War drives forest fire risks and highlights the need for more ecologically-sound forest management in post-war Ukraine.

Since 24 February 2022, Ukraine has experienced full-scale military aggression initiated by the Russian Federation. The war has had a major negative impact on vegetation cover of war-affected regions. We explored interactions between pre-war forest management and the impacts of military activities in three of the most forested Ukrainian areas of interest (AOI), affected by the war. These were forests lying between Kharkiv and Luhansk cities (AOI 'East'), forests along the Dnipro River delta (AOI 'Kherson'), and those of the Chornobyl Exclusion Zone (AOI CEZ). We used Sentinel satellite imagery to create damaged forest cover masks for the year 2022. We mapped forests with elevated fire hazard, which was defined as a degree of exposure to the fire-supporting land use (mostly an agricultural land, a common source of ignitions in Ukraine). We evaluated the forest disturbance rate in 2022, as compared to pre-war rates. We documented significant increases in non-stand replacing disturbances (low severity fires and non-fire disturbances) for all three of the AOIs. Damaged forest cover varied among the AOIs (24,180 ± 4,715 ha, or 9.3% ± 1.8% in the 'East' AOI; 7,293 ± 1,925 ha, or 15.7% ± 4.1% in the 'Kherson' AOI; 7,116 ± 1,274 ha, or 5.0% ± 0.9% in the CEZ AOI). Among the forests damaged in 2022, the 'Kherson' AOI will likely have the highest proportion of an area with elevated fire hazard in the coming decades, as compared to other regions (89% vs. 70% in the 'East' and CEZ AOIs respectively). Future fire risks and extensive war-related disturbance of forest cover call for forest management to develop strategies explicitly addressing these factors.

A national-scale land cover reference dataset from local crowdsourcing initiatives in Indonesia.

Here we present a geographically diverse, temporally consistent, and nationally relevant land cover (LC) reference dataset collected by visual interpretation of very high spatial resolution imagery, in a national-scale crowdsourcing campaign (targeting seven generic LC classes) and a series of expert workshops (targeting seventeen detailed LC classes) in Indonesia. The interpreters were citizen scientists (crowd/non-experts) and local LC visual interpretation experts from different regions in the country. We provide the raw LC reference dataset, as well as a quality-filtered dataset, along with the quality assessment indicators. We envisage that the dataset will be relevant for: (1) the LC mapping community (researchers and practitioners), i.e., as reference data for training machine learning algorithms and map accuracy assessment (with appropriate quality-filters applied), and (2) the citizen science community, i.e., as a sizable empirical dataset to investigate the potential and limitations of contributions from the crowd/non-experts, demonstrated for LC mapping in Indonesia for the first time to our knowledge, within the context of complementing traditional data collection by expert interpreters.

Global forest management data for 2015 at a 100 m resolution.

Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki ( https://www.geo-wiki.org/ ). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.

Russian forest sequesters substantially more carbon than previously reported.

Since the collapse of the Soviet Union and transition to a new forest inventory system, Russia has reported almost no change in growing stock (+ 1.8%) and biomass (+ 0.6%). Yet remote sensing products indicate increased vegetation productivity, tree cover and above-ground biomass. Here, we challenge these statistics with a combination of recent National Forest Inventory and remote sensing data to provide an alternative estimate of the growing stock of Russian forests and to assess the relative changes in post-Soviet Russia. Our estimate for the year 2014 is 111 ± 1.3 × 109 m3, or 39% higher than the value in the State Forest Register. Using the last Soviet Union report as a reference, Russian forests have accumulated 1163 × 106 m3 yr-1 of growing stock between 1988-2014, which balances the net forest stock losses in tropical countries. Our estimate of the growing stock of managed forests is 94.2 × 109 m3, which corresponds to sequestration of 354 Tg C yr-1 in live biomass over 1988-2014, or 47% higher than reported in the National Greenhouse Gases Inventory.

Forest management can mitigate negative impacts of climate and land-use change on plant biodiversity: Insights from the Republic of Korea.

