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Record W3208504384 · doi:10.7939/r3-cp0y-cs89

Mountain pine beetle and forest harvest effects on hydrologic processes and streamflow in the Alberta Foothills

2021· article· en· W3208504384 on OpenAlexaboutno aff
Amy Goodbrand

Bibliographic record

VenueUniversity of Alberta Library · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsFoothillsStreamflowHydrology (agriculture)Environmental scienceForestryMountain pine beetleGeographyAgroforestryGeologyDrainage basin

Abstract

fetched live from OpenAlex

The Alberta Foothills region has experienced an unprecedented mountain pine beetle (MPB) outbreak. The provincial management strategy is to contain the infestation with forest harvest. The landscape becomes a patchwork of dead (MPB grey-attack), alive, and harvested stands. MPB attack affects the water transport in trees and results in the gradual loss of the canopy structure, which has the potential to affect hydrologic processes. Therefore, there is a need to understand MPB and forest harvest effects on runoff generation and the streamflow response, especially in watersheds that provide habitat for the endangered Athabasca Rainbow Trout (ARTR). Research questions addressed in this thesis were: 1) what is the effect of varied canopy cover loss on stand water cycling in the Foothills; 2) what is the effect of forest harvest on streamflow in a Foothills watershed; and, 3) what is the effect of potential streamflow changes from MPB grey-attack and forest harvest scenarios on ARTR fry recruitment in a Foothills stream? Methods included a combination of statistical and hydrological modelling as well as data from the MPB Ecohydrology stand-level study and a long-term dataset from the Tri-Creeks Experimental Watershed (Tri-Creeks) near Robb, Alberta. Tri-Creeks has complex glacial deposits underlain by sedimentary bedrock; a geological setting with large potential for subsurface water storage. In addition, climate variability, especially meteorologically driven changes from the Pacific Decadal Oscillation (PDO), influence streamflow. Results from stand-level water balance models showed root zone drainage from the MPB grey-attack stands were similar to an undisturbed mature lodgepole pine stand. Compensatory increases in evapotranspiration from surviving vegetation (unaffected trees or understory vegetation) were predicted in the grey-attacked stands. The greatest root zone drainage occurred in the harvested stand. Results indicate regional differences in hydrologic processes that generate runoff in MPB and harvested stands. Historical clear-cut harvest within Tri-Creeks sub-watersheds was predicted to result in a significant measurable increase in rainfall-generated peak runoff events and summer runoff. However, increased runoff from harvested watersheds may have been attenuated by the drier antecedent watershed conditions in the warm PDO phase. Climate variability, in relation to antecedent watershed storage, remained a strong control on runoff generation in the watersheds. Watershed disturbance scenarios showed MPB grey-attack produced no effect on simulated streamflow response, while simulated clear-cut harvest (52% watershed area) resulted in 15% greater mean annual water yield than if grey-attack trees were left standing. Increased streamflow from forest harvest above the critical discharge threshold for streambed movement of ARTR spawning substrate during the incubation period was predicted to reduce fry recruitment, but annual fry recruitment was estimated to occur over the 50-year simulated streamflow record. Reduced fry recruitment from forest harvest was not likely to produce measurable change at the population level. Overall, results from this thesis provide better understanding of the MPB and forest harvest effects on hydrologic processes and streamflow in the Alberta Foothills and could factor into decisions about MPB strategies with respect to the endangered Athabasca Rainbow Trout.

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 score0.043
Threshold uncertainty score0.942

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.161
Teacher spread0.157 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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