Annual Cropland Research Articles

IrriMap_CN: Annual irrigation maps across China in 2000–2019 based on satellite observations, environmental variables, and machine learning

Agricultural irrigation, as an important practice to protect crops from drought and promote grain yield, has a long history in China. A timely and precise dataset about the extent and dynamics of irrigated areas is necessary for water allocation and agricultural management but is scarce in China. Here we developed annual irrigated cropland maps across China (IrriMap_CN) at 500-m resolution from 2000 to 2019, using MODIS data, machine-learning method, and Google Earth Engine platform. First, we generated annual nationwide training samples by strictly screening the existing irrigation maps downscaled from the statistical data. Second, we implemented locally adaptive random forest classifiers in 511 nominal 1° × 1° grid cells across China with MODIS vegetation indices, climatic factors, and topography variables. Third, we conducted nationwide pixel-wise validation of the IrriMap_CN using independent samples. The validation results based on more than 3000 ground truth points revealed that IrriMap_CN had high accuracies ranging from 77.2% to 85.9%. The time series of IrriMap_CN detected substantial expansion of irrigated areas in Xinjiang and Heilongjiang (more than 50% in total) and pronounced decreases in Sichuan, Jiangsu, and Hebei. The analyses of irrigation frequency, start time, and end time implied that North China Plain was the most intensive irrigated area; but the irrigation area showed a decreasing trend since 2000, consistent with the reduced agricultural water consumption. The annual irrigation datasets allow us to understand the spatiotemporal dynamics of irrigated croplands in China and are expected to contribute to the improvement of earth system models and facilitate sustainable agricultural water management.

Agroforestry perennials reduce nitrous oxide emissions and their live and dead trees increase ecosystem carbon storage.

Agroforestry systems (AFS) contribute to carbon (C) sequestration and reduction in greenhouse gas emissions from agricultural lands. However, previously understudied differences among AFS may underestimate their climate change mitigation potential. In this 3-year field study, we assessed various C stocks and greenhouse gas emissions across two common AFS (hedgerows and shelterbelts) and their component land uses: perennial vegetated areas with and without trees (woodland and grassland, respectively), newly planted saplings in grassland, and adjacent annual cropland in central Alberta, Canada. Between 2018 and 2020 (~April-October), nitrous oxide emissions were 89% lower under perennial vegetation relative to the cropland (0.02 and 0.18gN m-2 year-1 , respectively). In 2020, heterotrophic respiration in the woodland was 53% lower in shelterbelts relative to hedgerows (279 and 600 g C m-2 year-1 , respectively). Within the woodland, deadwood C stock was particularly important in hedgerows (35 MgC ha-1 or 7% of ecosystem C) relative to shelterbelts (2Mg C ha-1 or <1% of ecosystem C), and likely affected C cycling differences between the woodland types by enhancing soil labile C and microbial biomass in hedgerows. Deadwood C stock was positively correlated with annual heterotrophic respiration and total (to ~100 cm depth) soil organic C, water-soluble organic C, and microbial biomass C. Total ecosystem C was 1.90-2.55 times greater within the woodland than all other land uses, with 176, 234, 237, and 449 Mg C ha-1 found in the cropland, grassland, planted saplings treatment, and woodland, respectively. Shelterbelt and hedgerow woodlands contained 2.09 and 3.03 times more C, respectively, than adjacent cropland. Our findings emphasize the importance of AFS for fostering C sequestration and reducing greenhouse gas emissions and, in particular, retaining hedgerows (legacy woodland) and their associated deadwood across temperate agroecosystems will help mitigate climate change.

