Dominant role of the non-forest woody vegetation in the post 2015/16 El Niño tropical carbon recovery.

The extreme dry and hot 2015/16 El Niño episode caused large losses in tropical live aboveground carbon (AGC) stocks. Followed by climatic conditions conducive to high vegetation productivity since 2016, tropical AGC are expected to recover from large losses during the El Niño episode; however, the recovery rate and its spatial distribution remain unknown. Here, we used low-frequency microwave satellite data to track AGC changes, and showed that tropical AGC stocks returned to pre-El Niño levels by the end of 2020, resulting in an AGC sink of 0.18 0.14 0.26 $$ {0.18}_{0.14}^{0.26} $$ Pg C year-1 during 2014-2020. This sink was dominated by strong AGC increases ( 0.61 0.49 0.84 $$ {0.61}_{0.49}^{0.84} $$ Pg C year-1) in non-forest woody vegetation during 2016-2020, compensating the forest AGC losses attributed to the El Niño event, forest loss, and degradation. Our findings highlight that non-forest woody vegetation is an increasingly important contributor to interannual to decadal variability in the global carbon cycle.

Environmental correlates of the forest carbon distribution in the Central Himalayas.

Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot-level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad-scale climatic water and energy availability and fine-scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high-elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas.

Geographic variation in projected US forest aboveground carbon responses to climate change and atmospheric deposition.

Forest composition and ecosystem services are sensitive to anthropogenic pressures like climate change and atmospheric deposition of nitrogen (N) and sulfur (S). Here we extend recent forest projections for the current cohort of trees in the contiguous US, characterizing potential changes in aboveground tree carbon at the county level in response to varying mean annual temperature, precipitation, and N and S deposition. We found that relative to a scenario with N and S deposition reduction and no climate change, greater climate change led generally to decreasing aboveground carbon (mean -7.5% under RCP4.5, -16% under RCP8.5). Keeping climate constant, reduced N deposition tended to lessen aboveground carbon (mean -7%), whereas reduced S deposition tended to increase aboveground carbon (+3%) by 2100. Through mid-century (2050), deposition was more important for predicting carbon responses except under the extreme climate scenarios (RCP8.5); but, by 2100, climate drivers generally outweighed deposition. While more than 70% of counties showed reductions in aboveground carbon relative to the reference scenario, these were not evenly distributed across the US. Counties in the Northwest and Northern Great Plains, and the northern parts of New England and the Midwest, primarily showed positive responses, while counties in the Southeast showed negative responses. Counties with greater initial biomass showed less negative responses to climate change while those which exhibited the greatest change in composition (>15%) had a 95% chance of losing carbon relative to a no-climate change scenario. This analysis highlights that declines in forest growth and survival due to increases in mean temperature and reductions in atmospheric N deposition are likely to outweigh positive impacts of reduced S deposition and potential increases in precipitation. These effects vary at the regional and county level, however, so forest managers must consider local rather than national dynamics to maximize forest carbon sinks in the future.

Assessing the impact of pine wilt disease on aboveground carbon storage in planted Pinus massoniana Lamb. forests via remote sensing.

The continuous spread of Bursaphelenchus xylophilus (Steiner and Buhrer) Nickle, commonly known as the organism that causes pine wilt disease (PWD), has become a notable threat to forest security in East Asia and southern Europe, and an assessment of the carbon loss caused by PWD damage is important to achieving carbon neutrality. This study used satellite remote sensing and 15-year ground monitoring data to measure the impact of PWD on the carbon storage of Pinus massoniana Lamb. (P. massoniana), the conifer with the largest planted area in southern China. This study showed that the occurrence of PWD had an impact on the increase in carbon storage of P. massoniana. The infected and dead P. massoniana trees accounted for only 1.46 % of the total number of trees but caused a carbon storage loss of 1.99 t/ha, which accounted for 6.23 % of the total carbon sink in healthy P. massoniana forests over the last 15 years. The most pronounced decline in carbon storage occurred in the first five years of PWD invasion. After 10 years of clearcutting and replanting of Schima superba Gardn. et Champ., the increase in carbon storage of the reformed forest far exceeded that of the healthy forest during the same period, which was 2.04 times (10 years) and 1.56 times (15 years) that of the healthy P. massoniana forest. In addition, our study found that during the 15-year period (from the forest age of 22 to the forest age of 37), the average carbon storage of P. massoniana forest was 31.9 t/ha. This study helps to evaluate the impact of PWD on the carbon sink of pine forests and provides methodological references for analyzing the impact of biological disturbances on the carbon cycle.

