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Record W2154707908 · doi:10.1111/gcb.13094

Human activities cause distinct dissolved organic matter composition across freshwater ecosystems

2015· article· en· W2154707908 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Change Biology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaMinistero dello Sviluppo EconomicoEnvironment CanadaOntario Ministry of Economic Development and Innovation
KeywordsDissolved organic carbonEcosystemFreshwater ecosystemEnvironmental scienceOrganic matterComposition (language)EcologyEnvironmental chemistryBiologyChemistry

Abstract

fetched live from OpenAlex

Dissolved organic matter (DOM) composition in freshwater ecosystems is influenced by the interactions among physical, chemical, and biological processes that are controlled, at one level, by watershed landscape, hydrology, and their connections. Against this environmental template, humans may strongly influence DOM composition. Yet, we lack a comprehensive understanding of DOM composition variation across freshwater ecosystems differentially affected by human activity. Using optical properties, we described DOM variation across five ecosystem groups of the Laurentian Great Lakes region: large lakes, Kawartha Lakes, Experimental Lakes Area, urban stormwater ponds, and rivers (n = 184 sites). We determined how between ecosystem variation in DOM composition related to watershed size, land use and cover, water quality measures (conductivity, dissolved organic carbon (DOC), nutrient concentration, chlorophyll a), and human population density. The five freshwater ecosystem groups had distinctive DOM composition from each other. These significant differences were not explained completely through differences in watershed size nor spatial autocorrelation. Instead, multivariate partial least squares regression showed that DOM composition was related to differences in human impact across freshwater ecosystems. In particular, urban/developed watersheds with higher human population densities had a unique DOM composition with a clear anthropogenic influence that was distinct from DOM composition in natural land cover and/or agricultural watersheds. This nonagricultural, human developed impact on aquatic DOM was most evident through increased levels of a microbial, humic-like parallel factor analysis component (C6). Lotic and lentic ecosystems with low human population densities had DOM compositions more typical of clear water to humic-rich freshwater ecosystems but C6 was only present at trace to background levels. Consequently, humans are strongly altering the quality of DOM in waters nearby or flowing through highly populated areas, which may alter carbon cycles in anthropogenically disturbed ecosystems at broad scales.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.272
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it