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Do non‐native invasive fish support elevated lamprey populations?

2009· article· en· W2109750820 on OpenAlexfundno aff
Richard Inger, Robbie A. McDonald, David L. Rogowski, Andrew L. Jackson, Andrew Parnell, Sarah Preston, Chris Harrod, Claire Goodwin, David Griffiths, Jaimie T. A. Dick, Robert W. Elwood, Jason Newton, Stuart Bearhop

Bibliographic record

VenueJournal of Applied Ecology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersQueen's UniversityNatural Environment Research CouncilQueen's University BelfastSight Research UKNorthern Ireland Environment Agency
KeywordsLampreyLampetraBiologyFish migrationPredationFisheryTrophic levelEcologyPopulationFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Summary 1. Managing populations of predators and their prey to achieve conservation or resource management goals is usually technically challenging and frequently socially controversial. This is true even in the simplest ecosystems but can be made much worse when predator–prey relationships are influenced by complex interactions, such as biological invasions, population trends or animal movements. 2. Lough Neagh in Northern Ireland is a European stronghold for pollan Coregonus autumnalis , a coregonine fish and for river lamprey Lampetra fluviatilis , which feeds parasitically as an adult. Both species are of high conservation importance. Lampreys are known to consume pollan but detailed knowledge of their interactions is scant. While pollan is well known to be a landlocked species in Ireland, the life cycle of normally anadromous river lamprey in Lough Neagh has been unclear. The Lough is also a highly perturbed ecosystem, supporting several invasive, non‐native fish species that have the potential to influence lamprey–pollan interactions. 3. We applied stable isotope techniques to resolve both the movement patterns of lamprey and trophic interactions in this complex community. Recognizing that stable isotope studies are often hampered by high‐levels of variability and uncertainty in the systems of interest, we employed novel Bayesian mixing models, which incorporate variability and uncertainty. 4. Stable isotope analyses identified trout Salmo trutta and non‐native bream Abramis brama as the main items in lamprey diet. Pollan only represented a major food source for lamprey between May and July. 5. Stable isotope ratios of carbon in tissues from 71 adult lamprey showed no evidence of marine carbon sources, strongly suggesting that Lough Neagh is host to a highly unusual, nonanadromous freshwater population. This finding marks out the Lough’s lamprey population as of particular scientific interest and enhances the conservation significance of this feature of the Lough. 6. Synthesis and applications. Our Bayesian isotopic mixing models illustrate an unusual pattern of animal movement, enhancing conservation interest in an already threatened population. We have also revealed a complex relationship between lamprey and their food species that is suggestive of hyperpredation, whereby non‐native species may sustain high lamprey populations that may in turn be detrimental to native pollan . Long‐term conservation of lamprey and pollan in this system is likely to require management intervention, but in light of this exceptional complexity, no simple management options are currently supported. Conservation plans will require better characterization of population‐level interactions and simulation modelling of interventions. More generally, our study demonstrates the importance of considering a full range of possible trophic interactions, particularly in complex ecosystems, and highlights Bayesian isotopic mixing models as powerful tools in resolving trophic relationships.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.993

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)0.0080.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations41
Published2009
Admission routes1
Has abstractyes

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