A new circa 2007 biomass map for China differs significantly from existing maps.

The forest area of China is the fifth largest of any country, and unlike in many other countries, in recent decades its area has been increasing. However, there are substantial differences in estimates of the amount of carbon this forest contains, ranging from 3.92 to 17.02 Pg C for circa 2007. This makes it unclear how the changes in China's forest area contribute to the global carbon cycle. We generate a circa 2007 aboveground biomass (AGB) map at a resolution of 50 m using optical, radar and LiDAR satellite data. Our estimates of total carbon stored in the forest in China was 9.52 Pg C, with an average forest AGB of 104 Mg ha-1. Compared with three existing AGB maps, our AGB map showed better correlation with a distributed set of forest inventory plots. In addition, our high resolution AGB map provided more details on spatial distribution of forest AGB, and is likely to help understand the carbon storage changes in China's forest.

Protected areas reduce deforestation and degradation and enhance woody growth across African woodlands.

Protected areas are increasingly promoted for their capacity to sequester carbon, alongside biodiversity benefits. However, we have limited understanding of whether they are effective at reducing deforestation and degradation, or promoting vegetation growth, and the impact that this has on changes to aboveground woody carbon stocks. Here we present a new satellite radar-based map of vegetation carbon change across southern Africa's woodlands and combine this with a matching approach to assess the effect of protected areas on carbon dynamics. We show that protection has a positive effect on aboveground carbon, with stocks increasing faster in protected areas (+0.53% per year) compared to comparable lands not under protection (+0.08% per year). The positive effect of protection reflects lower rates of deforestation (-39%) and degradation (-25%), as well as a greater prevalence of vegetation growth (+12%) inside protected lands. Areas under strict protection had similar outcomes to other types of protection after controlling for differences in location, with effect scores instead varying more by country, and the level of threat. These results highlight the potential for protected areas to sequester aboveground carbon, although we caution that in some areas this may have negative impacts on biodiversity, and human wellbeing.

Quasi-experimental analysis of new mining developments as a driver of deforestation in Zambia.

Mining is a vital part of the global, and many national, economies. Mining also has the potential to drive extensive land cover change, including deforestation, with impacts reaching far from the mine itself. Understanding the amount of deforestation associated with mining is important for conservationists, governments, mining companies, and consumers, yet accurate quantification is rare. We applied statistical matching, a quasi-experimental methodology, along with Bayesian hierarchical generalized linear models to assess the impact on deforestation of new mining developments in Zambia from 2000 to present. Zambia is a globally significant producer of minerals and mining contributes ~ 10% of its gross domestic product and ~ 77% of its exports. Despite extensive deforestation in mining impacted land, we found no evidence that any of the 22 mines we analysed increased deforestation compared with matched control sites. The extent forest lost was therefore no different than would likely have happened without the mines being present due to other drivers of deforestation in Zambia. This suggests previous assessments based on correlative methodologies may overestimate the deforestation impact of mining. However, mining can have a range of impacts on society, biodiversity, and the local environment that are not captured by our analysis.

Mapping native and non-native vegetation in the Brazilian Cerrado using freely available satellite products.

Native vegetation across the Brazilian Cerrado is highly heterogeneous and biodiverse and provides important ecosystem services, including carbon and water balance regulation, however, land-use changes have been extensive. Conservation and restoration of native vegetation is essential and could be facilitated by detailed landcover maps. Here, across a large case study region in Goiás State, Brazil (1.1 Mha), we produced physiognomy level maps of native vegetation (n = 8) and other landcover types (n = 5). Seven different classification schemes using different combinations of input satellite imagery were used, with a Random Forest classifier and 2-stage approach implemented within Google Earth Engine. Overall classification accuracies ranged from 88.6-92.6% for native and non-native vegetation at the formation level (stage-1), and 70.7-77.9% for native vegetation at the physiognomy level (stage-2), across the seven different classifications schemes. The differences in classification accuracy resulting from varying the input imagery combination and quality control procedures used were small. However, a combination of seasonal Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (surface reflectance) imagery resulted in the most accurate classification at a spatial resolution of 20 m. Classification accuracies when using Landsat-8 imagery were marginally lower, but still reasonable. Quality control procedures that account for vegetation burning when selecting vegetation reference data may also improve classification accuracy for some native vegetation types. Detailed landcover maps, produced using freely available satellite imagery and upscalable techniques, will be important tools for understanding vegetation functioning at the landscape scale and for implementing restoration projects.

Structural diversity and tree density drives variation in the biodiversity-ecosystem function relationship of woodlands and savannas.

Positive biodiversity-ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance-driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. We used > 1000 vegetation plots distributed across 10 southern African countries and structural equation modelling to determine the relationship between tree species diversity and above-ground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. We found positive effects of tree species diversity on above-ground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha-1 . We found that water availability mainly affects biomass indirectly, via increasing species diversity. The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under-appreciated determinant of wooded ecosystem structure and function.

Comment on "The global tree restoration potential".

