European soybean to benefit people and the environment

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha-1 from southern UK through to southern Europe (compared to a 3.5 t ha-1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37-291 Mt CO2e year-1 and fertiliser N use by 0.6-1.2 Mt year-1, concurrently improving human health and nutrition.

Prolonged low temperature exposure de-sensitises ABA-induced stomatal closure in soybean, involving an ethylene-dependent process

Chilling can decrease stomatal sensitivity to abscisic acid (ABA) in some legumes, although hormonal mechanisms involved are unclear. After evaluating leaf gas exchange of 16 European soybean genotypes at 14°C, 6 genotypes representing the range of response were selected. Further experiments combined low (L, 14°C) and high (H, 24°C) temperature exposure from sowing until the unifoliate leaf was visible and L or H temperature until full leaf expansion, to impose four temperature treatments: LL, LH, HL, and HH. Prolonged chilling (LL) substantially decreased leaf water content but increased leaf ethylene evolution and foliar concentrations of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid, indole-3-acetic acid, ABA and jasmonic acid. Across genotypes, photosynthesis linearly increased with stomatal conductance (Gs), with photosynthesis of HH plants threefold higher than LL plants at the same Gs. In all treatments except LL, Gs declined with foliar ABA accumulation. Foliar ABA sprays substantially decreased Gs of HH plants, but did not significantly affect LL plants. Thus low temperature compromised stomatal sensitivity to endogenous and exogenous ABA. Applying the ethylene antagonist 1 methyl-cyclopropene partially reverted excessive stomatal opening of LL plants. Thus, chilling-induced ethylene accumulation may mediate stomatal insensitivity to ABA, offering chemical opportunities for improving seedling survival in cold environments.

Agricultural expansion raises groundwater and increases flooding in the South American plains

Regional effects of farming on hydrology are associated mostly with irrigation. In this work, we show how rainfed agriculture can also leave large-scale imprints. The extent and speed of farming expansion across the South American plains over the past four decades provide an unprecedented case of the effects of rainfed farming on hydrology. Remote sensing analysis shows that as annual crops replaced native vegetation and pastures, floods gradually doubled their coverage, increasing their sensitivity to precipitation. Groundwater shifted from deep (12 to 6 meters) to shallow (4 to 0 meters) states, reducing drawdown levels. Field studies and simulations suggest that declining rooting depths and evapotranspiration in croplands are the causes of this hydrological transformation. These findings show the escalating flooding risks associated with rainfed agriculture expansion at subcontinental and decadal scales.

High-yield dairy cattle breeds improve farmer incomes, curtail greenhouse gas emissions and reduce dairy import dependency in Tanzania

Tanzania's dairy sector is poorly developed, creating reliance on imports for processed, value-added dairy products and threatening food security, particularly when supply chains are disrupted due to market volatility or armed conflicts. The Tanzanian Dairy Development Roadmap is a domestic development initiative that aims to achieve dairy self-sufficiency by 2030. Here, we model different outcomes of the roadmap, finding that adoption of high-yield cattle breeds is essential for reducing dairy import dependency. Avoided land use change resulting from fewer, higher yielding dairy cattle would lead to lower greenhouse gas emissions. Dairy producers' average incomes could increase despite capital expenditure and land allocation required for the adoption of high-yield breeds. Our findings demonstrate the importance of bottom-up development policies for sustainable food system transformations, which also support food sovereignty, increase incomes for smallholder farmers and contribute towards Tanzania's commitments to reduce greenhouse gas emissions.

