Sustainable Intensification Of Agriculture Research Articles

Integrated water availability modelling to assess sustainable agricultural intensification options in the Meki catchment, Central Rift Valley, Ethiopia

ABSTRACT The Meki catchment in the Central Rift Valley basin of Ethiopia is currently experiencing irrigation expansion and water scarcity challenges. The objective of this study is to understand the basin’s current and future water availability for agricultural intensification. This was done by simulating scenarios through an integrated SWAT-MODFLOW model to assess the water balance. The scenarios were co-developed with communities who expressed their aspirations for agricultural intensification in conjunction with projected climate change. The results show that with the present land use and climate, the catchment is already water stressed and communities cannot meet their irrigation water demand, particularly in the first irrigation season (October–January). However, in the second irrigation season (February–May) water resource availability is better and increasing irrigated area by 50% from the present extent is possible. With a climate change scenario that favours more rainfall and shallow groundwater use, agricultural intensification is feasible to some extent.

Gap analysis and methodological framework to assess and develop water centric sustainable agricultural intensification pathways in Sub-Saharan Africa

The sustainable agricultural intensification (SAI) debate, partly rooted in discussions over the Green Revolution, was developed in the 1990s in the context of smallholder agriculture in Africa. In many Sub-Saharan African (SSA) countries, production is still largely rainfed, with the prevalence of significant yield gaps and rapid environmental degradation. Projections indicate that climate and demographic changes will further intensify the competition for freshwater resources. Currently, SAI is centered around predominantly rain-fed agricultural systems, often at a farm and plot scales. There has been increased attention to the improved role of agricultural water management (AWM) to address the daunting challenges of climate change, land degradation and food and nutritional insecurity in SSA. Nonetheless, the supporting frameworks and tools remain limited and do not connect the sustainability assessment and the development of intensification pathways (SIP) along multiple scales of the rainfed irrigation continuum. This paper reviews the gaps in concepts and practices of SAI and suggests a methodological framework to design context-specific and water-centered SIP for the SSA region. Accordingly, the proposed methodological framework demonstrates: (a) how to couple sustainability assessment methods to participatory SIPs design and adaptive management approach; (b) how contextualized sustainability domains and indicators can help in AWM centered SIP development; (c) the approaches to handle multiple scales and water-related indicators, the heterogeneity of biophysical and social settings when tailoring technology options to local contexts; and (d) the principles which enable the SIP designs to enable synergies and complementarities of SAI measures to reinforce the rainfed-irrigation continuum. This methodological framework allows researchers to integrate the sustainability assessment and SIP design, and guides policymakers and practitioners in planning, implementing and monitoring SAI initiatives (e.g., Framework for Irrigation Development and Agricultural Water Management in Africa) across multiple scales.

Building resilience through improving groundwater management for sustainable agricultural intensification in African Sahel

BackgroundThis paper examines the role of improved groundwater access and management in providing opportunities for sustainable agricultural intensification and building the resilience of community farmers in Southern Burkina Faso. The findings contribute to current debates about pathways of commercialisation and adaptation in the African Sahel, especially those seeking to find responses to managing the impacts of climate change and delivering on the Sustainable Development Goals.MethodsThis paper presents data that has been thematically analysed based on the Framework for Sustainable Intensification developed by Pretty and Bharucha (Ann Bot 114:1571–1596, 2014). The data used includes 144 Vulnerability Baseline Assessments which were conducted at the start of the project with the four target Burkinabe communities (Kado, Poa, Tomo, and Zhilivele), and 33 monitoring interviews and vulnerability assessments from the Burkinabe communities of Poa and Tomo to track progress and behaviour change resulting from the BRAVE project interventions.ResultsThe data analysis showed that Burkinabe communities are already making some use of groundwater to support their agricultural livelihoods; most do this through accessing groundwater from shallow wells. It was also shown that there were improvements in the four main themes Identified by the Sustainable Intensification Framework. These included improved information sharing through increased peer-to-peer learning and improvements in confidence levels; improved social cohesion through reduction in community conflict over water resource management; asset improvements shown by tangible improvement of yields; and increased awareness exemplified by behaviour change.ConclusionsThrough using the Sustainable Intensification framework, this paper argues that such an approach improves essential aspects of resilience building such as information sharing, improved local governance and increased social capital and income. We argue that such changes provide essential pathways to reducing vulnerability and increasing resilience of at-risk communities in the Sahel, but that national policy alignment and investment is essential for long term change and sustainability.

