•Land use model are a central tool in land system science.•There is a lack of new land use modelling concepts published in recent years.•Land use models are frequently insufficiently ...evaluated.•Opportunities to better represent human agency in land use models are identified.•There is large potential for land use models to contribute to the identification and design of sustainability solutions.
Land use models play an important role in exploring future land change dynamics and are instrumental to support the integration of knowledge in land system science. However, only modest progress has been made in achieving these aims due to insufficient model evaluation and limited representation of the underlying socio-ecological processes. We discuss how land use models can better represent multi-scalar dynamics, human agency and demand-supply relations, and how we can achieve learning from model evaluation. By addressing these issues we outline pathways towards a new generation of land use models that allow not only the assessment of future land cover pattern changes, but also stimulate envisioning future land use by society to support debate on sustainability solutions and help design alternative solutions.
Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters ...the spatial dynamics of human‐wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent‐based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife‐human interactions in shared landscapes WHISL). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation‐planning tool because it provides a test bed for theories and predictions about human‐wildlife dynamics across a range of different agricultural landscapes.
Resultados Emergentes de Conservación de la Percepción Compartida sobre Riesgos en los Sistemas Humanos – Fauna
Resumen
La percepción humana de los riesgos relacionados con los daños económicos causados por la fauna vecina puede transmitirse por medio de las redes sociales. El entendimiento de cómo la propagación de la información sobre riesgos dentro de una comunidad humana altera las dinámicas espaciales de las interacciones humanos – fauna tiene implicaciones importantes para el diseño e implementación de las acciones de conservación efectiva. Desarrollamos un modelo basado en agentes que simula las decisiones y las actividades de subsistencia de los agricultores en un paisaje agrícola compartido con una especie genérica de fauna (interacciones humanos – fauna en paisajes compartidos WHISL, en inglés). En el modelo, con base en la percepción del riesgo y en la información económica, los agricultores decidieron cuánto trabajo asignar a la agricultura y si y en dónde excluir a la fauna de sus parcelas (por ejemplo, por medio de cercas, fosas o la reducción de la vegetación). En los escenarios en los que la percepción de riesgo de los agricultores estuvo fuertemente influenciada por otros agricultores, la exclusión de la fauna estuvo generalizada, lo que resultó en una disminución de la calidad del hábitat de la fauna y en la frecuencia de daños causados por los animales a lo largo del paisaje. Cuando las pérdidas económicas causadas por los encuentros con la fauna fueron altas, la percepción del riesgo incrementó y resultó en comportamientos altamente sincrónicos adoptados por los agricultores en el tiempo y el espacio. Las interacciones entre la fauna y los agricultores a veces resultaron en un efecto de derrama de daños causados por la fauna desplazada de las comunidades conectadas social y espacialmente hacia parcelas vecinas con una menor conexión. El modelo WHISL es una herramienta útil para la planificación de la conservación porque proporciona una plataforma de experimentación para las teorías y predicciones sobre las dinámicas humano – fauna en una extensión geográfica de diferentes paisajes agrícolas.
摘要
人类对附近野生动物造成经济损失的风险感知可以通过社会网络传播。理解人类社会中共享风险信息如何改变人类与野生动物互作的空间动态, 对设计和实施有效保护行动具有重要意义。我们开发了一种基于主体的模型, 以模拟存在野生动物种群的农业景观中农场主的生计决策和活动 (共享景观中的野生动物‐人类互作) 。在这个模型中, 农场主根据风险感知和经济方面的信息来决定如何分配农作劳动、是否以及在哪里将野生动物驱逐到农场之外 (如通过建围栏、挖沟渠或减少植被覆盖) 。在农场主的风险感知受到其它农场主强烈影响的情况下, 农场主普遍会驱逐野生动物, 导致整个景观中野生动物生境质量下降, 野生动物造成破坏的频率也下降。当遭遇野生动物造成的经济损失较高时, 农场主对风险的感知会增加, 从而导致他们的行为在时空上高度同步。野生动物和农场主之间的互作有时候也会产生溢出效应, 使野生动物造成的破坏从社会及空间上紧密联系的社区转移到联系不够紧密的临近农场。本研究的共享景观中野生动物‐人类互作模型是一种有效的保护规划工具, 为不同农业景观中人类‐野生动物动态变化的理论和预测提供了试验平台。 【翻译: 胡怡思; 审校: 聂永刚】
Article impact statement: Sharing of risk perception in social networks alters spatial patterns of human‐wildlife interactions, sometimes creating spillover effects.