Projecting future aboveground carbon sequestration rate of alpine forest on the eastern Tibetan Plateau in response to climate change.

The aboveground carbon sequestration rate (ACSR) of forests serves as an indicator of their carbon sequestration capacity over time, providing insights into the potential carbon sequestration capacity of forest ecosystems. To explore the long-term Spatiotemporal variation of ACSR in the transitional ecotone of the eastern Tibetan Plateau under climate change scenarios, we utilized a forest landscape model that was parameterized with forest inventory data from the eastern Tibetan Plateau to simulate this ecological function changes. The study found that climate warming had significant effect on forests ACSR in different types of forests. ACSR was significantly reduced (p<0.05) in cold temperate coniferous and temperate coniferous forests, whereas it was significantly increased in deciduous broad-leaved forests. However, the impact of climate warming on evergreen broad-leaved forests was found to be negligible. At the species level, climate warming has mostly suppressed the ACSR of coniferous trees, except for Chinese hemlock. The main dominant species, spruce and fir, have been particularly affected. Conversely, the ACSR of most broad-leaved trees has increased due to climate warming. In addition, at the landscape scale, the ACSR within this region is expected to experience a steady decline after 2031s-2036s. Despite the effects of climate warming, this trend is projected to persist. In conclusion, the forests ACSR in this region will be significantly affected by future climate warming. Our research indicates that climate warming will have a noticeable suppressive effect on conifers. It is imperative that this factor be taken into account when devising forest management plans for the future in this region.

Light to moderate long-term grazing enhances ecosystem carbon across a broad climatic gradient in northern temperate grasslands.

Grasslands are globally abundant and provide many ecosystem services, including carbon (C) storage. While grasslands are widely subject to livestock grazing, the influence of grazing on grassland ecosystem C remains unclear. We studied the effect of long-term livestock grazing on C densities of different ecosystem components in 110 northern temperate grasslands across a broad agroclimatic gradient in Alberta, Canada. These grasslands stored 50 to 180 t ha-1C in live and dead vegetation, as well as soil C to 30 cm depth, with the majority as soil organic C (SOC). The mulch layer comprised a large amount of C (~18 t ha-1C) especially within humid grasslands. Although grazing reduced C densities in litter mass, total ecosystem C was 8.5 % greater under grazing (127.8 t ha-1) compared to those non-grazed (117.8 t ha-1), primarily due to increases in SOC and roots. Increases in SOC were consistently observed in the 0-15 cm layer across all climatic conditions, with changes in SOC of the 15-30 cm layer inversely related to aridity. A structural equation model revealed that increased SOC under grazing was indirectly attributed to increases in eudicot rather than graminoid biomass. In addition, SOC increased with graminoid quality (i.e., a reduced carbon to nitrogen ratio), which together with elevated eudicots, increased litter and mulch C, and ultimately enhanced SOC densities. When applied to spatial maps of habitat type and land use (livestock grazing) activity across the region, an area of ~3.8 M ha of grassland was projected to contain an additional 17.1 M t of C under grazing, primarily in mesic grasslands, worth an estimated $3.1 B (Cdn.) under current C valuation guidelines in Canada. Overall, these results highlight the importance of grasslands for C storage and establishing policies that maintain and promote their sustainable use, including light to moderate grazing.

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.

Adoption of novel climate-smart farming systems for enhanced carbon stock and carbon dioxide equivalent emission reduction in cattle corridor areas of Uganda.