Coupled and decoupled legumes and cereals in prehistoric northern and southern China.

Legumes and cereals, which provide different nutrients, are cultivated as coupled crops in most centers of plant domestication worldwide. However, as the only legume domesticated in China, the spatio-temporal distribution of soybeans and its status in the millet- and rice-based agricultural system of the Neolithic and Bronze Ages remains elusive. Here, archaeobotanical evidence of soybeans (n=254), millet (n=462), rice (n=482), and zooarchaeological evidence of fish (n=138) were synthesized to elucidate the phenomenon of coupled or decoupled cereals and legumes in prehistoric China. During the Neolithic and Bronze Ages, soybeans was mostly confined to northern China and rarely found in southern China, serving as a companion to millet. In contrast, fish remains have been widely found in southern China, indicating a continuous reliance on fish as a staple food besides rice. Thus, an antipodal pattern of millet-soybeans and rice-fish agricultural systems may have been established in northern and southern China since the late Yangshao period (6000–5000 cal BP) respectively. These two agricultural systems were not only complementary in terms of diet, but they also exhibited positive interactions and feedback in the coculture system. Consequently, these two systems enabled the sustainable intensification of agriculture and served as the basis for the emergence of complex societies and early states in the Yellow and Yangtze Rivers.

Developing context-specific frameworks for integrated sustainability assessment of agricultural intensity change: An application for Europe

Agriculture plays a central role in achieving most Sustainable Development Goals (SDGs). Sustainable intensification (SI) of agriculture has been proposed as a promising concept for safeguarding global food security, while simultaneously protecting the environment and promoting good quality of life. However, SI often leads to context-specific sustainability trade-offs. Operationalising SI thus needs to be supported by transparent sustainability assessments. In this article, we propose a general systematic approach to developing context-specific frameworks for integrated sustainability assessment of agricultural intensity change. Firstly, we specify a comprehensive system representation for analysing how changes in agricultural intensity lead to a multitude of sustainability outcomes affecting different societal groups across geographical scales. We then introduce a procedure for identifying the attributes that are relevant for assessment within particular contexts, and respective indicator metrics. Finally, we illustrate the proposed approach by developing an assessment framework for evaluating a wide range of intensification pathways in Europe. The application of the approach revealed processes and effects that are relevant for the European context but are rarely considered in SI assessments. These include farmers’ health, workers’ living conditions, cultural heritage and sense of place of rural communities, animal welfare, impacts on sectors not directly related to agriculture (e.g., tourism), shrinking and ageing of rural population and consumers’ health. The proposed approach addresses important gaps in SI assessments, and thus represents an important step forward in defining transparent procedures for sustainability assessments that can stimulate an informed debate about the operationalisation of SI and its contribution towards achieving SDGs.

Maintaining higher grain production with less reactive nitrogen losses in China: A meta-analysis study

