Evidence map›Paper›PMID 42218191›Full record

ArticleScientific reports2026

Evaluating the predictive capacity of coral reef resilience assessments.

Orion S McCarthy, Eric Conklin, Katharine Ricke, Russell T Sparks, Jennifer E Smith

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Orion S McCarthyScripps Institution of Oceanography, UC San Diego, La Jolla, San Diego, CA, 92037, USA. omccarth@ucsd.edu.
Eric ConklinThe Nature Conservancy - Hawai'i and Palmyra, Honolulu, HI, 96817, USA.
Katharine RickeScripps Institution of Oceanography, UC San Diego, La Jolla, San Diego, CA, 92037, USA.
Russell T SparksHawaii Division of Aquatic Resources (Maui Office), Department of Land and Natural Resources, Wailuku, HI, 96793, USA.
Jennifer E SmithScripps Institution of Oceanography, UC San Diego, La Jolla, San Diego, CA, 92037, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Resilience assessments, which rely on ecological indicators to predict future ecosystem resilience across a management jurisdiction, are used to prioritize limited conservation resources toward "resilient" locations with the best chance of surviving climate change. While resilience assessments have been widely applied to inform management, particularly for coral reefs, their precision and accuracy have rarely been validated. We used a timeseries of coral reef 3D models to (1) conduct multiple resilience assessments of fixed sites over time, and (2) track the resistance and recovery of those same sites over a decade. This allowed us to compare resilience predictions across assessments (precision) and test whether resilience predictions aligned with observed patterns of resistance and recovery (accuracy). We found that resilience assessments are capable of generating consistent resilience predictions over time, but in our case those predictions were not correlated with observed resistance or recovery dynamics. We recommend modelling resistance and recovery as distinct processes, and emphasize the importance of validating predictions with long-term monitoring. We caution against using resilience assessments in isolation to drive conservation decision making. Instead, spatial prioritization should be driven by local community input, with management of priority sites informed by functional indicators of resistance and recovery.

Indexed as

Conservation of Natural ResourcesCoral ReefsAnimalsClimate ChangeEcosystem

Identifiers

PMID42218191
PMCPMC13457859

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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.