Climate Smart Agriculture最新文献

{"title":"Context-dependent arbuscular mycorrhizal fungal regulation of soil carbon flow through hyphal transport, microbial reprocessing, and mineral stabilization","authors":"Zhanku Shi,&nbsp;Xue Li,&nbsp;Zhan Shi,&nbsp;Qinli Lu,&nbsp;Andrea Pezzuolo,&nbsp;Nana Fan,&nbsp;Feihong Liang,&nbsp;Qi Feng","doi":"10.1016/j.csag.2026.100142","DOIUrl":"10.1016/j.csag.2026.100142","url":null,"abstract":"<div><div>Arbuscular mycorrhizal fungi (AMF) form symbioses with most terrestrial plants and act as major conduits linking photosynthetic carbon fixation to soil carbon turnover. Plants allocate substantial carbon to AMF, which redistribute plant-derived carbon beyond roots through extraradical hyphae into rhizosphere-associated microsites and hyphosphere environments. Within these interconnected interfaces, AMF-derived carbon is transformed by microbial communities into biomass, necromass, extracellular compounds, or CO₂, with the ultimate fate determined by the balance between stabilization and loss processes. Microbial functional traits, including carbon-use efficiency, necromass formation, and mineral interaction capacity, regulate whether AMF-derived carbon contributes to persistent soil organic matter formation or is returned to the atmosphere. Accumulating evidence shows that AMF does not inherently promote soil carbon sequestration; instead, their effects are context-dependent, shaped by plant traits, AMF functional characteristics, microbial interactions, nutrient availability, mineral properties, and environmental conditions. Moreover, short-term hyphosphere carbon fluxes cannot be directly extrapolated to long-term ecosystem carbon sequestration. This AMF-centered microecological framework provides a mechanistic basis for understanding how AMF regulate soil carbon dynamics and for identifying the conditions under which they may contribute to persistent carbon storage and sustainable soil carbon management.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 4","pages":"Article 100142"},"PeriodicalIF":0.0,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149348886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A transparent crop model-driven and AI-assisted framework for agricultural decision support","authors":"Bangyou Zheng,&nbsp;Yusuke Kikuchi,&nbsp;Enli Wang,&nbsp;Kirsten Verburg","doi":"10.1016/j.csag.2026.100143","DOIUrl":"10.1016/j.csag.2026.100143","url":null,"abstract":"<div><div>Agricultural decision-making requires evaluation of complex interactions under variable environment and management conditions. Process-based crop models are widely used to support these decisions by providing scientifically grounded analysis of management alternatives. However, their application remains constrained by technical complexity and the difficulty of translating informal decision contexts into complete and reproducible model analyses without expert knowledge. Recent advances in artificial intelligence (AI) offer opportunities to improve accessibility, but questions remain regarding transparency, reproducibility, trustworthiness, and the appropriate role of AI in scientific decision-support systems. We present Agricultural Large Language Model (AgriLLM), a transparent crop model-driven and AI-assisted framework for agricultural decision support that explicitly separates AI-assisted interpretation, deterministic decision processing, and scientific inference. A central feature of the framework is its target-driven design, in which decision objectives rather than user phrasing determine the information requirements, simulation design, and evaluation procedures needed to support decision-making. Using Agricultural Production Systems Simulator (APSIM) Next Generation as a proof-of-concept platform, we demonstrate the framework across cultivar selection, time of sowing, and nitrogen management scenarios. The results show how diverse and incomplete user inputs can be transformed into transparent and reproducible decision workflows while maintaining explicit representation of assumptions, evidence, and decision logic. The framework demonstrates how AI can be integrated with process-based crop modelling to improve accessibility and usability while preserving transparency, reproducibility, and scientific integrity in agricultural decision support.