Managing reactive nitrogen (Nr) in agricultural production is crucial for addressing the triple challenges of food security, climate change and environmental degradation. Intensive work has been conducted to investigate the effects of mitigation strategies on reducing Nr losses by ammonia emission (Nr-NH3), nitrous oxide emission (Nr-N2O) and nitrate leaching (Nr-NO3-) separately. This meta-analysis evaluated the efficiency of each strategy in mitigating Nr losses coupled with grain yield responses. The results indicate that producing one Megagram (Mg) of wheat grains caused higher Nr losses, twice that of rice and 17% that of maize. The Nr-NH3 and Nr-NO3- were the dominant sources of Nr losses of the three crops (96%), while Nr-NH3 only presented 86% of the total Nr losses for rice. Reducing the N rate strategy decreased the yield by 33% and the Nr losses by 62% compared with the conventional rate (150–250 kg N ha−1) as an average of the three crops. In contrast, increasing the N rate higher than 250 kg N ha−1 amplified the yield by 15% but also caused a 71% increase in Nr losses compared with the conventional rate. Although subsurface application decreased Nr losses by 5%, this study rejected this approach as an effective strategy due to a 4% yield decline on average of the grain crops. Slow-release fertilizers decreased Nr-NH3 and Nr-N2O losses by 41–58% and 54–89%, respectively, of the highest losses under urea in the three crops, but also led to yield reductions. Organic amendments achieved the highest drop in Nr-NO3- loss by 66% in maize coupled with yield declines. Biochar increased wheat and maize yields by 0.3 and 0.1 Mg, respectively, coupled with 1 kg reduction in Nr losses. On average, inhibitors augmented the grain yields by 0.2 Mg ha−1 for each 1 kg decline in Nr losses. In conclusion, for sustainable agricultural intensification, biochar (for wheat only) and inhibitors (for the three crops) are strongly recommended as mitigation strategies for Nr losses from grain crop production systems in China.

Sustainable intensification in jeopardy: Transdisciplinary evidence from Malawi.

In Africa, achieving sustainable agricultural intensification-increasing agricultural output without deleterious environmental impacts or converting more land for cultivation-will depend greatly on the actions of smallholder farmers and the policies that influence them. Whatever the future holds, the vast majority of farmers right now are small. Using multiple lines of evidence across disciplines, we examine trends in productivity of land and fertilizers in Malawi. Unfortunately, our effort uncovers disturbing trends that indicate intensification and sustainability are at risk. Two time-series datasets of satellite-based vegetative indices show a generally flat but highly variable trend in the productivity of agricultural land with epochs of steep decline. This is notably despite substantial (and successful) government effort to promote fertilizer use. We also compile evidence from several studies over three decades that use field-level data from farmers and suggest substantial declining maize yield response to fertilizer over time. These trends are consistent with soil degradation, the disappearance of fallow land and minimal investment in rehabilitation practices in densely populated areas, putting agricultural productivity in jeopardy. These signs of the harmful impacts that narrow approaches to productivity improvement may be having in Malawi are an early warning sign to policy makers in Malawi and around the continent that a more holistic and nuanced strategy is necessary for sustainable intensification in agriculture.

Do youth conceptualizations influence the inclusion of young people in sustainable agriculture intensification? Insights from Ghana and Malawi

Do youth conceptualizations influence the inclusion of young people in sustainable agriculture intensification? Insights from Ghana and Malawi

Coupling the environmental impacts of reactive nitrogen losses and yield responses of staple crops in China

Cropland reactive nitrogen losses (Nr) are of the greatest challenges facing sustainable agricultural intensification to meet the increases in food demand. The environmental impacts of Nr losses and their yield responses to the mitigation strategies were not completely evaluated. We assessed the environmental impacts of Nr losses in China and coupled the efficiency of mitigation actions with yield responses. Datasets about Nr losses in China were collected, converted into potentials of acidification (AP), global warming (GWP), and aquatic eutrophication (AEP), and analyzed by a meta-analysis program. Results showed that producing 1 Mg of rice grains had the highest AP (153 kg acid equiv.), while wheat had the highest GWP and AEP (74 kg CO2 equiv. and 0.37 kg PO4 equiv., respectively). Using the conventional rates (averagely, 200, 230, and 215 kg N ha−1) of urea as a surface application to produce 131.4, 257.2, and 212.1 Tg of wheat, maize, and rice resulted in 17–33 Tg, 7–10 Tg, and 6–87 Gg of AP, GWP, and AEP, respectively. For their balanced effect on reducing AP, GWP, and AEP while maximizing yields, inhibitors, and subsurface application could be set as the best mitigation strategies in wheat production. Inhibitors usage and biochar are strongly recommended strategies for sustainable production of maize. None of the investigated strategies had a balanced effect on rice yield and the environment, thus new mitigation technologies should be developed.

