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Record W6911120652 · doi:10.5063/aa/duc_merp.26.12

Marsh Ecology Research Program (MERP): Water table levels (1982-1989)

2011· dataset· en· W6911120652 on OpenAlexaffabout

Bibliographic record

VenueUC Santa Barbara · 2011
Typedataset
Languageen
Field
Topic
Canadian institutionsDucks Unlimited Canada
Fundersnot available
KeywordsMarshWetlandHydrology (agriculture)Ecosystem ecologyEcosystemWater tableWater yearTable (database)

Abstract

fetched live from OpenAlex

The Marsh Ecology Research Program (MERP) was a long-term interdisciplinary study on the ecology of prairie wetlands. A scientific team from a variety of disciplines (hydrology, plant ecology, invertebrate ecology, vertebrate ecology, nutrient dynamics, marsh management) was assembled to design and oversee a long-term experiment on the effects of water-level manipulation on northern prairie wetlands. Ten years of fieldwork (1980 -1989), combining a routine long-term monitoring program and a series of short-term studies, generated a wealth of new and diverse information on the ecology and function of prairie wetlands (Murkin, Batt, Caldwell, Kadlec and van der Valk, 2000). This data set includes water table levels, collected as part of the hydrology section of MERP. Studies of marsh ecosystems are frequently hampered by inadequate information about water budgets (Carter et al., 1979). Marshes are often open systems, particularly with respect to movement of water and associated particulate and dissolved materials (Kadlec, 1983). Efforts to evaluate the plant-nutrient relationships in such systems are contingent on knowledge of the hydrology of the system (Kadlec, 1979). Accurate estimates of water budgets are also essential pre-requisites for studies of wetland ecosystem nutrient cycles. Hence, the objective of the measurements described below, together with weather and water level/volume data, was to provide water budgets for nutrient budget calculations for the Marsh Ecology Research Program (MERP; Kadlec, 1989). The approach to hydrology used was the concept of mass balance: Inputs - Outputs = change in volume For this approach, all 3 terms had to be estimated. Change in volume was calculated from daily records of water level and water level - volume tables. Inputs of water to diked cells can be in 3 forms: precipitation, water pumped to maintain design levels, and seepage through the dike or sand ridge forming the north end of the cells. Precipitation inputs were calculated from weather records and pumping was metered, providing direct measurement. Seepage was estimated by difference, with checks based on groundwater topography and hydraulic conductivity, as well as seepage meter spot checks. Outputs of water were evapotranspiration, pumping, and seepage. Seepage out was also derived primarily by difference. Because the hydrologic characteristics of different cells in different years were replicated, estimates of the standard error in the seasonal water budgets were possible and proved to be 10% or less (Kadlec, 1989). In order to refine estimates of the inputs and outputs for the water budget of the cells, additional physical measurements were made. These factors were monitored in order to more accurately define the water storage of the cells, groundwater levels, and losses through seepage. The additional monitoring programs included: supplementary groundwater sampling adjacent to cells for nutrients, and monitoring water storage in the cells (Kadlec, 1989). The groundwater monitoring program was organized on a seasonal basis, due to the more gradual shift in groundwater makeup and supply. Sampling was done monthly for water table level and nutrients in conjunction with the regular groundwater sampling within the cells, and twice during the season for hydraulic conductivity. Note: additional hydrological data sets collected as park of MERP (i.e. water levels, pump meter volumes, precipitation, evaporation) are contained in separate data packages on the KNB. For further information on the Marsh Ecology Research Program (MERP), please visit: http://www.ducks.ca/conserve/research/projects/merp/index.html References: Carter, V., M.S. Bedinger, R.P. Novitski and W.O. Wilen. 1979. Water resources and wetlands. In: Wetland Functions and Values: The State of Our Understanding. (Eds.) P.E. Greeson, J.R. Clark and J.E. Clark, pp. 344-376. American Water Resources Association: Minneapolis, Minnesota. Kadlec, J.A. 1979. Nitrogen and phosphorus dynamics in inland freshwater wetlands. In: Waterfowl and Wetlands: An Integrated Review. (Ed.) T.A. Bookhout, pp. 17-41. North Central Section, The Wildlife Society. Kadlec, J.A. 1983. Water budgets for small diked marshes. Water Resources Bulletin 19: 223-229. Kadlec, J.A. 1989. Hydrology. In: Marsh Ecology Research Program: Long-term Monitoring Procedures Manual. (Eds.) E.J. Murkin and H.R. Murkin, pp. 8-11. Manitoba, Canada: Delta Waterfowl and Wetlands Research Station. Murkin, H.R., B.D.J. Batt, P.J. Caldwell, J.A. Kadlec and A.G. van der Valk. 2000a. Introduction to the Marsh Ecology Research Program. In Prairie Wetland Ecology: The Contribution of the Marsh Ecology Research Program. (Eds) H.R. Murkin, A.G. van der Valk and W.R. Clark. pp. 3-15. Ames: Iowa State University Press. Resulting Publications on MERP Hydrology data: Kadlec, J.A. 1983. Water budgets for small diked marshes. Water Resources Bulletin 19: 223-229. Kadlec, J.A. 1993. Effects of depth of flooding on summer water budgets for small diked marshes. Wetlands 13: 1-9.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0050.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0510.314

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 head0.147
GPT teacher head0.398
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2011
Admission routes2
Has abstractyes

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