Crop production in the food basket of South Asia faces serious challenges of the water table and environmental sustainability driving to future food insecurity. Thus, the conventional rice-wheat (CTRW) system practices are no more sustainable in South Asia.
OBJECTIVE
To design and develop alternative, optimal crop management options and assess their scalability through comprehensive system optimization practices (SOP), ensuring high productivity and profitability with lower environmental footprints along with potential for carbon credit generation.
METHODS
Field experiments were conducted at the four locations of farmer's fields in Karnal districts of Haryana, India. We evaluated SOP with CTR-zero-tillage (ZT) wheat-mungbean (CTR-ZTWMb) and direct seeded rice-ZT wheat-mungbean (DSR-ZTWMb) and triple ZT (raised bed) systems of maize-wheat-mungbean (ZTMWMb), maize-mustard-mungbean and soybean-wheat-mungbean (ZTSWMb).
RESULTS AND CONCLUSIONS
The system productivity enhanced by 26.4–29.2 and 26.9–36.9 % with enhanced net returns of 483–553 and 847–1006 US$/ha in rice-based and diversified (ZTMWMb, ZTMMuMb, and ZTSWMb) SOP, respectively over conventional rice-wheat system (CTRW). The diversified SOP had significantly lesser water use by 1023 to 1102 ha-mm with reduced global warming potential (GWP) by 4611–5100 kg CO2 eq./ha (∼5 carbon credit) over CTRW. Based on our study, the adoption of diversified SOP on 0.1 m ha and CTR-ZTWMb on 1.7 m ha can produce additional 0.27–1.23 m t alternate crops with additional net revenue of 906–921 million US$/year and reduction of the GWP by 564–603 million kg CO2 eq./year over CTRW. Additionally, the non-renewable energy saving from one ha of diversified SOP could help in CTR-ZTWMb adoption on 42–56 ha over CTRW. The on-farm study evidenced that crop production with system optimization practices of legume inclusion and zero tillage could be scaled up in the non-basmati conventional rice-wheat system to achieve higher productivity and profitability as well as environmental stewardship in the North-Western Indo-Gangetic Plains and similar agro-ecologies.
SIGNIFICANCE
The system optimization practices adoption in conventional rice-wheat system of North-Western Indo-Gangetic plains could help in enhancing farm profitability and lowering environmental footprint with generation of 5–6 carbon credit.
{"title":"System optimization practices for profitable and agro-ecologically sustainable agriculture in North-Western Indo-Gangetic Plains","authors":"Radheshyam , Shankar Lal Jat , Mangi Lal Jat , Hanuman Sahay Jat , Aditya Kumar Singh , Deep Mohan Mahala , Chiter Mal Parihar , Rajbir Singh , Deepak Bijarniya , Kailash Chandra Kalvaniya , Smruti Ranjan Padhan","doi":"10.1016/j.agsy.2025.104579","DOIUrl":"10.1016/j.agsy.2025.104579","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Crop production in the food basket of South Asia faces serious challenges of the water table and environmental sustainability driving to future food insecurity. Thus, the conventional rice-wheat (CTRW) system practices are no more sustainable in South Asia.</div></div><div><h3>OBJECTIVE</h3><div>To design and develop alternative, optimal crop management options and assess their scalability through comprehensive system optimization practices (SOP), ensuring high productivity and profitability with lower environmental footprints along with potential for carbon credit generation.</div></div><div><h3>METHODS</h3><div>Field experiments were conducted at the four locations of farmer's fields in Karnal districts of Haryana, India. We evaluated SOP with CTR-zero-tillage (ZT) wheat-mungbean (CTR-ZTWMb) and direct seeded rice-ZT wheat-mungbean (DSR-ZTWMb) and triple ZT (raised bed) systems of maize-wheat-mungbean (ZTMWMb), maize-mustard-mungbean and soybean-wheat-mungbean (ZTSWMb).</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The system productivity enhanced by 26.4–29.2 and 26.9–36.9 % with enhanced net returns of 483–553 and 847–1006 US$/ha in rice-based and diversified (ZTMWMb, ZTMMuMb, and ZTSWMb) SOP, respectively over conventional rice-wheat system (CTRW). The diversified SOP had significantly lesser water use by 1023 to 1102 ha-mm with reduced global warming potential (GWP) by 4611–5100 kg CO2 eq./ha (∼5 carbon credit) over CTRW. Based on our study, the adoption of diversified SOP on 0.1 m ha and CTR-ZTWMb on 1.7 m ha can produce additional 0.27–1.23 m t alternate crops with additional net revenue of 906–921 million US$/year and reduction of the GWP by 564–603 million kg CO<sub>2</sub> eq./year over CTRW. Additionally, the non-renewable energy saving from one ha of diversified SOP could help in CTR-ZTWMb adoption on 42–56 ha over CTRW. The on-farm study evidenced that crop production with system optimization practices of legume inclusion and zero tillage could be scaled up in the non-basmati conventional rice-wheat system to achieve higher productivity and profitability as well as environmental stewardship in the North-Western Indo-Gangetic Plains and similar agro-ecologies.</div></div><div><h3>SIGNIFICANCE</h3><div>The system optimization practices adoption in conventional rice-wheat system of North-Western Indo-Gangetic plains could help in enhancing farm profitability and lowering environmental footprint with generation of 5–6 carbon credit.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104579"},"PeriodicalIF":6.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621990","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}
<div><h3>CONTEXT</h3><div>Pakistan's agricultural system, ranked among the world's most water-stressed, demonstrates a critical resource utilization challenge. Despite a 21.8 % expansion in harvested area since 1991 and consuming 90 % of national freshwater resources, wheat productivity remains stagnant at half the global average. This disconnect between input use and output is further exacerbated by 50 % groundwater over-extraction, declining irrigation efficiency, and increasing reliance on chemical inputs. Collectively, these trends reveal the systemic fragility of input-driven growth and underscore the urgent need for an integrated water-energy-food (WEF) nexus approach to reconcile productivity with sustainability.</div></div><div><h3>OBJECTIVE</h3><div>This study has three key objectives: (1) quantify dynamic relationships between five critical agricultural inputs and productivity, (2) project sustainability thresholds under current practices, and (3) develop transferable optimization frameworks for water-scarce agricultural systems.