A club model of nature-smart agriculture for biodiversity, climate, and productivity enhancements.

This article considers horizontal and vertical intensification interactions between environmental conservation and agricultural production to investigate a top-down partnership in agriculture. It addresses the issues underlying the challenge of food security. It explores a nature-based landscape approach to agriculture management that simultaneously ensures food security and safeguards the natural environment. The economic theory of clubs is applied to extend farm-level sustainable agricultural intensification and conservation practices to encompass interconnected activities within the entire landscape. A theoretical ecological-economic club model is used to explore how biodiversity and climate-related environmental goods and agricultural products are coproduced by private producers in agroecosystems of any spatial scale. The model considers any given agroecosystem as a club producing two goods: private economic output and public ecological output. It also proposes a dual environmental incentive approach to promote participants' individual and collaborative efforts. The model derives (a) the social conditions for the optimal application and allocation of resources for producing sustainable agricultural and ecological outputs and (b) the producer's incentive conditions for adequate levels of individual and collaborative conservation activities. Thus, the study identifies conditions that optimize horizontal and vertical agri-environmental farming intensification while preventing crowding out voluntary conservation activities. The model presented here can set a theoretical "benchmark" model to address real-life deviations comparatively. A practical proposition derived from the analysis points to the possibility that farm-scale conservation (of biodiversity and climate-related attributes), when extended to the landscape level, can optimally enhance the interconnected goals of agri-environmental farming. Thus, a data-driving methodology is described to outline a practical approach to the agricultural transition toward landscape conservation, a practical guide for policymakers and regulators who need to develop and provide tailor-made support to agricultural producer members of the club. Integr Environ Assess Manag 2023;19:412-421. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Spatial governance of Beijing-Tianjin-Hebei urban agglomeration towards low-carbon transition

PurposeThis paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.Design/methodology/approachThe authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.FindingsThe study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.Research limitations/implicationsThe authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.Originality/valueThe authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.

Impact of Landscape Management Scenarios on Ecosystem Service Values in Central Ethiopia

This study aimed at modeling scenarios of future land use and land cover (LULC) change and estimating ecosystem service (ES) values for the year 2051 compared to 2021 in Central Ethiopia. The future LULC changes for the year 2051 were simulated for four scenarios, namely Business-as-Usual (BAU), Rapid Agricultural Expansion (RAE), Ecosystems Protection and Agricultural Development (EPAD) and Landscape Ecosystems Restoration and Conservation (LERC). The four LULC change scenarios were simulated based on anticipated assumptions that were derived from existing spatial policies, a consultation workshop report on scenarios of agricultural development in Ethiopia, suitability analysis, population growth analysis and expert knowledge of the study area characteristics. We used a Multi-Layer Perceptron–Artificial Neuron Network (MLP–ANN) model-based projected LULC for the BAU scenario and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to generate RAE, EPAD and LERC scenarios in the study landscape. The benefit transfer method was used to estimate the total ES values and for trade-off analysis. The result showed that LULC changes in the study area varied across simulated scenarios compared to the base year 2021. Under the BAU and RAE scenarios, cultivated land increased by 146,548 ha (22%) and 193,965 ha (29%), whereas forest, water body, wetland and shrub-bush land were reduced. However, forest cover increased by 31,725 ha and 100,080 ha but bare land was reduced by 8466 ha (21%) and 10,379 ha (25%) under the EPAD and LERC scenarios. The forest cover annual rate of change was 3.2% and 6% under the EPAD and LERC scenarios. As a result, the total ES value increased by USD 24.5 and 78.5 million under the EPAD and LERC scenarios for the year 2051, whereas the total ES value was reduced under the BAU and RAE scenarios by USD 27.1 and 73.2 million. The trade-offs among ecosystem services were significantly synergized under the LERC scenario compared to RAE. Therefore, EPAD and LERC could be used as a reference for sustainable landscape planning and management. Landscape ecosystems restoration integrated with a sustainable agricultural intensification approach would enable us to ensure the sustainability of both agricultural production and ecosystem service synergies without negatively affecting the natural environment.

Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model

Prediction of crop yield, evapotranspiration, and crop water productivity are essential aspects for water management and the sustainable intensification of agriculture. The goal of this study was to evaluate the Cropping System Model (CSM)-CROPGRO-Soybean model for simulating evapotranspiration and crop water productivity of soybean grown in a tropical environment. Energy balance evapotranspiration was measured daily using a Bowen Ratio Energy Balance (BREB) system for irrigated experiments that were conducted in Piracicaba, SP, Brazil, during the 2016-2017 and 2017-2018 growing seasons. Evapotranspiration was simulated with the CROPGRO-Soybean model using either the Priestley–Taylor or the FAO-56 Penman–Monteith method for potential ET combined with either the Ritchie-Two-Stage or the Suleiman–Ritchie soil water evaporation methods. The model provided good predictions of daily (D-statistic > 0.7) and cumulative evapotranspiration (RMSE ranged from 8 to 64 mm). FAO-56 Penman–Monteith with the Ritchie-Two-Stage method provided a better fit than the Priestley–Taylor with Suleiman–Ritchie when compared with measured data. Simulated crop water productivity agreed well with observed, but with a systematic underprediction (variation between simulated and measured ranged from -2.2 to -16.8 %). Simulation of long-term scenarios was conducted for different tropical environments, i.e., Piracicaba and Teresina, with soil tillage and water management practices. The results demonstrated that the implementation of no-tillage can increase 0.1 kg/m3 (11%) crop water productivity for grain. This study also showed that when irrigation was triggered at more than 60% of available soil water, irrigation did not result in an increase in yield despite an increase in water supply.

Can soil fertility properties in rice fields in sub-Saharan Africa be predicted by digital soil information? A case study of AfSoilGrids250m

Soil information is essential for sustainable agricultural intensification in sub-Saharan Africa (SSA). This is the case for rice production, for which soil fertility is one of the main constraints. Through the Africa Soil Information Service (AfSIS), digital soil information at 250 m resolution (AfSoilGrids250m) is available for SSA. However, it was not validated in a wide range of rice-growing conditions. The objective of this study was to assess the accuracy of AfSoilGrids250m by comparing predicted soil fertility properties including pH H2O, clay and silt contents, total nitrogen (TN) and organic carbon (OC) with wet chemistry (WC) analysis and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) methods. Soil samples were collected from 1002 rice fields in three production systems (irrigated lowland, rainfed lowland, and rainfed upland) in 32 sites and over five agro-ecological zones (AEZ). The coefficient of determination (R2), index of Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), and percent bias (PBias) were used to assess the predictive performance of AfSoilGrids250m. In comparison with WC and DRIFTS methods, AfSoilGrids250m underestimated the studied soil fertility properties. At the field scale, the prediction accuracy of AfSoilGrids250m for pH H2O, clay and silt contents, total nitrogen (TN), and organic carbon (OC) were poor (R2 < 0.50). The best predictive performances were obtained when data were aggregated by site-production system combination (site x PS) (n = 40). With this aggregation, AfSoilGrids250m achieved satisfactory to good prediction accuracy for TN and OC. The classification of AfSoilGrids250m had a fair to moderate agreement with both WC and DRIFTS classifications for clay content, TN, and OC. We conclude that current digital soil information (AfSoilGrids250m) is useful for assessing and classifying soil fertility properties of rice fields in different production systems at the site scale in SSA, but not as much for predicting them at the farmers' field scale.

