Cheick Amed Diloma Gabriel TRAORE

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Cheick Amed Diloma Gabriel TRAORE

Affiliations

Nazi Boni University, Cheikh Anta Diop University

ORCID more info

https://orcid.org/0000-0002-7160-4069

GitHub more info

No associated GitHub account.

I am Cheick Amed Diloma Gabriel Traoré, holding a PhD in Multi-Agent System Modeling from Cheikh Anta Diop University (UCAD), Senegal. My doctoral research focused on formalizing and simulating Sahelian transhumance as a complex adaptive system. Leveraging mathematical and computational techniques, I developed agent-based models to analyze the spatio-temporal dynamics of transhumant herds, considering factors such as herd behavior, environmental conditions, and socio-economic pressures.

My background includes a Master’s and Bachelor’s in Mathematics from the University of Nazi Boni, Burkina Faso, where I developed a rectangular mesh for image processing and applied the Hough transform to detect discrete lines. My studies at the University of Nazi Boni were funded by the Burkinabe government.
For my PhD, I conducted extensive fieldwork in Senegal, collaborating with interdisciplinary teams to gather data on transhumant practices. Using this data, I developed a multi-objective optimization framework to model herd movement decisions. Furthermore, I created a real-time monitoring system for transhumant herds based on discrete mathematics. My PhD research was funded by the CaSSECS project (Carbon Sequestration and Sustainable Ecosystem Services in the Sahel).

Sahelian transhumance is a type of socio-economic and environmental pastoral mobility. It involves the movement of herds from their terroir of origin (i.e., their original pastures) to one or more host terroirs, followed by a return to the terroir of origin.  According to certain pastoralists, the mobility of herds is planned to prevent environmental degradation, given the continuous dependence of these herds on their environment. However, these herds emit Greenhouse Gases (GHGs) in the spaces they traverse. Given that GHGs contribute to global warming, our long-term objective is to quantify the GHGs emitted by Sahelian herds. The determination of these herds’ GHG emissions requires: (1) the artificial replication of the transhumance, and (2) precise knowledge of the space used during their transhumance.
This article presents the design of an artificial replication of the transhumance through an agent-based model named MSTRANS. MSTRANS determines the space used by transhumant herds, based on the decision-making process of Sahelian transhumants.
MSTRANS integrates a constrained multi-objective optimization problem and algorithms into an agent-based model. The constrained multi-objective optimization problem encapsulates the rationality and adaptability of pastoral strategies. Interactions between a transhumant and its socio-economic network are modeled using algorithms, diffusion processes, and within the multi-objective optimization problem. The dynamics of pastoral resources are formalized at various spatio-temporal scales using equations that are integrated into the algorithms.
The results of MSTRANS are validated using GPS data collected from transhumant herds in Senegal. MSTRANS results highlight the relevance of integrated models and constrained multi-objective optimization for modeling and monitoring the movements of transhumant herds in the Sahel. Now specialists in calculating greenhouse gas emissions have a reproducible and reusable tool for determining the space occupied by transhumant herds in a Sahelian country. In addition, decision-makers, pastoralists, veterinarians and traders have a reproducible and reusable tool to help them make environmental and socio-economic decisions.

Transhumants move their herds based on strategies simultaneously considering several environmental and socio-economic factors. There is no agreement on the influence of each factor in these strategies. In addition, there is a discussion about the social aspect of transhumance and how to manage pastoral space. In this context, agent-based modeling can analyze herd movements according to the strategy based on factors favored by the transhumant. This article presents a reductionist agent-based model that simulates herd movements based on a single factor. Model simulations based on algorithms to formalize the behavioral dynamics of transhumants through their strategies. The model results establish that vegetation, water outlets and the socio-economic network of transhumants have a significant temporal impact on transhumance. Water outlets and the socio-economic network have a significant spatial impact. The significant impact of the socio-economic factor demonstrates the social dimension of Sahelian transhumance. Veterinarians and markets have an insignificant spatio-temporal impact. To manage pastoral space, water outlets should be at least 15 km
from each other. The construction of veterinary centers, markets and the securitization of transhumance should be carried out close to villages and rangelands.

Under development.

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