</div></div><div><h3>METHODS</h3><div>We employ Autoregressive Distributed Lag (ARDL) cointegration analysis to examine long-term relationships and short-term dynamics between annual agricultural productivity (AAP) and five key inputs: agricultural water withdrawal (AWW), energy utilization (TEU), cultivated land area (THA), pesticide use (TPU), and fertilizer use (TFU) over a 30-year peroids (1991–2021). Additionally, Autoregressive Integrated Moving Average (ARIMA) forecasting models were employed to project future scenarios (2022−2031) for both inputs and AAP. The approach validates cointegration through rigorous diagnostic testing (ADF/PP, CUSUM), ensuring robust model performance for forecasting productivity (AAP) under varying input scenarios.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings reveal unsustainable input trajectories: a projected 15.1 % increase in productivity by 2031 would require continued expansion of land (+21.8 % compared with 1991), pesticide use (+82.25 %) and fertilizer application (+19 %). Meanwhile agricultural water (−4.22 %) and energy availability (−6.15 %) are declining, highlighting that these critical resources are becoming increasingly limited. This combination of rising input demands and decreasing essential resources highlights the urgent need for policy interventions such as precision irrigation, integrated nutrient management, and pesticide regulation to avoid ecological collapse.</div></div><div><h3>SIGNIFICANCE</h3><div>This research provides the first quantitative framework demonstrating the infeasibility of area-expansion strategies in Pakistan's agriculture. The findings call for immediate policy shifts toward precision irrigation, renewable energy integration, regulated agrochemical use and strengthened institutional coordination across water, energy, and agricultural sectors. The proposed WEF nexus framework offers scalable, evidence-based solutio
{"title":"Optimizing the water-energy-food Nexus for sustainable agriculture in Pakistan: A systems analysis with global implications","authors":"Hassan Iqbal , Chen Yaning , Syed Turab Raza , Sona Karim","doi":"10.1016/j.agsy.2025.104572","DOIUrl":"10.1016/j.agsy.2025.104572","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Pakistan's agricultural system, ranked among the world's most water-stressed, demonstrates a critical resource utilization challenge. Despite a 21.8 % expansion in harvested area since 1991 and consuming 90 % of national freshwater resources, wheat productivity remains stagnant at half the global average. This disconnect between input use and output is further exacerbated by 50 % groundwater over-extraction, declining irrigation efficiency, and increasing reliance on chemical inputs. Collectively, these trends reveal the systemic fragility of input-driven growth and underscore the urgent need for an integrated water-energy-food (WEF) nexus approach to reconcile productivity with sustainability.</div></div><div><h3>OBJECTIVE</h3><div>This study has three key objectives: (1) quantify dynamic relationships between five critical agricultural inputs and productivity, (2) project sustainability thresholds under current practices, and (3) develop transferable optimization frameworks for water-scarce agricultural systems.</div></div><div><h3>METHODS</h3><div>We employ Autoregressive Distributed Lag (ARDL) cointegration analysis to examine long-term relationships and short-term dynamics between annual agricultural productivity (AAP) and five key inputs: agricultural water withdrawal (AWW), energy utilization (TEU), cultivated land area (THA), pesticide use (TPU), and fertilizer use (TFU) over a 30-year peroids (1991–2021). Additionally, Autoregressive Integrated Moving Average (ARIMA) forecasting models were employed to project future scenarios (2022−2031) for both inputs and AAP. The approach validates cointegration through rigorous diagnostic testing (ADF/PP, CUSUM), ensuring robust model performance for forecasting productivity (AAP) under varying input scenarios.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The findings reveal unsustainable input trajectories: a projected 15.1 % increase in productivity by 2031 would require continued expansion of land (+21.8 % compared with 1991), pesticide use (+82.25 %) and fertilizer application (+19 %). Meanwhile agricultural water (−4.22 %) and energy availability (−6.15 %) are declining, highlighting that these critical resources are becoming increasingly limited. This combination of rising input demands and decreasing essential resources highlights the urgent need for policy interventions such as precision irrigation, integrated nutrient management, and pesticide regulation to avoid ecological collapse.</div></div><div><h3>SIGNIFICANCE</h3><div>This research provides the first quantitative framework demonstrating the infeasibility of area-expansion strategies in Pakistan's agriculture. The findings call for immediate policy shifts toward precision irrigation, renewable energy integration, regulated agrochemical use and strengthened institutional coordination across water, energy, and agricultural sectors. The proposed WEF nexus framework offers scalable, evidence-based solutio","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104572"},"PeriodicalIF":6.1,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567421","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}
Pub Date : 2025-11-21DOI: 10.1016/j.agsy.2025.104576
Xinlin Li , Zezhu Wei , Jianhang Cui , Ruoyan Yao , Puyu Feng , De Li Liu , Chengcheng Yuan , Yong Chen
CONTEXT
Climate warming and elevated atmospheric CO₂ concentrations, coupled with an ongoing transition from double-cropping rice systems (DCRS) to single-cropping rice systems (SCRS), are reshaping yield and hydrological processes in the subtropical monsoon regions of southern China. These concurrent shifts intensify the tension between yield stability and water sustainability under future climate scenarios.
OBJECTIVE
This study aims to evaluate the differential responses of DCRS and SCRS to future climate change, with a particular focus on rice yield and hydrological dynamics, in order to identify resilient cropping strategies under warming and CO₂ enrichment.
METHODS
An integrated modeling framework was developed for the Zishui River Basin (ZRB), a representative DCRS region in southern China. This framework combined high-resolution paddy field mapping, an enhanced Soil and Water Assessment Tool (SWAT) incorporating dynamic CO₂ response mechanisms, and multi-scenario climate projections from Coupled Model Intercomparison Project (CMIP6). Simulations were conducted under three Shared Socioeconomic Pathways (SSP) scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5) for the periods 2041–2070 and 2071–2100.
