Agricultural Systems最新文献

{"title":"Optimizing rice management to reduce methane emissions and maintain yield with the CSM-CERES-rice model","authors":"Dorsa Darikandeh ,&nbsp;Ali Shahnazari ,&nbsp;Mojtaba Khoshravesh ,&nbsp;Mostafa Yousefian ,&nbsp;Cheryl H. Porter ,&nbsp;Gerrit Hoogenboom","doi":"10.1016/j.agsy.2024.104248","DOIUrl":"10.1016/j.agsy.2024.104248","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Irrigated paddy fields are major contributors to methane (CH₄) emissions, significantly impacting global warming. Flood irrigation, the traditional method for rice cultivation, significantly increases water consumption and CH₄ emissions.</div></div><div><h3>OBJECTIVE</h3><div>The primary objective of this study was to quantify the benefits of deficit irrigation in reducing CH₄ emissions and maintaining yield compared to traditional flood irrigation using a systems analysis approach.</div></div><div><h3>METHODS</h3><div>The field study was conducted from May to August in both 2015 and 2016 at the Rice Research Institute in Amol, northern Iran. The site has a warm temperate climate, with the soil characterized as silty clay loam. The data collected during these two years were used for the calibration and evaluation of the CSM-CERES-Rice model. Calibration was performed using the data collected in 2016 while the model's performance was evaluated using data collected in 2015. Following model calibration and evaluation, a seasonal analysis was employed to assess alternative management practices for single growing seasons. This analysis feature of DSSAT allowed us to evaluate alternate management scenarios with the model using 35 years of long-term historical daily weather data from 1984 to 2018 obtained from a local weather station.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The simulation revealed that early rice planting, in April or May, yielded the highest production and the lowest CH₄ emissions, when using the direct seeding method. This strategy resulted in a 15 % increase in yield, 13 % better irrigation efficiency, and a 9 % reduction in CH₄ emissions compared to transplanting. Among tillage systems, no-tillage further reduced CH₄ emissions by 29 % without compromising yield or irrigation efficiency. Although sowing depth did not significantly affect CH₄ emissions or yield, an optimal depth of 10–15 cm was identified. Additionally, maintaining a plant population of 10 transplants per hill exhibited the lowest CH₄ emissions compared to higher plant populations. Higher nitrogen fertilization rates increased both yield and CH₄ emissions. In conclusion, the best approach among different strategies was early cultivation for direct-seeded rice coupled with a nitrogen fertilizer rate of 250 kg ha⁻¹, resulting in both the highest yield and the lowest emissions simultaneously.</div></div><div><h3>SIGNIFICANCE</h3><div>The findings from this study offer a comprehensive exploration, identifying specific agronomic practices that optimize rice cultivation by enhancing yield, conserving water, and significantly reducing CH₄ emissions, thereby providing actionable insights for policymakers and farmers in fostering sustainable agriculture.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104248"},"PeriodicalIF":6.1,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional modelling of rice yields and nitrogen loss in Hubei Province using the WHCNS model","authors":"Chao Li ,&nbsp;Xinrui Shi ,&nbsp;William D. Batcholer ,&nbsp;Puyu Feng ,&nbsp;Kelin Hu","doi":"10.1016/j.agsy.2024.104249","DOIUrl":"10.1016/j.agsy.2024.104249","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Excessive nitrogen (N) fertilization has led to serious environmental problems. Exploring the spatial distribution of rice yields and N loss is crucial to determine optimal N fertilizer management. However, previous studies are mostly based on field scale, it's a big challenge to use model approach to explore the spatial distribution and influencing factors of rice yields and N loss due to lack of field management, soil and crop information at regional scale.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to evaluate the feasibility of the WHCNS (soil Water Heat Carbon Nitrogen Simulator) model in simulating rice yield and N loss at regional scale, explore the spatial distribution of yield and N loss under traditional water and N management, and determine the main factors causing spatial differences in Hubei Province.</div></div><div><h3>METHODS</h3><div>The WHCNS model was calibrated and validated using data collected on statistical yields and N losses in Hubei Province. Then, the model was used to simulate rice yield and NH₃ volatilization, denitrification, N leaching and runoff for single, early and late season rice at regional scale. The spatial distribution of yield and N loss and their correlation with meteorological factors and soil properties were analyzed.