Which retail data analytics technique has been most successfully adapted by wildlife conservationists to predict animal migration patterns and habitat usage?

Environmental conservation organizations increasingly rely on sophisticated data analytics to track biodiversity, monitor endangered species, and measure conservation success. This poll tests your knowledge about how retail data analytics methodologies have been adapted for wildlife conservation and natural resource management—where the customers are animals and the products are habitats and ecosystems. Can you identify the cutting-edge analytical approaches being used in the natural world?

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Market basket analysis, modified to track which species co-exist in the same habitats
Predictive modeling using machine learning algorithms that incorporate seasonal variables and historical movement data
Customer segmentation techniques, applied to categorize species by their territorial behaviors
Inventory optimization algorithms, repurposed to calculate optimal distribution of conservation resources