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 4","pages":"Article 100143"},"PeriodicalIF":0.0,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149348885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term cropping systems shape soil organic matter dynamics and related soil indicators in a Paraguayan agroecosystem","authors":"Carlos Alcides Villalba Algarin,&nbsp;Cassio Carlette Thiengo,&nbsp;Wanderlei Bieluczyk,&nbsp;Maurício Roberto Cherubin,&nbsp;Lucas T. Greschuk,&nbsp;Antonio Leite Florentino,&nbsp;Deoclecio Jardim Amorim,&nbsp;Moacir Tuzzin de Moraes,&nbsp;Alodia Concepción González,&nbsp;José Lavres","doi":"10.1016/j.csag.2026.100141","DOIUrl":"10.1016/j.csag.2026.100141","url":null,"abstract":"<div><div>Long-term evidence on how predominant cropping systems affect soil organic matter (SOM) dynamics and soil functioning is scarce in Paraguay. In a 32-year field experiment, we evaluated conventional (CT) and reduced (RT) tillage and no-tillage (NT₁) under the same crop succession, plus two no-tillage systems with diversified rotations and cover crops (NT₂ and NT₃). In the 0–10, 10–20, and 20–30 cm layers, we quantified total carbon (C) and nitrogen (N) stocks, particulate and mineral-associated organic matter (POM and MAOM), natural-abundance δ¹³C and δ¹⁵N, and their relationships with physical, chemical, and biological soil health indicators. The clearest responses occurred at 0–10 cm, where all NT systems had C stocks at least 30% greater than CT, and NT₃ had an N stock 36% greater than CT. Across 0–30 cm, NT₂ and NT₃ maintained greater C stocks than CT, and all NT systems maintained greater N stocks, with differences among NT systems clearer for N than for C. Within NT systems, crop diversification did not consistently increase total C stocks, but its effects were more evident for N stocks and C and N stocks in MAOM. Stable isotopes differentiated SOM pools, whereas cropping-system effects on isotopic composition were weak and inconsistent. Greater SOM pools were associated with more favorable soil health indicators. Reducing soil disturbance through long-term NT is a central pathway for increasing SOM and strengthening soil health in Paraguay, while additional gains may depend on improved crop diversification and fertility management.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 4","pages":"Article 100141"},"PeriodicalIF":0.0,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149348887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial distribution and drivers of cropland-phosphorus runoff in China","authors":"Zihan Yu,&nbsp;Zhihao Xu,&nbsp;Wulahati Adalibieke,&nbsp;Qingwen Zhang,&nbsp;Longsheng Shangguan,&nbsp;Chen Liang,&nbsp;Xiaoying Zhan,&nbsp;Fangli Wang","doi":"10.1016/j.csag.2026.100128","DOIUrl":"10.1016/j.csag.2026.100128","url":null,"abstract":"<div><div>The unidirectional flow of phosphorus (P) from mineral reserves to croplands, freshwaters and ultimately to marine environments surpasses sustainable limits for human development. Addressing the dual challenges of rising food production and mitigating P pollution necessitates spatially explicit assessments. However, significant uncertainties persist regarding the spatial patterns of cropland-P runoff in China, largely due to inadequate methodologies for accurately estimating P runoff that incorporate climate variability, soil characteristics, and P fertilization rates. Here, we conducted a fine-gridded estimation of cropland-P runoff across China, using a data-driven artificial intelligence model in conjunction with county-level P fertilization data. Results indicated that cropland-P runoff in 2018 totaled 109.9 kilotons P yr⁻¹, representing 0.79% of China's mineral P fertilization, aligning with national surveys from 2017. Notably, P runoff fluxes from uplands exhibited an inverse relationship with latitude, highlighting hotspots in regions south of the Yangtze River, driven by lower soil pH, intensive crop ration, and elevated soil organic matter. In rice paddies, hotspots were concentrated in the Pearl River Delta, Yangtze River Delta and western Sichuan basin, linked to higher irrigation and P fertilization. These patterns suggest that mineral-fertilizer-induced cropland-P runoff hotspots mainly occur where high P input coincides with runoff-prone soil, climate and irrigation conditions. This study provides a spatially explicit basis for prioritizing future monitoring and management of cropland-P runoff in these vulnerable regions.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 3","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148624978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of climate change on vegetable crop production, quality, and safety in Sub-Saharan Africa: A systematic review of tomato, onion, and pepper","authors":"Robert Agyemang,&nbsp;Simbo Diakite,&nbsp;Ayitey Bless Kodzo,&nbsp;Pius Yao Adenyo,&nbsp;Ernest Kwesi Aboagye,&nbsp;Prince Emmanuel Norman","doi":"10.1016/j.csag.2026.100129","DOIUrl":"10.1016/j.csag.2026.100129","url":null,"abstract":"<div><div>Climate change poses escalating threats to agricultural systems in Sub-Saharan Africa (SSA), with vegetable crops among the most vulnerable due to their sensitivity to biotic and abiotic stresses. Impacts of climate change on crop productivity have been widely documented, but its effects on vegetable quality and food safety remain less comprehensively synthesized. This systematic review analyzes evidence from 140 peer-reviewed studies published between 2014 