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The WHCNS model performed well in simulation of regional rice yield and N loss compared with other models. <em>R</em>² and <em>d</em> of simulated and measured yields, ammonia volatilization and N runoff were &gt; 0.55 and 0.84 respectively. The yield was higher in central Hubei and lower in western and southeastern Hubei, mainly driven by solar radiation and temperature, soil clay content, pH and bulk density. N runoff loss decreased from east to west of Hubei, mainly affected by rainfall and temperature for single and early season rice, and bulk density for late season rice. Higher N leaching and denitrification in northwestern Hubei were related to high nutrient content (soil total N and organic matter) and poor aeration. Higher NH₃ emission was found in eastern Hubei, mainly affected by temperature and precipitation. The average total N loss for single, early and late season rice was 77.2, 65.6, and 81.5 kg N ha⁻¹, respectively, accounting for 33.6 %, 31.5 %, and 40.8 % of the N application rates.</div></div><div><h3>SIGNIFICANCE</h3><div>The WHCNS model was used to determine the spatial distribution and main factors influencing rice yields and N loss in Hubei Province. These findings provide a scientific basis for optimizing N management to minimize N loss while maintaining yield.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104249"},"PeriodicalIF":6.1,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A farm typology development cycle: From empirical development through validation, to large-scale organisational deployment","authors":"Rhys Manners ,&nbsp;Jim Hammond ,&nbsp;David Renaud Umugabe ,&nbsp;Milindi Sibomana ,&nbsp;Marc Schut","doi":"10.1016/j.agsy.2024.104250","DOIUrl":"10.1016/j.agsy.2024.104250","url":null,"abstract":"<div><h3>CONTEXT</h3><div>The publication of farm (or farmer) typologies has increased over recent years. The purpose of these studies is usually to differentiate groups of farmers so that they are “targeted” with specific agricultural innovations, or best-bet interventions can be “prioritised”. The degree to which such typologies actually influence development practice is however unclear, and little has been published on that topic.</div></div><div><h3>OBJECTIVE</h3><div>The paper aims to move narratives and practices around farm typologies from theoretical to applied and present a novel methodology for typology validation. We worked with a large-scale development organisation to develop a typology for their use, and report here on the process of enabling the organisation to make use of the typology. The lessons from this process are intended to inform the use of farm typologies in agricultural development work.</div></div><div><h3>METHODS</h3><div>A typology of farming households was derived from a household survey in Rwanda (previously published), in partnership with a large-scale agricultural development organisation. Responding to the organisation's requests, the researchers created a decision tree tool to rapidly assign households to types; conducted validation exercises to establish confidence in the typology and the decision tree (making adaptations as needed). Validation was with farmers and extensionists and included developing key word and pictorial representations of farm types which were compared against the empirical typology. The decision tree was tested and questions adapted to maximise accuracy. The organisation then used the tools for a period of two years. Finally, the researchers interviewed representatives of the organisation to find out how the tools had been used.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The typology validation exercises showed a high level of agreement between farmers and extensionists, and a moderate level of agreement between the empirical typology and the types defined by farmers and extensionists. There was a low level of agreement in the Western province of Rwanda, where the socio-economic situation was radically different to other areas, which had not been accounted for in the empirical typology definition. Establishing the correct questions in the decision tree tool proved important. The organisation reduced the number of farm types, and categorised over 350,000 households, with four use cases developed for the farm typologies: planning for the recruitment of clients (farming households are referred to as clients by the organisation), client needs assessment, intervention adoption rate assessment, and monitoring of farmers along the organisation's conception of their (farmers') journey to prosperity.</div></div><div><h3>SIGNIFICANCE</h3><div>This study provides lessons on what is required for the application of farm typologies by development organisations.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104250"},"PeriodicalIF":6.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field estimates of current and predicted cotton yield loss due to pink bollworm and boll rot in India","authors":"Babasaheb B. Fand ,&nbsp;Vivek Shah ,&nbsp;D.T. Nagrale ,&nbsp;D.J. Mahule ,&nbsp;S.P. Gawande ,&nbsp;S.H. Thube ,&nbsp;K. Pandiyan ,&nbsp;Indal Ramteke ,&nbsp;Rishi Kumar ,&nbsp;K. Rameash ,&nbsp;T. Prabhulinga ,&nbsp;V.S. Nagrare ,&nbsp;G.T. Behere ,&nbsp;Y.G. Prasad","doi":"10.1016/j.agsy.2024.104246","DOIUrl":"10.1016/j.agsy.2024.104246","url":null,"abstract":"<div><h3>Context</h3><div>The development of pink bollworm (PBW) resistance to Bt cotton and the rise of boll rot (BR) disease pose significant challenges to cotton production in India. Both PBW and BR significantly reduce cotton yields by damaging seeds and lint. Damage caused by PBW often resembles BR infection leading to misdiagnosis and incorrect control measures. The lack of precise methods for quantifying yield losses caused by PBW and BR prompted genesis of this study.