While a growing proportion of global food consumption is obtained through international trade, there is an ongoing debate on whether this increased reliance on trade benefits or hinders food ...security, and specifically, the ability of global food systems to absorb shocks due to local or regional losses of production. This paper introduces a model that simulates the short-term response to a food supply shock originating in a single country, which is partly absorbed through decreases in domestic reserves and consumption, and partly transmitted through the adjustment of trade flows. By applying the model to publicly-available data for the cereals commodity group over a 17 year period, we find that differential outcomes of supply shocks simulated through this time period are driven not only by the intensification of trade, but as importantly by changes in the distribution of reserves. Our analysis also identifies countries where trade dependency may accentuate the risk of food shortages from foreign production shocks; such risk could be reduced by increasing domestic reserves or importing food from a diversity of suppliers that possess their own reserves. This simulation-based model provides a framework to study the short-term, nonlinear and out-of-equilibrium response of trade networks to supply shocks, and could be applied to specific scenarios of environmental or economic perturbations.
The nexus of food, energy, and water systems (FEWS) has become a salient research topic, as well as a pressing societal and policy challenge. Computational modeling is a key tool in addressing these ...challenges, and FEWS modeling as a subfield is now established. However, social dimensions of FEWS nexus issues, such as individual or social learning, technology adoption decisions, and adaptive behaviors, remain relatively underdeveloped in FEWS modeling and research. Agent-based models (ABMs) have received increasing usage recently in efforts to better represent and integrate human behavior into FEWS research. A systematic review identified 29 articles in which at least two food, energy, or water sectors were explicitly considered with an ABM and/or ABM-coupled modeling approach. Agent decision-making and behavior ranged from reactive to active, motivated by primarily economic objectives to multi-criteria in nature, and implemented with individual-based to highly aggregated entities. However, a significant proportion of models did not contain agent interactions, or did not base agent decision-making on existing behavioral theories. Model design choices imposed by data limitations, structural requirements for coupling with other simulation models, or spatial and/or temporal scales of application resulted in agent representations lacking explicit decision-making processes or social interactions. In contrast, several methodological innovations were also noted, which were catalyzed by the challenges associated with developing multi-scale, cross-sector models. Several avenues for future research with ABMs in FEWS research are suggested based on these findings. The reviewed ABM applications represent progress, yet many opportunities for more behaviorally rich agent-based modeling in the FEWS context remain.
In the global South, a rush of large-scale land acquisitions (LSLAs) is occurring by governments and transnational and domestic investors seeking to secure access to land in developing countries to ...produce food, biofuels, and other agricultural commodities. Complex interactions between regional and global market dynamics and local institutional, socioeconomic, and agro-ecological conditions can lead to widely varying causal processes, land-use change (LUC), and socioeconomic and environmental outcomes. Systematic understanding of how characteristics of LSLAs across multiple social and environmental contexts produce spillover effects on local communities, ranging from employment opportunities to displacement and indirect land-use change (iLUC), is lacking. We conceptualize agricultural commodity production and land-acquisition processes associated with LSLAs as catalyzing causal pathways of direct and indirect land-use changes. Using the case of economic land concessions (ELCs) in Cambodia, we employed a novel synthesis research approach combining remote sensing, spatio-temporal statistics, and case study meta-analysis to construct archetypical pathways of the causes, timing, and consequences of ELC-driven land change. Archetypical pathways generally diverged based on specialized or flex commodity crops and rates of direct LUC, and rapid rates of direct LUC tended to cause displacement and iLUC. In contrast, ELCs producing commodity crops associated with more gradual land-use change and/or organized local resistance lead to less iLUC. Systematic knowledge generated through synthesis of local causes and consequences of LSLA-driven land change is now possible and needed to better address the direct and indirect consequences of LSLAs for commodity crop production.