Over the past century, the decline in biodiversity due to climate change and habitat loss has become unprecedentedly serious. Multiple drivers, including climate change, land-use/cover change, and qualitative change in habitat need to be considered in an integrated approach, which has rarely been taken, to create an effective conservation strategy. The purpose of this study is to quantitatively evaluate and map the combined impacts of those multiple drivers on biodiversity in the Republic of Korea (ROK). To this end, biodiversity persistence (BP) was simulated by employing generalized dissimilarity modeling with estimates of habitat conditions. Habitat Condition Index was newly developed based on national survey datasets to represent the changes in habitat quality according to the land cover changes and forest management, especially after the ROK's National Reforestation Programme. The changes in habitat conditions were simulated for a period ranging from the 1960s to the 2010s; additionally, future (2050s) spatial scenarios were constructed. By focusing on the changes in forest habitat quality along with climate and land use, this study quantitatively and spatially analyzed the changes in BP over time and presented the effects of reforestation and forest management. The results revealed that continuous forest management had a positive impact on BP by offsetting the negative effects of past urbanization. Improvements in forest habitat quality also can effectively reduce the negative impacts of climate change. This quantitative analysis of successful forest restoration in Korea proved that economic development and urbanization could be in parallel with biodiversity enhancement. Nevertheless, current forest management practices were found to be insufficient in fully offsetting the decline in future BP caused by climate change. This indicates that there is a need for additional measures along with mitigation of climate change to maintain the current biodiversity level.

A map of the extent and year of detection of oil palm plantations in Indonesia, Malaysia and Thailand.

In recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived.

Verifiable soil organic carbon modelling to facilitate regional reporting of cropland carbon change: A test case in the Czech Republic.

Regional monitoring, reporting and verification of soil organic carbon change occurring in managed cropland are indispensable to support carbon-related policies. Rapidly evolving gridded agronomic models can facilitate these efforts throughout Europe. However, their performance in modelling soil carbon dynamics at regional scale is yet unexplored. Importantly, as such models are often driven by large-scale inputs, they need to be benchmarked against field experiments. We elucidate the level of detail that needs to be incorporated in gridded models to robustly estimate regional soil carbon dynamics in managed cropland, testing the approach for regions in the Czech Republic. We first calibrated the biogeochemical Environmental Policy Integrated Climate (EPIC) model against long-term experiments. Subsequently, we examined the EPIC model within a top-down gridded modelling framework constructed for European agricultural soils from Europe-wide datasets and regional land-use statistics. We explored the top-down, as opposed to a bottom-up, modelling approach for reporting agronomically relevant and verifiable soil carbon dynamics. In comparison with a no-input baseline, the regional EPIC model suggested soil carbon changes (~0.1-0.5 Mg C ha-1 y-1) consistent with empirical-based studies for all studied agricultural practices. However, inaccurate soil information, crop management inputs, or inappropriate model calibration may undermine regional modelling of cropland management effect on carbon since each of the three components carry uncertainty (~0.5-1.5 Mg C ha-1 y-1) that is substantially larger than the actual effect of agricultural practices relative to the no-input baseline. Besides, inaccurate soil data obtained from the background datasets biased the simulated carbon trends compared to observations, thus hampering the model's verifiability at the locations of field experiments. Encouragingly, the top-down agricultural management derived from regional land-use statistics proved suitable for the estimation of soil carbon dynamics consistently with actual field practices. Despite sensitivity to biophysical parameters, we found a robust scalability of the soil organic carbon routine for various climatic regions and soil types represented in the Czech experiments. The model performed better than the tier 1 methodology of the Intergovernmental Panel on Climate Change, which indicates a great potential for improved carbon change modelling over larger political regions.

The impact of climate change on Brazil's agriculture.