RESULTS AND CONCLUSIONS
Under SSP5–8.5 by the end of the century, the SCRS exhibited up to 29.9 % yield loss, primarily due to heat-induced phenological shortening. In contrast, the DCRS demonstrated greater climate resilience: early rice consistently benefited from elevated CO₂ and increased thermal accumulation, resulting in robust gains in yield, while late rice, though more heat-sensitive, maintained stable productivity under moderate warming. Overall, the DCRS outperformed the SCRS, highlighting its systemic advantage in balancing water inputs with grain production.
SIGNIFICANCE
These findings emphasize the importance of embedding climate resilience into future rice production systems. Promoting double-cropping practices presents a viable adaptation pathway to enhance regional food–water sustainability under climate change.
{"title":"Future climate resilience in rice systems of southern China: Double-cropping outperforms single-cropping in water-food sustainability","authors":"Xinlin Li , Zezhu Wei , Jianhang Cui , Ruoyan Yao , Puyu Feng , De Li Liu , Chengcheng Yuan , Yong Chen","doi":"10.1016/j.agsy.2025.104576","DOIUrl":"10.1016/j.agsy.2025.104576","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Climate warming and elevated atmospheric CO₂ concentrations, coupled with an ongoing transition from double-cropping rice systems (DCRS) to single-cropping rice systems (SCRS), are reshaping yield and hydrological processes in the subtropical monsoon regions of southern China. These concurrent shifts intensify the tension between yield stability and water sustainability under future climate scenarios.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to evaluate the differential responses of DCRS and SCRS to future climate change, with a particular focus on rice yield and hydrological dynamics, in order to identify resilient cropping strategies under warming and CO₂ enrichment.</div></div><div><h3>METHODS</h3><div>An integrated modeling framework was developed for the Zishui River Basin (ZRB), a representative DCRS region in southern China. This framework combined high-resolution paddy field mapping, an enhanced Soil and Water Assessment Tool (SWAT) incorporating dynamic CO₂ response mechanisms, and multi-scenario climate projections from Coupled Model Intercomparison Project (CMIP6). Simulations were conducted under three Shared Socioeconomic Pathways (SSP) scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5) for the periods 2041–2070 and 2071–2100.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Under SSP5–8.5 by the end of the century, the SCRS exhibited up to 29.9 % yield loss, primarily due to heat-induced phenological shortening. In contrast, the DCRS demonstrated greater climate resilience: early rice consistently benefited from elevated CO₂ and increased thermal accumulation, resulting in robust gains in yield, while late rice, though more heat-sensitive, maintained stable productivity under moderate warming. Overall, the DCRS outperformed the SCRS, highlighting its systemic advantage in balancing water inputs with grain production.</div></div><div><h3>SIGNIFICANCE</h3><div>These findings emphasize the importance of embedding climate resilience into future rice production systems. Promoting double-cropping practices presents a viable adaptation pathway to enhance regional food–water sustainability under climate change.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104576"},"PeriodicalIF":6.1,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560041","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}
Pub Date : 2025-11-21DOI: 10.1016/j.agsy.2025.104567
Kexin Li , Yanan Jiang , Ang Li , Xiangzhe Tian , Jiatong Lu , Tingting Wei , Jiangfeng Xiangli , Xifeng Huang , Yongmin Li , Shikun Sun
CONTEXT
The imbalance between crop water demand and supply often exerts negative impacts on local agricultural development in climate variability sensitive areas with increasing extreme weather conditions. Optimizing irrigation strategies is essential for alleviating irrigation water scarcity and promoting sustainable agriculture.
OBJECTIVE
The main objective of this work is to propose an Integrated Meteorological Adaptive Simulation-Optimization (IMASO) framework for crop irrigation strategies, enabling within-season real-time optimization of irrigation strategies and leveraging perfect weather forecasts to enhance irrigation guidance and maximize irrigation water productivity (IWP).
METHODS
The (IMASO) framework combines both short (5 days) -and medium (15 days) - term perfect weather forecast with Dynamic Time Warping (DTW) algorithm, AquaCrop-OSPy model, and NSGA-III multi-objective optimization algorithm (with a population size of 200, 150 generations) for the first time. This work focuses on winter wheat, the crop model was calibrated and validated using experimental data. Four different maximum single irrigation amounts were considered, and an optimal fixed irrigation strategy was developed by optimizing for maximum average yield, minimum irrigation water use, and highest water productivity over multiple years, serving as the baseline scenario. The IMASO framework was applied during a typical growing season to assess real-time optimization performance.
RESULTS AND CONCLUSIONS
Results show that incorporating short-term perfect weather forecasts can delay or reduce irrigation events. Considering medium-term perfect weather forecasts for real-time dynamic optimization of irrigation strategies allowed better adaptation to current seasonal conditions. The IMASO framework significantly reduced irrigation water use (by 26 %–57 %) while simultaneously maintaining crop yield. IWP improvements across different maximum single irrigation amounts ranged from 0.19 to 0.66 kg/m3.
SIGNIFICANCE
The IMASO framework enables within-season real-time optimization of irrigation strategies by dynamically adapting to weather changes. Ensuring efficient water use while maintaining agricultural productivity.
