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abstract: Farmers have time and again adopted new methods or technologies. However, recent increases in global temperatures and occurrences of extreme weather events, call for an urgency to address and reduce the risks associated with climate change. Irrigation is a key adaptation that reduces crop heat stress and enhances agricultural production. Alabama is considered water-rich but lately has experienced increased rainfall variability and temperature extremes. Various state-wide initiatives to increase irrigation have been implemented, but adoption remains limited. Existing studies have explored factors influencing irrigation uptake, but none have engaged in a state-level assessment of its adoption potential. In this study, we provide spatially explicit estimates of the potential to implement irrigation practices across the state. Moreover, we derive an irrigation adoption index map for Alabama to identify areas where implementation is more or less likely based on a multi-criteria analysis. The results highlight a large potential for expansion in areas that have high shares of existing irrigation. Such an analysis can enable targeted mobilization of resources towards areas where uptake is currently low but feasible through increased adaptation efforts. Additionally, these estimates can be further used to evaluate future water demands or conduct other regional analyses. 

Abstract Achieving large-scale, transformative climate change adaptations in agriculture while mitigating further climate impacts and supporting sustainable and equitable rural livelihoods is a grand challenge for society. Transformation of the agri-food system is necessary and inevitable, but the extent to which transformation can be intentionally guided toward desirable states remains unclear. We argue that instead of targeting leverage points in isolation, coordinated interventions multiple leverage points and their interactions are necessary to create broader system transformation towards more adaptive futures. Using the Southeastern U.S. as a case study, we conceptualize a way of doing transformation research in agri-food systems that integrates multiple theoretical and practical perspectives of how transformative pathways can be constructed from ‘chains’ of interacting leverage points. We outline several principles for transformative research; the core of which are participatory, transdisciplinary, and convergence research methods needed for articulating a shared vision. These principles embrace an action-oriented approach to research in which the act of assembling diverse networks of researchers, stakeholders, and community partners itself can activate community- and regional-level leverage points to scale-up changes. Finally, we present tangible examples of specific leverage points and their interactions targeted by agri-food systems interventions currently underway or planned. This work offers an ‘anticipatory’ vision for agri-food systems transformation research that recognizes the need to normatively create an enabling environment to build momentum toward shared visions of secure, equitable, and sustainable regional agri-food systems. 

Responding to the challenges of societal transformation in the face of climate change, efforts to integrate behaviorally rich models of adaptation decision-making into large-scale macroeconomic and Earth system models are growing and agent-based models (ABMs) are an effective tool for doing so. However, behavioral richness in ABMs has been limited to implementations of single decision models for all agents in a simulated population. The main goals of this study were to: 1) implement the ‘building-block processes’ (BBPs) approach for decision model heterogeneity; 2) demonstrate the application of sensitivity and uncertainty analyses to quantify the scope of structural uncertainty produced by alternative decision models under variable price and climate conditions; and 3) apply the Observing System Simulation Experiment (OSSE) approach to validate such a behaviorally rich BBPs model at the level of individual agent decisions. Using an ABM of agricultural producers’ decision-making, we demonstrated that uncertainty in crop and farm management decisions introduced by heterogeneous decision models was equal to and in some instances greater than that due to variable price or precipitation conditions. Unrealistically rapid or stagnant behavioral dynamics were evident in model versions implementing single decision models for all agents. Moreover, interactions among agents with diverse decision models in the same population produced consistently more accurate outcomes and realistic behavioral dynamics. The BBPs framework and accompanying sensitivity and uncertainty analyses demonstrated here offer a path forward for increasing behavioral richness in ABMs, which is key to understanding processes of adaptation central to societal responses to climate change. 

For decades, nations around the world have been promoting irrigation expansion as a method for improving agricultural growth, smoothing production risk, and alleviating rural poverty. Despite its apparent advantages, suboptimal adoption rates persist. According to the existing literature, determinants of irrigation adoption are often highly dependent on cultural, contextual, and/or local institutional factors. Yet, studies from diverse geographies identify a consistent set of factors. Thus, to be able to make generalizable inferences from such studies, a global geographic representativeness assessment of irrigation adoption studies was conducted to determine whether identified factors influencing irrigation were the result of geographic, epistemological, or disciplinary biases. The results indicate that multiple geographic biases exist with respect to studying farmers’ irrigation adoption decision-making. More research on this topic is being conducted in regions that have little to a high percentage of irrigation (>1%), are readily accessible, receive moderate amounts of average annual rainfall, and have moderate amounts of cropland cover. The results suggest the need to expand research efforts in areas with little to no irrigation to identify constraints and help accelerate economic growth, poverty reduction, and food and livelihood security for rural communities in these regions. 

Rates of poverty and economic inequality in rural Alabama are among the nation's highest and increasing agricultural productivity can provide a needed boost to these communities. The transition from rain-fed to irrigation-fed (RFtoIF) agriculture has significantly increased farm productivity and profitability elsewhere in the United States. Despite this potential to enhance stability and resilience in rural economies, irrigated cropland accounts for only 5% of Alabama's total cropland as numerous barriers remain to irrigation adoption. To encourage RFtoIF transition, it is imperative to identify the challenges faced by individual farmers at farm, community, and state levels. This study presents a multi-level mixed effects survival analysis to identify the physiographic, socioecological, and economic factors that influence the location and timing of irrigation adoption. We integrate spatiotemporal cropland and climatological data with field-verified locations of center-pivot irrigation systems, local physiographic characteristics, and parcel-level surface water access and average well depth. Access to surface water, costs to access groundwater, and soil characteristics were generally important influences in all regions, but regions were differentiated by the extent to which new irrigation was more responsive to social influences vs. precipitation and price trends. Our findings also highlighted the diversity of farming conditions across the state, which suggested that diverse policy tools are needed that acknowledge the varying motivations and constraints faced by Alabama's farmers.