COMMENTARY / Why ZIMS data changes what we know about species: A biodemographer’s perspective
James R. Carey*, University of California, Davis
‘To say the life history information now available from zoos and aquariums (i.e., from Species360) as potentially important is an understatement.”
Having been immersed in all aspects of biological and human demography throughout my academic career ranging from data collection and methods development to cohort analysis and population modeling, for me to describe the life history information now available from zoos and aquariums (i.e., from Species360) as potentially important is a description bordering on understatement. The phylogenetic and taxonomic diversity, the numerical scale, the multi-decadal and (often) multi-generational record-keeping, and the biological, behavioral, epidemiological and biomedical details contained in the databases are bursting with demographic possibilities.
5 Reasons ZIMS Impacts Research: Here are the five reasons I believe ZIMS (the Zoological Information Management System) holds so much promise for science and policy-making in basic and applied ecology:
- Controlled conditions. Data derived from captive individuals in zoos and aquariums are based on life histories observed under controlled and protected (i.e., essentially laboratory) conditions. These data serve as baselines relative to similar (but largely confounded) information gathered on free-ranging populations. Datasets created from observations in the wild versus those from observations under controlled conditions are not mutually-exclusive but rather mutually-informing.
- Age- and sex-specificity. These are two of the most foundational categories in demography because the basis of much of demographic analysis involves risk (e.g., of mating, reproducing, migrating, dying) for which age (or stage) and sex are two of the most important determinants. Without age data, as is the case for much of field research, the number and richness of the cohort and population models that are available for both analyses and projection is hugely diminished.
- Health. With the exception of field studies on a small number of large, high-profile species that are critically endangered (e.g., mountain gorillas), studies of healthspan and morbidity dynamics in non-human species that are neither domesticated (dogs; cats) nor used as model organisms (mice; rhesus monkeys) are virtually non-existent outside of data from zoos and aquariums. These health data are not only important in comparative medical contexts, but also for providing insights into underlying health conditions that, in the incipient stages of disease development, render individuals more vulnerable to predation, disease and injury in the wild.
- Scale. Although there are many biological and demographic contexts in which detailed life history information (e.g., age-specific death rates) on large numbers of individuals is important, one example from aging studies is this: Suppose 100 newborn individuals are required for achieving a 95% level of confidence in both the length of life at birth and the trajectory of mortality at early ages. Then to achieve a similar level of statistical confidence in the results of aging studies involving identical actuarial metrics for the ages at which, for example, 10% and 1% of the original individuals remain alive (i.e., the elderly) will require initial numbers of 1,000 and 10,000, respectively. There are a relatively large number of species in the Species360 database that contain records on these scales (e.g., the African Big Five).
- Hard to study species. Zoo and aquarium records are often the only life history data-sources available for many of the species that are exceptionally difficult to study in the field due to their small size, secretive behavior, small numbers, long-range migrations, or extremely remote locations (e.g., deep sea “Midnight Zone”).
These collective characteristics of the life history and biomedical information available in the Species360 databases create the conditions for three complementary outcomes concerned with science and policy-making in population biology and applied ecology. First, expansion of the number of the most sophisticated demographic models originally developed for humans that can be brought to bear on analyses of non-human species. Second, the new data will have the potential to both facilitate and inspire development of entirely new demographic models that are more relevant to the challenges associated with models that incorporate the relatively complex life histories of many non-human species. Third, the classic demographic models as well as new ones have the potential to suggest the gathering of new types of data from individuals in zoos and aquariums as well as in the field.
Like the requirements in all areas of science, those for moving conservation and population biology forward include high quality data, powerful models, and guiding visions. Without the former the road is blocked, but without the latter there is no road ahead. The confluence of the original new data now becoming available from zoos and aquariums (Species360), the cohort and population models that constitute the corpus of both classical demography and population biology, and the nascent but rapidly-emerging field of biodemography create conditions for advancing both basic and applied ecology that are as exciting and stimulating as they are complementary and synergistic. The Species360 databases now and in the future will, without question, be central to this scientific quest.
*James R. Carey is distinguished professor of entomology at the University of California (UC), Davis, senior scholar at the Center for the Economics and Demography of Aging at UC Berkeley, and lead author (with Deborah Roach) of the book Biodemography: An Introduction to Concepts and Methods (2020, Princeton). He received his B.S. degree in Fisheries and Wildlife Biology from Iowa State University and his Ph.D. in Entomology from UC Berkeley.
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