Bastin et al (Reports, 5 July 2019, p. 76) state that the restoration potential of new forests globally is 205 gigatonnes of carbon, conclude that "global tree restoration is our most effective climate change solution to date," and state that climate change will drive the loss of 450 million hectares of existing tropical forest by 2050. Here we show that these three statements are incorrect.

Oil palm concessions in southern Myanmar consist mostly of unconverted forest.

The increased demand for palm oil has led to an expansion of oil palm concessions in the tropics, and the clearing of abundant forest as a result. However, concessions are typically incompletely planted to varying degrees, leaving much land unused. The remaining forests within such concessions are at high risk of deforestation, as there are normally no legal hurdles to their clearance, therefore making them excellent targets for conservation. We investigated the location of oil palm plantations and the other major crop - rubber plantations in southern Myanmar, and compared them to concession boundaries. Our results show that rubber plantations cover much larger areas than oil palm in the region, indicating that rubber is the region's preferred crop. Furthermore, only 15% of the total concession area is currently planted with oil palm (49,000 ha), while 25,000 ha is planted outside concession boundaries. While this may in part be due to uncertain and/or changing boundaries, this leaves most of the concession area available for other land uses, including forest conservation and communities' livelihood needs. Reconsidering the remaining concession areas can also significantly reduce future emission risks from the region.

Carbon losses from deforestation and widespread degradation offset by extensive growth in African woodlands.

Land use carbon fluxes are major uncertainties in the global carbon cycle. This is because carbon stocks, and the extent of deforestation, degradation and biomass growth remain poorly resolved, particularly in the densely populated savannas which dominate the tropics. Here we quantify changes in aboveground woody carbon stocks from 2007-2010 in the world's largest savanna-the southern African woodlands. Degradation is widespread, affecting 17.0% of the wooded area, and is the source of 55% of biomass loss (-0.075 PgC yr-1). Deforestation losses are lower (-0.038 PgC yr-1), despite deforestation rates being 5× greater than existing estimates. Gross carbon losses are therefore 3-6x higher than previously thought. Biomass gains occurred in 48% of the region and totalled +0.12 PgC yr-1. Region-wide stocks are therefore stable at ~5.5 PgC. We show that land cover in African woodlands is highly dynamic with globally high rates of degradation and deforestation, but also extensive regrowth.

The tropical forest carbon cycle and climate change.

Tropical forests make an approximately neutral contribution to the global carbon cycle, with intact and recovering forests taking in as much carbon as is released through deforestation and degradation. In the near future, tropical forests are likely to become a carbon source, owing to continued forest loss and the effect of climate change on the ability of the remaining forests to capture excess atmospheric carbon dioxide. This will make it harder to limit global warming to below 2 °C. Encouragingly, recent international agreements commit to halting deforestation and degradation, but a lack of fundamental data for use in monitoring and model design makes policy action difficult.

Understanding 'saturation' of radar signals over forests.

There is an urgent need to quantify anthropogenic influence on forest carbon stocks. Using satellite-based radar imagery for such purposes has been challenged by the apparent loss of signal sensitivity to changes in forest aboveground volume (AGV) above a certain 'saturation' point. The causes of saturation are debated and often inadequately addressed, posing a major limitation to mapping AGV with the latest radar satellites. Using ground- and lidar-measurements across La Rioja province (Spain) and Denmark, we investigate how various properties of forest structure (average stem height, size and number density; proportion of canopy and understory cover) simultaneously influence radar backscatter. It is found that increases in backscatter due to changes in some properties (e.g. increasing stem sizes) are often compensated by equal magnitude decreases caused by other properties (e.g. decreasing stem numbers and increasing heights), contributing to the apparent saturation of the AGV-backscatter trend. Thus, knowledge of the impact of management practices and disturbances on forest structure may allow the use of radar imagery for forest biomass estimates beyond commonly reported saturation points.

A small subset of protected areas are a highly significant source of carbon emissions.

Protected areas (PAs) aim to protect multiple ecosystem services. However, not all are well protected. For the first time, using published carbon and forest loss maps, we estimate carbon emissions in large forest PAs in tropical countries (N = 2018). We found 36 ± 16 Pg C stored in PA trees, representing 14.5% of all tropical forest biomass carbon. However the PAs lost forest at a mean rate of 0.18% yr-1 from 2000-2012. Lower protection status areas experienced higher forest losses (e.g. 0.39% yr-1 in IUCN cat III), yet even highest status areas lost 0.13% yr-1 (IUCN Cat I). Emissions were not evenly distributed: 80% of emissions derived from 8.3% of PAs (112 ± 49.5 Tg CO2 yr-1; n = 171). Unsurprisingly the largest emissions derived from PAs that started with the greatest total forest area; accounting for starting forest area and relating that to carbon lost using a linear model (r2 = 0.41), we found 1.1% outlying PAs (residuals >2σ; N = 23), representing 1.3% of the total PA forest area, yet causing 27.3% of all PA emissions. These results suggest PAs have been a successful means of protecting biomass carbon, yet a subset causing a disproportionately high share of emissions should be an urgent priority for management interventions.