</div></div><div><h3>Objective</h3><div>This study aimed to develop a reliable and robust method for quantifying yield losses caused by PBW and BR, and to predict future yield loss trends for PBW by integrating a phenology model with field data collected from various cotton-growing regions of India.</div></div><div><h3>Methods</h3><div>Yield loss calculation involved assessing the PBW and BR incidence levels and working proportionate weight loss in randomly sampled loculi from cotton fields. Using a temperature-driven phenology model coupled with a geographic information system, PBW infestation risk was mapped across India's cotton-growing areas and its population growth was simulated under various climate change scenarios predicting temperature rise between 0.5 and 2.5 °C over current temperature. Phenology model driven activity index, expressed as population abundance of PBW was regressed over field damage data from 15 different Indian cotton-growing locations to predict future yield loss trends under climate change scenarios.</div></div><div><h3>Results and conclusions</h3><div>Without control measures, PBW and BR individually could cause potential yield losses of ∼25 %, equating to an annual loss of 4.27 million tons out of 17.09 million tons of seed cotton produced in India. With control measures, PBW caused an actual yield loss of 3.75 %, equating 0.64 million tons of seed cotton, annually. Currently PBW undergoes over six generations annually in about 60 % of India's cotton-growing areas, increasing to 80 % by 2050 with climate change. Future PBW population abundance is expected to decline due to reduced survival and reproduction at higher temperatures, resulting in a slight decline in future yield loss trends.</div></div><div><h3>Significance</h3><div>This study provides a robust and reliable tool for quick yield loss assessment during pest or disease outbreaks and also introduces a new dimension of linking PBW phenology model with actual field damage data to improve management strategies for cotton pink bollworm.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104246"},"PeriodicalIF":6.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological indicators for monitoring coffee agroforestry systems in protected areas: A case study in São Paulo State, Brazil","authors":"Vitoria Duarte Derisso ,&nbsp;Ricardo Gomes César ,&nbsp;Ricardo Augusto Gorne Viani ,&nbsp;Haroldo Borges Gomes ,&nbsp;Edson Vidal","doi":"10.1016/j.agsy.2024.104245","DOIUrl":"10.1016/j.agsy.2024.104245","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Biodiverse coffee agroforestry systems (AFS) offer high potential for forest restoration. However, long-term monitoring using appropriate indicators is necessary to ensure successful ecological restoration. In the State of São Paulo, Brazil, legal instruments define ecological indicators and reference values for monitoring AFS-mediated ecological restoration.</div></div><div><h3>OBJECTIVE</h3><div>We assessed whether biodiverse coffee AFS of different age groups achieved legal reference values in the Brazilian Atlantic Forest and recommended strategies for improving legal instruments.</div></div><div><h3>METHODS</h3><div>We evaluated four ecological indicators in AFS areas of two age groups and compared them with reference values. Additionally, we analyzed the relationships among the ecological indicators under study.</div></div><div><h3>RESULTS AND CONCLUSION</h3><div>Half of the AFS sites did not achieve reference values for all ecological indicators, primarily owing to the management practices used. Additionally, we found that canopy cover had a direct relationship with soil cover; thus, not only did most AFS areas where farmers pruned native trees had canopy cover values lower than those required by legislation but, indeed, lower than the reference value for soil cover. However, this is subject to improvement via ecological restoration-friendly practices, reinforcing the feasibility of establishing this AFS design in protected areas. Despite proper choice of ecological indicators, we recommend that tree and sapling population density be measured separately.</div></div><div><h3>SIGNIFICANCE</h3><div>Despite its narrow scope, this study provided novel insights into the effects of coffee AFS management on the trajectory of ecological restoration and on the construction of proper monitoring frameworks using ecological indicators evaluated in other Brazilian regions or countries.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104245"},"PeriodicalIF":6.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The future of agricultural lands under the combined influence of shared socioeconomic pathways and urban expansion by 2050","authors":"Ali Sadian,&nbsp;Hossein Shafizadeh-Moghadam","doi":"10.1016/j.agsy.2024.104234","DOIUrl":"10.1016/j.agsy.2024.104234","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Food security is increasingly at risk due to rising demand, unprecedented population growth, and challenges such as climate change and urbanization. Consequently, modeling the combined effects of climate change and land conversion on agricultural lands is of strategic importance.