Evidence map›Paper›PMID 41637394›Full record

ArticlePloS one2026

Variation in food web reliance on green and brown energy pathways across ecosystem gradients.

James W Sturges, W Ryan James, Ryan J Rezek, Rolando O Santos, Mack White, Gina A Badlowski, Shakira Trabelsi, Jordan Massie, Justin S Lesser, Joel C Trexler and 2 more

Abstract read
In one paragraph

Article in PloS one, 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

12 authors.

James W SturgesDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.ORCID https://orcid.org/0009-0005-1321-0466
W Ryan JamesDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.ORCID https://orcid.org/0000-0002-4829-7742
Ryan J RezekDepartment of Marine Science, Coastal Carolina University, Conway, South Carolina, United States of America.
Rolando O SantosDepartment of Biological Sciences, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Mack WhiteDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Gina A BadlowskiDepartment of Biological Sciences, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Shakira TrabelsiDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Jordan MassieDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Justin S LesserDepartment of Biological Sciences, Institute of Environment, Florida International University, Miami, Florida, United States of America.
Joel C TrexlerDepartment of Biological Science, Florida State University, Florida, United States of America.
James NelsonDepartment of Marine Sciences, University of Georgia, Athens, Georgia.
Jennifer S RehageDepartment of Earth and Environment, Institute of Environment, Florida International University, Miami, Florida, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aquatic food webs typically include highly coupled fast, 'green' energy pathways driven by algae or phytoplankton and slower, 'brown' energy channels driven by detritus and terrestrial plants. Quantifying how much energy biological communities obtain from each of these pathways is essential, particularly across multiple interconnected food webs over large areas, because energy dynamics are known to influence ecosystem structure and function. Despite their importance, few studies track variance in energy channel contributions to food webs across interconnected habitats during distinct hydrologic seasons. In this study, we used tri-isotope Bayesian mixing models to quantify seasonal contributions of energy pathways to consumers in nine aquatic food webs across two river drainages in the Florida coastal Everglades. Sites span an ecosystem gradient from freshwater marshes to estuarine riverine mangroves and marine seagrass habitats. We found that green energy channels were the dominant pathway for consumers in 12 of 18 seasonal food webs, with the remaining 6 being more reliant on detrital energy channels. There were contrasting spatiotemporal trends between river networks. Shark River Slough food webs showed a clearer pattern of greener marsh food webs upstream switching to browner food webs more heavily reliant on mangrove detritus downstream. In contrast, Taylor Slough food webs showed the opposite pattern of browner marsh food webs upstream switching to greener food webs downriver and in marine seagrass habitats. Seasonal switching of the dominant energy channel was less common than expected, with 2 of 9 food webs shifting from green to brown dominance between the dry and wet season. Seasonal shifts disrupted spatial gradients in energy channel use, but the seasonal dynamics quantified in this single year study require further contextualization. Our findings provide a short but dynamic view of energy pathways in aquatic communities across the Everglades, but continued research will allow us to better predict how species, food webs, and ecological networks may respond to environmental drivers under future global change.

Indexed as

EcosystemEnergy MetabolismFood ChainAnimalsBayes TheoremFloridaPhytoplanktonRiversSeasons

Identifiers

PMID41637394
PMCPMC12871965

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.