Site-based vs. species-based analyses of long-term farmland bird datasets: Implications for conservation policy evaluations

Conservation of Europe’s biodiversity increasingly depends on funds invested within Natura 2000 farmland. Performance of these investments is estimated by the official Farmland Bird Index indicator, that merges species-specific trends for farmland species estimated with the standard TRIM method. We here reanalyze the long-term datasets used to calculate the Spanish Farmland Bird Index by computing abundance and richness of selected bird groups at the point census scale rather than by merging species’ trends. We test whether community trends at site scales differed according to agricultural habitat types (annual, perennial, and mosaic croplands) and locations inside or outside Natura 2000 sites, using both the TRIM method and generalized mixed models. Site-based analyses showed a general increase in bird abundance and richness outside the Natura 2000 network, and a general decrease in perennial and mosaic croplands inside it. Increasing trends were due to non-farmland birds occupying farmland, as farmland species showed significant decreasing trends overall, especially inside Natura 2000 sites and for steppic birds. Trends for threatened birds in annual cropland located inside Nature 2000 were positive, but trends for threatened farmland birds were negative overall, especially in mosaic croplands. Results were qualitatively consistent among statistical methods, although quantitative estimates varied widely among methods, habitats, Natura 2000 location, and relevant bird groups. Site-based analyses of long-term databases confirmed overall trends detected by species-based official reports, and complement them by suggesting additional reasons for failures at reverting negative trends in farmland biodiversity. Regionally-targeted conservation measures should be developed and/or extended to improve these results, and their results monitored at the farm scale to complement the low spatial resolution of volunteer-based bird monitoring schemes. Combination of broad–scale citizen science programs with cause-effect, finer-scale studies will help disentangle the causes of the observed patterns to develop better and more efficient recommendations for conservation measures in farmland areas.

Nitrate losses across 29 Iowa watersheds: Measuring long-term trends in the context of interannual variability.

In the U.S. Corn Belt, annual croplands are the primary source of nitrate loading to waterways. Long periods of fallow cause most nitrate loss, but there is extreme interannual variability in the magnitude of nitrate loss due to weather. Using mean annual (2001-2018) flow-weighted nitrate-N concentration (FWNC; mg NO3 - -N L-1 ), load (kg NO3 - -N), and yield (kg NO3 - -N ha-1 cropland) for 29 watersheds, our objectives were (a) to quantify the magnitude and interannual variability of 5-yr moving average FWNC, load, and yield; (2) to estimate the probability of measuring 41% reductions in nitrate loss after isolating the effect of weather on nitrate loss by quantifying the interannual variability of nitrate loss in watersheds where there was no trend in 5-yr moving average nitrate loss (Iowa targets a 41% nitrate loss reduction from croplands); and (c) to identify factors that, in the absence of long-term trends in nitrate loss, best explain the interannual variability in nitrate loss. Averaged across all watersheds, the mean probability of measuring a statistically significant 41% reduction in FWNC across 15 yr, should it occur, was 96%. However, the probabilities of measuring 41% reductions in nitrate load and yield were only 44 and 32%. Across watersheds, soil organic matter, tile drainage, interannual variability of precipitation, and watershed area accounted for interannual variability in these nitrate loss indices. Our results have important implications for setting realistic timelines to measure nitrate loss reductions against the background of interannual weather variation and can help to target monitoring intensity across diverse watersheds.

Bioenergy potential from invasive alien plants: Environmental and socio-economic impacts in Eastern Cape, South Africa

South Africa's natural resources and ecosystems are negatively affected by Invasive Alien Plants (IAPs). We used a life-cycle approach to assess the environmental and socio-economic impacts of using IAPs for electricity generation in South Africa or exported and used for electricity generation in the Netherlands. Supply chain greenhouse gas (GHG) emissions of electricity from IAPs pellets, excluding land use change-related GHG emissions, are 31.5 gCO2eq MJ−1 for electricity generation in South Africa and 31.2 gCO2eq MJ−1 for electricity generation in the Netherlands. An additional 3.9 gCO2eq MJ−1 is accounted for if emissions of land use change are included and land is rehabilitated to its natural state. The removal of IAPs results in water savings when considering any potential land use transition, ranging between 1,263 mm year−1 for annual cropland to 12 mm year−1 for dense forest. The supply chain costs of pellets are 5,344 ZAR Mg−1 (285 € Mg−1) delivered at the power plant in South Africa and 2,535 ZAR Mg−1 (159 € Mg−1) delivered at Rotterdam port. Direct full-time jobs generated from removing IAPs up to the conversion-factory-gate are 604 FTE year−1 for South Africa and 525 FTE year−1 for the Netherlands. There are clear trade-offs between environmental and social benefits and costs. There are generally net carbon losses when considering the land use transitions after IAP removal, even when land is rehabilitated to its natural state. Using IAPs for electricity can be a valuable strategy for South Africa to generate employment, conserve water resources and reduce GHG emissions.