Climate change remains the single major threat to the realization of increased livestock production because of its impact on the quantity and quality of feed crops and forages, water availability, animal reproduction, and biodiversity. To minimize the negative impacts of climate change on livestock, an agroforestry project was implemented in the cattle corridor areas of Uganda. Predominant agroforestry tree species and improved grass were planted. At the age of 1.5 years, the aboveground biomass, aboveground carbon stock, and carbon dioxide equivalent emissions sequestrated by each sapling species strand and grass species were determined. From the results, the aboveground biomass (F = 92.21, p = 0.020), aboveground carbon stock (F = 101.01, p = 0.035), and the carbon dioxide equivalent emissions sequestrated (F = 71.02, p = 0.0401) varied significantly among the studied species. Among the agroforestry saplings, Calliandra callothyrus (10.0 ± 0.7 ton/acre) had the highest aboveground biomass, while Markhamia lutea (4.3 ± 0.3 tons/acre) and Albizia chinense (4.1 ± 0.2 tons/acre) had the lowest aboveground biomass. Similarly, the aboveground carbon stock was the highest in Calliandra callothyrus strand (4.70 ± 0.1 tons/acre) and lowest in the Albizia chinense strand (1.94 ± 0.2 tons/acre). At a strand level, Calliandra callothyrus (17 ± 0.4 ton/acre) sequestrated the highest quantities of carbon dioxide equivalent emissions, followed by Maesopsis eminii (10 ± 0.2 ton/acre) and Grevillea robusta (9 ± 0.5 ton/acre) species strands. Markhamia lutea (7 ± 0.2 ton/acre) and Albizia Chinense (7 ± 0.1 ton/acre) strands sequestrated the lowest quantities of carbon dioxide equivalent emissions. At the age of 1.5 years, the grass species were fully grown but only stored 0.51 ± 0.0 and 0.47 ± 0.0 tons/acre of Aboveground carbon for Chloris gayana and Centrosema pubescens, respectively. The carbon dioxide equivalent emissions sequestrated by the grass: Chloris gayana (1.9 ± 0.0 ton/acre) and Centrosema pubescens (1.7 ± 0.0 ton/acre) were also less than that of the agroforestry saplings. From this study, the agroforestry species with higher wood biomass and fast growth rate are recommended for carbon dioxide emission sequestration.

The distribution of carbon stocks between tree woody biomass and soil differs between Scots pine and broadleaved species (beech, oak) in European forests.

While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe. We used 21 triplets (5 beech-oak, 8 pine-beech, 8 pine-oak mixed stands, and their respective monocultures at the same sites) in seven European countries. We computed biomass C stocks from total stand inventories and species-specific allometric equations, and soil organic C data down to 40 cm depth. On average, the broadleaved species stored more C in aboveground woody biomass than soil, while C storage in pine was equally distributed between both components. Stand density had a strong effect on C storage in tree woody biomass but not in the soil. After controlling for stand basal area, the mixed stands had, on average, similar total C stocks (in aboveground woody biomass + coarse roots + soil) to the most performing monocultures. Although species composition and stand density affect total C stocks and its partitioning between aboveground woody biomass and soil, a large part of variability in soil C storage was unrelated to stand characteristics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10342-022-01453-9.

Effects of drivers and their variations on the number of stems and aboveground carbon removals in miombo woodlands of mainland Tanzania.

BACKGROUND: Removals caused by both natural and anthropogenic drivers such as logging and fire in miombo woodlands causes substantial carbon emissions. Here we present drivers and their effects on the variations on the number of stems and aboveground carbon (AGC) removals based on an analysis of Tanzania's national forest inventory (NFI) data extracted from the National Forest Resources Assessment and Monitoring (NAFORMA) database using allometric models that utilize stump diameter as the sole predictor. RESULTS: Drivers of AGC removals in miombo woodlands of mainland Tanzania in order of importance were timber, fire, shifting cultivation, charcoal, natural death, firewood collection, poles, grazing by wildlife animals, carvings, grazing by domestic animals, and mining. The average number of stems and AGC removals by driver ranged from 0.006 to 16.587 stems ha-1 year-1 and 0.0-1.273 tCha-1 year-1 respectively. Furthermore, charcoal, shifting cultivation and fuelwood caused higher tree removals as opposed to timber, natural death and fire that accounted for higher AGC removals. CONCLUSIONS: Drivers caused substantial effects on the number of stems and carbon removals. Increased mitigation efforts in addressing removals by timber, fires, shifting cultivation, charcoal and natural death would be effective in mitigating degradation in miombo woodlands of Tanzania. Additionally, site-specific studies need to be conducted to bring information that would be used for managing woodlands at local levels. This kind of study need to be conducted in other vegetation types like montane and Mangrove forest at national scale in Tanzania.

