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Record W6958995233 · doi:10.7302/22607

Accelerating Watershed Conservation Planning & Implementation in Michigan’s Stony Creek Subwatershed: A Bottom-Up Approach to Reducing Phosphorus Loading into Lake Erie

2024· other· en· W6958995233 on OpenAlexaboutno aff

Bibliographic record

VenueDeep Blue (University of Michigan) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsVegetation (pathology)SustainabilityAgricultural productivityAgricultureWatershedGovernment (linguistics)Hydrology (agriculture)

Abstract

fetched live from OpenAlex

Since the mid-1990s, an increase in annual cyanobacterial harmful algal blooms (HABs) in the Western Lake Erie Basin (WLEB) has driven a focus on nonpoint source (NPS) nutrient pollution in tributary watersheds, especially in the states of Michigan, Indiana and Ohio, and in the Canadian province of Ontario (EGLE et al., 2021; Green et al., 2023; Watson et al., 2016). Attention to the issue was intensified in 2014 when a HAB in WLEB led to a drinking water crisis in Toledo, Ohio, which spurred commitments by the governments of Ohio, Michigan, and Ontario to achieve a 40% reduction of phosphorus loading into the lake by the year 2025 (Snyder et al., 2015; Steffen et al., 2017). However, these states are not currently on track to meet their reduction targets. To address NPS loading into the lake, government attention turned to the approximately 7 million acres draining directly into the WLEB, as well as the region’s primary land use: agricultural production (OSU Extension, 2024). Agricultural production is associated with 70-90% of NPS phosphorus loading into WLEB (Wilson et al., 2019), which can be mitigated through the use of agricultural best management practices (BMPs) for conservation. In Michigan’s 2021 Adaptive Management Plan for Lake Erie, the state identifies and prioritizes 13 subwatersheds for data collection and evaluation toward increased BMP adoption. To explore a new approach in localized conservation planning, the Michigan Department of Agriculture and Rural Development (MDARD) partnered with the University of Michigan School for Environment and Sustainability (SEAS) to research the factors contributing to producer conservation choices in a select priority subwatershed. The Stony Creek (South Branch River Raisin), a HUC-12 component of the River Raisin watershed, was chosen for this research effort. Over a sixteen-month period, our team of five SEAS graduate students reviewed literature related to agricultural, social, biochemical, and economic aspects of WLEB algal blooms; performed informal outreach and information gathering through event participation and farm visits; conducted 12 stakeholder interviews with producers, community members, and local experts; developed an erosion risk map of the subwatershed through GIS analysis utilizing the RUSLE model; and formed a steering committee to direct the development of a Watershed Conservation Plan (WCP) for Stony Creek. Through these various research efforts and their respective results, we synthesized three Key Themes that affect BMP adoption in Stony Creek: 1. Socio-cultural influences and personal attitudes factor heavily in farmer decisionmaking around BMP adoption; 2. Simplicity and specificity of conservation programming play a large role in adoption rates of conservation practices; and 3. Financial incentives are necessary but not alone sufficient for improving BMP adoption rates. Within these three themes, we identified nine cross-cutting barriers and six motivators to conservation adoption in Stony Creek. Based on these barriers and motivators, we developed five key recommendations for improving BMP adoption in Stony Creek: 1. Increase and stabilize funding and support for Lenawee Conservation District; 2. Improve accessibility and simplicity of conservation programming; 3. Improve information and education efforts in Stony Creek concerning BMPs; 4. Enhance avenues for collaboration between producer communities, trusted organizations, and stakeholders to engage with cost-share policies; and 5. Develop a strategic approach to attract and retain younger producers in rural farming communities. Our research findings drove the completion of a Sub-Watershed Conservation Plan (WCP) for Stony Creek, guided by a steering committee of local producers and stakeholders in agricultural conservation and watershed management. In the Stony Creek WCP, we recommend precision agriculture practices (nutrient management, nutrient mass-balance calculations, and precision application of nutrients) and two suites of BMPs based on field topography. While our research findings and recommendations are specific to Stony Creek

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.266
Teacher spread0.237 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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