Climate-Resilient Agriculture: Systems, Science and Solutions for a Warming World

Agroforestry and Diversified Farming Systems as Climate Buffers: Implications for Climate-resilient Agriculture

2026-09-01T10:59:33+00:00

Agroforestry practices play a pivotal role in addressing the dual challenges of climate change mitigation and adaptation. The intensification of climate change poses unprecedented challenges to global food production systems, threatening agricultural stability through rising temperatures, erratic precipitation, extreme weather events, and accelerating land degradation. Agroforestry and diversified farming systems have emerged as scientifically credible and practically viable strategies for enhancing the resilience of agricultural landscapes to these climate-driven pressures. This review synthesises a broad body of evidence drawn from peer-reviewed literature published between 1993 and 2024 to evaluate the roles of agroforestry and diversified farming systems as climate buffers across ecological, agronomic, and socioeconomic scales. This review was conducted through a systematic search of peer-reviewed academic literature using multiple bibliographic databases, including Web of Science, Scopus, Google Scholar, and PubMed. The review examines how the deliberate integration of trees and perennial vegetation with annual crops and livestock modulates microclimate, sequesters carbon, conserves soil and water, and reduces vulnerability to climatic extremes. Evidence from multiple tropical, subtropical, and temperate contexts confirms that well-designed agroforestry systems can sequester substantial quantities of carbon in both above-ground biomass and soil organic matter, whilst simultaneously improving food security and farmer livelihoods. Diversified farming systems, including polycultures, intercropping, and integrated crop–livestock arrangements, are shown to enhance functional biodiversity, distribute agricultural risk, and maintain productivity under variable climatic conditions. The review also identifies critical gaps in the literature, including insufficient long-term data on system performance under future climate scenarios and limited integration of gender and equity dimensions in agroforestry research. Policy frameworks that align agroforestry with national climate adaptation and mitigation commitments are found to be nascent but growing. The synthesis underscores the need for systemic transitions from input-intensive monocultures towards diversified, tree-integrated landscapes as a cornerstone of climate-smart agriculture globally.

Soil Health Management Under Drought: Carbon Sequestration, Microbiome, and Structural Resilience

2026-09-01T11:03:12+00:00

Drought is increasingly recognised as a systems-level stressor that compromises the biological, physical, and biogeochemical foundations of soil health. Its effects are not limited to short-term water deficits for crops; rather, drought reorganises the pathways through which soils store carbon, sustain microbiome function, and retain structural integrity. This review synthesises the current understanding of soil health management under drought through the linked lenses of carbon sequestration, soil microbiome dynamics, and structural resilience. The literature for this review was selected through structured searches in Web of Science, Scopus, Google Scholar, and PubMed. Searches were conducted for publications from 2005 to 2026, with additional earlier seminal or foundational papers considered when necessary for conceptual framing. The article argues that drought resilience emerges not from any single soil property but from the interaction among plant-derived carbon inputs, microbial physiological responses, organo-mineral stabilisation, aggregate turnover, pore continuity, and management history. Recent literature shows that drought can reduce plant carbon inputs, constrain microbial activity through diffusion limitation, alter microbial carbon use efficiency, and increase the vulnerability of stored organic matter during drying–rewetting cycles. At the same time, management can moderate these risks. Practices that increase continuous carbon supply, protect habitat heterogeneity, reduce mechanical disturbance, and enhance aggregate stability can improve resistance during drought and recovery after rewetting. Particular emphasis is placed on the rhizosphere, arbuscular mycorrhizal fungi, microbial necromass formation, biochar-mediated aggregation, and the role of diversified management in preserving microbial and structural functions. The review concludes that drought-oriented soil health management must move beyond the narrow aim of increasing soil organic carbon stocks and instead target the quality, spatial protection, and functional resilience of carbon within living and structured soils. An integrated framework is proposed in which resilient soils are those that maintain carbon inputs, buffer microbial stress, and preserve a physically connected yet hierarchically aggregated architecture under repeated moisture stress.

