Bridging Ecological Inference and Decision Optimization for Conservation Using Artificial Intelligence
This work developed an adaptive decision model that selects production and distribution decisions of the supplementation program in response to the observed demographic, hydrological, and genetic environment and demonstrates that minimum sub-population size and total population size were primary drivers of the model’s decisions.
Hyun Seok Yoon, C. Yackulic, A. Lawson et al.
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