[Spatiotemporal dynamic simulation on aboveground carbon storage of bamboo forest and its influence factors in Zhejiang Province, China.] / æµ™æ±Ÿçœç«¹æž—åœ°ä¸Šç¢³å‚¨é‡çš„æ—¶ç©ºåŠ¨æ€æ¨¡æ‹ŸåŠå½±å“å› ç´ .

Bamboo forests have an efficient carbon sequestration capacity and play an important role in responding to global climate change. However, the current estimation of bamboo carbon storage has some errors, leading to uncertainty in the spatiotemporal pattern of bamboo forest carbon storage. This study simulated aboveground carbon storage of Zhejiang Province, China, during 1984-2014 based on the combination of an improved BIOME-BGC (biogeochemical cycles) model and remote sensing data, with the accuracy being verified with forest resource inventory data. The spatio-temporal distribution and environmental factors of aboveground carbon storage were analyzed. The results showed that the simulated carbon storage was accurate, with average correlation coefficient (r), root mean square error (RMSE) and relative bias (rBIAS) being 0.75, 7.24 Mg C·hm-2 and -2.57 Mg C·hm-2, respectively. Generally, the aboveground carbon storage of bamboo forests in the whole province tended to increase from 1984 to 2014, the range of aboveground carbon density was 13.10-17.14 Mg C·hm-2, and that of the total aboveground carbon storage was between 9.94-17.19 Tg C. The high aboveground carbon storage of bamboo was mainly distributed in developed bamboo industry areas, such as Anji, Lin'an, and Longyou. The change of aboveground carbon storage in bamboo forest was significantly correlated with temperature, precipitation, radiation, CO2 concentration and nitrogen deposition, with higher partial correlation coefficients between precipitation and temperature and carbon storage.

Large-sized rare tree species contribute disproportionately to functional diversity in resource acquisition in African tropical forest.

Increasing evidence is available for a positive effect of biodiversity on ecosystem productivity and standing biomass, also in highly diverse systems as tropical forests. Biodiversity conservation could therefore be a critical aspect of climate mitigation policies. There is, however, limited understanding of the role of individual species for this relationship, which could aid in focusing conservation efforts and forest management planning. This study characterizes the functional specialization and redundancy for 95% of all tree species (basal area weighted percentage) in a diverse tropical forest in the central Congo Basin and relates this to species' abundance, contribution to aboveground carbon, and maximum size. Functional characterization is based on a set of traits related to resource acquisition (wood density, specific leaf area, leaf carbon, nitrogen and phosphorus content, and leaf stable carbon isotope composition). We show that within both mixed and monodominant tropical forest ecosystems, the highest functional specialization and lowest functional redundancy are solely found in rare tree species and significantly more in rare species holding large-sized individuals. Rare species cover the entire range of low and high functional redundancy, contributing both unique and redundant functions. Loss of species supporting functional redundancy could be buffered by other species in the community, including more abundant species. This is not the case for species supporting high functional specialization and low functional redundancy, which would need specific conservation attention. In terms of tropical forest management planning, we argue that specific conservation of large-sized trees is imperative for long-term maintenance of ecosystem functioning.

Elephants limit aboveground carbon gains in African savannas.

Understanding the drivers of vegetation carbon dynamics is essential for climate change mitigation and effective policy formulation. However, most efforts focus on abiotic drivers of plant biomass change, with little consideration for functional roles performed by animals, particularly at landscape scales. We combined repeat airborne Light Detection and Ranging with measurements of elephant densities, abiotic factors, and exclusion experiments to determine the relative importance of drivers of change in aboveground woody vegetation carbon stocks in Kruger National Park, South Africa. Despite a growing elephant population, aboveground carbon density (ACD) increased across most of the landscape over the 6-year study period, but at fine scales, bull elephant density was the most important factor determining carbon stock change, with ACD losses recorded only where bull densities exceeded 0.5 bulls/km2 . Effects of bull elephants were, however, spatially restricted and landscape dependent, being especially pronounced along rivers, at mid-elevations, and on steeper slopes. In contrast, elephant herds and abiotic drivers had a comparatively small influence on the direction or magnitude of carbon stock change. Our findings demonstrate that animals can have a substantive influence on regional-scale carbon dynamics and warrant consideration in carbon cycling models and policy formulation aimed at carbon management and climate change mitigation.