and 2026 to evaluate how climate variability and change affect the production, quality, and safety of tomato (<em>Solanum lycopersicum</em> L.), onion (<em>Allium cepa</em> L.), and pepper (<em>Capsicum</em> spp.) in SSA. Findings reveal that climate impacts on vegetable quality are complex and context-dependent. Elevated temperatures, drought, erratic rainfall, and increased atmospheric carbon dioxide (CO₂) alter physiological processes and nutrient composition, affecting concentrations of vitamin C, lycopene, capsaicin, quercetin, sulfur compounds, and essential minerals. These responses depend on crop species, cultivar, stress intensity, timing of exposure, and post-harvest handling practices. Climate change intensifies food safety risks by favoring the proliferation of fungal pathogens and mycotoxin-producing species, increasing the incidence of bacterial diseases, and facilitating the spread of invasive pests such as <em>Tuta absoluta</em> and onion thrips. These challenges are further compounded by inadequate storage and cold-chain infrastructure, contributing to post-harvest losses (PHL) that frequently exceed 40% across many SSA vegetable value chains. Findings indicate that effective adaptation requires integrated pre- and post-harvest interventions, including stress-tolerant cultivars, climate-smart irrigation, integrated pest management, biological control agents, improved curing and storage systems, modified-atmosphere packaging, and digital climate advisory services. Major knowledge gaps identified are (i) predominance of studies examining single climate stressors, despite the reality that vegetables are increasingly exposed to multiple interacting stresses; and (ii) post-harvest quality and food safety impacts remain under-researched relative to production outcomes. In conclusion, this review suggests that: (i) safeguarding vegetable production systems in SSA requires a shift from yield-centered adaptation approaches toward strategies that simultaneously protect productivity, nutritional quality, and food safety; (ii) strengthening breeding programs for nutritional resilience, expanding affordable cold-chain infrastructure, and promoting integrated climate-smart technologies for enhanced food security, public health, and smallholder livelihoods under future climate change scenarios.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 3","pages":"Article 100129"},"PeriodicalIF":0.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148730950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights into drought tolerance in sugar beet (Beta vulgaris L.) focusing on adaptive mechanisms and mitigation approaches","authors":"Tasfiqure Amin Apon ,&nbsp;Aysha Siddika Jarin ,&nbsp;Tamima Akter Shorna ,&nbsp;Md Asadujjaman Rasel ,&nbsp;Al Rahat ,&nbsp;Akbar Hossain ,&nbsp;Akm Rashadul Islam ,&nbsp;Sheikh Faruk Ahmed ,&nbsp;Md Arifur Rahman Khan","doi":"10.1016/j.csag.2026.100101","DOIUrl":"10.1016/j.csag.2026.100101","url":null,"abstract":"<div><div>Drought stress is a major environmental factor limiting global sugar beet production. Water deficit impairs photosynthesis, disrupts osmotic balance, induces oxidative stress, and disturbs source–sink relationships, ultimately leading to inhibited root growth, reduced sucrose accumulation, and decreased overall yield. In response to drought stress, sugar beet initiates a series of adaptive mechanisms. Morphologically, it develops deeper roots and reduces leaf area to optimize water uptake and conservation. Physiologically and biochemically, it accumulates osmoregulatory compounds such as proline and glycine betaine to maintain cellular turgor and enhances the activity of antioxidant enzymes to mitigate oxidative damage. At the molecular level, drought tolerance involves the induction of stress-responsive genes and transcription factors including DREB (dehydration-responsive element-binding) proteins, MYB (myeloblastosis) factors, NAC transcription factors (e.g., NAM (no apical meristem), ATAF (Arabidopsis transcription activation factor), and CUC (cup-shaped cotyledon)), and WRKY transcription factors, as well as signaling molecules such as abscisic acid and aquaporins. In addition to these inherent tolerance mechanisms, external management practices can enhance drought resistance. These include optimized irrigation scheduling, soil amendments such as biochar and vermicompost, foliar application of plant hormones (e.g., abscisic acid, gibberellic acid, and jasmonic acid), and the use of nanoparticles such as fullerenol and silicon. However, the efficacy of nanoparticles is strongly dose-dependent. This review synthesizes current knowledge on drought responses in sugar beet, identifies key research gaps, and proposes strategies to alleviate drought stress, with an emphasis on morpho-physiological, biochemical, and molecular adaptations. It aims to provide a theoretical foundation for developing drought-tolerant sugar beet cultivars and formulating sustainable production strategies under changing climatic conditions.