Impact of Conservation Agriculture on Soil Erosion in the Annual Cropland of the Apulia Region (Southern Italy) Based on the RUSLE-GIS-GEE Framework

The processes of soil erosion and land degradation are more rapid in the case of inappropriate agricultural management, which leads to increased soil loss rates. Moreover, climatic conditions are one of the most important determining factors affecting agriculture, especially in the Mediterranean areas featuring irregular rainfall and high summer temperatures. Conservation agriculture (CA) can make a significant contribution to reducing soil erosion risk on the annual cropland (ACL) of the Mediterranean region in comparison with conventional management (CM). The objective of this study is to provide soil loss rate maps and calculate the values for each altitude and slope class and their combination for the Apulia region in four annual production cycles for the scenarios CM and CA. The present study estimates the significance of the adoption of CA on soil erosion assessment at regional scale based on the Revised Universal Soil Loss Equation (RUSLE) model. The parameters of the RUSLE model were estimated by using remote sensing (RS) data. The erosion probability zones were determined through a Geographic Information System (GIS) and Google Earth Engine (GEE) approach. Digital terrain model (DTM) at 8 m, ACL maps of the Apulia region, and rainfall and soil data were used as an input to identify the most erosion-prone areas. Our results show a 7.5% average decrease of soil loss rate during the first period of adoption of the four-year crop cycle—from 2.3 t ha−1 y−1 with CM to 2.1 t ha−1 y−1 with the CA system. CA reduced soil loss rate compared to CM in all classes, from 10.1% in hill class to 14.1% for hill + low slope class. These results can therefore assist in the implementation of effective soil management systems and conservation practices to reduce soil erosion risk in the Apulia region and in the Mediterranean basin more generally.

How the ecosystem extent is changing: A national-level accounting approach and application

Assessing the spatial and temporal changes in ecosystems is essential to account for natural capital contribution to human well-being. However, various methods to quantify these changes challenge the development of reliable values which can be integrated into national statistical accounts. Following the international system of environmental-economic accounting framework, which recently adopts an ecosystem accounting standard. We present a novel approach to develop an ecosystem extent account from existing ecosystem classifications. This study shows the spatial and statistical extent account of 26 ecosystems (i.e. forests, grasslands, croplands, and urban, among others) between 1970 and 2015 at the national scale. Extent accounts were developed at a resolution of 25 m and provided reliable information on how ecosystem types have changed over time in Spain. Our results reflect three main patterns in the extension account: (i) an increase in forest ecosystems, (ii) a considerable decrease in agroecosystems (especially annual croplands), and (iii) substantial development of urban areas. To the best of our knowledge, this method is the first attempt to develop a robust methodology to measure the extent of ecosystems at the national level. The proposed approach is crucial for a strong knowledge of ecosystem dynamics and their implications for ecosystem conditions and services at a national level. This has potential applications in urban planning, green infrastructure development, and multiple uses for territory management and policies, integrating natural capital into official statistics and mainstreaming ecosystems into national-level planning and monitoring processes.

Could domestic soybean production avoid Europe’s protein imports in 2050?

