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Understanding Organisms Using Ecological Observatory Networks

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...

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Autores principales: Dantzer, B, Mabry, K E, Bernhardt, J R, Cox, R M, Francis, C D, Ghalambor, C K, Hoke, K L, Jha, S, Ketterson, E, Levis, N A, McCain, K M, Patricelli, G L, Paull, S H, Pinter-Wollman, N, Safran, R J, Schwartz, T S, Throop, H L, Zaman, L, Martin, L B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10586040/
https://www.ncbi.nlm.nih.gov/pubmed/37867910
http://dx.doi.org/10.1093/iob/obad036
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author Dantzer, B
Mabry, K E
Bernhardt, J R
Cox, R M
Francis, C D
Ghalambor, C K
Hoke, K L
Jha, S
Ketterson, E
Levis, N A
McCain, K M
Patricelli, G L
Paull, S H
Pinter-Wollman, N
Safran, R J
Schwartz, T S
Throop, H L
Zaman, L
Martin, L B
author_facet Dantzer, B
Mabry, K E
Bernhardt, J R
Cox, R M
Francis, C D
Ghalambor, C K
Hoke, K L
Jha, S
Ketterson, E
Levis, N A
McCain, K M
Patricelli, G L
Paull, S H
Pinter-Wollman, N
Safran, R J
Schwartz, T S
Throop, H L
Zaman, L
Martin, L B
author_sort Dantzer, B
collection PubMed
description 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 observatory 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 Observatory 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 expansions, 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 observatory networks for understanding the causes and consequences of morphological, behavioral, molecular, and physiological variation among individual organisms.
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spelling pubmed-105860402023-10-20 Understanding Organisms Using Ecological Observatory Networks Dantzer, B Mabry, K E Bernhardt, J R Cox, R M Francis, C D Ghalambor, C K Hoke, K L Jha, S Ketterson, E Levis, N A McCain, K M Patricelli, G L Paull, S H Pinter-Wollman, N Safran, R J Schwartz, T S Throop, H L Zaman, L Martin, L B Integr Org Biol Review 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 observatory 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 Observatory 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 expansions, 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 observatory networks for understanding the causes and consequences of morphological, behavioral, molecular, and physiological variation among individual organisms. Oxford University Press 2023-09-25 /pmc/articles/PMC10586040/ /pubmed/37867910 http://dx.doi.org/10.1093/iob/obad036 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Dantzer, B
Mabry, K E
Bernhardt, J R
Cox, R M
Francis, C D
Ghalambor, C K
Hoke, K L
Jha, S
Ketterson, E
Levis, N A
McCain, K M
Patricelli, G L
Paull, S H
Pinter-Wollman, N
Safran, R J
Schwartz, T S
Throop, H L
Zaman, L
Martin, L B
Understanding Organisms Using Ecological Observatory Networks
title Understanding Organisms Using Ecological Observatory Networks
title_full Understanding Organisms Using Ecological Observatory Networks
title_fullStr Understanding Organisms Using Ecological Observatory Networks
title_full_unstemmed Understanding Organisms Using Ecological Observatory Networks
title_short Understanding Organisms Using Ecological Observatory Networks
title_sort understanding organisms using ecological observatory networks
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10586040/
https://www.ncbi.nlm.nih.gov/pubmed/37867910
http://dx.doi.org/10.1093/iob/obad036
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