Author Correction: Feeding efficiency gains can increase the greenhouse gas mitigation potential of the Tanzanian dairy sector

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Agricultural land is the main source of stream sediments after conversion of an African montane forest

In many parts of Africa, soil erosion is an important problem, which is evident from high sediment yields in tropical montane streams. Previous studies in Kenya pointed to a large contribution from catchments cultivated by smallholder farmers. This led to the hypothesis that unpaved tracks and gullies are the main sediment sources in smallholder agriculture catchments of the highlands of Kenya. The aim of this study was to investigate the sediment sources with sediment fingerprinting to generate the knowledge base to improve land management and to reduce sediment yields. Four main sediment sources (agricultural land, unpaved tracks, gullies and channel banks) and suspended sediments were analysed for biogeochemical elements as potential tracers. To apportion the catchments target sediment to different sources, we applied the MixSIAR un-mixing modelling under a Bayesian framework. Surprisingly, the fingerprinting analysis showed that agricultural land accounted for 75% (95% confidence interval 63-86%) of the total sediment. Channel banks contributed 21% (8-32%), while the smallest contributions to sediment were generated by the unpaved tracks and gullies with 3% (0-12%) and 1% (0-4%), respectively. Erosion management strategies should target agricultural lands with an emphasis on disconnecting unpaved tracks form hillslope source areas to reduce sediment yields to Lake Victoria.

Advances in sensing ammonia from agricultural sources

Reducing ammonia emissions is one of the most difficult challenges for environmental regulators around the world. About 90% of ammonia in the atmosphere comes from agricultural sources, so that improving farm practices in order to reduce these emissions is a priority. Airborne ammonia is the key precursor for particulate matter (PM2.5) that impairs human health, and ammonia can contribute to excess nitrogen that causes eutrophication in water and biodiversity loss in plant ecosystems. Reductions in excess nitrogen (N) from ammonia are needed so that farms use N resources more efficiently and avoid unnecessary costs. To support the adoption of ammonia emission mitigation practices, new sensor developments are required to identify sources, individual contributions, to evaluate the effectiveness of controls, to monitor progress towards emission-reduction targets, and to develop incentives for behavioural change. There is specifically a need for sensitive, selective, robust and user-friendly sensors to monitor ammonia from livestock production and fertiliser application. Most currently-available sensors need specialists to set up, calibrate and maintain them, which creates issues with staffing and costs when monitoring large areas or when there is a need for high frequency sampling. This paper reports advances in monitoring airborne ammonia in agricultural areas. Selecting the right method of monitoring for each agricultural activity will provide critical data to identify and implement appropriate ammonia controls. Recent developments in chemo-resistive materials allow electrochemical sensing at room temperature, and new spectroscopic methods are sensitive enough to determine low concentrations in the order of parts per billion. However, these new methods still compromise selectivity and sensitivity due to the presence of ambient dust and other interferences, and are not yet suitable to be applied in agricultural monitoring. This review considers how ammonia measurements are made and applied, including the need for sensors that are suitable for routine monitoring by non-specialists. The review evaluates how monitoring information can be used for policies and regulations to mitigate ammonia emissions. The increasing concerns about ammonia emissions and the particular needs from the agriculture sector are addressed, giving an overview of the state-of-the-art and an outlook on future developments.

Diurnal Patterns in Solute Concentrations Measured with In Situ UV-Vis Sensors: Natural Fluctuations or Artefacts?

In situ spectrophotometers measuring in the UV-visible spectrum are increasingly used to collect high-resolution data on stream water quality. This provides the opportunity to investigate short-term solute dynamics, including diurnal cycling. This study reports unusual changes in diurnal patterns observed when such sensors were deployed in four tropical headwater streams in Kenya. The analysis of a 5-year dataset revealed sensor-specific diurnal patterns in nitrate and dissolved organic carbon concentrations and different patterns measured by different sensors when installed at the same site. To verify these patterns, a second mobile sensor was installed at three sites for more than 3 weeks. Agreement between the measurements performed by these sensors was higher for dissolved organic carbon (r > 0.98) than for nitrate (r = 0.43–0.81) at all sites. Higher concentrations and larger amplitudes generally led to higher agreement between patterns measured by the two sensors. However, changing the position or level of shading of the mobile sensor resulted in inconsistent changes in the patterns. The results of this study show that diurnal patterns measured with UV-Vis spectrophotometers should be interpreted with caution. Further work is required to understand how these measurements are influenced by environmental conditions and sensor-specific properties.