Enhancing Crop Drought Resilience through Genetic, Physiological and Agronomic Innovation: A Critical Integrative Review

2026-09-01T11:07:57+00:00

Drought resilience in crops is often treated as a unitary tolerance phenotype, yet field performance emerges from interactions among genotype, developmental stage, soil water distribution, atmospheric demand and management. This critical narrative review evaluates how genetic, physiological and agronomic innovations can be combined to stabilise crop yield under water limitation while avoiding misleading gains in survival or leaf-level water-use efficiency that do not translate into harvestable production. Literature published from 1 January 2000 to 14 June 2026 was identified through complementary searches of major open scholarly indexes and agriculture- and life-science databases, with selective inclusion of foundational studies. Evidence was appraised for mechanistic strength, field realism, yield relevance, replication, environmental characterisation and transferability across target production environments. The synthesis indicates that the strongest individual advances are those that connect a defined drought scenario with a causal trait and a yield endpoint, as illustrated by deeper rooting, stay-green canopy regulation and selected engineered alleles. Nevertheless, trait value is conditional: deeper roots require accessible subsoil water, conservative transpiration may protect late-season water at the cost of early biomass, and osmotic or antioxidant responses can improve stress status without guaranteeing yield. Agronomic interventions show the same context dependence. Regulated deficit irrigation, residue retention, mulching and rhizosphere manipulation can improve water productivity, but their benefits vary with crop stage, soil, rainfall pattern, input access and long-term system effects. The central inference is that durable drought resilience is best pursued as a genotype x environment x management optimisation problem rather than by stacking nominal tolerance traits. Progress therefore depends on managed-stress phenotyping, explicit target-environment definition, genomic prediction linked to crop models, recovery phenotyping and multi-environment validation of integrated trait-management portfolios. This framework shifts evaluation from whether an intervention reduces stress symptoms to whether it reliably preserves yield, resource productivity and system viability across credible drought scenarios.

Climate Change and Agriculture: Understanding the Crisis Nexus

2026-09-01T11:12:41+00:00

Climate change and agriculture are locked in a profoundly consequential relationship that threatens global food security, ecosystem stability, and the livelihoods of billions of people. Rising temperatures, shifting precipitation regimes, increasing frequency of extreme weather events, elevated atmospheric carbon dioxide concentrations, and accelerating sea-level rise collectively challenge agricultural systems in ways that are unprecedented in the history of modern farming. Simultaneously, agriculture itself is a significant contributor to the greenhouse gas emissions that drive climate change, thereby creating a dangerous feedback loop that demands urgent and integrated responses. While previous reviews have examined specific aspects of the climate change–agriculture nexus, only a few studies have provided an integrated synthesis encompassing biophysical, socioeconomic, mitigation, adaptation, and policy dimensions—an important gap this review seeks to address. This review synthesises evidence from peer-reviewed literature published primarily between 2005 and 2026 to examine the multidimensional interactions between climate change and agricultural systems across diverse regions and crop types. It evaluates the mechanisms through which climatic variables affect crop physiology, soil health, pest and disease dynamics, water availability, and farmer livelihoods, whilst also exploring the pathways through which the agricultural sector contributes to climatic destabilisation. The review further assesses adaptation and mitigation strategies, including precision agriculture, agroecological approaches, climate-smart agriculture, and policy frameworks. A wide range of adaptation strategies—from climate-resilient crop varieties and conservation agriculture to agroecology, digital technologies, and reformed agricultural policies—offer meaningful pathways toward more resilient food systems. Mitigation options within the agricultural sector, including soil carbon sequestration, improved livestock management, and enhanced nitrogen use efficiency, can contribute significantly to global greenhouse gas reduction targets whilst also delivering co-benefits for productivity and environmental quality. The findings underscore the urgent need for transformative governance, cross-sector collaboration, and investment in resilient food systems to avert the most severe consequences of this escalating crisis nexus.

