ManyZoos: A New Collaborative Approach to Multi-Institution Research in Zoos.

Area of Science:

• Zoological research
• Conservation science
• Big data analytics

Background:

• Zoo research traditionally relies on small-scale studies with limited geographical scope.
• Combining data retrospectively is challenging due to methodological inconsistencies across studies.
• Recent multi-institution research highlights the value of broader data collection.

Purpose of the Study:

• Introduce the ManyZoos consortium initiative.
• Expand zoo science geographically and across disciplines.
• Foster collaborations between zoological institutions, academia, and conservation organizations.

Main Methods:

• Establish a collaborative framework for zoo research.
• Incorporate open science and big data approaches.
• Develop transparent protocols for data collection and sharing.

Main Results:

• Addressing limitations of small sample sizes and siloed expertise in zoo science.
• Facilitating the creation of large, open datasets.
• Embedding collaboration from study conception through results dissemination.

Conclusions:

• ManyZoos aims to improve the robustness of zoo animal management and conservation strategies.
• The initiative promotes evidence-based decision-making through collaborative, data-driven research.
• Wider geographical and interdisciplinary participation will enhance the impact of zoo science.