The European Union has a high demand for plant proteins for food and feed. Its self-sufficiency rate is about 5% for soya crude proteins. The European Union and its Member States have launched initiatives for reducing soya imports that come mainly from South America and promoting domestic production of protein-rich crops. In the future, climate suitability for soybean cultivation is likely to increase in oceanic and continental Europe. The recent AE2050 study (INRAE. 2020. Role of European agriculture in world trade by 2050: Balancing climate change and global food security issues. Summary report of the study. INRAE (France), 12 p; Tibi A, Forslund A, Debaeke P, et al. 2020. Place des agricultures européennes dans le monde à l’horizon 2050 : entre enjeux climatiques et défis de la sécurité alimentaire. Rapport de synthèse de l’étude. INRAE (France), 159 p + Annexes) concluded that, in some parts of Europe (defined here as the European Union-27 plus other Balkan countries, Switzerland, Norway and the United Kingdom), cropland requirements in 2050 may be lower than “2010” cropland areas given possible changes in European food demand (related to glooming demographic growth and under the assumption of healthy diets) and in crop yields (influenced by technological developments and climate change). In this study, we examine to what extent this “cropland surplus” could be used to increase soybean production in Europe and reduce the dependency ratio on protein imports. Only in the case of a Healthy Diets scenario (less meat consumption, inducing less animals fed with cakes), substantial soybean acreages could be envisaged to reduce the European reliance on imports. In addition to the surplus allowed by increasing yields, land surplus was also made available by the reduction of livestock production and its grain feed requirements. The best-case scenario, combining healthy diets and trend-based yield growth, would reduce European imports to only 15% of its total domestic requirements versus 45% for the Trend-based Diets scenario. This can be compared to a dependency rate of 51% in our base year “2010”, and of 53%–54% for the two 2050 scenarios without growing soybean on cropland surplus. If the range of these quite optimistic estimations of surplus land dedicated to soybean was reduced to more plausible levels (limited to 10% of annual field cropland in 2050) and considering current soybean yield levels (“2019” instead of “2010”), the decrease in Europe’s oil cake imports levels would be lower. However, its dependency rate could still be reduced from 54% to 46% in the Trend-based Diets scenario, and from 53% to 38% in the Healthy Diets scenario. One important conclusion is that adopting healthy diets would allow a significant reduction of imports of soybean cakes from abroad with expected environmental benefits in Europe and overseas. On the supply side, challenges for a higher self-sufficiency rate of proteins in Europe resulting from the development of soybean domestic production will come from both available and suitable crop areas, attainable yields and relative profitability.

Conversion of Conservation Reserve Program land back to cropland: Changes in soil carbon and nitrogen dynamics during the first five years

In the United States, Texas has one of the largest areas of land enrolled as well as expiring from the Conservation Reserve Program (CRP), and most of these restored grasslands are in the Southern High Plains region. Crop market forces and agency reductions in the number of hectares that can reenroll in CRP have resulted in many farmers considering recultivating this land. Converting grasslands to conventionally tilled annual croplands could reverse the accumulated benefits afforded from perennial grasslands. Three soil profile depths (0 to 10, 0 to 30, and 0 to 50 cm) from three long-term (&gt;23 years) CRP and three converted CRP (C-CRP) sites were assessed annually from 2012 to 2015 (representing one to five years following conversion). Soil health indicators related to soil carbon (C) and nitrogen (N) dynamics were evaluated including soil organic C (SOC), total N (TN), particulate organic matter C and N (POM-C and POM-N), permanganate oxidizable C (POXC), microbial biomass C and N (MBC and MBN), in situ soil carbon dioxide (CO₂) efflux, and metabolic quotient (<i>q</i>CO₂). Redistribution of C following CRP conversion was detected in the MBC stock in 2012 with values higher in C-CRP than CRP at 0 to 30 cm and 0 to 50 cm profiles but not at 0 to 10 cm. The increase was short-lived with lower MBC in C-CRP than CRP in subsequent years. Most C and N stocks were lower in C-CRP compared to CRP across all depth profiles. The greatest losses of soil C and N stocks occurred at 0 to 10 cm, with the magnitude of loss varying by indicator and soil depth profile. Five years following conversion, SOC was reduced 2.7 Mg ha^–1 at 0 to 10 cm, and averaged across all sample years, SOC was reduced by 4.3 Mg ha^–1 at 0 to 50 cm. Drought stress was present from 2011 to 2014 and exerted an additional pressure to both systems, but the CRP system responded more positively to increased precipitation in 2014 and 2015. In CRP, the <i>q</i>CO₂, an indicator of microbial stress, remained below 1.0 throughout the study, and MBC increased by 81% from 2012 to 2014, when drought stress was lessened. In contrast, MBC decreased and <i>q</i>CO₂ doubled under C-CRP from 2012 to 2014. Overall, this study showed negative impacts on soil C and N stocks within five years after CRP to C-CRP conversion.

Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century

Spatiotemporally consistent data on global cropland extent is essential for tracking progress towards sustainable food production. In the present study, we present an analysis of global cropland area change for the first two decades of the twenty-first century derived from satellite data time-series. We estimate that, in 2019, the cropland area was 1,244 Mha with a corresponding total annual net primary production (NPP) of 5.5 Pg C year−1. From 2003 to 2019, cropland area increased by 9% and cropland NPP by 25%, primarily due to agricultural expansion in Africa and South America. Global cropland expansion accelerated over the past two decades, with a near doubling of the annual expansion rate, most notably in Africa. Half of the new cropland area (49%) replaced natural vegetation and tree cover, indicating a conflict with the sustainability goal of protecting terrestrial ecosystems. From 2003 to 2019, global per-capita cropland area decreased by 10% due to population growth. However, the per-capita annual cropland NPP increased by 3.5% as a result of intensified agricultural land use. The presented global, high-resolution, cropland map time-series supports monitoring of natural land appropriation at the local, national and international levels.

Bioenergy sorghum’s deep roots: A key to sustainable biomass production on annual cropland

AbstractBioenergy sorghum has high biomass yield potential, drought resilience, good nitrogen use efficiency, and a root system that contributes to the accumulation of soil organic carbon. In this study, field grown bioenergy sorghum root systems were analyzed during the growing season to characterize their depth, biomass, morphology, anatomy, and gene expression profiles. Bioenergy sorghum roots grew continuously during a 155‐day growing season producing ~175 nodal roots, accumulating ~7 Mg of dry biomass per hectare, and reaching &gt;2 m deep in the soil profile. Nodal roots within 20 cm of the stem were 1–5 mm in diameter, whereas roots deeper in soil profiles were enriched in lateral roots with small diameters (~30–500 µm) enabling growth through soil macropores. In older field‐grown plants, roots with intact endodermal, vascular and inner root tissues were surrounded by degraded or aerenchyma‐filled epidermal and cortical cell layers. Transcriptome analysis of nodal, surface, and deep roots identified &gt;2,500 differentially expressed genes involved in root growth, transport, adaptation, defense, and AMF–root interaction. Deep roots (180–240 cm) differentially expressed genes that regulate lateral root growth. Surface roots (0–20 cm) located mid‐row differentially expressed genes involved in nitrate transport, whereas ammonium transport genes were expressed in surface and deep roots and genes involved in phosphate transport were expressed in nodal, surface, and deep roots. Overall, bioenergy sorghum's long growing season enables root systems to grow deeper and accumulate more biomass than annual grain crops such as maize, attributes that could help restore annual cropland soil organic carbon levels and improve soil productivity. Deep roots active in nutrient transport are positioned to take‐up fertilizer leached deep into soil profiles mitigating potential nutrient run‐off. Bioenergy sorghum's large and deep root system is a key to sustainable production of biofuels, biopower, and bioproducts on annual cropland.