Large-scale land acquisitions (LSLAs) have received considerable scholarly attention over the last decade, and progress has been made towards quantifying their direct impacts. There is also a growing ...recognition of the importance of indirect effects of LSLAs, such as 'spillover' or indirect land-use change (iLUC), and the substantial challenges they pose for attribution and quantification. In fact, the relative contributions of direct and indirect LUC associated with LSLAs are unknown. This study aims to address these knowledge gaps using Economic Land Concessions (ELCs) in Cambodia, now the most targeted country for LSLAs in Southeast Asia. We leverage findings on archetypical pathways of direct and indirect LUC in Cambodia, developed through previous mixed-methods synthesis efforts, to quantify remotely sensed forest loss to specific ELCs. During 2000-2016, Cambodia roughly 1611 kha of forest, or 22% of total forest cover. Although ELCs (as of 2016) contained roughly 16% of Cambodia's forest cover (2000), forest lost within ELC boundaries accounted for nearly 30% (476 kha) of total forest lost by 2016. Furthermore, iLUC contributed an additional 49-174 kha of forest loss (3.0%-10.7% of all forest lost in Cambodia) over the same period. Thus, iLUC contributed to Cambodia's total forest loss at the rate of 11.4%-40.8% of direct LUC caused by ELCs. Such findings suggest that the total amount of LUC caused by LSLAs may well be underestimated globally. This and related synthesis research efforts can be valuable approaches for better targeting remote sensing analyses to specific locations and time periods needed to disentangle and quantify forest loss due to direct and indirect land change processes.
Rural populations are undergoing rapid changes in both their livelihoods and land uses, with associated impacts on ecosystems, global biogeochemistry, and climate change. A primary challenge is, ...thus, to explain these shifts in terms of the actors and processes operating within a variety of land systems in order to understand how land users might respond locally to future changes in broader-scale environmental and economic conditions. Using 'induced intensification' theory as a benchmark, we develop a generalized agent-based model to investigate mechanistic explanations of relationships between agricultural intensity and population density, environmental suitability, and market influence. Land-use and livelihood decisions modeled from basic micro-economic theories generated spatial and temporal patterns of agricultural intensification consistent with predictions of induced intensification theory. Further, agent actions in response to conditions beyond those described by induced intensification theory were explored, revealing that interactions among environmental constraints, population pressure, and market influence may produce transitions to multiple livelihood regimes of varying market integration. The result is new hypotheses that could modify and enrich understanding of the classic relationship between agricultural intensity and population density. The strength of this agent-based model and the experimental results is the generalized form of the decision-making processes underlying land-use and livelihood transitions, creating the prospect of a virtual laboratory for systematically generating hypotheses of how agent decisions and interactions relate to observed land-use and livelihood patterns across diverse land systems.
Counterdrug interdiction efforts designed to seize or disrupt cocaine shipments between South American source zones and US markets remain a core US “supply side” drug policy and national security ...strategy. However, despite a long history of US-led interdiction efforts in the Western Hemisphere, cocaine movements to the United States through Central America, or “narco-trafficking,” continue to rise. Here, we developed a spatially explicit agent-based model (ABM), called “NarcoLogic,” of narco-trafficker operational decision making in response to interdiction forces to investigate the root causes of interdiction ineffectiveness across space and time. The central premise tested was that spatial proliferation and resiliency of narco-trafficking are not a consequence of ineffective interdiction, but rather part and natural consequence of interdiction itself. Model development relied on multiple theoretical perspectives, empirical studies, media reports, and the authors’ own years of field research in the region. Parameterization and validation used the best available, authoritative data source for illicit cocaine flows. Despite inherently biased, unreliable, and/or incomplete data of a clandestine phenomenon, the model compellingly reproduced the “cat-and-mouse” dynamic between narco-traffickers and interdiction forces others have qualitatively described. The model produced qualitatively accurate and quantitatively realistic spatial and temporal patterns of cocaine trafficking in response to interdiction events. The NarcoLogic model offers a much-needed, evidence-based tool for the robust assessment of different drug policy scenarios, and their likely impact on trafficker behavior and the many collateral damages associated with the militarized war on drugs.
