Using connectivity data in Marxan.

There are several different quantitative methods to directly incorporate connectivity data into the standard Marxan workflow . These include: (a) treating connectivity properties of planning units as conservation features for which a target is set; (b) including connectivity strengths among planning units as spatial dependencies within the objective function; (c) treating connectivity properties of planning units as a connectivity cost; and (d) customizing the objective function to incorporate connectivity performance metrics.


Data processing workflow for two possible methods for using raw connectivity data in spatial prioritization: (1) Connectivity as Spatial Dependency in the objective function (Spatial Data → Connectivity Matrix → Connectivity as Spatial Dependency), or (1) Discrete conservation features (Raw Data → Connectivity Matrix → Continuous Metrics → Threshold Setting → Discrete Feature → Target Setting). Black Arrows indicate a logical workflow, while red and yellow indicate a decision point. Red arrows indicate the conservation feature versus connectivity strength method decision point and yellow arrows new metric or new threshold decision point after target setting and post-hoc evaluation of conservation success

REFERENCES.

Daigle, Rémi M., et al. "Operationalizing ecological connectivity in spatial conservation planning with Marxan Connect." Methods in Ecology and Evolution 11.4 (2020): 570-579. https://doi.org/10.1111/2041-210X.13349