Age, extent and carbon storage of the central Congo Basin peatland complex.

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 1015 grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation.

Material flows accounting for Scotland shows the merits of a circular economy and the folly of territorial carbon reporting.

BACKGROUND: It is essential that the human race limits the environmental damage created by our consumption. A realistic pathway to limiting consumption would be to transition to a system where materials are conserved and cycled through the economy as many times as possible and as slowly as possible, greatly reducing the greenhouse gas intensive processes of resource extraction, resource processing and waste management. Material flow analysis (MFA) is a method used to understand how materials are consumed within a nation. In this study, we attempt a MFA for Scotland which links carbon emissions to material consumption using data directly based on the mass of materials used in the Scottish economy. It is the first time such an analysis has been conducted for an economy in its entirety. RESEARCH AIMS: This study aims to create a detailed material flow account (MFA) for Scotland, compare the environmental impacts and possible policy implications of different future material consumption scenarios and consider two materials, steel and neodymium, in detail. RESULTS: The model estimated that 11.4 Mg per capita of materials are consumed per year in Scotland, emitting 10.7 Mg CO2e per capita in the process, of which, 6.7 Mg CO2e per capita falls under territorial carbon accounting. Only the circular economy scenario for 2050 allowed for increases in living standards without increases in carbon emissions and material consumption. This result was mirrored in the steel and neodymium case studies-environmental impacts can be minimised by a national strategy that first reduces use, and then locally reuses materials. CONCLUSIONS: Material consumption accounts for a large proportion of the carbon emissions of Scotland. Strategic dematerialisation, particular of materials such as steel, could support future efforts to reduce environmental impact and meet climate change targets. However, policy makers should consider consumption carbon accounting boundaries, as well as territorial boundaries, if carbon savings are to be maximised. This is because imports and recyclate sent abroad can have significant effect on the carbon emissions from material consumption. We demonstrate that the more circular an economy is, the smaller the difference between global and territorial carbon emissions, and therefore that climate change targets based solely on territorial carbon emissions create perverse incentives. The study also found that there could be areas of economic development which are compatible with environmental aims, based around encouraging reprocessing activities in developed nations.

An integrated pan-tropical biomass map using multiple reference datasets.

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

Erosion rates as a potential bottom-up control of forest structural characteristics in the Sierra Nevada Mountains.

The physical characteristics of landscapes place fundamental constraints on vegetation growth and ecosystem function. In actively eroding landscapes, many of these characteristics are controlled by long-term erosion rates: increased erosion rates generate steeper topography and reduce the depth and extent of weathering, limiting moisture storage capacity and impacting nutrient availability. Despite the potentially important bottom-up control that erosion rates place on substrate characteristics, the relationship between the two is largely unexplored. We investigate spatial variations in aboveground biomass (AGB) across a structurally diverse mixed coniferous/deciduous forest with an order of magnitude erosion-rate gradient in the Northern Californian Sierra Nevada, USA, using high resolution LiDAR data and field plots. Mean basin slope, a proxy for erosion rate, accounts for 32% of variance in AGB within our field area (P < 0.001), considerably outweighing the effects of mean annual precipitation, temperature, and bedrock lithology. This highlights erosion rate as a potentially important, but hitherto unappreciated, control on AGB and forest structure.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites.

AIM: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. LOCATION: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. METHODS: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. RESULTS: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. MAIN CONCLUSIONS: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Are inventory based and remotely sensed above-ground biomass estimates consistent?

Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km(2) study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha(-1), for Mozambique from 12.7 to 68.3 Mg ha(-1), and for the 1160 km(2) study area estimates range from 35.6 to 102.4 Mg ha(-1). The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed.

Woody encroachment and forest degradation in sub-Saharan Africa's woodlands and savannas 1982-2006.

We review the literature and find 16 studies from across Africa's savannas and woodlands where woody encroachment dominates. These small-scale studies are supplemented by an analysis of long-term continent-wide satellite data, specifically the Normalized Difference Vegetation Index (NDVI) time series from the Global Inventory Modeling and Mapping Studies (GIMMS) dataset. Using dry-season data to separate the tree and grass signals, we find 4.0% of non-rainforest woody vegetation in sub-Saharan Africa (excluding West Africa) significantly increased in NDVI from 1982 to 2006, whereas 3.52% decreased. The increases in NDVI were found predominantly to the north of the Congo Basin, with decreases concentrated in the Miombo woodland belt. We hypothesize that areas of increasing dry-season NDVI are undergoing woody encroachment, but the coarse resolution of the study and uncertain relationship between NDVI and woody cover mean that the results should be interpreted with caution; certainly, these results do not contradict studies finding widespread deforestation throughout the continent. However, woody encroachment could be widespread, and warrants further investigation as it has important consequences for the global carbon cycle and land-climate interactions.