Chemical and spectroscopic evaluations supporting superior P availability after biochar-P fertilizer application

Sustainable agriculture intensification requires optimization of agriculture resources such as new fertilizers with higher nutrient use efficiency. Biochar has been a promisor alternative not only as a P source but also as a matrix to host P fertilizer to improve its use efficiency by intrinsic features. In our previous work, biochar enriched with P lead to higher sugarcane biomass yield and P use efficiency than conventional P fertilizer in a greenhouse trial, however, the effects of biochar enriched with P in the fate of available-P were not plenty understood. In this work, we investigated the superior P availability after fast-pyrolysis biochar-P fertilizer (BioFert) over the incubation time of 240 days in three distinct soils (sandy, loamy and clayey), evaluating the available-P by an anionic exchangeable membrane (AER) and bicarbonate solution extractions, as also solid P speciation by X-ray Absorption Near Edge Structure (XANES) analysis performed at a Synchrotron source. The AER results showed that available-P in BioFert treatment was, on average, 14% superior in sandy, 56% in loamy, and 72% in clayey soil than triple superphosphate (TSP). XANES results pointed out Al- and Fe-phosphates as the main P-sink for all soils, however both fertilizers introduced P-Ca in the system. The superiority of BioFert was associated with its capacity to buffer the soil pH in values higher than 7 potentially reducing P immobilization. In summary, results support the higher efficiency of BioFert than TSP observed in previous work because it supplies more available P synchronized to plant demand over time.

Creating a Solar-Powered Drip Irrigation Optimal Performance model (SDrOP) to lower the cost of drip irrigation systems for smallholder farmers

Smallholder farmers, who hold 84% of the approximately 570 million farms worldwide, are vital stakeholders in the process of sustainable agricultural intensification, but often lack the capital to invest in sustainable farming practices. Solar-powered drip irrigation has the potential to increase crop productivity for minimal water use, but these systems are prohibitively expensive for smallholders. Reducing the life cycle cost (LCC) of solar-powered drip irrigation systems could make this technology more accessible, enabling smallholders to increase their household incomes and contribute to greater global food security. This paper presents the Solar-Powered Drip Irrigation Optimal Performance model (SDrOP), which optimizes solar-powered drip irrigation system designs. Unlike existing commercial software, SDrOP models the behavior of the entire system and simulates seasonal performance to reduce LCC while maintaining operational reliability. SDrOP improves on previous design optimization frameworks by taking in all location-dependent parameters as inputs, which makes the model independent of case specifics and, therefore, broadly applicable. To demonstrate the model theory, the sensitivity of the optimal design to field area, the system reliability constraint, and varying weather conditions are explored for a Moroccan olive orchard case study. The results demonstrate opportunities for system cost reduction, including operational changes to reduce the system power requirement, irrigation pump opportunities for the smallholder market, and reductions in system reliability when it is shown to have minimal impact on crop yield. When benchmarked against a commercially available software, SDrOP was able to reduce system LCC by up to 56%. The simulated performance of an SDrOP optimal design was benchmarked against operational data from an existing field site, and was shown to be capable of operating 92% of the recorded irrigation events. These results indicate that SDrOP offers an advantage over existing software as it produces significantly reduced cost designs that can operate in real-world conditions.

Effects of cyanobacterial-based biostimulants on plant growth and development: a case study on basil (Ocimum basilicum L.)

In the coming years biostimulants will play a key role in the sustainable intensification of agriculture due to their capacity to improve crops quality, nutrient use efficiency and tolerance to abiotic stresses. Cyanobacteria are nowadays considered one of the most promising sources of new biostimulants; however, in vivo studies using cyanobacteria are still scarce and often limited to a few genera. In this work the biostimulant activity of five cyanobacterial hydrolysates was evaluated on Ocimum basilicum L. grown in hydroponics. Plants were treated weekly with foliar applications of the cyanobacterial hydrolysates and of two commercial products. Three of the tested cyanobacterial hydrolysates, administered at the concentration of 1 g L-1, were effective in increasing plant growth (up to +32%), and number (up to +24%) and fresh weight (up to +26%) of the leaves compared to controls. Moreover, the cyanobacterial hydrolysates performed better than the commercial biostimulants. The biochemical characterization of the hydrolysates suggests that the observed bioactivity can be related to a high carbohydrate content. Our results indicate that cyanobacteria-based biostimulants can be an effective tool for sustainably enhancing plant growth and yields.