Aboveground forest carbon shows different responses to fire frequency in harvested and unharvested forests.

Sequestration of carbon in forest ecosystems has been identified as an effective strategy to help mitigate the effects of global climate change. Prescribed burning and timber harvesting are two common, co-occurring, forest management practices that may alter forest carbon pools. Prescribed burning for forest management, such as wildfire risk reduction, may shorten inter-fire intervals and potentially reduce carbon stocks. Timber harvesting may further increase the susceptibility of forest carbon to losses in response to frequent burning regimes by redistributing carbon stocks from the live pools into the dead pools, causing mechanical damage to retained trees and shifting the demography of tree communities. We used a 27-yr experiment in a temperate eucalypt forest to examine the effect of prescribed burning frequency and timber harvesting on aboveground carbon (AGC). Total AGC was reduced by ~23% on harvested plots when fire frequency increased from zero to seven fires, but was not affected by fire frequency on unharvested plots. The reduction in total AGC associated with increasing fire frequency on harvested plots was driven by declines in large coarse woody debris (≥10 cm diameter) and large trees (≥20 cm diameter). Small tree (<20 cm DBH) AGC increased with fire frequency on harvested plots, but decreased on unharvested plots. Carbon in dead standing trees decreased with increasing fire frequency on unharvested plots, but was unaffected on harvested plots. Small coarse woody debris (<10 cm diameter) was largely unaffected by fire frequency and harvesting. Total AGC on harvested plots was between 67% and 82% of that on unharvested plots, depending on burning treatment. Our results suggest that AGC in historically harvested forests may be susceptible to declines in response to increases in prescribed burning frequency. Consideration of historic harvesting will be important in understanding the effect of prescribed burning programs on forest carbon budgets.

Topography shapes the structure, composition and function of tropical forest landscapes.

Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo - at a site where 70-m-tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient-depleted dip slopes - we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old-growth forest. We found that subtle differences in elevation - which control soil chemistry and hydrology - profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape-scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long-standing ecological questions.

Aboveground Carbon Storage and Its Links to Stand Structure, Tree Diversity and Floristic Composition in South-Eastern Tanzania.

African savannas and dry forests represent a large, but poorly quantified store of biomass carbon and biodiversity. Improving this information is hindered by a lack of recent forest inventories, which are necessary for calibrating earth observation data and for evaluating the relationship between carbon stocks and tree diversity in the context of forest conservation (for example, REDD+). Here, we present new inventory data from south-eastern Tanzania, comprising more than 15,000 trees at 25 locations located across a gradient of aboveground woody carbon (AGC) stocks. We find that larger trees disproportionately contribute to AGC, with the largest 3.7% of individuals containing half the carbon. Tree species diversity and carbon stocks were positively related, implying a potential functional relationship between the two, and a 'win-win' scenario for conservation; however, lower biomass areas also contain diverse species assemblages meaning that carbon-oriented conservation may miss important areas of biodiversity. Despite these variations, we find that total tree abundance and biomass is skewed towards a few locally dominant species, with eight and nine species (5.7% of the total) accounting for over half the total measured trees and carbon, respectively. This finding implies that carbon production in these areas is channelled through a small number of relatively abundant species. Our results provide key insights into the structure and functioning of these heterogeneous ecosystems and indicate the need for novel strategies for future measurement and monitoring of carbon stocks and biodiversity, including the use for larger plots to capture spatial variations in large tree density and AGC stocks, and to allow the calibration of earth observation data.

Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

Urban areas are sources of land use change and CO2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha-1 calculated across the entire urban land area, and 110.9±19.7MgCha-1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented.

Who owns the Brazilian carbon?