{"title":"An integrated meteorological adaptive simulation-optimization framework for real-time irrigation scheduling considering perfect weather forecasts","authors":"Kexin Li , Yanan Jiang , Ang Li , Xiangzhe Tian , Jiatong Lu , Tingting Wei , Jiangfeng Xiangli , Xifeng Huang , Yongmin Li , Shikun Sun","doi":"10.1016/j.agsy.2025.104567","DOIUrl":"10.1016/j.agsy.2025.104567","url":null,"abstract":"<div><h3>CONTEXT</h3><div>The imbalance between crop water demand and supply often exerts negative impacts on local agricultural development in climate variability sensitive areas with increasing extreme weather conditions. Optimizing irrigation strategies is essential for alleviating irrigation water scarcity and promoting sustainable agriculture.</div></div><div><h3>OBJECTIVE</h3><div>The main objective of this work is to propose an Integrated Meteorological Adaptive Simulation-Optimization (IMASO) framework for crop irrigation strategies, enabling within-season real-time optimization of irrigation strategies and leveraging perfect weather forecasts to enhance irrigation guidance and maximize irrigation water productivity (IWP).</div></div><div><h3>METHODS</h3><div>The (IMASO) framework combines both short (5 days) -and medium (15 days) - term perfect weather forecast with Dynamic Time Warping (DTW) algorithm, AquaCrop-OSPy model, and NSGA-III multi-objective optimization algorithm (with a population size of 200, 150 generations) for the first time. This work focuses on winter wheat, the crop model was calibrated and validated using experimental data. Four different maximum single irrigation amounts were considered, and an optimal fixed irrigation strategy was developed by optimizing for maximum average yield, minimum irrigation water use, and highest water productivity over multiple years, serving as the baseline scenario. The IMASO framework was applied during a typical growing season to assess real-time optimization performance.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Results show that incorporating short-term perfect weather forecasts can delay or reduce irrigation events. Considering medium-term perfect weather forecasts for real-time dynamic optimization of irrigation strategies allowed better adaptation to current seasonal conditions. The IMASO framework significantly reduced irrigation water use (by 26 %–57 %) while simultaneously maintaining crop yield. IWP improvements across different maximum single irrigation amounts ranged from 0.19 to 0.66 kg/m<sup>3</sup>.</div></div><div><h3>SIGNIFICANCE</h3><div>The IMASO framework enables within-season real-time optimization of irrigation strategies by dynamically adapting to weather changes. Ensuring efficient water use while maintaining agricultural productivity.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104567"},"PeriodicalIF":6.1,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145567437","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}
Pub Date : 2025-11-19DOI: 10.1016/j.agsy.2025.104569
Ismail I. Garba , Wolfram Buss , Enli Wang , Cathryn A. O’Sullivan , Vadakattu V.S.R. Gupta , Alison R. Bentley , Kirsten Verburg
CONTEXT
Retaining nitrogen (N) in soils in the form of ammonium (NH4+) by inhibiting nitrification has been proposed as a strategy to reduce N gaseous losses and nitrate (NO3-) leaching. Biological nitrification inhibition (BNI) involves the release of natural metabolites from crop roots that suppress nitrifying microbes. Unlike synthetic nitrification inhibitors BNIs act directly in the rhizosphere and may provide a more spatially and temporally sustained inhibition. Because BNI effectiveness depends on crop species, and interactions with biophysical factors, a systems modelling approach is needed to assess its plausible benefits in cropping systems.
OBJECTIVE
(1) develop a BNI model suitable for integration into systems models, enabling simulation of BNI release, fate, and bioactivity within cropping systems, and (2) use the model in-silico to illustrate how system interactions influence BNI impacts.
METHODS
A BNI subroutine was developed and integrated into the Agricultural Production Systems sIMulator (APSIM) Next Generation to model BNI exudation, bioactivity, fate, and persistence in soil. Simulations for wheat, canola and sorghum were conducted to assess its plausible effects on N cycling and crop productivity.
RESULTS AND CONCLUSIONS
Four prerequisite conditions under which within-season plausible N loss and yield benefits may be realized from BNI: (i) adequate root growth and BNI release achieving effective bioactivity, (ii) BNI persistence with slow degradation at most 50% daily degradation to ensure longevity of inhibition, (iii) the crop being able to take up N in both NH4+ and NO3- forms ensuring that ‘saved N’ is assimilated and (iv) occurrence of N loss events when BNI is active. When these conditions co-occurred, simulated systems showed decreased N loss, and/or yield responses.
SIGNIFICANCE
The integrated APSIM-BNI framework provides a tool for exploring where and when BNI may deliver agronomic and environmental benefits and guiding future field experiment and trait improvement efforts.
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Pub Date : 2025-11-19DOI: 10.1016/j.agsy.2025.104573
Lanping Tang , Peter H. Verburg , Xinli Ke , Chengcheng Wang , Shaohua Wu , Wuyan Li , Jinxia Zhu
<div><h3>CONTEXT</h3><div>Global food security remains a pressing concern, with rising undernourishment rates exacerbated by urbanization, climate change, and soil degradation. Understanding the dynamics of cropland systems is therefore crucial for enhancing grain production, particularly in countries like China, which supports a significant portion of the world's population with limited cropland resources.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to analyze spatial variability in cropland intensification at the prefectural scale in China from 1980 to 2018. It further reveals the spatial-temporal changes of the cropland management systems by combining cropland-use intensity and spatial variability in cropland intensification. This focuses on the relationship between changes in cropland area and intensification and evaluates their relative contributions to grain production.</div></div><div><h3>METHODS</h3><div>A K-means clustering algorithm was adopted to identify distinct cropland management systems. The LMDI (Logarithmic Mean Divisia Index) method was applied to quantify the contribution of changes in cropland area and intensification to grain production.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results indicate a sharp rise in agricultural input intensity, particularly pesticide and fertilizer, alongside a notable decline in time investment by laborers. Six distinct cropland management systems were identified, with Type 1 and Type 3 being the most prevalent. Type 1, predominantly observed in the northeast and northwest, exhibited low initial intensity with a slight input growth and a minor time investment decrease. Type 3, concentrated in the south, demonstrated stable input increases accompanied by a moderate drop in time investment. Furthermore, expansion of cropland area and intensification co-occur in 58 % of the prefectures. Intensification drove 79 % of grain production growth, yet with clear spatial disparities: large gains in northeastern and central prefectures contrasted with declines in southeastern coastal areas due to cropland loss. The study underscores the pivotal role of cropland intensification in enhancing grain production. These findings advocate for targeted, region-specific strategies to support sustainable intensification and labor-saving technologies, thereby ensuring long-term food security amid urbanization and rising labor costs.