•Generalized knowledge claims (GKC) link site observations to broader-scale changes.•GKCs on the causes or effects of global environmental change are increasingly contested.•A standard approach is ...presented for assessing/producing robust and transparent GKCs.•A typology and evaluation criteria are applied to two illustrative GKCs.•This approach aims to strengthen future synthesis efforts and support peer-review.
Concerns over rapid widespread changes in social-ecological systems and their consequences for biodiversity, ecosystem functioning, food security, and human livelihoods are driving demands for globally comprehensive knowledge to support decision-making and policy development. Claims of regional or global knowledge about the patterns, causes, and significance of changes in social-ecological systems, or ‘generalized knowledge claims’ (GKCs), are generally produced by synthesis of evidence compiled from local and regional case study observations. GKCs now constitute a wide and varied body of research, yet they are also increasingly contested based on disagreements about their geographic, temporal, and/or thematic validity. There are no accepted guidelines for detecting biases or logical gaps between GKC’s and the evidence used to produce them. Here, we propose a typology of GKCs based on their evidence base and the process by which they are produced. The typology is structured by three dimensions: i) the prior state of knowledge about the phenomenon of interest; ii) the logic of generalization underlying the claim; and iii) the methodology for generalization. From this typology, we propose a standardized approach to assess the quality and commensurability of these dimensions for any given GKC, and their ability to produce robust and transparent knowledge based on constituent evidence. We then apply this approach to evaluate two contested GKCs – addressing global biodiversity and large-scale land acquisitions – and in doing so demonstrate a coherent approach to assessing and evaluating the scope and validity of GKCs. With this approach, GKCs can be produced and applied with greater transparency and accuracy, advancing the goal of actionable science on social-ecological systems.
Social and economic costs in coastal zones resulting from natural hazard events, such as hurricanes, are increasing. Household residential location decisions and adaptive behaviors (i.e., purchasing ...insurance) are influenced by perceived risk of storms events, and can have long-term consequences for development patterns and regional resilience. Perceived risks may be capitalized into housing prices in hazardous areas, but the attraction of coastal amenities may dampen market responses to risk information. Empirical studies provide contradictory conclusions about the effect of storm events on housing market dynamics, and thus the decision-making processes leading to post-storm residential location and insurance purchase choices remain unclear. Here, an economic agent-based model (ABM) of coupled housing and land markets (CHALMS), adapted to a coastal setting, or C-CHALMS, is used to investigate alternative decision-making models and associated behavioral mechanisms driving post-storm responses. A pattern-oriented modeling (POM) and abductive reasoning approach is used to compare the ability of alternative decision-making models to explain empirical patterns of housing and insurance market dynamics. By explicitly modeling individual decision-making, results demonstrate that post-storm location and insurance purchasing decisions vary greatly within a coastal landscape. Coastal amenities dampen the effects of storm events on housing price dynamics for properties immediately adjacent to the coast, while areas with the lowest risk of damages (and lowest coastal amenities) are most responsive to storm events. Further, psychological factors, such as the perceived salience of positive and negative consequences, explain dynamics of insurance policy uptake after storms better than rational economic decision-making alone.
•Household residential location and mitigation decisions are adaptive and subjective.•Empirical analysis of post-storm market dynamics do not elucidate adaptive decision-making processes.•Mechanisms of subjective risk perception and psychological biases in post-storm responses investigated.•Post-storm location and insurance purchasing decisions vary greatly within a coastal landscape.•Perceived salience of positive and negative consequences explain dynamics of insurance policy uptake better than economic decision-making alone.
PDF