Intensification of dairy production can increase the GHG mitigation potential of the land use sector in East Africa

Sub-Saharan Africa (SSA) could face food shortages in the future because of its growing population. Agricultural expansion causes forest degradation in SSA through livestock grazing, reducing forest carbon (C) sinks and increasing greenhouse gas (GHG) emissions. Therefore, intensification should produce more food while reducing pressure on forests. This study assessed the potential for the dairy sector in Kenya to contribute to low-emissions development by exploring three feeding scenarios. The analyses used empirical spatially explicit data, and a simulation model to quantify milk production, agricultural emissions and forest C loss due to grazing. The scenarios explored improvements in forage quality (Fo), feed conservation (Fe) and concentrate supplementation (Co): FoCo fed high-quality Napier grass (Pennisetum purpureum), FeCo supplemented maize silage and FoFeCo a combination of Napier, silage and concentrates. Land shortages and forest C loss due to grazing were quantified with land requirements and feed availability around forests. All scenarios increased milk yields by 44%-51%, FoCo reduced GHG emission intensity from 2.4 ± 0.1 to 1.6 ± 0.1 kg CO₂ eq per kg milk, FeCo reduced it to 2.2 ± 0.1, whereas FoFeCo increased it to 2.7 ± 0.2 kg CO₂ eq per kg milk because of land use change emissions. Closing the yield gap of maize by increasing N fertilizer use reduced emission intensities by 17% due to reduced emissions from conversion of grazing land. FoCo was the only scenario that mitigated agricultural and forest emissions by reducing emission intensity by 33% and overall emissions by 2.5% showing that intensification of dairy in a low-income country can increase milk yields without increasing emissions. There are, however, risks of C leakage if agricultural and forest policies are not aligned leading to loss of forest to produce concentrates. This approach will aid the assessment of the climate-smartness of livestock production practices at the national level in East Africa.

Citizen science in hydrological monitoring and ecosystem services management: State of the art and future prospects

Hydrological monitoring is essential to guide evidence-based decision making necessary for sustainable water resource management and governance. Limited hydrometric datasets and the pressure on long-term hydrological monitoring networks make it paramount to explore alternative methods for data collection. This is particularly the case for low-income countries, where data scarcity is more pronounced, and where conventional monitoring methods are expensive and logistically challenging. Citizen science in hydrological research has recently gained popularity and crowdsourced monitoring is a promising cost-effective approach for data collection. Citizen science also has the potential to enhance knowledge co-creation and science-based evidence that underpins the governance and management of water resources. This paper provides a comprehensive review on citizen science and crowdsourced data collection within the context of hydrology, based on a synthesis of 71 articles from 2001 to 2018. Application of citizen science in hydrology is increasing in number and breadth, generating a plethora of scientific data. Citizen science approaches differ in scale, scope and degree of citizen involvement. Most of the programs are found in North America and Europe. Participation mostly comprises a contributory citizen science model, which engages citizens in data collection. In order to leverage the full potential of citizen science in knowledge co-generation, future citizen science projects in hydrology could benefit from more co-created types of projects that establish strong ties between research and public engagement, thereby enhancing the long-term sustainability of monitoring networks.

The value of manure - Manure as co-product in life cycle assessment

Livestock production is important for food security, nutrition, and landscape maintenance, but it is associated with several environmental impacts. To assess the risk and benefits arising from livestock production, transparent and robust indicators are required, such as those offered by life cycle assessment. A central question in such approaches is how environmental burden is allocated to livestock products and to manure that is re-used for agricultural production. To incentivize sustainable use of manure, it should be considered as a co-product as long as it is not disposed of, or wasted, or applied in excess of crop nutrient needs, in which case it should be treated as a waste. This paper proposes a theoretical approach to define nutrient requirements based on nutrient response curves to economic and physical optima and a pragmatic approach based on crop nutrient yield adjusted for nutrient losses to atmosphere and water. Allocation of environmental burden to manure and other livestock products is then based on the nutrient value from manure for crop production using the price of fertilizer nutrients. We illustrate and discuss the proposed method with two case studies.