Internet of Things for Climate-resilient Agriculture: A Critical Synthesis of Smart Farming Systems, Evidence and Implementation Constraints

2026-09-01T11:16:38+00:00

Agricultural climate resilience increasingly depends on the capacity to detect environmental change early, interpret it correctly and respond before stress becomes irreversible. Internet of Things (IoT) technologies promise to strengthen this capacity by linking field sensors, communication networks, edge or cloud computing, analytics, decision support and automated actuators. Yet much of the smart-farming literature evaluates connectivity, prediction accuracy or input efficiency rather than resilience itself. This critical narrative review examines how IoT-enabled smart farming can contribute to climate-resilient agriculture and where the evidence remains insufficient. Peer-reviewed literature published principally from 1 January 2015 to 14 June 2026 was selected through searches of agricultural, biomedical and multidisciplinary scholarly sources, supplemented by citation tracing and bibliographic verification. Evidence was synthesised across system architecture, irrigation and microclimate management, artificial intelligence integration, reliability, governance and adoption. The strongest operational evidence concerns soil- and plant-informed irrigation, where multi-season orchard trials and recent field comparisons show that sensor-driven scheduling can reduce water application while maintaining commercially relevant crop performance. IoT-controlled protective structures and irrigation can also buffer heat and excess-rainfall exposure, but such studies remain geographically and technologically narrow. Across the wider literature, resilience claims are often inferred from technical performance, resource efficiency or short-duration prototypes rather than tested through multi-season exposure to drought, heat, flooding or compound extremes. Network outages, power failure, sensor drift, model transferability, cybersecurity, data governance and affordability can themselves become points of vulnerability. Artificial intelligence can improve anticipatory decision support, but historical predictive accuracy does not guarantee performance under climate non-stationarity. IoT should therefore be understood not as a resilience intervention in isolation, but as an enabling infrastructure whose value depends on reliable closed-loop operation, agronomic validity and institutional capacity. Progress requires field trials designed around resilience outcomes, stress-tested architectures, uncertainty-aware analytics, interoperable data systems and business models accessible to small and resource-constrained farms.

Climate Change and Agriculture: Historical Context, Current Trends, and Future Trajectories: A Comprehensive Review

2026-09-01T11:20:23+00:00

Agriculture underpins global food security and rural livelihoods, yet it remains among the sectors most vulnerable to the escalating consequences of climate change. This review synthesises evidence from the peer-reviewed literature and authoritative institutional reports to examine the historical relationship between climate variability and agricultural systems, and to assess current trends in climate-driven agricultural disruption. From pre-industrial climatic fluctuations that shaped early farming civilisations to the anthropogenically forced warming of the twenty-first century, the interplay between climate and crop production has been continuous and consequential. Rising mean temperatures, shifting precipitation regimes, elevated atmospheric carbon dioxide concentrations, and increasing frequency of extreme weather events collectively threaten to undermine crop yields, destabilise food systems, and exacerbate socio-economic inequalities at regional and global scales. Evidence indicates that global yields of major cereals, including wheat, maize, and rice, have already been negatively affected by observed warming trends. Projections under various emissions scenarios suggest further yield reductions in the range of two to six per cent per decade in the absence of robust adaptation. Regional vulnerabilities are pronounced, with sub-Saharan Africa, South Asia, and parts of Latin America facing disproportionate risks. Adaptation strategies — ranging from heat-tolerant crop varieties and altered planting calendars to policy reforms and water management innovations — offer meaningful but insufficient responses in isolation. The review also highlights the bidirectional relationship between agriculture and climate, as agricultural land use and practices contribute significantly to greenhouse gas emissions. Identified knowledge gaps include the inadequate representation of socioeconomic feedbacks in crop models, the compounding effects of simultaneous climate hazards, and the limited data available from smallholder-dominated farming systems in low-income countries. Addressing these gaps is essential to formulating effective, equitable, and evidence-based responses to the climate–agriculture nexus.

