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Record W1899436577 · doi:10.5268/iw-3.1.589

Toward a better understanding of Lake Simcoe through integrative and collaborative monitoring and research

2013· article· en· W1899436577 on OpenAlexaffabout
Michelle E. Palmer

Bibliographic record

VenueInland Waters · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsEnvironmental scienceHydrology (agriculture)Environmental resource managementGeology

Abstract

fetched live from OpenAlex

This special section of Inland Waters features the first of numerous papers that highlight trends and insights emerging from decades of ecological monitoring and research activities on Lake Simcoe, Canada. Lake Simcoe is the largest lake in southern Ontario after the Laurentian Great Lakes. Like most large lakes, Simcoe has been negatively impacted over the past century by human activities, which accelerated dramatically around the 1930s (Hawryshyn et al. 2012). Phosphorus (P) loading from point and nonpoint sources caused excessive growth of plants and algae that consume hypolimnetic oxygen during decomposition, which limited coldwater fish habitat and contributed to the recruitment failure of popular sportfish such as lake trout ( Salvelinus namaycush ) and lake whitefish ( Coregonus clupeaformis ; Evans et al. 1996). The establishment in recent decades of invasive fish, invertebrates, and plants is changing lake habitat, food webs, and native species dynamics (Evans et al. 2011, Ginn 2011, Ozersky et al. 2011). Increasing air temperature associated with climate change has prolonged thermal stratification and shortened the period of ice cover (OMOE et al. 2009, Stainsby et al. 2011). Metals and organic pollutants originating from urban and industrial sources have accumulated in lake and tributary sediments (Helm et al. 2011, Landre et al. 2011), potentially affecting aquatic biota and increasing the risk associated with human fish consumption (Gewurtz et al. 2011, Lembcke et al. 2011). Additionally, the cumulative effects of these and other stressors have drastically altered aquatic communities (Depew et al. 2011, Ginn 2011, Jimenez et al. 2011, Winter et al. 2011). In response to public concern about the ecological health of the lake, the Lake Simcoe Protection Act was approved by the Government of Ontario in 2008 with a mandate to protect and restore the Lake Simcoe watershed (Government of Ontario 2008). The Act established the Lake Simcoe Protection Plan (LSPP; OMOE et al. 2009) that identifies a number of targets and indicators to characterize environmental health in the Lake Simcoe watershed and details 119 policies and actions to achieve these targets. Scientific monitoring and research play an integral role in the success of the LSPP, which supports an ecosystem approach to informing policies and actions, taking into account the interconnectedness of the lake and watershed. The LSPP mandates the enhancement of current monitoring programs, development of new monitoring programs, and the promotion and implementation of research projects that build upon existing science to continually update management decisions as part of an adaptive management approach. The challenges posed by the LSPP necessitate collaborative research efforts and sharing of responsibilities, resources, and knowledge among federal, provincial, and local governments, academics, conservation authorities, agricultural, commercial, and industrial sectors, First Nations communities, the general public, and other stakeholders. The collection of papers shows the value of a collaborative approach and demonstrates how strong partnerships can facilitate integrative approaches to scientific monitoring and research efforts being used to protect Lake Simcoe.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.078
GPT teacher head0.312
Teacher spread0.234 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

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