Citizen science pioneers in Kenya - A crowdsourced approach for hydrological monitoring

Although water is involved in many ecosystem services, the absence of monitoring data restricts the development of effective water management strategies especially in remote regions. Traditional monitoring networks can be expensive, with unaffordable costs in many low-income countries. Involving citizens in monitoring through crowdsourcing has the potential to reduce these costs but remains uncommon in hydrology. This study evaluates the quality and quantity of data generated by citizens in a remote Kenyan basin and assesses whether crowdsourcing is a suitable method to overcome data scarcity. We installed thirteen water level gauges equipped with signboards explaining the monitoring process to passers-by. Results were sent via a text-message-based data collection framework that included an immediate feedback to citizens. A public web interface was used to visualize the data. Within the first year, 124 citizens reported 1175 valid measurements. We identified thirteen citizens as active observers providing more than ten measurements, whereas 57% only sent one record. A comparison between the crowdsourced water level data and an automatic gauging station revealed high data quality. The results of this study indicate that citizens can provide water level data of sufficient quality and with high temporal resolution.

Management intensity controls soil N2O fluxes in an Afromontane ecosystem

Studies that quantify nitrous oxide (N₂O) fluxes from African tropical forests and adjacent managed land uses are scarce. The expansion of smallholder agriculture and commercial agriculture into the Mau forest, the largest montane forest in Kenya, has caused large-scale land use change over the last decades. We measured annual soil N₂O fluxes between August 2015 and July 2016 from natural forests and compared them to the N₂O fluxes from land either managed by smallholder farmers for grazing and tea production, or commercial tea and eucalyptus plantations (n=18). Air samples from 5 pooled static chambers were collected between 8:00am and 11:30am and used within each plot to calculate the gas flux rates. Annual soil N₂O fluxes ranged between 0.2 and 2.9kgNha^-1yr^-1 at smallholder sites and 0.6-1.7kgNha^-1yr^-1 at the commercial agriculture sites, with no difference between land uses (p=0.98 and p=0.18, respectively). There was marked variation within land uses and, in particular, within those managed by smallholder farmers where management was also highly variable. Plots receiving fertilizer applications and those with high densities of livestock showed the highest N₂O fluxes (1.6±0.3kgN₂O-Nha^-1yr^-1, n=7) followed by natural forests (1.1±0.1kgN₂O-Nha^-1yr^-1, n=6); although these were not significantly different (p=0.19). Significantly lower fluxes (0.5±0.1kgNha^-1yr^-1, p<0.01, n=5) were found on plots that received little or no inputs. Daily soil N₂O flux rates were not correlated with concurrent measurements of water filled pore space (WFPS), soil temperature or inorganic nitrogen (IN) concentrations. However, IN intensity, a measure of exposure of soil microbes (in both time and magnitude) to IN concentrations was strongly correlated with annual soil N₂O fluxes.

Land use affects total dissolved nitrogen and nitrate concentrations in tropical montane streams in Kenya

African tropical montane forests are facing fast and dynamic changes in land use. However, the impacts of these changes on stream water quality are understudied. This paper aims at assessing the effect of land use and physical catchment characteristics on stream water concentrations of dissolved organic carbon (DOC), total dissolved nitrogen (TDN), nitrate (NO₃-N) and dissolved organic nitrogen (DON) in the Mau Forest, the largest tropical montane forest in Kenya. We conducted five synoptic stream water sampling campaigns at the outlets of 13-16 catchments dominated by either natural forest, smallholder agriculture or commercial tea and tree plantations. Our data show a strong effect of land use on TDN and NO₃-N, with highest concentrations in stream water of catchments dominated by tea plantations (1.80±0.50 and 1.62±0.60mgNl^-1, respectively), and lowest values in forested catchments (0.55±0.15 and 0.30±0.08mgNl^-1, respectively). NO₃-N concentration increased with stream temperature and specific discharge, but decreased with increasing catchment area. DOC concentrations increased with catchment area and precipitation and decreased with specific discharge, drainage density and topographic wetness index. Precipitation and specific discharge were also strong predictors for DON concentrations, with an additional small positive effect of tree cover. In summary, land use affects TDN and NO₃-N concentrations in stream water in the Mau Forest region in Kenya, while DOC and DON were more related to hydrologic regimes and catchment properties. The importance of land use for NO₃-N and TDN concentrations emphasizes the risk of increased nitrogen export along hydrological pathways caused by intensified land use and conversion of land to agricultural uses, which might result in deterioration of drinking water quality and eutrophication in surface water in tropical Africa.