Remote Sensing and Geo AI for Climate-smart Agriculture: From Monitoring and Mapping to Actionable Decision Support

2026-09-03T12:24:58+00:00

Climate-smart agriculture requires information systems that can detect crop and environmental change early enough, at spatial scales fine enough, and with sufficient reliability to alter management or policy decisions. Remote sensing now provides dense optical, radar, thermal and structural observations from satellites and uncrewed aerial vehicles, while geospatial artificial intelligence (GeoAI) can transform these observations into crop maps, phenological indicators, stress diagnostics, yield estimates and risk forecasts. This critical narrative review evaluates whether that technical progress has translated into dependable decision support for the three linked objectives of climate-smart agriculture: productivity, adaptation and, where feasible, mitigation. Literature published principally from 2015 to 15 June 2026 was identified through multidisciplinary scholarly sources and supplementary citation searching, with earlier seminal work retained when needed to establish methodological or operational context. Evidence was appraised for sensor suitability, reference-data quality, spatial and temporal validation, model transferability, uncertainty characterisation, decision relevance and implementation conditions. The strongest evidence supports crop-area and crop-type mapping, seasonal condition monitoring, phenology characterisation and several forms of yield and water-stress assessment, especially when multi-temporal optical data are complemented by synthetic aperture radar or targeted thermal and hyperspectral observations. Yet high mapping accuracy does not by itself establish climate-smart impact. Performance frequently deteriorates under spatial transfer, small and heterogeneous fields, cloud-related data gaps, shifting crop calendars and weak ground reference data. Deep learning and multimodal fusion improve representational capacity, but their advantage is contingent on training diversity, validation design and computational access. Operational systems such as GEOGLAM demonstrate that Earth observation becomes most useful when algorithmic outputs are combined with agronomic knowledge, field reports, institutional interpretation and explicit uncertainty. The central challenge is therefore no longer simply producing more accurate maps; it is building auditable, transferable and inclusive sensing-to-decision chains that connect observations to timely actions and measurable climate-smart outcomes.

Artificial Intelligence in Sustainable and Climate-Smart Dairy Farming: A Critical Narrative Review of Evidence, Limitations and Research Priorities

2026-09-08T09:54:47+00:00

Dairy production must expand to meet rising demand while reducing greenhouse gas emissions, using scarce feed, land and water more efficiently, and protecting animal welfare under a warming climate. Artificial intelligence is frequently presented as the technology capable of reconciling these objectives, yet the evidence supporting that expectation has developed unevenly. This critical narrative review examines the state of knowledge on artificial intelligence in sustainable and climate-smart dairy farming, with attention to the strength, consistency and methodological quality of the underlying research rather than to the volume of publication. Literature was identified through structured searching of open scholarly databases and indexes, supplemented by backward and forward citation searching and by examination of authoritative institutional sources, with a final search date of 15 June 2026. Four analytical domains are synthesised: estimation and mitigation of enteric methane; monitoring of health, welfare and productive efficiency as an indirect route to lower emission intensity; adaptation to thermal stress; and the systemic, economic and governance conditions that determine whether algorithmic capability becomes farm-level benefit. The evidence is strongest for narrow, well-instrumented detection tasks in intensive housed systems, where models trained on sensor and image data achieve performance approaching or exceeding trained human observers. It is substantially weaker for the claims that matter most to the climate-smart argument. Very few studies trace a validated causal path from improved prediction to measured reductions in emission intensity, and external validation across farms, breeds, housing systems and climates remains uncommon. Recurrent methodological weaknesses include data leakage through inappropriate partitioning, imprecise reference standards, incomplete reporting, and a pronounced concentration of evidence in high-income intensive systems. Economic evaluation is fragmentary, and governance questions concerning data ownership, transparency and the welfare implications of algorithmic management remain largely unresolved. Progress requires multi-farm external validation, prospective evaluation against emission and welfare outcomes rather than classification metrics alone, and deliberate investment in evidence from smallholder and pasture-based systems.