</div></div><div><h3>OBJECTIVE</h3><div>This study simulates the combined effects of climate change and urban expansion on agricultural lands in western Iran, a region recognized as the food basket of the country.</div></div><div><h3>METHODS</h3><div>Land use maps for the past 30 years (1990–2020) were generated using Google Earth Engine and a scene-based approach. Urban expansion was simulated using the combination of multilayer perceptron, Markov chain and cellular automata. Data between 2000 and 2010 were used for calibration and data between 2010 and 2020 were used for validation. Subsequently, urban expansion by the year 2050 was simulated. To explore the influence of climate change, three climate models from the general circulation models were evaluated using mean absolute error, mean bias error, and root mean square error. The effects of precipitation deficiency on rainfed farming were investigated through three shared socioeconomic pathways (SSPs): SSP1–2.6, SSP2–4.5, and SSP3–7.0.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Land use maps were generated with overall accuracies ranging from 93 % to 96 %, while the urban expansion model demonstrated an accuracy of 85 %, as determined by the area under the curve. Simulated maps showed figure of merit and producer accuracy values of 63 % and 67 %, respectively. Urban areas expanded by 110 % between 1990 and 2020, with a projected 78 % increase between 2020 and 2050, resulting in the loss of 71 km² of agricultural land. Rainfed farming losses are projected to be insignificant by 2030 and 2040. However, by 2050, losses are estimated to range from 168 to 790 km² in the SSP1–2.6 scenario, 260 to 865 km² in SSP2–4.5, and 135 to 733 km² in SSP3–7.0, depending on precipitation thresholds of 250 mm and 300 mm.</div></div><div><h3>SIGNIFICANCE</h3><div>The study shows that while climate change can damage agricultural lands on a broad scale, urban expansion threatens high-quality irrigated and garden lands, posing serious risks to food security and sustainability. These insights are valuable for governments and decision-makers assessing the future risks posed by climate change and land conversion to agricultural lands.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104234"},"PeriodicalIF":6.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Organic farming enhances the synergy of the water-energy-food-ecology nexus","authors":"Meixi Pan,&nbsp;Zishu Tang,&nbsp;Guishen Zhao","doi":"10.1016/j.agsy.2024.104247","DOIUrl":"10.1016/j.agsy.2024.104247","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Synergies between water-energy-food-ecology (WEFE) nexus essentially embody the sound functioning of complex adaptive systems. As an effective way of promoting the transformation of agricultural systems, it is critical to compare the synergies between conventional and organic farming systems from a nexus perspective, and to explore the contribution of synergies to achieving sustainable development in agriculture.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to develop an integrated framework to facilitate assessment of the complex dynamics and potential for coordinated development of the WEFE nexus under organic and conventional farming. We also try to explore the relationship between system synergies and gross ecosystem product values, identifying key factors that influence systematic synergy.</div></div><div><h3>METHODS</h3><div>In this study, we developed a comprehensive WEFE nexus evaluation index and applied it to a case study of the tea industry in Simao District, Pu'er City, Yunnan Province, China. We employed the coupled coordination degree (CCD) model and Pearson's correlation coefficient to compare the synergies between organic and conventional farming systems. Regression analysis and the co-effect gradation index were used to investigate the relationship between system synergy and gross ecosystem product values. Additionally, the random forest method was applied to identify factors dominating the synergies of the WEFE nexus, providing strategic directions for system optimization.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results show that the sustainable development index and the degree of coordination of the organic tea farming system were 72.41 % and 53.40 % higher, respectively, than those of the conventional tea farming system. Hence, the organic tea farming system displayed clear advantages in terms of enhancing its synergy related to sustainability. Furthermore, the synergies of WEFE nexus were significantly positively correlated with the gross ecosystem product values (GEPV), and a 0.1 enhancement in the CCD of the organic farming is associated with an increase of approximately 4130 CNY of GEPV, which is 2.6 times the marginal benefit of conventional farming. We also find that the ecology and energy subsystems play dominant roles in influencing synergy, and thus improving ecosystem services and energy efficiency can be seen as key strategies for promoting multidimensional coordination.</div></div><div><h3>SIGNIFICANCE</h3><div>This study demonstrates the feasibility of applying the nexus concept to sustainable development in agriculture, illustrating the potential of organic farming for coordinated growth and the substantial benefits that can generated through synergistic optimization of integrated systems. Therefore, enhancing synergies of WEFE nexus can offer valuable insights for advancing the sustainable development of agricultural systems.