Human migration triggered by flooding will create sociodemographic, economic, and cultural challenges in coastal communities, and adaptation to these challenges will primarily occur at the municipal level. However, existing migration models at larger spatial scales do not necessarily capture relevant social responses to flooding at the local and municipal levels. Furthermore, projecting migration dynamics into the future becomes difficult due to uncertainties in human–environment interactions, particularly when historic observations are used for model calibration. This study proposes a stochastic agent-based model (ABM) designed for the long-term projection of municipal-scale migration due to repeated flood events. A baseline model is demonstrated initially, capable of using stochastic bottom-up decision rules to replicate county-level population. This approach is then combined with physical flood-exposure data to simulate how population projections diverge under different flooding assumptions. The methodology is applied to a study area comprising 16 counties in coastal Virginia and Maryland, U.S., and include rural areas which are often overlooked in adaptation research. The results show that incorporating flood impacts results in divergent population growth patterns in both urban and rural locations, demonstrating potential municipal-level migration response to coastal flooding.

Simulation of Flood-Induced Human Migration at the Municipal Scale: A Stochastic Agent-Based Model of Relocation Response to Coastal Flooding

This paper establishes a concept of the expansion capability order of complex system model from the perspective of structuralism, synthesizes the extension level from zero to second order to graphically represent the model architecture, and gives a parallel computing method for the “domain” with second-order scalability, as well as the corresponding estimation method and model of the upper bound of update time overhead. 

Second-order Scalable Complex System Modeling Framework and Parallelization Dynamics Method

Abstract Conservation efforts under the nature-based solutions (NbS) framework aim at better management of ecosystems and improvement of human well-being. Policies targeting forest-based livelihoods align well with the NbS principles, but their social-ecological outcomes are often confounded by complex human-environment interactions. In this study, we identify one major feedback effect of the ecosystem dynamic on people’s livelihoods based on datasets collected from two study areas in China and Nepal. Our methodology integrates satellite remote sensing, household surveys, and statistical models to investigate households’ cropland abandonment decisions under the influence of crop-raiding by wildlife. Results show that cropland parcels that have experienced crop-raiding are more likely to be abandoned in the following years. The more damage the crops have suffered on a given parcel, the more likely it is that the parcel will be abandoned. Parcels in proximity to natural forests, farther away from the house location, and with poorer access to paved roads bear a higher risk of being abandoned. These effects are robust and consistent after controlling for multiple parcel features and household characteristics at different levels and using the dataset from each study area separately. We conclude that policymakers need to consider this undesirable feedback of the ecological system to the livelihoods of local people to better achieve co-benefits for ecosystems and human society. 

Crop-raiding by wildlife and cropland abandonment as feedback from nature-based solutions: Lessons from case studies in China and Nepal

Enhancing wave parameters prediction: machine learning models combined with PCHIP

We studied the significance of stakeholder engagement in climate change adaptation within the context of coastal resilience. Our approach aimed to enhance collaboration in environmental planning processes by leveraging modeling tools to facilitate learning about the complexity of the socioecological system. A comprehensive questionnaire survey was conducted using Google Forms. The questionnaire included clear instructions and structured response formats, aiming to gather stakeholder perspectives on adaptation measures and define action thresholds in response to climate uncertainties. A total of 47 responses were received and included consulting firm professionals, freelance engineers, local authority professionals, port authority professionals, researchers, and university professors in the field of coastal management. The survey data were analyzed using statistical methods in SPSS to identify key insights and patterns. The survey findings offer valuable insights into the effectiveness of adaptation measures, threshold perceptions for initiating adaptation actions, and the dynamics of stakeholder perspectives. Therefore, the importance of incorporating diverse perspectives in climate change adaptation efforts is highlighted. As answers tend to vary for different stakeholder occupations, the urge for collaboration in future decision-making procedures is highlighted. By bridging the gap between stakeholder input and climate change adaptation measures, this study demonstrates the potential of participatory approaches in enhancing resilience and fostering sustainable development in coastal regions vulnerable to climate change. 

Climate Change Adaptation Strategies for Coastal Resilience: A Stakeholder Surveys

Global warming and climate variations are expected to alter hydrologic conditions and exacerbate flooding, primarily through increasingly frequent and intense storm events and sea-level rise. The interactions between coastlines and their inhabitants around the world are highly diverse, making them challenging to model due to the non-homogeneous, nonlinear, and complex nature of human decision-making. Agent-based modeling has proven valuable in various fields, enabling researchers to explore various social phenomena and emergent patterns under different institutional frameworks, including climate change scenarios and policy decisions, particularly at local scales. This approach is particularly useful in providing insights into possible outcomes and feedback resulting from the convergence of individual- and community-level adaptation decisions, and it has increasingly been used to model coastal systems. However, there are a limited number of studies that examine the effects of climate adaptation decisions on coastal tourism systems. This paper aims to address this gap by first providing an overview of the current state of agent-based modeling literature that explores coastal community adaptation responses to climate change. Subsequently, the paper argues for the application of these methods to simulate the effects of adaptation on coastal tourism dynamics. To better capture the interactions within subsystems and potential redistributed effects inherent in multi-scale and multi-stakeholder decision-making processes within these systems, we propose integrating agent-based modeling with a novel system of socio-environmental systems (SoSES) approach. This integration aims to assist city planners, policymakers, stakeholders, and attraction managers in effectively assessing adaptation options to safeguard their communities from the multifaceted impacts of climate change. 

A Review of Climate Adaptation Impacts and Strategies in Coastal Communities: From Agent-Based Modeling towards a System of Systems Approach

Agent-based modeling of the effects of conservation policies on social-ecological feedbacks between cropland abandonment and labor migration

Corrigendum to “Challenges, tasks, and opportunities in modeling agent-based complex systems”, Ecological Modeling, 2021, 457: 109,685, page 1–15

Measuring Neighborhood Impacts on Labor Out-Migration from Fanjingshan National Nature Reserve, China

Summary Protected areas (PAs) are critical for achieving conservation, economic and development goals, but the factors that lead households to engage in prohibited resource collection in PAs are not well understood. We examine collection behaviours in community forests and the protected Chitwan National Park in Chitwan, Nepal. Our approach incorporates household and ecological data, including structured interviews, spatially explicit data on collection behaviours measured with computer tablets and a systematic field survey of invasive species. We pair our data with a framework that considers factors related to a household’s demand for resources, barriers to prohibited resource collection, barriers to legal resource collection and alternatives to resource collection. The analysis identifies key drivers of prohibited collection, including sociodemographic variables and perceptions of an invasive plant (Mikania micrantha). The social-ecological systems approach reveals that household perceptions of the presence of M. micrantha were more strongly associated with resource collection decisions than the actual ecologically measured presence of the plant. We explore the policy implications of our findings for PAs and propose that employing a social-ecological systems approach leads to conservation policy and scientific insights that are not possible to achieve with social or ecological approaches alone.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/20E0CA8ECE4AB2F2DB952B00050334F5/S0376892922000121a.pdf/div-class-title-drivers-of-prohibited-natural-resource-collection-in-chitwan-national-park-nepal-div.pdf

Drivers of prohibited natural resource collection in Chitwan National Park, Nepal

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