Evidence map›Paper›PMID 41730909›Full record

ReviewNature communications2026

Best practices for moving from correlation to causation in ecological research.

Hannah E Correia, Laura E Dee, Jarrett E K Byrnes, John R Fieberg, Marie-Josée Fortin, Clark Glymour, Jakob Runge, Bill Shipley, Ilya Shpitser, Katherine J Siegel and 3 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Hannah E CorreiaDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA. hec0003@auburn.edu.ORCID 0000-0003-3476-3674
Laura E DeeDepartment of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA.ORCID 0000-0003-0471-1371
Jarrett E K ByrnesDepartment of Biology, University of Massachusetts Boston, Boston, MA, USA.ORCID 0000-0002-9791-9472
John R FiebergDepartment of Fisheries, Wildlife and Conservation Biology, University of Minnesota, Saint Paul, MN, USA.ORCID 0000-0002-3180-7021
Marie-Josée FortinDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-9935-1366
Clark GlymourDepartment of Philosophy, Carnegie Mellon University, Pittsburgh, PA, USA.
Jakob RungeDepartment of Computer Science, University of Potsdam, Potsdam, Germany.
Bill ShipleyDépartement de biologie, Université de Sherbrooke, Sherbrooke, QC, Canada.
Ilya ShpitserDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-2571-7326
Katherine J SiegelDepartment of Geography, University of Colorado Boulder, Boulder, CO, USA.ORCID 0000-0001-6294-2130
George SugiharaScripps Institution of Oceanography, University of California San Diego, San Diego, CA, USA.ORCID 0000-0002-2863-6946
Betsy von HolleDepartment of Biology, George Washington University, Washington, DC, USA.ORCID 0000-0002-3116-3027
Paul J FerraroDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA. pferrar5@jhu.edu.ORCID 0000-0002-4777-5108

Funding

United States Department of Agriculture | National Institute of Food and Agriculture (NIFA) 2023-67023-39033
6 · The paper itself

Abstract

In ecology, causal questions are ubiquitous, yet the literature describing systematic approaches to answering these questions is vast and fragmented across different traditions (e.g., randomization, structural equation modeling, convergent cross mapping). In our Perspective, we connect the causal assumptions, tasks, frameworks, and methods across these traditions, thereby providing a synthesis of the concepts and methodological advances for detecting and quantifying causal relationships in ecological systems. Through a newly developed workflow, we emphasize how ecologists' choices among empirical approaches are guided by the pre-existing knowledge that ecologists have and the causal assumptions that ecologists are willing to make.

Indexed as

CausalityEcologyResearch DesignEcosystem

Identifiers

PMID41730909
PMCPMC12932701

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.