Large spatial variation and stagnation of cropland gross primary production increases the challenges of sustainable grain production and food security in China

Sustainable crop grain production and food security is a grand societal challenge. Substantial investments in China's agriculture have been made in the past decades, but our knowledge on cropland gross primary production in China remains limited. Here we analyzed gross primary production (GPP), solar-induced chlorophyll fluorescence (SIF), terrestrial water storage, crop grain production, and agricultural investment and policy during 2000–2018. We found that based on croplands in 2000, approximately 52 × 106 ha (~37%) had continuous increasing trends in GPP during 2000–2018, which were mainly located in northern China. GPP for 63% of croplands was stagnant, declined, or had no significant change. At the national scale, annual cropland GPP increased during 2000–2008 but became stagnant in 2009–2018, which was inconsistent with the interannual trend in the crop grain production data for 2009–2018. The spatial mismatch between crop production and water availability became worse. The major grain exporting provinces, mostly located in water-stressed regions, experienced increased water resource constraints, which posed a challenge for sustainable grain production. The stagnant cropland GPP and increasing water resource constraints highlight the urgent need for sustainable management for crop production and food security in China.

Spatial heterogeneity of changes in cropland ecosystem water use efficiency and responses to drought in China.

Understanding cropland ecosystem water use efficiency (eWUE) responses to drought is important for sustainable water resource management and food security. Today in China, the spatiotemporal patterns of eWUE and responses to drought across different cropland classes remain poorly quantified. In this study, we characterized the spatial temporal variability in cropland eWUE and response to drought in China from 1982 to 2017 using the satellite-retrieved evapotranspiration (ET), gross primary production (GPP), and self-calibrating Palmer Drought Severity Index (scPDSI), in conjunction with the Global Food Security-support Analysis Data product for Crop Dominance (GFSAD1KCD) data. Results indicated that (1) mean annual cropland eWUE had a spatial range from 0 to 9.94 g C kg-1 H2O, with higher values (2.06 g C kg-1 H2O) in class 4 (rainfed: wheat, rice, and soybeans dominant), whereas the lowest eWUE (1.58 g C kg-1 H2O) occurred in class 2 (irrigated mixed crop 1: wheat, rice, barley, and soybeans). (2) Annual eWUE, GPP, and ET values for croplands in China increased significantly between 1982 and 2017. Class 1 (irrigated wheat and rice) had the highest trend of 0.011 g C kg-1 H2O yr-1, and class 6 (rainfed: corn and soybeans) had the lowest of 0.0007 g C kg-1 H2O yr-1. Apart from class 4, annual GPP and ET were enhanced in most cropland classes from 1982 to 2017 (p<0.01). (3) Rainfed croplands generally had higher eWUE, GPP, and ET values than irrigated croplands. Except for rainfed cropland eWUE, all other cropland variables increased significantly (p<0.001) from 1982 to 2017. (4) Correlation analysis found that the 19.66% (15.62%) of cropland had significant negative (positive) correlations between eWUE and current-year scPDSI. The legacy effects of drought on cropland eWUE indicated that previous and current-year drought impacts on cropland eWUE were in the same direction. Our results provide insights into variability in cropland eWUE and its response to drought in China, where there is a growing demand for agricultural water resource management.

Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses

Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia’s GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC30) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC30 with no overall bias, and showed good performance at the LU level with no significant (p &lt; 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC30 and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting.

A meta-analysis of the effects of land management practices and land uses on soil loss in Ethiopia

