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Record W2066192900 · doi:10.1086/655977

Niche Dimensions in Fishes: An Integrative View

2010· review· en· W2066192900 on OpenAlexaff
Hans‐Otto Pörtner, Patricia M. Schulte, Chris M. Wood, F. Schiemer

Bibliographic record

VenuePhysiological and Biochemical Zoology · 2010
Typereview
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNicheBiologyEcologyEcological nicheEcosystemAdaptation (eye)Psychological resilienceOrganismCline (biology)Climate changeBiosphereHabitatPopulation

Abstract

fetched live from OpenAlex

Current shifts in ecosystem composition and function emphasize the need for an understanding of the links between environmental factors and organism fitness and tolerance. The examples discussed here illustrate how recent progress in the field of comparative physiology may provide a better mechanistic understanding of the ecological concepts of the fundamental and realized niches and thus provide insights into the impacts of anthropogenic disturbance. Here we argue that, as a link between physiological and ecological indicators of organismal performance, the mechanisms shaping aerobic scope and passive tolerance set the dimensions of an animal's niche, here defined as its capacity to survive, grow, behave, and interact with other species. We demonstrate how comparative studies of cod or killifish populations in a latitudinal cline have unraveled mitochondrial mechanisms involved in establishing a species' niche, performance, and energy budget. Riverine fish exemplify how the performance windows of various developmental stages follow the dynamic regimes of both seasonal temperatures and river hydrodynamics, as synergistic challenges. Finally, studies of species in extreme environments, such as the tilapia of Lake Magadi, illustrate how on evolutionary timescales functional and morphological shifts can occur, associated with new specializations. We conclude that research on the processes and time course of adaptations suitable to overcome current niche limits is urgently needed to assess the resilience of species and ecosystems to human impact, including the challenges of global climate change.

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.

How this classification was reachedexpand

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.297
Teacher spread0.264 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations113
Published2010
Admission routes1
Has abstractyes

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