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Record W4283809141 · doi:10.1111/jfb.15153

The movement ecology of fishes

2022· review· en· W4283809141 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

VenueJournal of Fish Biology · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrent UniversitySt. Francis Xavier UniversityUniversity of OttawaFisheries and Oceans CanadaCarleton University
FundersDivision of Environmental BiologyNatural Sciences and Engineering Research Council of CanadaNational Oceanic and Atmospheric AdministrationDirectorate for Biological SciencesUniversity of CambridgeNorges ForskningsrådNational Science FoundationRoyal SocietyNatural EnglandCambridge Philosophical SocietyGreat Lakes Fishery CommissionUniversity of OxfordCanada Foundation for InnovationFondation BertarelliVillum Fonden
KeywordsBiologyEcologyMovement (music)Fishery

Abstract

fetched live from OpenAlex

Movement of fishes in the aquatic realm is fundamental to their ecology and survival. Movement can be driven by a variety of biological, physiological and environmental factors occurring across all spatial and temporal scales. The intrinsic capacity of movement to impact fish individually (e.g., foraging) with potential knock-on effects throughout the ecosystem (e.g., food web dynamics) has garnered considerable interest in the field of movement ecology. The advancement of technology in recent decades, in combination with ever-growing threats to freshwater and marine systems, has further spurred empirical research and theoretical considerations. Given the rapid expansion within the field of movement ecology and its significant role in informing management and conservation efforts, a contemporary and multidisciplinary review about the various components influencing movement is outstanding. Using an established conceptual framework for movement ecology as a guide (i.e., Nathan et al., 2008: 19052), we synthesized the environmental and individual factors that affect the movement of fishes. Specifically, internal (e.g., energy acquisition, endocrinology, and homeostasis) and external (biotic and abiotic) environmental elements are discussed, as well as the different processes that influence individual-level (or population) decisions, such as navigation cues, motion capacity, propagation characteristics and group behaviours. In addition to environmental drivers and individual movement factors, we also explored how associated strategies help survival by optimizing physiological and other biological states. Next, we identified how movement ecology is increasingly being incorporated into management and conservation by highlighting the inherent benefits that spatio-temporal fish behaviour imbues into policy, regulatory, and remediation planning. Finally, we considered the future of movement ecology by evaluating ongoing technological innovations and both the challenges and opportunities that these advancements create for scientists and managers. As aquatic ecosystems continue to face alarming climate (and other human-driven) issues that impact animal movements, the comprehensive and multidisciplinary assessment of movement ecology will be instrumental in developing plans to guide research and promote sustainability measures for aquatic resources.

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 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 score0.550
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.287
Teacher spread0.256 · 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