Agricultural Innovization: An Optimization-Driven solution for sustainable agricultural intensification in Michigan

Humanity, now increasingly populous and affluent, poses a new challenge for the twentieth-first century farmer: increase food supply while maintaining the earth’s underlying ecosystems. This paper proposes a novel systems approach, agricultural innovization, to sustainably increase food production. Innovization applies the knowledge obtained through multi-objective optimization to discover new agricultural management practices which reduce the risk of climate variabilities on crop yields. In agricultural innovization, an optimization platform generated the near-optimal management actions for 30 years using a calibrated crop model for maize. From those near-optimal solutions, recommendations for improving management practices were data mined. Then these improved recommended practices were evaluated over 420 validation seasons. The validation results were promising as the recommended practices obtained from the innovization increased yields and generated no negative change in nitrogen leaching. Furthermore, these recommendations can be applied to future seasons of management, which makes them a fully predictive application of multi-objective optimization.

Impact of Productive Activities on Forest Cover Change in the Calakmul Biosphere Reserve Region: Evidence and Research Gaps

Background and Research Aims Human activities seeking to satisfy various needs have resulted in deforestation and other forest cover change processes. The Natural Protected Areas are among the most efficient instruments to contain forest loss. The compensation from conservation is not sufficient to compete with land uses with higher economic rent, such as timber extraction and food production. This study summarizes the evidence and identifies research gaps on forest processes caused by productive activities in Mexico’s Calakmul Biosphere Reserve. Methods We systematically reviewed the scientific literature investigating forest processes caused by the productive activities in the Calakmul, including the transition zone. We calculated the frequencies of codes on forest processes and productive activities in the entire sample (53), evaluated each code’s significance in the qualitative synthesis and interpretation, and summarized the measurements of forest processes considering only the primary studies (46). Results Deforestation was the most commonly investigated process. Traditional agriculture initially caused deforestation, while livestock and conventional agriculture became more dominant recently with the agricultural intensification policies. Few articles investigated forest degradation experiencing a steady increase from fallow shortening and selective logging. Also, few studies identified forest recovery resulting from long fallows and core zone delimitation. No publications evaluated the forest cover impact of sustainable initiatives. Conclusion The tendency to quantify deforestation on a regional scale masks presence of other forest processes. The rural development programs in Calakmul did not include the environmental perspective, while participation in sustainable initiatives was low. The understanding of productive activities at the local level will allow differentiation of the long-term from temporary forest dynamic. Implications for Conservation To assure resilient and inclusive growth in Calakmul, the reduced-impact logging, sustainable agricultural intensification, improved fallows, and beekeeping should be supported with monetary resources that cover the transaction costs of unsustainable livestock breeding and industrial agriculture.

Adoption of Sustainable Agriculture Intensification in Maize-Based Farming Systems of Katete District in Zambia

Sustainable agricultural intensification (SAI) has been hailed as the solution to increasing crop productivity among farmers. Despite the significant promotion, there still remains a dearth of information on the adoption and intensity of SAI in Zambia. This study sought to identify factors that influence farmers’ adoption of SAI practices and intensity of use. A cross-sectional survey was conducted among 300 smallholder farmers of Katete district in Zambia. The Cragg’s double hurdle model was used to assess the key decision factors for SAI adoption and intensity of use. Empirical estimates revealed that limited years of farming and smaller total cropped field size were statistically significant decision factors that led to a reduced likelihood of SAI adoption. The results of the truncated model showed that smaller farm sizes and limited access to farmer extension services reduced the adoption intensity of SAI practices, whereas farmer affiliation with farmer associations and farmer training in crop production increased SAI adoption intensity. We recommend an increase in farmer training on and sensitization to the benefits of SAI practices aligned to their respective landholdings.