Reducing emissions from agriculture to meet the 2 °C target

More than 100 countries pledged to reduce agricultural greenhouse gas (GHG) emissions in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change. Yet technical information about how much mitigation is needed in the sector vs. how much is feasible remains poor. We identify a preliminary global target for reducing emissions from agriculture of ~1 GtCO₂ e yr^-1 by 2030 to limit warming in 2100 to 2 °C above pre-industrial levels. Yet plausible agricultural development pathways with mitigation cobenefits deliver only 21-40% of needed mitigation. The target indicates that more transformative technical and policy options will be needed, such as methane inhibitors and finance for new practices. A more comprehensive target for the 2 °C limit should be developed to include soil carbon and agriculture-related mitigation options. Excluding agricultural emissions from mitigation targets and plans will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2 °C limit.

Methane and Nitrous Oxide Emissions from Cattle Excreta on an East African Grassland

Greenhouse gas (GHG) emission measurements from livestock excreta in Africa are limited. We measured CH and NO emissions from excreta of six Boran () and six Friesian () steers near Nairobi, Kenya. The steers were fed one of three diets (T1 [chaffed wheat straw], T2 [T1 + Meissner - 0.2% live weight per day], and T3 [T1 + calliandra - 0.4% live weight every 2 d]). The T1 diet is similar in quality to typical diets in the region. Calliandra is a leguminous fodder tree promoted as a feed supplement. Fresh feces and urine were applied to grasslands and emissions measured using static chambers. Cumulative 28-d fecal emissions were 302 ± 52.4 and 95 ± 13.8 mg CH-C kg dry matter for Friesen and Boran steers, respectively, and 11.5 ± 4.26 and 24.7 ± 8.32 mg NO-N kg dry matter for Friesian and Boran steers, respectively. For urine from Friesian steers, the NO emissions were 2.8 ± 0.64 mg NO-N 100 mL urine. The CH emission factors (EFs) (246 ± 49.5 and 87 ± 12.7 g CH-C yr animal for Friesan and Boran, respectively) were lower than the International Panel on Climate Change EFs (750 g CH-C animal yr), whereas the NO EFs (0.1 and 0.2% for the Friesian and Boran feces, respectively, and 1.2% for urine) were also lower than International Panel on Climate Change estimates. The low N content of the excreta likely caused the low emissions and indicates that current models probably overestimate CH and NO emissions from African livestock manure.

Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems

We present a unique, biologically consistent, spatially disaggregated global livestock dataset containing information on biomass use, production, feed efficiency, excretion, and greenhouse gas emissions for 28 regions, 8 livestock production systems, 4 animal species (cattle, small ruminants, pigs, and poultry), and 3 livestock products (milk, meat, and eggs). The dataset contains over 50 new global maps containing high-resolution information for understanding the multiple roles (biophysical, economic, social) that livestock can play in different parts of the world. The dataset highlights: (i) feed efficiency as a key driver of productivity, resource use, and greenhouse gas emission intensities, with vast differences between production systems and animal products; (ii) the importance of grasslands as a global resource, supplying almost 50% of biomass for animals while continuing to be at the epicentre of land conversion processes; and (iii) the importance of mixed crop–livestock systems, producing the greater part of animal production (over 60%) in both the developed and the developing world. These data provide critical information for developing targeted, sustainable solutions for the livestock sector and its widely ranging contribution to the global food system.