</div></div><div><h3>SIGNIFICANCES</h3><div>This study offers a novel, long-term analysis of cropland system dynamics in China—integrating cropland intensification and area changes—at a fine spatial scale and examines their collective impact on grain production. The study not only helps to understand that production can be increased through area expansion or intensification, but also to understand which pathway dominates where, to what degree, and in what combination. The study provides critical insights for policymakers and stakeholders, contributing to the discou
{"title":"Spatio-temporal changes in cropland system and its impacts on grain production in China","authors":"Lanping Tang , Peter H. Verburg , Xinli Ke , Chengcheng Wang , Shaohua Wu , Wuyan Li , Jinxia Zhu","doi":"10.1016/j.agsy.2025.104573","DOIUrl":"10.1016/j.agsy.2025.104573","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Global food security remains a pressing concern, with rising undernourishment rates exacerbated by urbanization, climate change, and soil degradation. Understanding the dynamics of cropland systems is therefore crucial for enhancing grain production, particularly in countries like China, which supports a significant portion of the world's population with limited cropland resources.</div></div><div><h3>OBJECTIVE</h3><div>This study aims to analyze spatial variability in cropland intensification at the prefectural scale in China from 1980 to 2018. It further reveals the spatial-temporal changes of the cropland management systems by combining cropland-use intensity and spatial variability in cropland intensification. This focuses on the relationship between changes in cropland area and intensification and evaluates their relative contributions to grain production.</div></div><div><h3>METHODS</h3><div>A K-means clustering algorithm was adopted to identify distinct cropland management systems. The LMDI (Logarithmic Mean Divisia Index) method was applied to quantify the contribution of changes in cropland area and intensification to grain production.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>The results indicate a sharp rise in agricultural input intensity, particularly pesticide and fertilizer, alongside a notable decline in time investment by laborers. Six distinct cropland management systems were identified, with Type 1 and Type 3 being the most prevalent. Type 1, predominantly observed in the northeast and northwest, exhibited low initial intensity with a slight input growth and a minor time investment decrease. Type 3, concentrated in the south, demonstrated stable input increases accompanied by a moderate drop in time investment. Furthermore, expansion of cropland area and intensification co-occur in 58 % of the prefectures. Intensification drove 79 % of grain production growth, yet with clear spatial disparities: large gains in northeastern and central prefectures contrasted with declines in southeastern coastal areas due to cropland loss. The study underscores the pivotal role of cropland intensification in enhancing grain production. These findings advocate for targeted, region-specific strategies to support sustainable intensification and labor-saving technologies, thereby ensuring long-term food security amid urbanization and rising labor costs.</div></div><div><h3>SIGNIFICANCES</h3><div>This study offers a novel, long-term analysis of cropland system dynamics in China—integrating cropland intensification and area changes—at a fine spatial scale and examines their collective impact on grain production. The study not only helps to understand that production can be increased through area expansion or intensification, but also to understand which pathway dominates where, to what degree, and in what combination. The study provides critical insights for policymakers and stakeholders, contributing to the discou","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104573"},"PeriodicalIF":6.1,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578129","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}
Pub Date : 2025-11-19DOI: 10.1016/j.agsy.2025.104566
Mina Devkota , Krishna Prasad Devkota , Mohie El Din Omar , Samar Attaher , Ajit Govind , Vinay Nangia
CONTEXT
Wheat (Triticum aestivum) is Egypt's staple crop, crucial for national food security. However, the country remains heavily reliant on imports to meet domestic demand. Enhancing production sustainably requires a systematic assessment of attainable yield and profit gaps along with the identification of key factors driving.
OBJECTIVES
This study aims to identify major determinants of wheat yield and profit gaps across different governorates in New and Old Lands; to develop context-specific integrated agronomic solutions for sustainably closing these gaps while reducing environmental footprints.
MATERIALS AND METHODS
We used random field survey samples of 2042 individual wheat fields across 23 wheat-growing governorates covering New and Old Lands during 2021/2022 growing season. Based on crop yield, farmers were categorized into three groups, and attainable yield and profit gaps were calculated from difference between mean yield of top 10th decile and average farmers' yield. Random Forest model is used to analyze data and identify major factors affecting yield, profit, and nitrogen use efficiency (NUE). Sustainability of wheat production was assessed using various indicators. Comparative analyses were conducted to evaluate differences in yield, input use efficiency, and profitability between Old and New Land, as well as across different yield gap categories.
RESULTS AND DISCUSSION
Analysis revealed significant yield and profit gaps between average and high-yielding farmers in both Old and New Lands. In Old Land, high-yield farmers (10th decile) achieved average yields of 8.4 t ha−1 and net profits of US$1097 ha−1, compared with 6.5 t ha−1 and US$675 ha−1 for medium-yield farmers. In the New Lands, the yield gap was more pronounced, with high-yield farmers achieving average yields of 7.5 t ha−1 compared to 4.63 t ha−1 for medium-yield farmers, highlighting a significant opportunity to increase productivity. Determinants for yield and profit varied across governorates, indicating need for governorate-specific strategies to sustainably close yield and profit gaps. Water productivity, NUE, and labor productivity were notably lower, while production cost showed no strong correlation with yield and was negatively correlated with greenhouse gas emission intensity (GHGI). Raised bed planting improved NUE by 29 %, increased water productivity by 18 %, and reduced GHGI by 15 % compared with conventional flat planting.
