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This study evaluates the dynamics of soil organic carbon (SOC) underperennial crops across the globe. It quantifies the effect of change fromannual to perennial crops and the subsequent temporal changes in SOCstocks during the perennial crop cycle. It also presents an empiricalmodel to estimate changes in the SOC content under crops as a functionof time, land use, and site characteristics. We used a harmonised globaldataset containing paired-comparison empirical values of SOC andincluding different types of perennial crops (perennial grasses, palms,and woody plants) with different end-uses: bioenergy, food, other bioproducts, and short rotation coppice crops. Salient outcomes include: a20-year period encompassing a change from annual to perennial cropsled to an average 20% increase in SOC at 0-30 cm (6.0 ± 4.6 Mg ha-1gain) and a total of 10% increase over the 0-100 cm soil profile (5.7 ±10.9 Mg ha-1). A change from natural pasture to perennial cropdecreased SOC stocks by 1% over 0-30 cm (-2.5 ± 4.2 Mg ha-1) and10% over 0-100 cm (-13.6 ± 8.9 Mg ha-1). The effect of a land usechange from forest to perennial crops did not have significant impacts,probably due to the limited number of plots; but the data indicated thatwhile a 2% increase in SOC was observed at 0-30 cm (16.81 ± 55.1 Mgha-1), a decrease of 24% was observed at 30-100 cm (-40.1 ± 16.8 Mgha-1); perennial crops generally accumulate SOC through time,especially woody crops; and temperature was the main driver explainingdifferences in SOC dynamics, followed by crop age, soil bulk density, claycontent and depth. We present empirical evidence showing that the FAOperennialization strategy is reasonable, underscoring the role ofperennial crops as a useful component of climate change mitigationstrategies.

In order to limit global warming to 2°C, a variety of mitigation measures are needed, including those that result in net negative emissions. Soil carbon sequestration (SCS) through changed land management practices has the potential to help meet this need, but it requires further study to represent a viable policy option. Rice cultivation plays a major role in South Asian agriculture, accounting for almost 40% of the crop’s harvested area worldwide. Its greenhouse gas (GHG) profile means it contributes disproportionately more than other crops to the region’s emissions. Adapting rice system management for SCS may therefore represent a compelling mitigation opportunity for the agricultural sectors of South Asian countries. This study uses a process-based modelling approach to compare the performance of two models, ECOSSE and DAYCENT, in assessing the mitigation potential of increasing soil organic carbon (SOC) stocks on a Bangladeshi test site under rice cultivation. A previous study using DAYCENT showed an increase in SOC stock as well as an overall GHG emissions reduction for several management practices relative to the baseline scenario. ECOSSE, calibrated to the same measurements, also showed an increase in SOC and net emissions reduction relative to the baseline. However, the models differed significantly in the extent of mitigation predicted as well as the GHG emissions profile. Given these differences, further analysis is needed to reduce error and uncertainty in these models. The results of this study form a basis for spatial model approaches to assess the mitigation potential of rice production in Bangladesh.

To limit warming to well below 2°C, most scenario projections rely on greenhouse gas removal technologies (GGRTs); one such GGRT uses soil carbon sequestration (SCS) in agricultural land. In addition to their role in mitigating climate change, SCS practices play a role in delivering agroecosystem resilience, climate change adaptability and food security. Environmental heterogeneity and differences in agricultural practices challenge the practical implementation of SCS, and our analysis addresses the associated knowledge gap. Previous assessments have focused on global potentials, but there is a need among policymakers to operationalise SCS. Here, we assess a range of practices already proposed to deliver SCS, and distil these into a subset of specific measures. We provide a multidisciplinary summary of the barriers and potential incentives towards practical implementation of these measures. First, we identify specific practices with potential for both a positive impact on SCS at farm level and an uptake rate compatible with global impact. These focus on: (a) optimising crop primary productivity (e.g. nutrient optimisation, pH management, irrigation); (b) reducing soil disturbance and managing soil physical properties (e.g. improved rotations, minimum till); (c) minimising deliberate removal of C or lateral transport via erosion processes (e.g. support measures, bare fallow reduction); (d) addition of C produced outside the system (e.g. organic manure amendments, biochar addition); (e) provision of additional C inputs within the cropping system (e.g. agroforestry, cover cropping). We then consider economic and non‐cost barriers and incentives for land managers implementing these measures, along with the potential externalised impacts of implementation. This offers a framework and reference point for holistic assessment of the impacts of SCS. Finally, we summarise and discuss the ability of extant scientific approaches to quantify the technical potential and externalities of SCS measures, and the barriers and incentives to their implementation in global agricultural systems., To limit warming to well below 2°C, many scenario projections rely on greenhouse gas removal by soil carbon sequestration (SCS) in agricultural land. Here, we provide a multidisciplinary summary of the barriers and potential incentives towards practical implementation SCS. First, we identify specific practices with potential for both a positive impact on SCS and an uptake rate compatible with global impact. Then, we then consider economic and non‐cost barriers and incentives for implementing SCS, and potential externalised impacts of implementation. Finally, we discuss the ability of existing methods to model the potential of SCS in global agricultural systems.

Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66-0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China's crop cultivation were estimated to be 194 Gg N2O-N with a 95% confidence interval of 180-208 Gg N2O-N in the year 2016.

