Evidence map›Paper›PMID 39462824›Full record

ArticleEcology2024

Multiple resiliency metrics reveal complementary drivers of ecosystem persistence: An application to kelp forest systems.

Jorge Arroyo-Esquivel, Riley Adams, Sarah Gravem, Ross Whippo, Zachary Randell, Jason Hodin, Aaron W E Galloway, Brian Gaylord, Marissa L Baskett

Abstract read
In one paragraph

Article in Ecology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Jorge Arroyo-EsquivelDepartment of Mathematics, University of California, Davis, California, USA.ORCID 0000-0003-4399-954X
Riley AdamsDepartment of Environmental Science and Policy, University of California, Davis, California, USA.
Sarah GravemDepartment of Integrative Biology, Oregon State University, Corvallis, Oregon, USA.ORCID 0000-0002-3857-9930
Ross WhippoDepartment of Biology, University of Oregon, Charleston, Oregon, USA.ORCID 0000-0001-5725-2215
Zachary RandellSeattle Aquarium, Seattle, Washington, USA.
Jason HodinFriday Harbor Labs, University of Washington, Friday Harbor, Washington, USA.
Aaron W E GallowayDepartment of Biology, University of Oregon, Charleston, Oregon, USA.ORCID 0000-0001-7826-299X
Brian GaylordBodega Marine Laboratory, University of California, Davis, California, USA.
Marissa L BaskettDepartment of Environmental Science and Policy, University of California, Davis, California, USA.ORCID 0000-0001-6102-1110

Funding

California Sea Grant, University of California, San Diego R/HCE-15Directorate for Biological Sciences 2108002
6 · The paper itself

Abstract

Human-caused global change produces biotic and abiotic conditions that increase the uncertainty and risk of failure of restoration efforts. A focus of managing for resiliency, that is, the ability of the system to respond to disturbance, has the potential to reduce this uncertainty and risk. However, identifying what drives resiliency might depend on how one measures it. An example of a system where identifying how the drivers of different aspects of resiliency can inform restoration under climate change is the northern coast of California, where kelp experienced a decline in coverage of over 95% due to the combination of an intense marine heat wave and the functional extinction of the primary predator of the kelp-grazing purple sea urchin, the sunflower sea star. Although restoration efforts focused on urchin removal and kelp reintroduction in this system are ongoing, the question of how to increase the resiliency of this system to future marine heat waves remains open. In this paper, we introduce a dynamical model that describes a tritrophic food chain of kelp, purple urchins, and a purple urchin predator such as the sunflower sea star. We run a global sensitivity analysis of three different resiliency metrics (recovery likelihood, recovery rate, and resistance to disturbance) of the kelp forest to identify their ecological drivers. We find that each metric depends the most on a unique set of drivers: Recovery likelihood depends the most on live and drift kelp production, recovery rate depends the most on urchin production and feedbacks that determine urchin grazing on live kelp, and resistance depends the most on feedbacks that determine predator consumption of urchins. Therefore, an understanding of the potential role of predator reintroduction or recovery in kelp systems relies on a comprehensive approach to measuring resiliency.

Indexed as

KelpModels, BiologicalAnimalsClimate ChangeEcosystemFood ChainSea UrchinsStarfishdisturbancekelp forestresiliency metricsrestorationtrophic model

Identifiers

PMID39462824
PMCPMC11610656

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.