Extensively managed grasslands are recognized globally for their high biodiversity and their social and cultural values. However, their capacity to deliver multiple ecosystem services (ES) as parts ...of agricultural systems is surprisingly understudied compared to other production systems. We undertook a comprehensive overview of ES provided by natural and semi‐natural grasslands, using southern Africa (SA) and northwest Europe as case studies, respectively. We show that these grasslands can supply additional non‐agricultural services, such as water supply and flow regulation, carbon storage, erosion control, climate mitigation, pollination, and cultural ES. While demand for ecosystems services seems to balance supply in natural grasslands of SA, the smaller areas of semi‐natural grasslands in Europe appear to not meet the demand for many services. We identified three bundles of related ES from grasslands: water ES including fodder production, cultural ES connected to livestock production, and population‐based regulating services (e.g., pollination and biological control), which also linked to biodiversity. Greenhouse gas emission mitigation seemed unrelated to the three bundles. The similarities among the bundles in SA and northwestern Europe suggest that there are generalities in ES relations among natural and semi‐natural grassland areas. We assessed trade‐offs and synergies among services in relation to management practices and found that although some trade‐offs are inevitable, appropriate management may create synergies and avoid trade‐offs among many services. We argue that ecosystem service and food security research and policy should give higher priority to how grasslands can be managed for fodder and meat production alongside other ES. By integrating grasslands into agricultural production systems and land‐use decisions locally and regionally, their potential to contribute to functional landscapes and to food security and sustainable livelihoods can be greatly enhanced.
Drainage has turned peatlands from a carbon sink into one of the world's largest greenhouse gas (GHG) sources from cultivated soils. We analyzed a unique data set (12 peatlands, 48 sites and 122 ...annual budgets) of mainly unpublished GHG emissions from grasslands on bog and fen peat as well as other soils rich in soil organic carbon (SOC) in Germany. Emissions and environmental variables were measured with identical methods. Site‐averaged GHG budgets were surprisingly variable (29.2 ± 17.4 t CO2‐eq. ha−1 yr−1) and partially higher than all published data and the IPCC default emission factors for GHG inventories. Generally, CO2 (27.7 ± 17.3 t CO2 ha−1 yr−1) dominated the GHG budget. Nitrous oxide (2.3 ± 2.4 kg N2O‐N ha−1 yr−1) and methane emissions (30.8 ± 69.8 kg CH4‐C ha−1 yr−1) were lower than expected except for CH4 emissions from nutrient‐poor acidic sites. At single peatlands, CO2 emissions clearly increased with deeper mean water table depth (WTD), but there was no general dependency of CO2 on WTD for the complete data set. Thus, regionalization of CO2 emissions by WTD only will remain uncertain. WTD dynamics explained some of the differences between peatlands as sites which became very dry during summer showed lower emissions. We introduced the aerated nitrogen stock (Nair) as a variable combining soil nitrogen stocks with WTD. CO2 increased with Nair across peatlands. Soils with comparatively low SOC concentrations showed as high CO2 emissions as true peat soils because Nair was similar. N2O emissions were controlled by the WTD dynamics and the nitrogen content of the topsoil. CH4 emissions can be well described by WTD and ponding duration during summer. Our results can help both to improve GHG emission reporting and to prioritize and plan emission reduction measures for peat and similar soils at different scales.
Grassland degradation compromises the profitability of Brazilian livestock production, and pasture recovery is a promising strategy for sustainable intensification of agriculture (SAI). Recovery ...increases carbon sequestration into the soil and can potentially avoid deforestation; thereby reducing emissions intensity (EI), but only at increased investment cost per unit of area. We develop a multi-period linear programming (LP) model for grazing beef production planning to represent a typical Cerrado stocking and finishing beef farm. We compare economic and environmental performance of two alternative optimized pasture management approaches relative to the traditional practice (TRP), which is based on restoring pasture after a full degradation cycle of 8years. The scenarios considered the difference made by access to subsidized credit through the Low Carbon Agriculture program (“Programa ABC”). The model estimates EI using upstream life cycle assessment (LCA), and dynamically estimates soil organic carbon (SOC) changes as a function of pasture management. The results show net present values (NPV) ranging from −67 Brazilian reals per hectare-year (R$·ha−1·yr−1) to around 300 R$·ha−1·yr−1, respectively for traditional and optimized pasture management strategies. Estimated EI of the TRP is 9.26 kgCO2 equivalent per kg of carcass weight equivalent (kgCO2e/kg CWE) relative to 3.59kgCO2e/kg CWE for optimized management. Highest emission abatement results from improved SOC sequestration, while access to credit could further reduce EI by around 20%. We consider the effects of alternative credit interest on both NPV and EI. The results provide evidence to inform the design of Brazil's key domestic policy incentive for low carbon agriculture, which is an important component of the country's Intended Nationally Determined Contributions (INDC) on emissions mitigation. The results also contribute to the global debate on the interpretation of SAI.
•More than half of Brazilian livestock production is on degraded pastures.•Alternative pasture restoration could out-perform traditional practices in terms of profit and emissions.•Improved management means soil organic carbon sequestration could abate up to 85% of cattle emissions from stocking to finishing.
Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing ...enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.
