Towards integrated management of Sandy Anthropogenic Shores: Exploring Human Natural Interactions
Elham Bakhshianlamouki is a PhD student in the department Coastal Systems and Nature-Based Engineering. (Co)Promotors are prof.dr. K. Wijnberg; prof.dr. A.A. Voinov and dr.ir. P.W.M. Augustijn from the faculty Engineering Technology, University of Twente.
Sandy Anthropogenic Shores (SAS) are coasts formed or heavily modified by moving large amounts of dredged sand from offshore to land. Natural processes like waves, wind, and currents then redistribute the sand, with wind helping to transport sand into the foredune area, reinforcing it for long-term coastal safety. SAS represents a modern, integrated approach to coastal management, balancing flood safety with ecological and recreational goals, though it remains in a "learning by doing" phase, with many aspects still not fully understood. Most existing research has focused primarily on the flood safety functions of SAS in relation to natural processes, overlooking the complex interactions between human activities and biophysical systems, as well as the implications for the multifunctionality of these systems, which are key for integrated management. Therefore, this study aims to provide insights into the influence of human activities, including management and recreational activities, on the landscape dynamics of SAS, exploring their spatial and temporal interactions with biophysical elements of the system such as vegetation cover and recreational facilities. These insights will inform management practices, highlighting plausible impacts of human activities and considerations for integrated SAS management.
In the first step of the study (First Objective), the Participatory Modelling (PM) approach was employed to investigate the role of management activities and their interactions with biophysical systems in SAS. Through multiple interviews and workshops with diverse stakeholders, discussions were facilitated to identify management objectives, activities, key socio-biophysical drivers, their interactions, and managerial indicators for analysing the multifunctionality of SAS. The insights gathered from stakeholders were organised into a collective cognitive map (CCM), which served as a tool for qualitatively assessing how specific management decisions affect trade-offs among the various functions of SAS. The CCM revealed the complexity of the system, illustrating the interconnected relationships between elements and their collective influence on the multifunctionality of SAS. This mapping process represents a critical step in consolidating the fragmented knowledge accumulated since SAS were established. Furthermore, the CCM offers several key benefits by facilitating stakeholder discussions, enabling qualitative assessments of the system, identifying knowledge gaps, and informing the development of quantitative models.
In the second step of the study (Second Objective), surveys were conducted among beach visitors at the Sand Motor and Hondsbossche Dunes to explore their attitudes toward SAS and recreational behaviour. Drawing from insights gained through stakeholder engagement and the CCM, several beach visitor surveys were carried out across different seasons, primarily during summers from 2021 to 2023. The surveys examined motivations for visiting, opinions on landscape features, preferences for specific beach areas and activities, facility needs, and seasonal visitation trends, using both multiple-choice and open-ended responses. To analyse visitor behaviour, they were categorised into three types: local, one-day, and overnight visitors. The analysis identified three distinct visitor motivation clusters: socialising, relaxation while appreciating beach landscapes, and engaging in sports activities. The study found that landscape features such as beach width, natural elements (embryo dunes, vegetation cover), features like lagoons or lakes, and the dynamic nature of the landscape are key factors in attracting nature lovers, who constitute the majority of SAS visitors. Moreover, SAS visitors expressed satisfaction with the current beach width, highlighting their appreciation for the spaciousness and sense of freedom it provides. Insights into beach visitors’ preferences and behaviours provide valuable guidance for designing new SAS landscapes and recreational activities management. The dynamic nature of SAS environments, with changing morphology, water bodies, and vegetation, makes understanding visitor preferences essential for anticipating how evolving landscapes affect visitor types, numbers, and activities. This knowledge supports adaptive recreation policies that align with SAS changes while addressing visitor needs. The survey findings also informed the development of an ABM to simulate recreational behaviour.
From the analysis performed for the First and Second objectives, it became evident that the interactions between human activities and the biophysical system are highly complex, making it challenging to comprehensively address this complexity within the scope of the research. As a result, this study focuses on a specific aspect of this complexity: the interactions between recreational activities and vegetation dynamics, which represent an important but underexplored human-biophysical interaction in SAS. To address this gap, an Agent Based Modelling (ABM) approach was employed to simulate these interactions through two interconnected sub-models: Recreational Dynamics and Vegetation Dynamics.
The Third Objective aims to explore how the arrangement of services, recreational facilities, and weather conditions influence visitation intensity and, consequently, the landscape's biophysical characteristics, such as vegetation. So, the Recreational Dynamics sub-model focuses on the spatial behaviour and temporal dynamics of beach visitors, analysing their numbers, activities, and distribution in response to landscape design. By monitoring visitation intensity, the model identifies areas most impacted by visitor activity. The model assessed the effects of changes in landscape layout such as introducing facilities like restaurants, entrances, or parking on areas with intensive and low visitation intensity. Scenario analysis highlights the model's effectiveness for analysing the interactions between SAS landscape layout, weather conditions, and visitation intensity.
The Fourth Objective focuses on exploring the cumulative impact of environmental factors (e.g., weather conditions, sediment moisture, sand burial) and beach visitor movement on vegetation distribution and dispersal, particularly during initial growth phases. To achieve this objective, the vegetation sub-model was developed and integrated with recreation sub-model, simulating vegetation establishment based on four main processes: growth, reproduction, germination, and mortality, using parameters such as growth temperature thresholds, growth rates, and germination rates. The model's dynamics rely on input data for key ratios, such as germination by seed, germination by rhizome, vertical growth, and horizontal growth. Parameter values were chosen based on a combination of literature and calibration. However, due to a lack of empirical data, the values of these parameters remained uncertain, which affects the model's accuracy. To address this issue, a sensitivity analysis was performed to identify which parameters have the most significant impact on the model's predictions. The results indicated that variations in horizontal growth rates were the most influential factor affecting the model's ability to replicate real-world vegetation patterns, followed by minimum germination rates by seed, and finally, temperature thresholds for growth and germination (maximum and minimum).
The outcomes of each recreation and vegetation sub-model inform and influence one another, creating a comprehensive analysis of the interaction between recreational activities and vegetation growth and development. In an area with high visitation intensity, the mortality ratio of vegetation is higher. We used the Recreation-Vegetation ABM to analyse the impact of various scenarios on vegetation development, such as changes in recreational activity patterns, facility layouts, and weather conditions. The results from our analysis using the ABM demonstrated that the interactions among recreational facility layouts, weather conditions, recreational activities, and vegetation development are highly complex and sensitive to the parameters considered.
This study takes initial steps to develop a model simulating the interaction between human activities and biophysical systems, with a focus on the interplays between vegetation development and recreational activities. The results reveal the interconnectedness of various factors, which adds complexity to the system despite efforts to maintain simplicity. While uncertainties in the quantitative values assigned to some model parameters may influence the outcomes, scenario analyses provide valuable semi-quantitative insights for decision-making. These insights include trends in vegetation area (upward or downward), vegetation spread patterns, and areas experiencing high or low visitation impacts under varying weather conditions and landscape layouts. Such insights are crucial for balancing the ecological and recreational functions of the system. The current ABM, however, does not account for morphological dynamics, an essential factor influencing all system functions. Further development of the model should aim to integrate all three functions of the SAS by coupling the ABM with existing models, such as DUBEVEG, which simulate morphological changes in the SAS.
