soil horizon is observed.

Soil carbon sequestration potential of different land use systems: evidence from sub-humid southern plains and Aravalli hills of Rajasthan, India.

This study has assessed total soil organic carbon (TOC) fractions, carbon management index (CMI), and carbon sequestration economic value under diverse land use systems (LUSs) of sub-humid Southern plains of Rajasthan, India. The study dealt with six LUSs: barren land (BL), agricultural land (AL), agri-horticulture (AH), horticultural land (HL), grassland (GL), and natural forest land (FL) were selected for the study. FL contained the highest TOC (13.04 ± 0.74 g kg-1), particulate organic carbon (POC) (2.2 ± 0.19 g kg-1), mineral-associated organic carbon (MAC) (10.84 ± 0.54 g kg-1), and CMI (230.36 ± 4.13), whereas BL had the lowest amount of TOC (3.53 ± 0.4 g kg-1), POC (0.47 ± 0.06 g kg-1), MAC (3.06 ± 0.32 g kg-1), and CMI (54.60 ± 4.2). The impact of LUSs on soil carbon lability index (LI) was minimal in all LUSs except FL exhibited statistically insignificant variations in LI. TOC stock showed the highest decline in BL (71.04%), AL (55.29%), AH (44.38%), and HL (25.92%) uses compared with the FL system. Different LUSs result in varying amounts of carbon stocks, representing the relative carbon credit gain. The maximum carbon credit was achieved by FL, which was roughly US $49,303 and 245% higher than BL. These results indicate the reinstatement of BL and AL towards HL and AH systems, and effective recycling of residues could improve the TOC storage in the study region.

Permafrost thaw causes large carbon loss in boreal peatlands while changes to peat quality are limited.

Rapid, ongoing permafrost thaw of peatlands in the discontinuous permafrost zone is exposing a globally significant store of soil carbon (C) to microbial processes. Mineralization and release of this peat C to the atmosphere as greenhouse gases is a potentially important feedback to climate change. Here we investigated the effects of permafrost thaw on peat C at a peatland complex in western Canada. We collected 15 complete peat cores (between 2.7 and 4.5 m deep) along four chronosequences, from elevated permafrost peat plateaus to saturated thermokarst bogs that thawed up to 600 years ago. The peat cores were analysed for peat C storage and peat quality, as indicated by decomposition proxies (FTIR and C/N ratios) and potential decomposability using a 200-day aerobic laboratory incubation. Our results suggest net C loss following thaw, with average total peat C stocks decreasing by ~19.3 ± 7.2 kg C m-2 over <600 years (~13% loss). Average post-thaw accumulation of new peat at the surface over the same period was ~13.1 ± 2.5 kg C m-2 . We estimate ~19% (±5.8%) of deep peat (>40 cm below surface) C is lost following thaw (average 26 ± 7.9 kg C m-2 over <600 years). Our FTIR analysis shows peat below the thaw transition in thermokarst bogs is slightly more decomposed than peat of a similar type and age in permafrost plateaus, but we found no significant changes to the quality or lability of deeper peat across the chronosequences. Our incubation results also showed no increase in C mineralization of deep peat across the chronosequences. While these limited changes in peat quality in deeper peat following permafrost thaw highlight uncertainty in the exact mechanisms and processes for C loss, our analysis of peat C stocks shows large C losses following permafrost thaw in peatlands in western Canada.

Potential aboveground biomass increase in Brazilian Atlantic Forest fragments with climate change.

Fragmented tropical forest landscapes preserve much of the remaining biodiversity and carbon stocks. Climate change is expected to intensify droughts and increase fire hazard and fire intensities, thereby causing habitat deterioration, and losses of biodiversity and carbon stock losses. Understanding the trajectories that these landscapes may follow under increased climate pressure is imperative for establishing strategies for conservation of biodiversity and ecosystem services. Here, we used a quantitative predictive modelling approach to project the spatial distribution of the aboveground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest (AF) domain. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report. Our AGB models had a satisfactory performance (area under the curve > 0.75 and p value < .05). The models projected a significant increase of 8.5% in the total carbon stock. Overall, the projections indicated that 76.9% of the AF domain would have suitable climatic conditions for increasing biomass by 2100 considering the RCP 4.5 scenario, in the absence of deforestation. Of the existing forest fragments, 34.7% are projected to increase their AGB, while 2.6% are projected to have their AGB reduced by 2100. The regions likely to lose most AGB-up to 40% compared to the baseline-are found between latitudes 13° and 20° south. Overall, although climate change effects on AGB vary latitudinally for the 2071-2100 period under the RCP 4.5 scenario, our model indicates that AGB stocks can potentially increase across a large fraction of the AF. The patterns found here are recommended to be taken into consideration during the planning of restoration efforts, as part of climate change mitigation strategies in the AF and elsewhere in Brazil.

Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling.

Forest carbon is a large and uncertain component of the global carbon cycle. An important source of complexity is the spatial heterogeneity of vegetation vertical structure and extent, which results from variations in climate, soils, and disturbances and influences both contemporary carbon stocks and fluxes. Recent advances in remote sensing and ecosystem modeling have the potential to significantly improve the characterization of vegetation structure and its resulting influence on carbon. Here, we used novel remote sensing observations of tree canopy height collected by two NASA spaceborne lidar missions, Global Ecosystem Dynamics Investigation and ICE, Cloud, and Land Elevation Satellite 2, together with a newly developed global Ecosystem Demography model (v3.0) to characterize the spatial heterogeneity of global forest structure and quantify the corresponding implications for forest carbon stocks and fluxes. Multiple-scale evaluations suggested favorable results relative to other estimates including field inventory, remote sensing-based products, and national statistics. However, this approach utilized several orders of magnitude more data (3.77 billion lidar samples) on vegetation structure than used previously and enabled a qualitative increase in the spatial resolution of model estimates achievable (0.25° to 0.01°). At this resolution, process-based models are now able to capture detailed spatial patterns of forest structure previously unattainable, including patterns of natural and anthropogenic disturbance and recovery. Through the novel integration of new remote sensing data and ecosystem modeling, this study bridges the gap between existing empirically based remote sensing approaches and process-based modeling approaches. This study more generally demonstrates the promising value of spaceborne lidar observations for advancing carbon modeling at a global scale.

Depth-dependent effects of ericoid mycorrhizal shrubs on soil carbon and nitrogen pools are accentuated under arbuscular mycorrhizal trees.

Plant mycorrhizal associations influence the accumulation and persistence of soil organic matter and could therefore shape ecosystem biogeochemical responses to global changes that are altering forest composition. For instance, arbuscular mycorrhizal (AM) tree dominance is increasing in temperate forests, and ericoid mycorrhizal (ErM) shrubs can respond positively to canopy disturbances. Yet how shifts in the co-occurrence of trees and shrubs with different mycorrhizal associations will affect soil organic matter pools remains largely unknown. We examine the effects of ErM shrubs on soil carbon and nitrogen stocks and indicators of microbial activity at different depths across gradients of AM versus ectomycorrhizal (EcM) tree dominance in three temperate forest sites. We find that ErM shrubs strongly modulate tree mycorrhizal dominance effects. In surface soils, ErM shrubs increase particulate organic matter accumulation and weaken the positive relationship between soil organic matter stocks and indicators of microbial activity. These effects are strongest under AM trees that lack fungal symbionts that can degrade organic matter. In subsurface soil organic matter pools, by contrast, tree mycorrhizal dominance effects are stronger than those of ErM shrubs. Ectomycorrhizal tree dominance has a negative influence on particulate and mineral-associated soil organic matter pools, and these effects are stronger for nitrogen than for carbon stocks. Our findings suggest that increasing co-occurrence of ErM shrubs and AM trees will enhance particulate organic matter accumulation in surface soils by suppressing microbial activity while having little influence on mineral-associated organic matter in subsurface soils. Our study highlights the importance of considering interactions between co-occurring plant mycorrhizal types, as well as their depth-dependent effects, for projecting changes in soil carbon and nitrogen stocks in response to compositional shifts in temperate forests driven by disturbances and global change.

Material Requirements of Decent Living Standards.

Decent living standards (DLS) provide a framework to estimate a practical threshold for the energy, GHG, and material consumption required to alleviate poverty. Currently, most research has focused on estimating the energy required to provide the DLS. However, no attempt has been made to estimate the material consumption needed to provide the DLS. Thus, we ask the following questions: First, what is the amount of materials in stocks and flows needed to provide a DLS? Second, which lifestyle and technology choices are effective in providing a DLS without creating an excessive demand for additional materials? To provide a DLS, a material footprint (MF) of 6 t/(cap*yr) with a lower and upper bound between 3 and 14 t/(cap*yr) is required. The direct and indirect in-use stocks required are estimated at 32 t/cap and 11 t/cap, respectively. Nutrition (39%) and mobility (26%) contribute the most to total MF. Buildings account for 98% of direct stocks, while the construction sector accounts for 61% of indirect stocks. We extend the coverage of the DLS by including the collective service dimension and link the material stock-flow-service nexus and life cycle assessment to compute the MF and in-use stocks needed to provide the DLS.