Food production is estimated to emit between 20–30 % of global anthropogenic carbon emissions. The need to achieve net zero emissions requires a transition to low carbon, sustainable food sources. Of the total greenhouse gas (GHG) emissions for food production, only 4 % are attributed to wild capture fisheries. However, within seafood GHG studies a wide range of estimates can be found across different species, fishing methods and regions. This study assesses the environmental impact of fish capture, including the carbon footprint (CF), by the Scottish pelagic fleet, a highly modernised fleet targeting herring, mackerel and blue whiting in the North Sea and Atlantic Ocean. A life cycle assessment (LCA) was undertaken to provide a standardised comparison of pelagic fish with other seafood studies. One kg of whole round fish caught by the Scottish pelagic trawl fleet had a CF of 0.452 kg CO2 eq. Fuel burned during fishing operations was the largest contributing factor, accounting for approximately 96% of a CF. This figure was consistent with the expected results for a fishery for small pelagics, which are typically under 1 kg CO2 eq. per kg of whole fish landed. When contrasted with other seafood LCAs, the results were found to be lower than most other seafood. Our results demonstrate that Scottish-caught pelagic fish are a low carbon food source that could contribute to minimising food-related GHG emissions.

Agriculture is a major contributor to India's environmental footprint, particularly through greenhouse gas (GHG) emissions from livestock and fresh water used for irrigation. These impacts are likely to increase in future as agriculture attempts to keep pace with India's growing population and changing dietary preferences. Within India there is considerable dietary variation, and this study therefore aimed to quantify the GHG emissions and water usage associated with distinct dietary patterns. Five distinct diets were identified from the Indian Migration Study – a large adult population sample in India – using finite mixture modelling. These were defined as: Rice & low diversity, Rice & fruit, Wheat & pulses, Wheat, rice & oils, Rice & meat. The GHG emissions of each dietary pattern were quantified based on a Life Cycle Assessment (LCA) approach, and water use was quantified using Water Footprint (WF) data. Mixed-effects regression models quantified differences in the environmental impacts of the dietary patterns. There was substantial variability between diets: the rice-based patterns had higher associated GHG emissions and green WFs, but the wheat-based patterns had higher blue WFs. Regression modelling showed that the Rice & meat pattern had the highest environmental impacts overall, with 0.77 (95% CI 0.64–0.89) kg CO2e/capita/day (31%) higher emissions, 536 (95% CI 449–623) L/capita/day (24%) higher green WF and 109 (95% CI 85.9–133) L/capita/day (19%) higher blue WF than the reference Rice & low diversity pattern. Diets in India are likely to become more diverse with rising incomes, moving away from patterns such as the Rice & low diversity diet. Patterns such as the Rice & meat diet may become more common, and the environmental consequences of such changes could be substantial given the size of India's population. As global environmental stress increases, agricultural and nutrition policies must recognise the environmental impacts of potential future dietary changes., Graphical abstract Unlabelled Image, Highlights • India's food system produces large environmental impacts but these vary by diets. • We explored differences in GHG emissions and water use of Indian dietary patterns. • Rice-based diets had higher emissions but wheat-based diets used more water. • Diets with more animal products had the highest environmental impacts overall. • Diversifying diets in India may have severe consequences for environmental impacts.

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O.

The world population is projected to increase to 9–10 billion by 2050, during which time it will be necessary to reduce anthropogenic greenhouse gas emissions to mitigate climate change. The particular challenge this places on agriculture is to identify practices which ensure stable and productive food supply that also have a low greenhouse gas (GHG) intensity. Maize is the principle staple crop in many parts of Africa with low and variable yields, averaging only 1.6 t/ha in sub-Saharan Africa (SSA). Food security and increasing crop yields are considered priorities in SSA over impacts of food production on GHG emissions. Here we describe an approach that can be used to inform a decision support tree for optimal interventions to obtain sufficient food production with low GHG intensity, and we demonstrate its applicability to SSA. We employed a derivative of the farm greenhouse gas calculator ‘Cool Farm Tool’ (CFT) on a large survey of Kenyan and Ethiopian smallholder maize-based systems in an assessment of GHG intensity. It was observed that GHG emissions are strongly correlated with nitrogen (N) input. Based on the relationship between yield and GHG emissions established in this study, a yield of 0.7 t/ha incurs the same emissions as those incurred for maize from newly exploited land for maize in the region. Thus, yields of at least 0.7 t/ha should be ensured to achieve GHG intensities lower than those for exploiting new land for production. Depending on family size, the maize yield required to support the average consumption of maize per household in these regions was determined to be between 0.3 and 2.0 t/ha, so that the desirable yield can be even higher from a food security perspective. Based on the response of the observed yield to increasing N application levels, average optimum N input levels were determined as 60 and 120 kg N/ha for Kenya and Ethiopia, respectively. Nitrogen balance calculations could be applied to other countries or scaled down to districts to quantify the trade-offs, and to optimise crop productivity and GHG emissions.

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.

In order to predict the response of carbon (C)-rich soils to external change, models are needed that accurately reflect the conditions of these soils. Here we present an example application of the new Estimation of Carbon in Organic Soils - Sequestration and Emissions (ECOSSE) model to estimate net change in soil C in response to changes in land use in Scotland. The ECOSSE estimate of annual change in soil C stocks for Scotland between 2000 and 2009 is -810 ± 89 kt yr -1 , equivalent to 0.037 ± 0.004% yr -1 . Increasing the area of land-use change from arable to grass has the greatest potential to sequester soil C, and reducing the area of change from grass to arable has the greatest potential to reduce losses of soil C. Across Scotland, simulated changes in soil C from C-rich soils (C content >6%) between 1950 and 2009 is -63 Mt, compared with -35 Mt from non-C-rich mineral soils; losses from C-rich soils between 2000 and 2009 make up 64% of the total soil C losses. One mitigation option that could be used in upland soils to achieve zero net loss of C from Scottish soils is to stop conversion of semi-natural land to grassland and increase conversion of grassland to semi- natural land by 125% relative to the present rate. Mitigation options involving forestry are not included here because the data available to calculate losses of soil C do not account for losses of soil C on drainage of semi-natural land.