SIGNIFICANCE
Adopting context-specific agronomic practices that combine integrated-fertilization, efficient irrigation, suitable varieties, and raised-bed planting can enhance agronomic gains while reducing environmental footprints. When tailored to local yield-limiting factors, these solutions provide a sustainable pathway to narrow
小麦（Triticum aestivum）是埃及的主要作物，对国家粮食安全至关重要。然而，该国仍然严重依赖进口来满足国内需求。可持续地提高生产需要系统地评估可实现的产量和利润差距，并确定关键驱动因素。本研究旨在确定新旧土地不同省份小麦产量和利润差距的主要决定因素；制定针对具体情况的综合农艺解决方案，以可持续地缩小这些差距，同时减少环境足迹。材料与方法在2021/2022年小麦生长季，我们对23个小麦种植省份的2042块单独的麦田进行了随机调查。根据作物产量将农户分为三类，通过前十分之一农户平均产量与农户平均产量之差计算可得产量和利润差距。采用随机森林模型对数据进行分析，找出影响产量、利润和氮素利用效率的主要因素。利用各种指标对小麦生产的可持续性进行了评价。通过比较分析，评价了新旧土地之间以及不同产量缺口类别之间在产量、投入物利用效率和盈利能力方面的差异。结果与讨论分析表明，在新旧土地上，平均产量和高产农民之间存在显著的产量和利润差距。在Old Land，高产农民（10十分之一）的平均产量为8.4 t hm2，净利润为1097 hm2，而中等产量农民的平均产量为6.5 t hm2，净利润为675 hm2。在新地，产量差距更为明显，高产农民的平均产量为7.5吨/公顷，而中等产量农民的平均产量为4.63吨/公顷，这表明提高生产力的机会很大。产量和利润的决定因素因省而异，这表明需要针对省的具体战略来持续缩小产量和利润差距。水分生产力、氮肥利用效率和劳动生产率显著降低，生产成本与产量的相关性不强，与温室气体排放强度呈负相关。与传统平面种植相比，垄作床种植提高了29%的氮肥利用效率，提高了18%的水分生产力，并减少了15%的温室气体排放。采用结合综合施肥、高效灌溉、适宜品种和高床种植的因地制宜的农艺措施可以提高农业效益，同时减少环境足迹。当针对当地的产量限制因素进行定制时，这些解决方案提供了一条缩小产量和利润差距的可持续途径。在有利的政策和有效的推广系统的支持下，扩大数据驱动的解决方案为加强埃及和类似干旱灌溉地区的小麦自给提供了可行的选择。
{"title":"Context-specific agronomic solutions for achieving agronomic gains with reduced environmental footprints in irrigated drylands of Egypt","authors":"Mina Devkota , Krishna Prasad Devkota , Mohie El Din Omar , Samar Attaher , Ajit Govind , Vinay Nangia","doi":"10.1016/j.agsy.2025.104566","DOIUrl":"10.1016/j.agsy.2025.104566","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Wheat (<em>Triticum aestivum</em>) is Egypt's staple crop, crucial for national food security. However, the country remains heavily reliant on imports to meet domestic demand. Enhancing production sustainably requires a systematic assessment of attainable yield and profit gaps along with the identification of key factors driving.</div></div><div><h3>OBJECTIVES</h3><div>This study aims to identify major determinants of wheat yield and profit gaps across different governorates in New and Old Lands; to develop context-specific integrated agronomic solutions for sustainably closing these gaps while reducing environmental footprints.</div></div><div><h3>MATERIALS AND METHODS</h3><div>We used random field survey samples of 2042 individual wheat fields across 23 wheat-growing governorates covering New and Old Lands during 2021/2022 growing season. Based on crop yield, farmers were categorized into three groups, and attainable yield and profit gaps were calculated from difference between mean yield of top 10th decile and average farmers' yield. Random Forest model is used to analyze data and identify major factors affecting yield, profit, and nitrogen use efficiency (NUE). Sustainability of wheat production was assessed using various indicators. Comparative analyses were conducted to evaluate differences in yield, input use efficiency, and profitability between Old and New Land, as well as across different yield gap categories.</div></div><div><h3>RESULTS AND DISCUSSION</h3><div>Analysis revealed significant yield and profit gaps between average and high-yielding farmers in both Old and New Lands. In Old Land, high-yield farmers (10th decile) achieved average yields of 8.4 t ha<sup>−1</sup> and net profits of US$1097 ha<sup>−1</sup>, compared with 6.5 t ha<sup>−1</sup> and US$675 ha<sup>−1</sup> for medium-yield farmers. In the New Lands, the yield gap was more pronounced, with high-yield farmers achieving average yields of 7.5 t ha<sup>−1</sup> compared to 4.63 t ha<sup>−1</sup> for medium-yield farmers, highlighting a significant opportunity to increase productivity. Determinants for yield and profit varied across governorates, indicating need for governorate-specific strategies to sustainably close yield and profit gaps. Water productivity, NUE, and labor productivity were notably lower, while production cost showed no strong correlation with yield and was negatively correlated with greenhouse gas emission intensity (GHGI). Raised bed planting improved NUE by 29 %, increased water productivity by 18 %, and reduced GHGI by 15 % compared with conventional flat planting.</div></div><div><h3>SIGNIFICANCE</h3><div>Adopting context-specific agronomic practices that combine integrated-fertilization, efficient irrigation, suitable varieties, and raised-bed planting can enhance agronomic gains while reducing environmental footprints. When tailored to local yield-limiting factors, these solutions provide a sustainable pathway to narrow","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"232 ","pages":"Article 104566"},"PeriodicalIF":6.1,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578178","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}
Pub Date : 2025-11-17DOI: 10.1016/j.agsy.2025.104561
Ralph J.M. Temmink , Kristiina Lång , Renske J.E. Vroom , Jens Leifeld , Christian Fritz , Walther Zeug , Daniela Thrän , Clemens Kleinspehn , Greta Gaudig , Josephine Neubert , Jürgen Kreyling , Jennifer M. Rhymes , Chris D. Evans , Wiktor Kotowski , Anke Nordt , Franziska Tanneberger
CONTEXT
Humanity must overcome the polycrisis of biodiversity loss, climate change and pollution. These challenges are especially urgent in peatlands, which develop slowly under waterlogged conditions, function as landscape filters and store large amounts of carbon. Drainage for agriculture, forestry or peat extraction leads to severe socio-ecological impacts, including greenhouse gas emissions, biodiversity loss, land subsidence, higher flood and drought risks and downstream pollution.
