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Record W4404097946 · doi:10.1016/j.agsy.2024.104169

Agronomic and economic effects of wetlands on crop yields using precision agriculture data

2024· article· en· W4404097946 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgricultural Systems · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsGenome PrairieUniversity of AlbertaUniversity of Saskatchewan
FundersEnvironment and Climate Change Canada
KeywordsWetlandAgriculturePrecision agricultureAgricultural engineeringCropEnvironmental scienceAgricultural economicsAgronomyAgroforestryEconomicsGeographyEcologyEngineeringBiologyArchaeology

Abstract

fetched live from OpenAlex

Wetland drainage has become an increasingly important conservation issue in the Prairie Pothole region of North America. Financial incentives for annual crop production have driven wetland drainage for decades, and the removal of wetlands has detrimentally impacted key wetland ecosystem services such as wildlife habitat and carbon sequestration. Past studies which model the farmer's decision to drain wetlands often operate on the assumption that drained wetlands will produce similar yields to upland regions of the field. Our objective is to estimate the effects of wetlands and their buffer zones on crop yields, farm financial performance, and incentives for wetland drainage in the Prairie Pothole Region. We combine precision yield data and detailed wetland mapping data from 36 fields in the Black and Dark Brown soil zones of Saskatchewan, Canada to estimate the agronomic impacts of wetlands and their buffer areas on crop yields. Then, we incorporate these yield effects into a farm accounting model with three wetland drainage scenarios to estimate the annual per cultivated acre net benefits of wetland drainage in the study area, and compare these results to those estimated without wetland yield effects. We find that yields in wetland basins are relatively lower than the field's average yield, with substantial variability with respect to crop type, soil zone, and annual precipitation. Wetland drainage can mitigate these yield effects, but yields in drained wetland basins still fail to meet the field average yield. These yield effects can extend more than 50 m beyond the wetland boundary. We find that these effects substantially impact the net benefits of wetland drainage. The returns from wetland drainage increase when yield effects are considered. On average, full wetland drainage within the study area increases net benefits by $17 to $33 per cultivated acre relative to full wetland restoration. The results demonstrate the importance of considering wetland and buffer zone yield effects in wetland drainage decisions, improve our understanding of wetland costs, and potentially inform policy development and the design of incentives for wetland conservation in agricultural landscapes. • The agronomic effects of wetlands have rarely been considered in previous studies of wetland conservation costs in the PPR. • Precision yield and wetland mapp data is used to estimate the effects of wetlands on crop yields and farm finances. • Wetlands and their buffer zones have substantial negative effects on crop yields in the Prairie Pothole Region. • Wetland drainage can mitigate these yield effects, providing further incentive for drainage in the PPR. • The financial incentives for wetland drainage vary with respect to soil zone, technology use, and annual precipitation.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.443

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 studies0.0000.000
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 head0.012
GPT teacher head0.218
Teacher spread0.205 · 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