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104247"},"PeriodicalIF":6.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stories, simulations and narratives: Collaboratively exploring food security and agricultural innovation in sub-Saharan Africa","authors":"Udita Sanga ,&nbsp;Maja Schlüter","doi":"10.1016/j.agsy.2024.104241","DOIUrl":"10.1016/j.agsy.2024.104241","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;CONTEXT&lt;/h3&gt;&lt;div&gt;Food insecurity remains a global challenge, with differing narratives shaping interventions in sub-Saharan Africa. The “crisis narrative,” favored by aid agencies, links insecurity to production issues, advocating agricultural innovations. Meanwhile, the “chronic poverty narrative,” reflected in African policy, ties insecurity to farmer poverty, emphasizing livelihood and economic solutions. Narrative subjectivity can lead to uncritical privileging of certain understandings and solutions, necessitating a critical exploration of contexts, causes, and solutions to food insecurity in the region. Our research addresses the need to understand and illustrate the complex problem of food insecurity in the region.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;This study employs a mixed-method approach, combining collaborative storytelling, model exploration, and scenario analysis, to investigate food security, agricultural innovation, and climate adaptation in Mali, West Africa.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;We developed a three-stage methodology represented as a story arc: beginning (exposition and problem statement), development (action), and completion (solution), providing a cohesive narrative framework. The arc unfolds with the story exposition introducing characters, plot, and problem statement. The story development includes participant-led model simulations and modeler-led scenario analysis. The story completion integrates insights from model simulations and scenario analysis to develop the collective understanding of the narratives surrounding food (in)security.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS AND CONCLUSIONS&lt;/h3&gt;&lt;div&gt;This study generates several insights that highlight the inherent complexities within agricultural innovation systems that emerge from the non-linear dynamic interaction of actors operating across scales that contribute to food insecurity. We redirect the focus of narratives of causes (and subsequent solutions) of food insecurity from solely climate-driven production losses and poverty to the complex interplay of climate, agroecology, innovation networks, risk perception, innovation beliefs, desires, and knowledge transmission. A shared narrative emerges, characterizing food security as a complex adaptive system influenced by factors such as climate-induced production variability, agroecological heterogeneity, network structures and climate risk perception. The study underscores the methodological value of collaborative storytelling and model simulation to enable a structured and reflective exploration of these complex systems. By transforming participants into co-creators of knowledge, this methodology fosters systems thinking, turning abstract systemic relationships into tangible, actionable insights.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;SIGNIFICANCE&lt;/h3&gt;&lt;div&gt;Our study demonstrates the need to critically reevaluate the role of narratives in shaping agricultural innovation systems and their capacity to transform food systems t","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104241"},"PeriodicalIF":6.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143182407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental effects of improved regional nitrogen cycling in crop-livestock systems – A generic modelling approach","authors":"W.J. Vonk ,&nbsp;A.G.T. Schut ,&nbsp;M.K. van Ittersum ,&nbsp;M. Grillot ,&nbsp;C.F.E. Topp ,&nbsp;R. Hendriks ,&nbsp;R. Hijbeek","doi":"10.1016/j.agsy.2024.104244","DOIUrl":"10.1016/j.agsy.2024.104244","url":null,"abstract":"<div><h3>CONTEXT</h3><div>More nutrient cycling may be achieved by using less external inputs (feed, fertilisers) and reduce losses to the environment, especially in intensive farming systems. Yet, changes in on-farm management may have unintended consequences at higher aggregation scales due to potential trade-offs.</div></div><div><h3>OBJECTIVE</h3><div>The objective of this study was to develop a multi-indicator and multi-level model which operates at farm and regional level to evaluate scenarios for improved nitrogen cycling.</div></div><div><h3>METHODS</h3><div>A new model, based on nitrogen flow analysis, was used to compare five scenarios with the current situation as reference. The model was applied to a case study region, the Dutch province Drenthe including typical arable, pig, poultry, and dairy farms. In the scenarios, the proportion of manure digested for biogas production, and imported amounts of synthetic fertiliser and feed into the region were varied, as single measures or in combination.