OBJECTIVE
This study evaluates paludiculture as an innovative wet agricultural land use that maintains wet peatlands, offers economic alternatives to drainage-based systems and reduces environmental impacts.
METHODS
We reviewed and synthesized ecological and socio-economic evidence from low- and high intensity paludiculture practices to assess their potential to balance human needs with peatland conservation.
RESULTS AND CONCLUSIONS
Paludiculture is a promising new agricultural land use that effectively reduces greenhouse gas emissions, supports biodiversity restoration and contributes to climate mitigation and sustainable development. Our findings show direct and indirect contributions to ten UN Sustainable Development Goals: no poverty, good health, clean water, clean energy, innovation, sustainable cities and communities, responsible production, climate action, life below water, and life on land. Nonetheless, challenges remain regarding economic viability, land-use competition and management.
SIGNIFICANCE
Paludiculture shows how wetland agriculture can create new revenue opportunities combined with ecological protection. By contributing to both climate and biodiversity goals, it is a sustainable alternative to drainage-based peatland use.
{"title":"Agriculture on wet peatlands: the sustainability potential of paludiculture","authors":"Ralph J.M. Temmink , Kristiina Lång , Renske J.E. Vroom , Jens Leifeld , Christian Fritz , Walther Zeug , Daniela Thrän , Clemens Kleinspehn , Greta Gaudig , Josephine Neubert , Jürgen Kreyling , Jennifer M. Rhymes , Chris D. Evans , Wiktor Kotowski , Anke Nordt , Franziska Tanneberger","doi":"10.1016/j.agsy.2025.104561","DOIUrl":"10.1016/j.agsy.2025.104561","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Humanity must overcome the polycrisis of biodiversity loss, climate change and pollution. These challenges are especially urgent in peatlands, which develop slowly under waterlogged conditions, function as landscape filters and store large amounts of carbon. Drainage for agriculture, forestry or peat extraction leads to severe socio-ecological impacts, including greenhouse gas emissions, biodiversity loss, land subsidence, higher flood and drought risks and downstream pollution.</div></div><div><h3>OBJECTIVE</h3><div>This study evaluates paludiculture as an innovative wet agricultural land use that maintains wet peatlands, offers economic alternatives to drainage-based systems and reduces environmental impacts.</div></div><div><h3>METHODS</h3><div>We reviewed and synthesized ecological and socio-economic evidence from low- and high intensity paludiculture practices to assess their potential to balance human needs with peatland conservation.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Paludiculture is a promising new agricultural land use that effectively reduces greenhouse gas emissions, supports biodiversity restoration and contributes to climate mitigation and sustainable development. Our findings show direct and indirect contributions to ten UN Sustainable Development Goals: no poverty, good health, clean water, clean energy, innovation, sustainable cities and communities, responsible production, climate action, life below water, and life on land. Nonetheless, challenges remain regarding economic viability, land-use competition and management.</div></div><div><h3>SIGNIFICANCE</h3><div>Paludiculture shows how wetland agriculture can create new revenue opportunities combined with ecological protection. By contributing to both climate and biodiversity goals, it is a sustainable alternative to drainage-based peatland use.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104561"},"PeriodicalIF":6.1,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568698","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}
Pub Date : 2025-11-17DOI: 10.1016/j.agsy.2025.104570
Belay Tizazu Mengistie, Ram L. Ray
Climate smart agriculture (CSA) is increasingly promoted as a solution to climate related threats to global food systems. While research on CSA is growing, critical analysis of its evolution, implementation, and future pathways remains limited, especially across diverse geopolitical contexts. Critics argue that several farming practices, interventions, and technologies are being introduced as climate-smart, even though they may not effectively address the issues caused by climate change. This review systematically examines 129 publications to assess challenges, recent advancements, and future directions in CSA practices and technologies. The findings reveal significant barriers to adoption, including policy gaps and technological limitations. This review identified several critical challenges and potential future pathways in the current structure of CSA adoption which includes fragmented definitions, practice vs. policy gap, insufficient integration of socio-economic dimensions; weak monitoring and accountability mechanisms; overreliance on quantitative metrics and fragmented indicator systems among others. CSA has advanced globally through diverse practices and technologies, yet faces political contestation, goal trade-offs, and power imbalances. Its adoption depends on personal, technological, economic, institutional, socio-cultural, and informational factors CSA is not a one-size-fits-all solution. It highlights concerns over CSA being lacking unified criteria, and unevenly addressing its three core pillars. Overall, this review analyzed that CSA implementation often reflects power imbalances, as policies, funding, and technologies are largely shaped by institutions in the Global North, frequently misaligned with the needs and realities of smallholder farmers in the Global South. Effective CSA requires context-specific solutions that optimize synergies and manage the trade-off between core pillars of CSA. The review calls for context specific interventions and broader engagement beyond scientific framing to make CSA more inclusive and effective for farmers, policymakers, and stakeholders globally.