Brazilian agricultural production provides a significant fraction of the food consumed globally, with the country among the top exporters of soybeans, sugar, and beef. However, current advances in Brazilian agriculture can be directly impacted by climate change and resulting biophysical effects. Here, we quantify these impacts until 2050 using GLOBIOM-Brazil, a global partial equilibrium model of the competition for land use between agriculture, forestry, and bioenergy that includes various refinements reflecting Brazil's specificities. For the first time, projections of future agricultural areas and production are based on future crop yields provided by two Global Gridded Crop Models (EPIC and LPJmL). The climate change forcing is included through changes in climatic variables projected by five Global Climate Models in two emission pathways (RCP2.6 and RCP8.5) participating in the ISIMIP initiative. This ensemble of twenty scenarios permits accessing the robustness of the results. When compared to the baseline scenario, GLOBIOM-Brazil scenarios suggest a decrease in soybeans and corn production, mainly in the Matopiba region in the Northern Cerrado, and southward displacement of agricultural production to near-subtropical and subtropical regions of the Cerrado and the Atlantic Forest biomes.

Expanding the Soy Moratorium to Brazil's Cerrado.

The Cerrado biome in Brazil is a tropical savanna and an important global biodiversity hot spot. Today, only a fraction of its original area remains undisturbed, and this habitat is at risk of conversion to agriculture, especially to soybeans. Here, we present the first quantitative analysis of expanding the Soy Moratorium (SoyM) from the Brazilian Amazon to the Cerrado biome. The SoyM expansion to the Cerrado would prevent the direct conversion of 3.6 million ha of native vegetation to soybeans by 2050. Nationally, this would require a reduction in soybean area of approximately 2%. Relative risk of future native vegetation conversion for soybeans would be driven by the Brazilian domestic market, China, and the European Union. We conclude that, to preserve the Cerrado's biodiversity and ecosystem services, urgent action is required, including a zero native vegetation conversion agreement such as the SoyM.

To burn or retain crop residues on croplands? An integrated analysis of crop residue management in China.

Crop residue burning influences human health and global climate change. In China-the world's largest crop residue producer-farmers burn almost one quarter of their crop residues in the field after harvest, despite the government providing financial incentives such as subsidies to retain crop residues. This study combined economic analyses with simulations of soil carbon accumulation and carbon emission reduction associated with different residue management practices to determine the minimum level of incentives needed for Chinese farmers to shift from burning to retaining crop residues for generating carbon benefits. Simulation results showed that [1] the density of topsoil organic carbon in China's croplands would have increased from about 21.8 t ha-1 in 2000 to 23.9 t ha-1 in 2010, and soil organic carbon sequestration would have reached 24.4 Tg C yr-1 if farmers had shifted from burning to retaining crop residues on croplands during this period; and [2] retaining crop residues would have avoided about 149.9 Tg of CO2 emission per year. Economic analyses showed that [1] existing subsidies in all regions of China, except Northeast China, only accounted for 18-82% of the incentives required for farmers to shift from burning to crop residue retention; [2] Northeast China required the lowest incentive (287 CNY ha-1), while eastern China required the highest (837 CNY ha-1); and [3] the prevailing market prices (1.4-60.2 CNY tCO2e-1) in China's seven pilot carbon markets seem to be below the required incentives (39.6-189.1 CNY tCO2e-1). Our study suggests that the Chinese government should increase subsidies or seek innovative incentive schemes to encourage farmers to change their crop residue management practices for global climate change mitigation and health benefits.

Identifying hotspots of land use cover change under socioeconomic and climate change scenarios in Mexico.

This study identifies the hotspots of land use cover change (LUCC) under two socioeconomic and climate change scenarios [business as usual (BAU) and a pessimistic scenario] at the national level for Mexico for three-time periods. Modelling suggests that by 2050 grassland and tropical evergreen forest will be the most endangered ecosystems, having lost 20-33% (BAU) or 43-46% (pessimistic scenario) of their extent in comparison to 1993. Agricultural expansion would be the major driver of LUCC, increasing from 24.4% of the country in 1993 to 30% (BAU) or 34% (pessimistic) in 2050. The most influential variables were distance from roads and human settlements, slope, aridity, and evapotranspiration. The hotspots of LUCC were influenced by environmental constraints and socioeconomic activities more than by climate change. These findings could be used to build proposals to reduce deforestation, including multiple feedbacks among urbanization, industrialization and food consumption.

Spatial distribution of arable and abandoned land across former Soviet Union countries.

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

Comment on "The extent of forest in dryland biomes".

