Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. AI and Social Good. Pages 9772-9780.
https://doi.org/10.24963/ijcai.2025/1086
Keywords
- Multidisciplinary Topics and Applications: General
- Constraint Satisfaction and Optimization: General
- Planning and Scheduling: General
Abstract
The Kunming-Montreal Global Biodiversity Framework aims to protect 30% of terrestrial, inland water, marine, and coastal ecosystems worldwide, and ensuring that at least 30% of these areas are under effective restoration by 2030.
Maintaining and restoring ecological connectivity between natural habitats and protected areas is a key feature of this target.
Achieving it will require effective and inclusive spatial planning supported by appropriate decision-support tools.
Most spatial planning models address budget as an objective and connectivity as a constraint, formulating problems with Steiner trees.
In many real-world cases, such as landscape-scale restoration planning, this formulation is inappropriate when environmental managers seek to optimise connectivity under a budget constraint.
This problem was previously addressed with Constraint Programming (CP) and graph variables, but the current approach is severely limited in terms of spatial resolution.
In this article, we formalise this problem as the budget-constrained graph connectivity optimisation problem. Based on a real case study: the restoration of forest connectivity in New Caledonia, we illustrate why ``naive'' CP approaches are inefficient.
In response, we provide a preprocessing method based on Hanan grids which preserves the existence of at least one optimal solution.
Finally, we assess the efficiency of our approach in the New Caledonian case study.
@inproceedings{ijcai2025p1086,
title = {Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning},
author = {Le Bozec-Chiffoleau, Sulian and Justeau-Allaire, Dimitri and Lorca, Xavier and Prud'homme, Charles and Simonin, Gilles and Vismara, Philippe and Birnbaum, Philippe and Rinck, Nicolas and Beldiceanu, Nicolas},
booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-25}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {James Kwok},
pages = {9772--9780},
year = {2025},
month = {8},
note = {AI and Social Good},
doi = {10.24963/ijcai.2025/1086},
url = {https://doi.org/10.24963/ijcai.2025/1086},
}
TY - CPAPER TI - Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning AU - Le Bozec-Chiffoleau, Sulian AU - Justeau-Allaire, Dimitri AU - Lorca, Xavier AU - Prud'homme, Charles AU - Simonin, Gilles AU - Vismara, Philippe AU - Birnbaum, Philippe AU - Rinck, Nicolas AU - Beldiceanu, Nicolas T2 - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2025 SP - 9772 EP - 9780 DO - 10.24963/ijcai.2025/1086 UR - https://doi.org/10.24963/ijcai.2025/1086 ER -Copied
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