Over the last three decades, land management practices have been extensively implemented in Ethiopia. Different attempts have been made to assess the effects of land management practices on soil loss at plot scales under a range of climatic and land use conditions. However, the plot-level studies were mostly focused on limited sites and were inadequate to show the effects of land management and land cover practices across a range of practices and under various environmental contexts. A meta-analysis of 82 plot-level experiments in 59 sites was conducted to assessing the effects of land management practices and land use/cover types on soil loss relative to control practice. Random effects were accounted for the association of soil loss and environmental factors including mean annual rainfall, soil texture, and slope length. The results showed that there were significant mean soil loss differences among the categories of land management and land cover practices (p < 0.049). A large amount of residual heterogeneity (I2 = 92%) suggests that the groups of practices are heterogeneous. Mechanical erosion control and agronomic practices with the largest number of studies and somewhat area closure showed large heterogeneity across experiments.The overall mean soil loss ratio of mechanical (0.086, R2 = 81%), agronomic (0.21, R2 = 85%), and area closure (0.09, R2 = 52%) practices were significant to reduce soil loss. There was no residual heterogeneity exhibited across studies for the rest of four groups of practices. The mean soil loss ratio of mechanical practices under non-cropland, annual cropland cover, drainage, and non-cropland cover types were 0.12, 0.14, 0.27, and 0.29, respectively. Yet, with a certain level of inconsistency, the overall effects of all groups of land management and land cover practices were positive. In general, the sensitivity of environmental factors and their magnitude of association with soil loss ratio could imply that the effects of the range of land management practices and land cover types on soil loss are very contextual.

Land-use harmonization datasets for annual global carbon budgets

Abstract. Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for simulations of the 6th Coupled Model Intercomparison Project (CMIP6), has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual wood harvest data updates from the Food and Agriculture Organization (FAO) of the United Nations for dataset years after 2015 and the History Database of the Global Environment (HYDE) gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of 1 or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use-change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil as far back as 1950. From 1951 to 2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100 000 km2) and in the year 2009 for cropland (difference of 77 000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates, including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time lags due to the multiple input dataset and model latencies.

Forest land-use increases soil organic carbon quality but not its structural or thermal stability in a hedgerow system

How land-use and soil depth affect soil organic carbon (SOC) quality and stability, properties that are key to the long-term storage of C, is poorly understood in agroforestry systems. We examined the effects of land-use (forest vs. annual cropland) and soil depth (0–10 vs. 10–30 cm) on the quality (availability of C for decomposition), structural stability (composition of C functional groups), and thermal stability (energy yield and temperature characteristics during thermal oxidation) of SOC in a hedgerow system in central Alberta, using solid-state 13C nuclear magnetic resonance (NMR) spectroscopy and thermal analysis methods. The SOC quality (proportion of O-alkyl C) was higher, while the proportion of H- and C-substituted aromatic C and structural stability (hydrophobicity index (HB/HI), aromaticity index (ARM), and alkyl index (A/OA)) were all lower in the forest than in the cropland. The SOC also had lower thermal stability (higher energy density and lower temperature at which 50% of the mass was lost (TG-T50)) in the forest than in the cropland. Between the two soil depths, SOC quality (proportion of N-alkyl C, O-alkyl C and di-O-alkyl C) was higher, but the proportion of H- and C-substituted aromatic C and structural and thermal stabilities were lower, within the surficial 0–10 cm layer than in the 10–30 cm soil. We conclude that while the forest land-use within the hedgerow system had a higher SOC quality, it had lower SOC structural and thermal stabilities, suggesting that SOC under the forest land-use may be more susceptible to decline under climate change or other forms of anthropogenic disturbance.

Nonlinear turnover rates of soil carbon following cultivation of native grasslands and subsequent afforestation of croplands

