Applying agent-based models to predict social-ecological dynamics in mangrove systems

Overview

Conserving biodiversity and maintaining the sustainable use of limited natural resources is a defining challenge of the 21st century. Increasingly, conservation goals are coming into conflict with goals that focus on food security and sustaining human livelihoods and well-being [1]. It is therefore critical to understand how both social and ecological dynamics jointly affect sustainability [2]. To predict the dynamics of social-ecological systems, models that integrate social and ecological processes are needed.

Mangrove forests are one of the most productive ecosystems on Earth, and they provide a wealth of goods and services including the following: food security, clean water provision, climate regulation, soil quality maintenance, coastal protection and recreational and spiritual space. Mangrove forests therefore have value by sustaining the livelihoods of millions of people, but also have real value in economic terms. However, over the past 50+ years, conflict between mangrove natural resources and human activity has developed, threatening the long-term survival of this globally important ecosystem. In order to succeed, mangrove conservation efforts need to consider both the natural resource and sensitivity towards local human livelihoods, enabling economic development in a sustainable way.

This project will develop and use individual-based (i.e., agent-based) models (IBMs) to simulate the social-ecological dynamics of mangrove systems in northern Vietnam. IBMs model discrete individuals using computer code, and can simulate complex systems in silico [3,4]. Interacting environmental, ecological, and social processes in the mangrove system will be modelled by developing the recently published GMSE R package (Generalised Management Strategy Evaluation) [5].

Research Objectives:

The primary objective is to develop and simulate new IBMs to predict ecological and social change in the mangrove system of the Xuan Thuy National Park, northern Vietnam, as a consequence of different proposed management decisions. Model development could also allow prediction of the effects of climate change (e.g. global warming) and the value of carbon storage in the mangrove system, or evaluation of the long-term benefit of mangrove shoreline protection versus land use development for aquaculture.

The student will address the following sub-objectives in the course of their research:

1. Develop a spatially-explicit social- ecological IBM that incorporates mangrove ecology and stakeholder behaviour within GMSE.

2. Parameterise their IBM using social and ecological data collected from the mangrove system in Vietnam.

3. Predict how social and ecological processes in the mangrove system will change as a consequence of changing environmental factors and different management policy options.

The student should have a background or strong interest in computer programming (ideally in R, C, or C++). They should also be interested in applying social-ecological models to real-world systems involving conservation and resource management. The student will benefit from supervisor expertise in theory, modelling, conservation biology and environmental sciences. They will also have the opportunity to interact with a wide network of international collaborators and stakeholders (e.g. local conservation organisations, national park rangers, fishers, farmers, tourism operators).

Click on an image to expand

Image Captions

sampling.jpg – “Sampling in shrimp pond-associated mangrove forests next to the Xuan Thuy National Park, northern Vietnam.”

park.png – “The Xuan Thuy National Park, where industries such as aquaculture (left) and artisanal fishing (right) are co-located with natural & restored mangrove ecosystems.”

Methodology

To address the research objectives of this project, the student will interact frequently with supervisors at both the University of Stirling and Heriot-Watt University, and with external collaborators in Vietnam.

International collaboration will be critical to the success of this IAPETUS led project. Collaborators include the following researchers:

– Dr. Nguyen Thi Kim Cuc (Thuyloi University), an expert in mangrove carbon storage, restoration, and environmental sustainability.
– Dr. Thi Thuy Duong (Vietnam Academy of Science & Technology), an expert in coastal water quality, aquatic ecology, and reverine pollution.
– Dr. Ha Thi Hien (Thuyloi University), an expert in environmental chemistry and mangrove carbon sequestration.
– Dr. Cuong Ho (Vietnam Academy of Science & Technology), an expert in environmental microbiology and microbial biotechnology.

The student will join the development team of the GMSE R package and participate in the STICS group in conservation science. The student will cultivate experience in the development of scientific software, predictive models, and conservation and environmental biology. All coding will be done collaboratively with the lead supervisor using GitHub, and all software developed will be published open access.

The student will build IBMs by writing their own code and integrating it with tools from GMSE. Data collected from the mangrove system will be used to parameterise new models, along with expertise contributed by external colleagues in Vietnam. Replicate simulations will be run across simulation values and potential policy options to understand and predict social-ecological dynamics. Results from simulations will be analysed and presented to stakeholders.

Project Timeline

Year 1

Introduction to the mangrove system and Vietnamese collaborators. Modelling skills development (R, C, git). Development of modelling framework and use of GMSE.

Year 2

Programming a new IBM for simulations and GMSE integration. In-country model validation via a visit to the Vietnam mangrove systems.

Year 3

Model analysis and presentation at national and international conferences. Publish R package update, and begin writing and completion of thesis.

Year 3.5

Writing and completion of thesis.

Training
& Skills

This project is an opportunity for the student to develop a range of modelling and quantitative skills. These skills include scientific software development, modelling, programming, and applying social and ecological data to a real case study in conservation biology. The student will benefit from a network of collaborators at the University of Stirling, Heriot-Watt University, Thuyloi University (Vietnam), and the Vietnamese Academy for Science and Technology.

The student will also benefit by attending workshops and training courses in programming, modelling, or data analysis early in the course of their post-graduate programme. They will also have the opportunity to visit colleagues and stakeholders in Vietnam, which will greatly increase their understanding of the mangrove system and the interests of stakeholders. Finally, the student will present their research at national and international conferences and the University of Stirling’s BES student symposium, and be encouraged to publish their results in international peer-reviewed journals.

References & further reading

[1] Redpath, S, et al. 2013. Understanding and managing conservation conflicts. Trends in Ecology & Evolution, 28:100-109.[2] Crist, E, et al. 2017. The interaction of human population, food production, and biodiversity protection. Science, 356:260-264.[3] DeAngelis, DL, & Mooij, WM. 2005. Individual-based modeling of ecological and evolutionary processes. Annual Review of Ecology, Evolution, and Systematics, 36: 147-168.[4] McLane, AJ, et al. 2011. The role of agent-based models in wildlife ecology and management. Ecological Modelling, 222:1544-1556.[5] Duthie, AB, et al. (2018). GMSE: an R package for generalised management strategy evaluation. Methods in Ecology and Evolution, 9:2396-2401.

Further Information

To apply, please email Dr Duthie
(CC Dr Burdett ), with (1) a one page cover letter indicating why you are interested in this project, (2) your CV with contact information for two references, and (3) full transcripts of previous qualifications obtained. The deadline for application is 10 JAN 2020 (17:00 GMT). For eligible candidates, funding is available to cover tuition fees, stipend and research costs. However, please note that this project is in competition with others for funding, and success will depend on the quality of applications received.

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