Contemporary issues in agriculture and natural resource management (AGNR) span a wide spectrum of challenges and scales—from global climate change to resiliency in national and regional food systems to the sustainability of livelihoods of small-holder farmers—all of which may be characterized as complex problems. With rapid development of tools and technologies over the previous half century (e.g., computer simulation), a plethora of disciplines have developed methods to address individual components of these multifaceted, complex problems, oftentimes neglecting unintended consequences to other systems. A systems thinking approach is needed to (1) address these contemporary AGNR issues given their multi- and interdisciplinary aspects; (2) utilize a holistic perspective to accommodate all of the elements of the problem; and (3) include qualitative and quantitative techniques to incorporate “soft” and “hard” elements into the analyses. System dynamics (SD) methodology is uniquely suited to investigate AGNR given their inherently complex behaviors. In this paper, we review applications of SD to AGNR and discuss the potential contributions and roles of SD in addressing emergent problems of the 21st century. We identified numerous SD cases applied to water, soil, food systems, and smallholder issues. More importantly, several case studies are shown illustrating the tradeoffs between short-term and long-term strategies and the pitfalls of relying on quick fixes to AGNR problems (known as “fixes that backfire” and “shifting the burden”, well-known, commonly occurring, systemic structures—or archetypes—observed across numerous management situations [Senge, P.M. The Fifth Discipline, 1st ed.; Doubleday: New York, NY, USA, 1990.]). We conclude that common attempts to alleviate AGNR problems, across continents and regardless of the type of resources involved, have suffered from reliance on short-term management strategies. To effectively address AGNR problems, longer-term thinking and strategies aimed at fundamental solutions will be needed to better identify and minimize the often delayed, and unintended, consequences arising from feedback between management interventions and AGNR systems.

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community‐managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally‐managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.

Agriculture-based irrigation communities of northern New Mexico have survived for centuries despite the arid environment in which they reside. These irrigation communities are threatened by regional population growth, urbanization, a changing demographic profile, economic development, climate change, and other factors. Within this context, we investigated the extent to which community resource management practices centering on shared resources (e.g., water for agricultural in the floodplains and grazing resources in the uplands) and mutualism (i.e., shared responsibility of local residents to maintaining traditional irrigation policies and upholding cultural and spiritual observances) embedded within the community structure influence acequia function. We used a system dynamics modeling approach as an interdisciplinary platform to integrate these systems, specifically the relationship between community structure and resource management. In this paper we describe the background and context of acequia communities in northern New Mexico and the challenges they face. We formulate a Dynamic Hypothesis capturing the endogenous feedbacks driving acequia community vitality. Development of the model centered on major stock-and-flow components, including linkages for hydrology, ecology, community, and economics. Calibration metrics were used for model evaluation, including statistical correlation of observed and predicted values and Theil inequality statistics. Results indicated that the model reproduced trends exhibited by the observed system. Sensitivity analyses of socio-cultural processes identified absentee decisions, cumulative income effect on time in agriculture, and land use preference due to time allocation, community demographic effect, effect of employment on participation, and farm size effect as key determinants of system behavior and response. Sensitivity analyses of biophysical parameters revealed that several key parameters (e.g., acres per animal unit or percentage of normal acequia ditch seepage) which created less variable system responses but which utilized similar pathways to that of the socio-cultural processes (e.g., socio-cultural or physical parameter change → agricultural profit → time in spent in agriculture → effect on socio-cultural or physical processes). These processes also linked through acequia mutualism to create the greatest variability in system outputs compared to the remainder of tests. Results also point to the important role of community mutualism in sustaining linkages between natural and human systems that increase resilience to stressors. Future work will explore scenario development and testing, integration with upland and downstream models, and comparative analyses between acequia communities with distinct social and landscape characteristics.

Due to tightly coupled physical, chemical, and biological processes that often behave in nonlinear, counterintuitive ways, it is argued that soil is an archetype of a complex system. Unfortunately, human intuition and decision making has been shown to be inadequate when dealing with complex systems. This poses significant challenges for managers or policy makers responding to environmental externalities where soil dynamics play a central role (e.g., biogeochemical cycles) and where full ranges of outcomes result from numerous feedback processes not easily captured by reductionist approaches. In order to improve interpretation of these soil feedbacks, a dynamic systems framework is outlined (capturing feedback often excluded from investigation or left to intuition) and then applied to agroecosystem management problems related to irrigation or tillage practices that drive nutrient cycling (e.g., soil water, nitrogen, carbon, and sodium). Key soil feedbacks are captured via a variety of previously developed models simulating soil processes and their interactions. Results indicated that soil system trade-offs arising from conservation adoption (drip irrigation or no-tillage) provided reasonable supporting evidence (via compensating feedbacks) to managers justifying slow adoption of conservation practices. Modeling soils on the foundation provided in the complex systems sciences remains an area for innovations useful for improving soil system management.

Grassland conversion to row-crop production in the north central United States has been a growing threat to socio-economic and environmental sustainability for producers, conservationists, and policy-makers alike. We used a system dynamics model of the region to forecast agriculturally driven land transformation through mid-twenty-first century. The base-case scenario projection showed that farmland area continued to increase, from under 200,000 km² to over 230,000 km². Unmitigated, the soil environmental risk (SER) of such changes reached conservative estimates of Dust Bowl-era externalities. Systems analyses show that reducing livestock production costs, doubling conservation compliance requirements, and livestock–cropping integration had the largest impact on grassland conservation and mitigating SER. The largest SER effects came from eliminating conservation incentives or raising cultivation incentives, despite improvements in reduced tillage and enhanced agronomy. Several system archetypes were identified within the policy scenarios: ‘fixes that backfire’ and ‘success-to-the-successful’. For scenarios creating favourable impacts, time delays caused some behaviours to worsen before positive gains were realized. If implemented, patience and persistence to ensure that these scenarios reach their full potential will be necessary. Our scenarios provide quantitative forecasts around measures for sustainable intensification. These projections can aid regional stakeholders in enhancing discussions currently taking place about sustainable agriculture in the region.