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Institutional networks in cooperative population management: Exploring patterns in transfer fulfillment.

Steven M GrayArielle W ParsonsJohn E AndrewsKristine Schad EebesLisa J FaustJudy P Che-Castaldo
Published in: Zoo biology (2023)
Long-term sustainability of ex-situ animal populations is important for zoos and aquariums, but challenging due to inconsistent compliance with Breeding and Transfer Plans. Transfer recommendations are key to promoting the sustainability of ex-situ animal populations by ensuring cohesive populations, genetic diversity, and demographic stability, but factors affecting their fulfillment are poorly understood. We used a network analysis framework to analyze data compiled from PMCTrack from 2011 to 2019 for three taxonomic classes (mammals, birds, and reptiles/amphibians) within the Association of Zoos and Aquariums to assess factors affecting transfer recommendation fulfillment. Of 2505 compiled transfer recommendations spanning 330 Species Survival Plan® (SSP) Programs and 156 institutions, 1628 (65%) of them were fulfilled. Transfers were most likely to be fulfilled between institutions in close proximity with an established relationship. Annual operating budget, SSP Coordinator experience, number of staff, and diversity of Taxonomic Advisory Groups in which an institution participates also influenced transfer recommendations and/or fulfillment, but effects varied with taxonomic class. Our results suggest that current practices of focusing on transfers between institutions in close proximity are working to maximize transfer success and that institutions with larger budgets and some degree of taxonomic specialization play important roles in promoting success. Success could be further enhanced by building reciprocal transfer relationships and encouraging further development of relationships between smaller institutions and larger ones. These results emphasize the utility of examining animal transfers using a network approach, which accounts for attributes of both sending and receiving institutions, describing novel patterns otherwise left undetected.
Keyphrases
  • genetic diversity
  • network analysis
  • healthcare
  • primary care
  • public health
  • electron transfer
  • deep learning
  • artificial intelligence
  • big data