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Modelling results showed that digestion of manure for biogas production reduced total regional nitrogen losses and produced renewable energy. A 20 % decrease in synthetic nitrogen fertiliser application reduced crop yields only slightly and improved the regional nitrogen use efficiency and nitrogen cycling, as manure availability in Drenthe was sufficient to meet a large proportion of the total crop nutrient requirements. Combining multiple measures was most effective in increasing nitrogen cycling (+65 %), leading to reduced greenhouse gas emissions (−49 %) and an improved net energy balance (+84 %) from agriculture in Drenthe, with the largest contribution coming from restricting feed import (resulting in a reduction of the total livestock herd in the region). However, when livestock was reduced, more synthetic nitrogen fertiliser was needed to maintain crop yields.</div><div>Our study also highlighted trade-offs: positive effects on nitrogen cycling, greenhouse gas emissions and nitrogen losses coincided with reduced food production and organic matter inputs to soils, with consequences for carbon stocks. Furthermore, results for the whole region were not always representative for each farm type.</div></div><div><h3>SIGNIFICANCE</h3><div>The results demonstrate that our systems approach, quantifying multiple indicators simultaneously at farm and region level, can provide a better understanding of benefits and trade-offs when aiming for an agricultural system which is productive, but with reduced emissions to the environment. The developed model is generic and can be applied to evaluate alternative nitrogen cycling scenarios in other European regions with only little parameterisation needed from publicly available data.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104244"},"PeriodicalIF":6.1,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review of APSIM's soil nitrogen modelling capability for agricultural systems analyses","authors":"Kirsten Verburg ,&nbsp;Heather R. Pasley ,&nbsp;Jody S. Biggs ,&nbsp;Iris Vogeler ,&nbsp;Enli Wang ,&nbsp;Henrike Mielenz ,&nbsp;Val O. Snow ,&nbsp;Chris J. Smith ,&nbsp;Chiara Pasut ,&nbsp;Andrea D. Basche ,&nbsp;Di He ,&nbsp;Sotirios V. Archontoulis ,&nbsp;Donald S. Gaydon ,&nbsp;Neil I. Huth ,&nbsp;Dean P. Holzworth ,&nbsp;Joanna M. Sharp ,&nbsp;Rogerio Cichota ,&nbsp;Edith N. Khaembah ,&nbsp;Edmar I. Teixeira ,&nbsp;Hamish E. Brown ,&nbsp;Peter J. Thorburn","doi":"10.1016/j.agsy.2024.104213","DOIUrl":"10.1016/j.agsy.2024.104213","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Over the last 26 years, researchers globally have successfully applied the soil nitrogen (N) model in the Agricultural Production Systems sIMulator (APSIM) to simulate N cycling and its effects on crop production across a range of agricultural systems and environments. As the modelling community further expands its focus to include environmental impacts of farming, it needs the model to be fit for this broader purpose.</div></div><div><h3>OBJECTIVE</h3><div>Accurately modelling N loss via different pathways demands more of the model and so, to inform and prioritise future development needs, we embarked on a detailed review of APSIM's soil N modelling capability.</div></div><div><h3>METHODS</h3><div>We conducted a comprehensive search of APSIM Soil N model verification studies and found 131 relevant publications across a wide range of systems, applications, and processes. We examined their approaches and findings, and distilled out the lessons learnt.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The model-data comparisons showed strong performance across all modelled processes, despite limited changes to the core of the soil N model since its inception. The model's relatively simple conceptual pool approach to modelling carbon (C) dynamics with N cycling linked via C:N ratios, has proven remarkably versatile. However, these conceptual pools have posed challenges relating to initialisation methods and the resulting sensitivity of predictions at different time scales, e.g. long-term C trajectories vs. short-term seasonal N dynamics. Correctly predicting timing of N loss on a daily timestep also proved challenging, but this level of resolution may not always be required. APSIM's adaptable code structure facilitated the creation of model prototypes (e.g., ammonia volatilisation and N in runoff) allowing testing of different conceptualisations ahead of formal release.</div></div><div><h3>SIGNIFICANCE</h3><div>APSIM is one of the most widely used agricultural systems models. This review, which covers model documentation, model-data comparisons, various approaches to parameterisation, and prototypes for additional processes, consolidates decades of research into insights about the model and its functioning. The review highlights the importance of model evaluations across a wide range of applications to ensure model robustness, to identify issues that may be masked in single studies, and to allow the emergence of solutions with broad applicability.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"224 ","pages":"Article 104213"},"PeriodicalIF":6.1,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143182552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}