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 2","pages":"Article 100101"},"PeriodicalIF":0.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nano-fertilizers for climate-smart agriculture: resource efficiency across soil-plant-environment systems","authors":"Md Asadujjaman Rasel ,&nbsp;Sayma Salam ,&nbsp;Md. Moshiul Islam","doi":"10.1016/j.csag.2026.100115","DOIUrl":"10.1016/j.csag.2026.100115","url":null,"abstract":"<div><div>Climate change is intensifying constraints on agricultural productivity by amplifying nutrient losses, yield instability, and environmental degradation. Climate-smart agriculture (CSA) seeks to address these challenges by integrating productivity, resilience, and sustainability; however, conventional fertilizer practices remain inefficient and environmentally burdensome. Recent advances in nano-fertilizer technologies offer new opportunities to improve nutrient management within CSA frameworks. Nano-fertilizers enhance nutrient delivery through controlled release, improved uptake, and targeted translocation, leading to higher nutrient use efficiency, improved crop performance, and greater tolerance to abiotic stresses such as drought, salinity, and temperature extremes. At the soil scale, nano-enabled formulations influence nutrient retention, microbial activity, and biogeochemical cycling, while at the environmental scale, they reduce nutrient leaching and mitigate emissions of nitrous oxide and ammonia. At the same time, concerns related to environmental fate, ecotoxicological effects, and long-term nanoparticle accumulation highlight the need for cautious deployment. The emerging integration of nano-fertilizers with precision agriculture, digital sensing, and artificial intelligence further strengthens their potential for adaptive nutrient management under climate variability. Overall, nano-fertilizers represent a promising component of climate-smart nutrient strategies, provided that their adoption is supported by field-scale validation, environmentally sound design, and appropriate regulatory oversight.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 2","pages":"Article 100115"},"PeriodicalIF":0.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global warming enhances soybean suitability and yield potential in the mid-high latitude Amur River Basin","authors":"Xinyue Chang ,&nbsp;Lingxue Yu ,&nbsp;Zhuoran Yan ,&nbsp;Lun Bao ,&nbsp;Xuan Li","doi":"10.1016/j.csag.2026.100099","DOIUrl":"10.1016/j.csag.2026.100099","url":null,"abstract":"<div><div>Understanding the spatiotemporal dynamics of soybean yield potential under climate change is crucial for improving crop productivity and guiding adaptive agricultural strategies in climatically sensitive regions. However, systematic assessments that integrate both historical and future climate conditions with crop suitability remain limited. In this study, we employed the Agro-Ecological Zones model to quantify soybean yield potential and climatic suitability across the Amur River Basin from 1980 to 2100, integrating historical observations and CMIP6 climate projections. Results indicate a continuous increase in yield potential under both rain-fed and irrigated conditions. Under SSP2-4.5 and SSP5-8.5, rain-fed soybean yields rise by 0.05 and 0.10 t ha decade⁻¹, while irrigated soybean yields increase by 0.04 and 0.12 t ha⁻¹ decade⁻¹. China and Russia show consistent productivity gains, especially in the Russian Far East under high-emission scenarios, whereas yield improvements in Mongolia depend strongly on irrigation due to persistent water limitations. Soybean suitability exhibits pronounced northwestward expansion driven by enhanced thermal and hydrological conditions. Moderately suitable areas expand by 135.97–185.97 % under rain-fed conditions and 106.51–132.10 % under irrigation. The suitability centroid migrates northwestward by up to 320.5 km by 2100, remaining within Heilongjiang Province. These findings highlight significant opportunities for soybean cultivation in northern high-latitude zones under climate warming. To harness this potential and strengthen system resilience, we recommend: (i) suitability-informed land reallocation, (ii) targeted investment in precision irrigation, and (iii) adaptive crop management aligned with shifting agro-climatic conditions, alongside enhanced transboundary cooperation among China, Russia, and Mongolia.