{"title":"Global dynamics of climate smart agricultural practices and technologies: Recent advancements, challenges and potential future pathways - A review","authors":"Belay Tizazu Mengistie, Ram L. Ray","doi":"10.1016/j.agsy.2025.104570","DOIUrl":"10.1016/j.agsy.2025.104570","url":null,"abstract":"<div><div>Climate smart agriculture (CSA) is increasingly promoted as a solution to climate related threats to global food systems. While research on CSA is growing, critical analysis of its evolution, implementation, and future pathways remains limited, especially across diverse geopolitical contexts. Critics argue that several farming practices, interventions, and technologies are being introduced as climate-smart, even though they may not effectively address the issues caused by climate change. This review systematically examines 129 publications to assess challenges, recent advancements, and future directions in CSA practices and technologies. The findings reveal significant barriers to adoption, including policy gaps and technological limitations. This review identified several critical challenges and potential future pathways in the current structure of CSA adoption which includes fragmented definitions, practice vs. policy gap, insufficient integration of socio-economic dimensions; weak monitoring and accountability mechanisms; overreliance on quantitative metrics and fragmented indicator systems among others. CSA has advanced globally through diverse practices and technologies, yet faces political contestation, goal trade-offs, and power imbalances. Its adoption depends on personal, technological, economic, institutional, socio-cultural, and informational factors CSA is not a one-size-fits-all solution. It highlights concerns over CSA being lacking unified criteria, and unevenly addressing its three core pillars. Overall, this review analyzed that CSA implementation often reflects power imbalances, as policies, funding, and technologies are largely shaped by institutions in the Global North, frequently misaligned with the needs and realities of smallholder farmers in the Global South. Effective CSA requires context-specific solutions that optimize synergies and manage the trade-off between core pillars of CSA. The review calls for context specific interventions and broader engagement beyond scientific framing to make CSA more inclusive and effective for farmers, policymakers, and stakeholders globally.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104570"},"PeriodicalIF":6.1,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568697","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}
Pub Date : 2025-11-15DOI: 10.1016/j.agsy.2025.104553
Elizabeth Heagney , Daniel Gregg , Dan Hill , James Radford , Grace Sutton , Fred Rainsford , Daniel O'Brien , Angela Hawdon , Imogen Semmler , Mark Gardner , Milly Taylor , Sue Ogilvy
CONTEXT
Ambitious targets under the Paris Climate Agreement and the Kunming-Montreal Global Biodiversity Framework bring increasing urgency for agriculture to play an active role as a nature-based solution to climate and biodiversity loss. But widespread uptake of nature-based solutions by the agriculture sector has proved elusive. This paper presents the results of the Farming for the Future Livestock Program, a large-scale program that sought to quantify the financial implications of natural capital for farm business performance in Australia's broadacre livestock sector, which covers 350 million ha and contributes more than 50% of the country's gross value of agricultural production.
OBJECTIVE
We aim to build a better understanding of the financial implications of natural capital on farms - a critical knowledge gap that limits effective policy and landholder adoption of nature-based solutions in the agriculture sector. We aim to quantify the effect of on-farm natural capital on farm business performance.
METHODS
We collected natural capital data from 114 farms via satellite imagery analysis and on-ground vegetation surveys, alongside production and financial data collected via detailed producer surveys. We used five natural capital metrics (Ecological Condition, Aggregation, Proximity, Ground Cover, and Forage Condition) to understand the effect of natural capital on farm business performance (productivity efficiency, profitability and financial resilience) on farms with a combined land area of >230,000 ha, in the largest analysis of its kind to date.
RESULTS AND CONCLUSIONS
Our multi-region models tested a total of 20 natural capital – farm business performance relationships (4 business performance measures x 5 natural capital metrics). There was moderate or strong evidence for 6 of these (5 positive, one negative) and weak statistical evidence for a further 6 relationships (4 positive, 2 negative). Region-specific models yielded similar results to the multi-region model. This suggests that high-performing livestock businesses benefit from high levels of natural capital. High levels of specific types of natural capital were associated with increased production efficiency of up to 3%, improved livestock gross margin, higher farm earnings, and higher levels of climate resilience.
SIGNIFICANCE
We highlight the important role that integrating robust information about the financial implications of natural capital in production systems can play in shaping appropriate and adoptable nature-based climate solutions for the agriculture sector.
{"title":"Natural capital enhances farm production, profitability and financial resilience: findings from a study on 230,000 ha of farmland in Australia","authors":"Elizabeth Heagney , Daniel Gregg , Dan Hill , James Radford , Grace Sutton , Fred Rainsford , Daniel O'Brien , Angela Hawdon , Imogen Semmler , Mark Gardner , Milly Taylor , Sue Ogilvy","doi":"10.1016/j.agsy.2025.104553","DOIUrl":"10.1016/j.agsy.2025.104553","url":null,"abstract":"<div><h3>CONTEXT</h3><div>Ambitious targets under the Paris Climate Agreement and the Kunming-Montreal Global Biodiversity Framework bring increasing urgency for agriculture to play an active role as a nature-based solution to climate and biodiversity loss. But widespread uptake of nature-based solutions by the agriculture sector has proved elusive. This paper presents the results of the <em>Farming for the Future Livestock Program</em>, a large-scale program that sought to quantify the financial implications of natural capital for farm business performance in Australia's broadacre livestock sector, which covers 350 million ha and contributes more than 50% of the country's gross value of agricultural production.</div></div><div><h3>OBJECTIVE</h3><div>We aim to build a better understanding of the financial implications of natural capital on farms - a critical knowledge gap that limits effective policy and landholder adoption of nature-based solutions in the agriculture sector. We aim to quantify the effect of on-farm natural capital on farm business performance.</div></div><div><h3>METHODS</h3><div>We collected natural capital data from 114 farms via satellite imagery analysis and on-ground vegetation surveys, alongside production and financial data collected via detailed producer surveys. We used five natural capital metrics (<em>Ecological Condition</em>, <em>Aggregation</em>, <em>Proximity</em>, <em>Ground Cover</em>, and <em>Forage Condition</em>) to understand the effect of natural capital on farm business performance (productivity efficiency, profitability and financial resilience) on farms with a combined land area of >230,000 ha, in the largest analysis of its kind to date.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Our multi-region models tested a total of 20 natural capital – farm business performance relationships (4 business performance measures x 5 natural capital metrics). There was moderate or strong evidence for 6 of these (5 positive, one negative) and weak statistical evidence for a further 6 relationships (4 positive, 2 negative). Region-specific models yielded similar results to the multi-region model. This suggests that high-performing livestock businesses benefit from high levels of natural capital. High levels of specific types of natural capital were associated with increased production efficiency of up to 3%, improved livestock gross margin, higher farm earnings, and higher levels of climate resilience.</div></div><div><h3>SIGNIFICANCE</h3><div>We highlight the important role that integrating robust information about the financial implications of natural capital in production systems can play in shaping appropriate and adoptable nature-based climate solutions for the agriculture sector.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"231 ","pages":"Article 104553"},"PeriodicalIF":6.1,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145516443","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}
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