Understanding Organisms Using Ecological Observatory Networks

B. Dantzer, K. E. Mabry, J. R. Bernhardt, R. M. Cox, C. D. Francis, C. K. Ghalambor, K. L. Hoke, S. Jha, E. Ketterson, N. A. Levis, K. M. McCain, G. L. Patricelli, S. H. Paull, N. Pinter-Wollman, R. J. Safran, T. S. Schwartz, H. L. Throop, L. Zaman, L. B. Martin

Research output: Contribution to journalReview articlepeer-review

Abstract

Synopsis Human activities are rapidly changing ecosystems around the world. These changes have widespread implications for the preservation of biodiversity, agricultural productivity, prevalence of zoonotic diseases, and sociopolitical conflict. To understand and improve the predictive capacity for these and other biological phenomena, some scientists are now relying on obser vator y networks, which are often composed of systems of sensors, teams of field researchers, and databases of abiotic and biotic measurements across multiple temporal and spatial scales. One well-known example is NEON, the US-based National Ecological Obser vator y Network. Although NEON and similar networks have informed studies of population, community, and ecosystem ecology for years, they have been minimally used by organismal biologists. NEON provides organismal biologists, in particular those interested in NEON's focal taxa, with an unprecedented opportunity to study phenomena such as range ex- pansions, disease epidemics, invasive species colonization, macrophysiology, and other biological processes that fundamentally involve organismal variation. Here, we use NEON as an exemplar of the promise of obser vator y networks for understanding the causes and consequences of morphological, behavioral, molecular, and physiological variation among individual organisms.

Original languageEnglish (US)
Article numberobad036
JournalIntegrative Organismal Biology
Volume5
Issue number1
DOIs
StatePublished - 2023

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Animal Science and Zoology
  • Plant Science

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