Habitat loss and fragmentation pose a critical threat to biodiversity. While systematic conservation planning has evolved to integrate elements of connectivity conservation, existing tools face significant limitations: they typically rely on structural indicators rather than functional connectivity ones and use heuristic methods that cannot guarantee optimal solutions, failing to account for cumulative effects between conservation or restoration actions.
Hamonic, F., Vaxès, Y., Couëtoux, B. and Albert, C.H. 2025. GECOT: Graph‐based ecological connectivity optimization tool. Methods in Ecology and Evolution 16(9): 1914-1922.
Researchers have developed GECOT (Graph-based Ecological Connectivity Optimization Tool), an open-source command-line tool that addresses these limitations by providing algorithms to optimize landscape connectivity under budget constraints using the probability of connectivity (PC) indicator.
GECOT builds on a rigorous theoretical framework that models conservation and restoration planning as a connectivity optimization problem where planning options can impact habitat quantity or quality and matrix permeability. This formalization encourages practitioners to think more carefully about the accuracy of their connectivity models and quantify the potential impacts of each planning option on the landscape.
GECOT is the first tool enabling optimal solutions for medium-sized instances using mixed-integer linear solvers, capable of handling landscapes with up to 300 habitat patches. However, this is not an absolute limit, since built-in preprocessing steps can greatly reduce the effective size of the landscape model while preserving the same set of solutions. The tool also offers four heuristic algorithms that provide sub-optimal solutions in seconds to minutes when optimal solutions are too computationally expensive. Computation times range from seconds for heuristic methods to approximately 40 minutes for optimal solutions on 300-patch landscapes.
GECOT’s most significant advantage lies in its ability to account for cumulative effects between conservation actions – something that simpler algorithms often miss. When multiple conservation options must work together (such as installing fish ladders along an entire river system), GECOT can identify these synergies and dependencies while heuristic methods may evaluate each option independently. This capability is particularly valuable in poorly connected landscapes with scarce habitat cover, where the difference between optimal and sub-optimal solutions can vary widely in conservation benefit.
The tool addresses both restoration and conservation scenarios. In restoration contexts, users can optimize habitat creation and corridor enhancement. For conservation, it helps prioritize which areas to protect to maintain habitat and connectivity.
GECOT supports multispecies planning by allowing users to specify multiple landscape models, each representing different species, all potentially impacted by the restoration or conservation options. Users can also set a custom criterion function for complex multispecies planning that prevents solutions benefiting only one species. This flexibility can also be used to optimize connectivity for multiple states of the landscape through seasons. GECOT also supports any landscape model that can be represented as a graph, encompassing both classical patch-based models where vertices represent habitat patches and raster models where vertices correspond to individual raster cells.
GECOT represents a significant advance in conservation planning tools by providing guaranteed optimal solutions for landscape connectivity problems. This capability makes it possible to benchmark and compare new heuristic and exact methods aimed at optimizing landscape connectivity through the PC indicator and represents a valuable tool for supporting conservation efforts addressing habitat fragmentation challenges.
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