Brazil is one of the major contributors to land-use change emissions, mostly driven by agricultural expansion for food, feed, and bioenergy feedstock. Policies to avoid deforestation related to private commitments, economic incentives, and other support schemes are expected to improve the effectiveness of current command and control mechanisms increasingly. However, until recently, land tenure was unknown for much of the Brazilian territory, which has undermined the governance of native vegetation and challenged support and incentive mechanisms for avoiding deforestation. We assess the total extent of public governance mechanisms protecting aboveground carbon (AGC) stocks. We constructed a land tenure dataset for the entire nation and modeled the effects and uncertainties of major land-use acts on protecting AGC stocks. Roughly 70% of the AGC stock in Brazil is estimated to be under legal protection, and an additional 20% is expected to be protected after areas in the Amazon with currently undesignated land undergo a tenure regularization. About 30% of the AGC stock is on private land, of which roughly two-thirds are protected. The Cerrado, Amazon, and Caatinga biomes hold about 40%, 30%, and 20% of the unprotected AGC, respectively. Effective conservation of protected and unprotected carbon will depend on successful implementation of the Forest Act, and regularization of land tenure in the Amazon. Policy development that prioritizes unprotected AGC stocks is warranted to promote conservation of native vegetation beyond the legal requirements. However, different biomes and land tenure structures may require different policy settings considering local and regional specifics. Finally, the fate of current AGC stocks relies upon effective implementation of command and control mechanisms, considering that unprotected AGC in native vegetation on private land only accounts for 6.5% of the total AGC stock.

Community-weighted mean of leaf traits and divergence of wood traits predict aboveground biomass in secondary subtropical forests.

Subtropical forests are globally important in providing ecological goods and services, but it is not clear whether functional diversity and composition can predict aboveground biomass in such forests. We hypothesized that high aboveground biomass is associated with high functional divergence (FDvar, i.e., niche complementarity) and community-weighted mean (CWM, i.e., mass ratio; communities dominated by a single plant strategy) of trait values. Structural equation modeling was employed to determine the direct and indirect effects of stand age and the residual effects of CWM and FDvar on aboveground biomass across 31 plots in secondary forests in subtropical China. The CWM model accounted for 78, 20, 6 and 2% of the variation in aboveground biomass, nitrogen concentration in young leaf, plant height and specific leaf area of young leaf, respectively. The FDvar model explained 74, 13, 7 and 0% of the variation in aboveground biomass, plant height, twig wood density and nitrogen concentration in young leaf, respectively. The variation in aboveground biomass, CWM of leaf nitrogen concentration and specific leaf area, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf explained by the joint model was 86, 20, 13, 7, 2 and 0%, respectively. Stand age had a strong positive direct effect but low indirect positive effects on aboveground biomass. Aboveground biomass was negatively related to CWM of nitrogen concentration in young leaf, but positively related to CWM of specific leaf area of young leaf and plant height, and FDvar of plant height, twig wood density and nitrogen concentration in young leaf. Leaf and wood economics spectra are decoupled in regulating the functionality of forests, communities with diverse species but high nitrogen conservative and light acquisitive strategies result in high aboveground biomass, and hence, supporting both the mass ratio and niche complementarity hypotheses in secondary subtropical forests.

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By synergistically using the object-based image analysis (OBIA) and the classification and regression tree (CART) methods, the distribution information, the indexes (including diameter at breast, tree height, and crown closure), and the aboveground carbon storage (AGC) of moso bamboo forest in Shanchuan Town, Anji County, Zhejiang Province were investigated. The results showed that the moso bamboo forest could be accurately delineated by integrating the multi-scale ima ge segmentation in OBIA technique and CART, which connected the image objects at various scales, with a pretty good producer's accuracy of 89.1%. The investigation of indexes estimated by regression tree model that was constructed based on the features extracted from the image objects reached normal or better accuracy, in which the crown closure model archived the best estimating accuracy of 67.9%. The estimating accuracy of diameter at breast and tree height was relatively low, which was consistent with conclusion that estimating diameter at breast and tree height using optical remote sensing could not achieve satisfactory results. Estimation of AGC reached relatively high accuracy, and accuracy of the region of high value achieved above 80%.