Bastin et al (Reports, 12 May 2017, p. 635) claim to have discovered 467 million hectares of new dryland forest. We would argue that these additional areas are not completely "new" and that some have been reported before. A second shortcoming is that not all sources of uncertainty are considered; the uncertainty could be much higher than the reported value of 3.5%.

A global dataset of crowdsourced land cover and land use reference data.

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

A dataset of forest biomass structure for Eurasia.

The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

Assessing the land resource-food price nexus of the Sustainable Development Goals.

The 17 Sustainable Development Goals (SDGs) call for a comprehensive new approach to development rooted in planetary boundaries, equity, and inclusivity. The wide scope of the SDGs will necessitate unprecedented integration of siloed policy portfolios to work at international, regional, and national levels toward multiple goals and mitigate the conflicts that arise from competing resource demands. In this analysis, we adopt a comprehensive modeling approach to understand how coherent policy combinations can manage trade-offs among environmental conservation initiatives and food prices. Our scenario results indicate that SDG strategies constructed around Sustainable Consumption and Production policies can minimize problem-shifting, which has long placed global development and conservation agendas at odds. We conclude that Sustainable Consumption and Production policies (goal 12) are most effective at minimizing trade-offs and argue for their centrality to the formulation of coherent SDG strategies. We also find that alternative socioeconomic futures-mainly, population and economic growth pathways-generate smaller impacts on the eventual achievement of land resource-related SDGs than do resource-use and management policies. We expect that this and future systems analyses will allow policy-makers to negotiate trade-offs and exploit synergies as they assemble sustainable development strategies equal in scope to the ambition of the SDGs.

New feed sources key to ambitious climate targets.

Net carbon sinks capable of avoiding dangerous perturbation of the climate system and preventing ocean acidification have been identified, but they are likely to be limited by resource constraints (Nature 463:747-756, 2010). Land scarcity already creates tension between food security and bioenergy production, and this competition is likely to intensify as populations and the effects of climate change expand. Despite research into microalgae as a next-generation energy source, the land-sparing consequences of alternative sources of livestock feed have been overlooked. Here we use the FeliX model to quantify emissions pathways when microalgae is used as a feedstock to free up to 2 billion hectares of land currently used for pasture and feed crops. Forest plantations established on these areas can conceivably meet 50 % of global primary energy demand, resulting in emissions mitigation from the energy and LULUC sectors of up to 544 [Formula: see text] 107 PgC by 2100. Further emissions reductions from carbon capture and sequestration (CCS) technology can reduce global atmospheric carbon concentrations close to preindustrial levels by the end of the present century. Though previously thought unattainable, carbon sinks and climate change mitigation of this magnitude are well within the bounds of technological feasibility.

Mapping global cropland and field size.

A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

Climate change mitigation through livestock system transitions.

Livestock are responsible for 12% of anthropogenic greenhouse gas emissions. Sustainable intensification of livestock production systems might become a key climate mitigation technology. However, livestock production systems vary substantially, making the implementation of climate mitigation policies a formidable challenge. Here, we provide results from an economic model using a detailed and high-resolution representation of livestock production systems. We project that by 2030 autonomous transitions toward more efficient systems would decrease emissions by 736 million metric tons of carbon dioxide equivalent per year (MtCO2e⋅y(-1)), mainly through avoided emissions from the conversion of 162 Mha of natural land. A moderate mitigation policy targeting emissions from both the agricultural and land-use change sectors with a carbon price of US$10 per tCO2e could lead to an abatement of 3,223 MtCO2e⋅y(-1). Livestock system transitions would contribute 21% of the total abatement, intra- and interregional relocation of livestock production another 40%, and all other mechanisms would add 39%. A comparable abatement of 3,068 MtCO2e⋅y(-1) could be achieved also with a policy targeting only emissions from land-use change. Stringent climate policies might lead to reductions in food availability of up to 200 kcal per capita per day globally. We find that mitigation policies targeting emissions from land-use change are 5 to 10 times more efficient--measured in "total abatement calorie cost"--than policies targeting emissions from livestock only. Thus, fostering transitions toward more productive livestock production systems in combination with climate policies targeting the land-use change appears to be the most efficient lever to deliver desirable climate and food availability outcomes.