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Ecological Linkages Between Headwaters and Downstream Ecosystems: Transport of Organic Matter, Invertebrates, and Wood Down Headwater Channels<sup>1</sup>

2007· article· en· W2132980453 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.

Bibliographic record

VenueJAWRA Journal of the American Water Resources Association · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSTREAMSRiparian zoneEnvironmental scienceDetritusOrganic matterDownstream (manufacturing)Hydrology (agriculture)WatershedEcosystemEcologyHabitatGeologyBiology

Abstract

fetched live from OpenAlex

Abstract: Headwater streams make up a large proportion of the total length and watershed area of fluvial networks, and are partially characterized by the large volume of organic matter (large wood, detritus, and dissolved organic matter) and invertebrate inputs from the riparian forest, relative to stream size. Much of those inputs are exported to downstream reaches through time where they potentially subsidize river communities. The relative rates, timing, and conversion processes that carry inputs from small streams to downstream reaches are reasonably well quantified. For example, larger particles are converted to smaller particles, which are more easily exported. Also, dissolved organic matter and surface biofilms are converted to larger particles which can be more easily intercepted by consumers. However, the quality of these materials as it affects biological activity downstream is not well known, nor is the extent to which timing permits biological use of those particles. These ecological unknowns need to be resolved. Further, land uses may disrupt and diminish material transport to downstream reaches by removing sources (e.g., forest harvest), by affecting transport and decomposition processes (e.g., flow regulation, irrigation, changes in biotic communities), and by altering mechanisms of storage within headwaters (e.g., channelization). We present conceptual models of energy and nutrient fluxes that outline small stream processes and pathways important to downstream communities, and we identify informational gaps that, if filled, could significantly advance the understanding of linkages between headwater streams and larger rivers. The models, based on empirical evidence and best professional judgment, suggest that navigable waters are significantly influenced by headwater streams through hydrological and ecological connectivities, and land use can dramatically influence these natural connectivities, impacting downstream riverine ecosystems.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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