Abstract. Land use conversions can strongly impact soil organic matter (SOM) storage, which creates paramount opportunities for sequestering atmospheric carbon into the soil. It is known that land uses such as annual cropping and afforestation can decrease and increase SOM, respectively; however, the rates of these changes over time remain elusive. This study focused on extracting the kinetics (k) of turnover rates that describe these long-term changes in soil C storage and also quantifying the sources of soil C. We used topsoil organic carbon density and δ13C isotopic composition data from multiple chronosequences and paired sites in Russia and United States. Reconstruction of soil C storage trajectory over 250 years following conversion from native grassland to continual annual cropland revealed a C depletion rate of 0.010 yr−1 (first-order k rate constant), which translates into a mean residence time (MRT) of 100 years (R2≥0.90). Conversely, soil C accretion was observed over 70 years following afforestation of annual croplands at a much faster k rate of 0.055 yr−1. The corresponding MRT was only 18 years (R2=0.997) after a lag phase of 5 years. Over these 23 years of afforestation, trees contributed 14 Mg C ha−1 to soil C accrual in the 0 to 15 cm depth increment. This tree-C contribution reached 22 Mg C ha−1 at 70 years after tree planting. Over these 70 years of afforestation, the proportion of tree C to whole-soil C increased to reach a sizable 79 %. Furthermore, assuming steady state of soil C in the adjacent croplands, we also estimated that 45 % of the prairie C existent at the time of tree planting was still present in the afforested soils 70 years later. As an intrinsic property of k modeling, the derived turnover rates that represent soil C changes over time are nonlinear. Soil C changes were much more dynamic during the first decades following a land use conversion than afterwards when the new land use system approached equilibrium. Collectively, results substantiated that C sequestration in afforested lands is a suitable means to proactively mitigate escalating climate change within a typical person's lifetime, as indicated by MRTs of a few decades.

How will land degradation neutrality change future land system patterns? A scenario simulation study

Land degradation is a major global issue and achieving a land degradation-neutral world is one of the Sustainable Development Goals. However, striving for land degradation neutrality (LDN) is challenged by increasing claims on land resources and could result in major land use conflicts. The aim of this study is to demonstrate how LDN can be implemented in land system modelling and how achieving LDN alongside sufficient supplies of food, timber and shelter could affect future land system patterns, using the Republic of Turkey as a case study. We developed a LDN scenario with full implementation of the guidelines and a business-as-usual scenario without pursuing LDN, and compared the resulting differences in land system changes. Additionally, the influence of different elements of the LDN framework on the land use projections was tested. Our results show that although it is possible to achieve LDN in the context of increasing demands for resources and housing, it might require a considerable re-organization of the land systems. Intensification of annual cropland systems was the main driver of new land degradation, which was in the LDN scenario primarily counterbalanced by large areas of afforestation, while other land improvement options only played a minor role. To achieve a no-net-loss, about 20% of Turkey’s territory was afforested in our scenario, mainly claiming extensively used annual cropland (∼70%) and grassland (∼30%). All individual LDN principles had a substantial impact on the final land system patterns meaning that the final outcome is not the result of just one of the principles, it is affected by all. Our findings suggest that pursuing LDN under growing demands for land-based products could stimulate a land sparing approach which might have trade-offs with other sustainability dimensions. This highlights the need for local support and new solutions for rural areas, thereby avoiding poverty, migration and illegal use of restoration areas.

COHERENCE and BACKSCATTER BASED CROPLAND MAPPING USING MULTI-TEMPORAL SENTINEL-1 with DYNAMIC TIME WARPING

Abstract. Cropland mapping is an important inventory for food security and decision making operated by governments. Crop mapping is used to identify the croplands and their spatial distribution. For a reliable analysis and forecast for projection, multi-temporal data play a key role. Even current open and frequent optical satellite data such as Sentinel-2 and Landsat support monitoring, they are not always operational due to atmospheric conditions (rain, cloud cover, haze, etc.). On the other hand, Synthetic Aperture Radar (SAR) satellites provide alternative data sets compared to optical satellites since they can acquire images under all weather conditions. In this study, an annual cropland monitoring study is conducted using Sentinel-1 SAR. For the investigation, Tokat Province an agricultural region of Turkey, where the main source of income is agriculture, was selected. There are 4 different vegetation species (wheat, sunflower, sugar beet, corn) in the study area. Sentinel-1 data was used to generate time-series of each class and phenological structures of the crops. In this context, backscatter images of both vertical-vertical (VV) and vertical-horizontal (VH) polarized data, and coherence of both VV and VH were produced from Sentinel-1 data. Time-Weighted Dynamic Time-Warping (TWDTW) classification approach was used over cropland. The produced time-series are classified under different scenarios. The results showed that only coherence has provided higher accuracies about 81% compared to using only backscatter images as 49%.