In agricultural settings, plant diversity is often associated with low biomass yield and forage quality, while biodiversity experiments typically find the opposite. We address this controversy by ...assessing, over 1 year, plant diversity effects on biomass yield, forage quality (i.e. nutritive values), quality-adjusted yield (biomass yield × forage quality), and revenues across different management intensities (extensive to intensive) on subplots of a large-scale grassland biodiversity experiment. Plant diversity substantially increased quality-adjusted yield and revenues. These findings hold for a wide range of management intensities, i.e., fertilization levels and cutting frequencies, in semi-natural grasslands. Plant diversity was an important production factor independent of management intensity, as it enhanced quality-adjusted yield and revenues similarly to increasing fertilization and cutting frequency. Consequently, maintaining and reestablishing plant diversity could be a way to sustainably manage temperate grasslands.
Intensive crop production on grassland-derived Mollisols has liberated massive amounts of carbon (C) to the atmosphere. Whether minimizing soil disturbance, diversifying crop rotations, or ...re-establishing perennial grasslands and integrating livestock can slow or reverse this trend remains highly uncertain. We investigated how these management practices affected soil organic carbon (SOC) accrual and distribution between particulate (POM) and mineral-associated (MAOM) organic matter in a 29-y-old field experiment in the North Central United States and assessed how soil microbial traits were related to these changes. Compared to conventional continuous maize monocropping with annual tillage, systems with reduced tillage, diversified crop rotations with cover crops and legumes, or manure addition did not increase total SOC storage or MAOM-C, whereas perennial pastures managed with rotational grazing accumulated more SOC and MAOM-C (18 to 29% higher) than all annual cropping systems after 29 y of management. These results align with a meta-analysis of data from published studies comparing the efficacy of soil health management practices in annual cropping systems on Mollisols worldwide. Incorporating legumes and manure into annual cropping systems enhanced POM-C, microbial biomass, and microbial C-use efficiency but did not significantly increase microbial necromass accumulation, MAOM-C, or total SOC storage. Diverse, rotationally grazed pasture management has the potential to increase persistent soil C on Mollisols, highlighting the key role of well-managed grasslands in climate-smart agriculture.
Soils under grasslands contribute significantly to terrestrial carbon (C) and nitrogen (N) pools, and grassland management practices directly impact pool size through effects on plant biomass. Our ...objective was to quantify above and belowground plant biomass and soil C and N accumulation for year-round forage systems based on N-fertilized grasses (GN; 290 kg N ha
−1
yr
−1
) or legume-grass mixtures (LG; 30 kg N ha
−1
yr
−1
) when grazed or harvested for hay. Soil C and N accumulation (0–0.4 m) were evaluated before and 6 yr after imposing treatments. Average root-rhizome mass did not differ for GN and LG systems (3690 and 3020 kg OM ha
−1
, respectively). Aboveground residual biomass was 55% greater for GN than LG (4890 vs. 3150 kg OM ha
−1
, respectively) and 46% greater for grazed than hayed swards (4770 vs. 3270 kg OM ha
−1
, respectively) at the end of the warm season. Aboveground C and N pools were 70 and 58% greater for GN than LG, respectively. After 6 yr, soil C and N concentration (0–0.1 m) increased 6.7 and 0.8 g C kg
−1
and 0.6 and 0.2 g N kg
−1
, for GN and LG, respectively. Annual C accumulation (0–0.1 m) was 1.3 and 0.2 Mg C ha
−1
for GN and LG systems, respectively. Thus, a year-round forage system based on N-fertilized grasses accumulated more plant biomass and surface soil C and N than a legume-grass mixture, with the grass system advantaged by presence of a perennial C4 species and application of moderate to high N fertilizer rates.
Accurate monitoring of grassland aboveground fresh biomass (called AGB in the study) and its spatial-temporal dynamics is indispensable for sustainable grassland management. The most common method ...used in estimating AGB with remotely sensed data is based on the relationship between field AGB measurements and vegetation indices (VIs); however, the existing VIs do not deliver adequate results due to the soil background and spatial, temporal and sampling size variability. In this study, the AGB estimation model with the normalized difference phenology index (NDPI) was evaluated in terms of model robustness and spatial and temporal scalability based on comparisons with the widely used ratio vegetation index (RVI), difference vegetation index (DVI), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), soil-adjusted vegetation index (SAVI), modified soil-adjusted vegetation index (MSAVI), and optimized soil-adjusted vegetation index (OSAVI). The field measurements of AGB of the natural grassland in Inner Mongolia, China, collected in 2013, 2016, and 2017 and Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance products were used for analysis. The results based on training and independent validation data showed the following: (1) The R2 value between AGB and the NDPI was the highest (0.73) among all VIs, followed by soil-line-adjusted VIs, while the R2 values of the RVI and DVI were the lowest; (2) The NDPI-based model had the best robustness for different sampling sizes; (3) The NDPI-based model also had superior spatial and temporal scalability. The results from simulation experiments using the PROSAIL model also support the superiority of the NDPI in estimating AGB. The simulation analysis further reveals that the overall superiority of the NDPI originates from the fact that the NDPI overcomes the adverse impacts of the heterogeneity of the soil background and accounts for changes in the leaf water content that contribute substantially to AGB in grassland. These findings suggest that the NDPI-based AGB estimation model is advantageous for monitoring AGB in large grasslands with significant spatial-temporal heterogeneity.
•The NDPI had preferable robustness, spatial and temporal scalability.•The NDPI provided a more reliable and accurate estimation of grassland AGB than other VIs.•The NDPI overcame the adverse impact of heterogeneous soil backgrounds and accounted for changes in leaf water content.