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The recovery of acid‐damaged zooplankton communities in Canadian Lakes: the relative importance of abiotic, biotic and spatial variables

2012· article· en· W1526583115 on OpenAlexaffabout
Derek K. Gray, Shelley E. Arnott, Justin A. Shead, Alison M. Derry

Bibliographic record

VenueFreshwater Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité du Québec à MontréalOntario Science CentreQueen's University
Fundersnot available
KeywordsAbiotic componentZooplanktonEcologyBiological dispersalBiotic componentEnvironmental scienceCommunity structureBiotaMultivariate statisticsBiologyPopulation

Abstract

fetched live from OpenAlex

Summary 1. Acidification has damaged biota in thousands of lakes and streams throughout eastern North America. Fortunately, reduced emissions of sulphur dioxide and nitrogen oxides beginning in the 1960s have allowed pH levels in many affected systems to increase. Determining the extent of biological and pH recovery in these systems is necessary to assess the success of emissions reductions programmes. 2. Although there have been promising signs of biological recovery in many systems, recovery has occurred more slowly than expected for some taxa. Past studies with crustacean zooplankton indicate that a mixture of local abiotic variables, biotic variables and dispersal processes may influence the structure of recovering communities. However, most studies have been unable to determine the relative importance of these three groups of variables. 3. We assessed chemical and biological recovery of acid‐damaged lakes in Killarney Park, Ontario. In addition, we assessed the relative importance of local abiotic variables, biotic variables and dispersal processes for structuring recovering communities. We collected zooplankton community data, abiotic and biotic data from 45 Killarney Park lakes. To assess the recovery of zooplankton communities, we compared zooplankton data collected in 2005 to a survey conducted for the same lakes in 1972–73 using several univariate measures of community structure, as well as multivariate methods based on relative species abundances. To determine the factors influencing the structure of recovering zooplankton communities, we used hierarchical partitioning for univariate measures and spatial modelling and variation partitioning techniques for multivariate analyses. 4. Our survey revealed significant pH increases for the majority of sampled lakes but univariate measures of community structure, such as species richness and diversity, indicated that only minor changes have occurred in many acid‐damaged lakes. Hierarchical partitioning identified several variables that may influence our univariate measures of recovery, including pH, dissolved organic carbon (DOC) levels, fish presence/absence, lake surface area and lake elevation. 5. Multivariate methods revealed a shift in communities through time towards a structure more typical of neutral lakes, providing some evidence for recovery. Variation partitioning suggested that the structure of recovering copepod communities was influenced most by dispersal processes and abiotic variables, while biotic ( Chaoborus densities, fish presence/absence) and abiotic variables were more important for cladoceran zooplankton. 6. Our results indicate that the recovery of zooplankton communities in Killarney Park is not yet complete, despite decades of emission reductions. The importance of variables related to acidification, such as pH and DOC, indicates that further chemical recovery may be necessary. The differing importance of abiotic, biotic and dispersal processes for structuring copepod versus cladoceran zooplankton might indicate that different management approaches and expectations for recovery are needed for these groups.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.806

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 studies0.0000.001
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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations38
Published2012
Admission routes2
Has abstractyes

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