Enteric Methane Inhibitors in Dairy Cattle: A Critical Appraisal of Mechanisms, Efficacy and the Conditions Required for Translation

2026-09-08T10:01:50+00:00

Enteric fermentation in dairy cattle is a large and policy-relevant source of methane, and the past decade has produced two classes of compound capable of suppressing ruminal methanogenesis far more strongly than conventional dietary manipulation. The first acts by direct inhibition of methyl-coenzyme M reductase, the terminal enzyme of methanogenesis; the second delivers halogenated methane analogues, chiefly bromoform, from red macroalgae of the genus Asparagopsis. Both have moved from proof of concept to commercial or near-commercial deployment more quickly than the supporting evidence has matured, and existing reviews were largely written before the appearance of grazing trials, dose-by-diet interaction studies, residue and animal-health assessments, and full-lactation datasets that now qualify earlier optimism. This critical narrative review evaluates the mechanistic basis, quantitative efficacy, consistency, and translational limits of enteric methane inhibitors in dairy cattle, and distinguishes conclusions that are well supported from those that remain conditional. Evidence was drawn from scholarly databases and indexes searched to a defined end date, appraised for design adequacy, measurement method, exposure duration and confounding, and synthesised thematically around mechanism, efficacy, hydrogen disposal, delivery, safety and system-level translation. The available evidence supports a reproducible reduction of roughly one third in methane production when 3-nitrooxypropanol is delivered continuously in a mixed ration, with efficacy declining as dietary fibre increases and rising with dose. Macroalgal preparations can achieve larger reductions but do so with less consistency, with frequent depression of feed intake, with substantial instability in the concentration of the active compound, and with unresolved residue and animal-health questions. Nitrate occupies an intermediate position constrained by stoichiometry and toxicity. The dominant unresolved problems are not mechanistic but translational: intermittent exposure in grazing systems, the fate of spared metabolic hydrogen, the durability of responses across whole lactations, and the credibility of measurement for emissions accounting. Progress now depends less on discovering new inhibitors than on designing delivery, verification and governance systems adequate to the compounds already available.

Regional Case Studies in Climate-Adaptive Farming: Lessons from Dryland Systems Worldwide—Comparative Field Evidence from Sub-Saharan Africa, South Asia, MENA, and Latin America

2026-09-24T07:46:01+00:00

Agricultural systems in dryland regions feature high climatic variability, fragile soils, and limited access to supplementary irrigation, making them highly vulnerable to the combined impacts of climate change. Climate change is progressively undermining agricultural productivity across the world's dryland regions, threatening food security for hundreds of millions of smallholder farmers. This review synthesises comparative field evidence on climate-adaptive farming strategies drawn from four major dryland zones: Sub-Saharan Africa, South Asia, the Middle East and North Africa (MENA), and Latin America. Through a systematic appraisal of peer-reviewed literature, intergovernmental reports, and longitudinal field datasets published between 2000 and 2026, this review examines how farmers and policymakers in these regions have responded to rising temperatures, shifting precipitation regimes, increasing drought frequency, and soil degradation. The review covers a spectrum of adaptive approaches, including conservation agriculture, agroforestry integration, indigenous water harvesting technologies, drought-tolerant crop varieties, integrated soil fertility management, and climate-smart land-use planning. Comparative analysis reveals significant convergence in the biophysical underpinnings of successful adaptations across regions, while also exposing context-specific social, institutional, and economic constraints that determine adoption rates and long-term sustainability. Soil health management, landscape-scale water harvesting, and agricultural diversification constitute the biophysical core of effective dryland adaptation, delivering co-benefits for productivity, resilience, and ecosystem services simultaneously. Key lessons highlight the critical role of farmer agency, local ecological knowledge, gender-inclusive extension services, and supportive policy environments in scaling adaptive practices. The review also identifies persistent research gaps, particularly in the areas of long-term monitoring, systems-level assessments, and the political economy of institutional change. These findings have direct implications for research prioritisation, international development investments, and the design of national adaptation plans under the United Nations Framework Convention on Climate Change.