Evidence map›Paper›PMID 37867910›Full record

ArticleIntegrative organismal biology (Oxford, England)2023

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 and 9 more

Open access · goldAbstract read
In one paragraph

Article in Integrative organismal biology (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 14 institutions in 3 countries.

B DantzerDepartment of Psychology, University of Michigan, Ann Arbor, MI 48109,USA.ORCID https://orcid.org/0000-0002-3058-265X
K E MabryDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109,USA.ORCID https://orcid.org/0000-0001-8138-8999
J R BernhardtDepartment of Biology, New Mexico State University, Las Cruces, NM 88003,USA.ORCID https://orcid.org/0000-0003-1824-2801
R M CoxDepartment of Biology, University of Virginia, Charlottesville, VA 22940,USA.ORCID https://orcid.org/0000-0001-8325-111X
C D FrancisDepartment of Biological Sciences, California Polytechnic State University, San Luis Obispo, CA 93407,USA.ORCID https://orcid.org/0000-0003-2018-4954
C K GhalamborDepartment of Biology, Centre for Biodiversity Dynamics (CBD), Norwegian University of Science and Technology (NTNU), N-7491 Trondheim, Norway.
K L HokeDepartment of Biology, Colorado State University, Fort Collins, CO 80523, USA.
S JhaDepartment of Integrative Biology, University of Texas at Austin, Austin, TX 78712,USA.
E KettersonDepartment of Biology, Indiana University, 1001 E. Third Street, Bloomington, IN 47405,USA.ORCID https://orcid.org/0000-0002-7375-6605
N A LevisDepartment of Biology, Indiana University, 1001 E. Third Street, Bloomington, IN 47405,USA.ORCID https://orcid.org/0000-0001-7650-2371
K M McCainGlobal Health and Infectious Disease Research Center, College of Public Health, University of South Florida, Tampa, FL 33612,USA.
G L PatricelliDepartment of Evolution and Ecology, University of California, Davis, CA 95616,USA.ORCID https://orcid.org/0000-0003-3397-8390
S H PaullBattelle, National Ecological Observatory Network, 1685 38th Street, Boulder, CO 80301, USA.
N Pinter-WollmanDepartment of Ecology and Evolutionary Biology, University of California Los Angeles, 621 Charles E. Young Drive South, Los Angeles, CA 90095, USA.ORCID https://orcid.org/0000-0002-0448-8037
R J SafranDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder 80309,USA.ORCID https://orcid.org/0000-0002-4762-2638
T S SchwartzDepartment of Biological Sciences, Auburn University, Auburn, AL 36849, USA.
H L ThroopSchool of Earth and Space Exploration and School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA.
L ZamanDepartment of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109,USA.
L B MartinGlobal Health and Infectious Disease Research Center and Center for Genomics, College of Public Health, University of South Florida, Tampa, FL 33612,USA.ORCID https://orcid.org/0000-0002-5887-4937
California Polytechnic State University · USIndiana University Bloomington · USNew Mexico State University · USUniversity of Michigan · USUniversity of South Florida · USArizona State University · USAuburn University · USBattelle · USColorado State University · USNorwegian University of Science and Technology · NOThe University of Texas at Austin · USUniversity of California, Davis · USUniversity of California, Los Angeles · USUniversity of Colorado Boulder · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID37867910
PMCPMC10586040
OpenAlexW4387058357

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.