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 1","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate-smart agriculture as disaster risk reduction: Effectiveness varies by hazard type in Pakistan","authors":"Aziz Ahmed ,&nbsp;Majid Mahar ,&nbsp;Peters Egbedi ,&nbsp;Amanullah Mahar ,&nbsp;Md Ali Haider ,&nbsp;Hafeez Ahmed Talpur ,&nbsp;Sirilak Chaiboontha ,&nbsp;Khalid Usman Shar ,&nbsp;Habibullah Abbasi ,&nbsp;Shakeel Ahmed Talpur","doi":"10.1016/j.csag.2025.100093","DOIUrl":"10.1016/j.csag.2025.100093","url":null,"abstract":"<div><div>Climate change increasingly threatens agricultural systems globally, with Pakistan ranking among the most climate-vulnerable countries. This study systematically compared climate-smart agriculture (CSA) effectiveness across different disaster types in Sindh Province, Pakistan: riverine flooding (Dadu), drought (Tharparkar), and coastal flooding (Thatta). A multi-scale analysis combined climate data, area-weighted agricultural vulnerability assessment using 3889 district-crop yield records (2004–2023), and farmer surveys (<em>n</em> ​= ​88). Climate analysis showed significant Arabian Sea warming (0.41 ​°C ​decade⁻¹, <em>p</em> ​&lt; ​0.01) with high precipitation variability (coefficient of variation ​≈ ​72 ​%). The corrected area-weighted vulnerability assessment ranked Tharparkar most vulnerable (#1, index: 66.23), followed by Thatta (#8, 31.69) and Dadu (#19, 24.77) among 23 districts. Drought analysis identified 2 of 20 years meeting drought criteria (Standardized Precipitation Index ≤ −0.5) in Tharparkar. CSA adoption varied significantly by disaster type (Kruskal-Wallis <em>H</em> ​= ​74.06, <em>p</em> ​&lt; ​0.001). Strong positive correlation between CSA practices and disaster resilience emerged in drought-vulnerable Tharparkar (<em>r</em> ​= ​0.756, <em>p</em> ​&lt; ​0.001, explaining 57 ​% of variance), while flood-prone districts showed negligible relationships (Thatta: <em>r</em> ​= ​−0.089, <em>p</em> ​&gt; ​0.05; Dadu: zero variance). Future projections indicate substantial sea-level rise of ∼331–751 ​mm by 2100 across Shared Socioeconomic Pathway scenarios. Results demonstrate CSA practices effectively reduce climate disaster risks in drought-prone systems, but effectiveness varies by disaster type, requiring tailored implementation approaches. This research provides the first systematic evidence comparing CSA effectiveness across different disaster contexts, supporting targeted rather than uniform adaptation policies.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 1","pages":"Article 100093"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145718986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adoption and intensity of climate smart agriculture practices: The case of smallholder farmers in East Hararghe Zone, Oromia Region, Ethiopia","authors":"Fami Abdurezak ,&nbsp;Jema Haji ,&nbsp;Kedir Jemal ,&nbsp;Beyan Ahmed ,&nbsp;Million Sileshi","doi":"10.1016/j.csag.2026.100100","DOIUrl":"10.1016/j.csag.2026.100100","url":null,"abstract":"<div><div>Climate change is a hot agenda among researchers and policymakers worldwide since it is seriously affecting the majority of the rural livelihoods that rely heavily on rain-fed agriculture. Climate smart agriculture practices (CSAPs) can address the adverse effects of climate change. Nevertheless, the rate of CSAPs adoption is quite low and varies across developing countries, particularly Ethiopia. Hence, this study identified determinants of CSAPs adoption and the intensity of these CSAPs across smallholder farmers of Ethiopia in general and particularly in the study area of the East Hararghe Zone of the Oromia Region. These CSAPs include crop-small ruminant livestock integration, sweet potato intercropping, electric water pumps, organic fertilizer, and sorghum seed varieties. The data about these CSAPs was collected from 422 households through questionnaires and analyzed using descriptive statistics and econometric models. The econometric analysis showed significant variables that influence CSAPs adoption and its intensity by applying the multivariate probit and ordered probit models, respectively. The study found that factors such as farm experience, family size, membership in a social group, and extension contact positively influence the adoption of CSAPs, whereas market and plot distance negatively affect smallholder farmers' adoption of CSAPs. Moreover, the ordered probit model revealed the factors determining the intensity of CSAPs adoption. The age of the household head, market distance, plot distance, soil fertility, and agroecology negatively affected the intensity of CSAPs adoption, while experience, social group, extension contact, perception of climate change, and climate information positively affected the adoption of CSAPs intensity. The study suggests that the policymaker should pay attention to the identified prioritized practices, recognized by local farmers as CSAPs, in order to promote sustainable agricultural practices and understand factors that shape the implementation of CSAPs among poor-resource-based farmers.</div></div>","PeriodicalId":100262,"journal":{"name":"Climate Smart Agriculture","volume":"3 1","pages":"Article 100100"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147396406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}