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Record W3136014982 · doi:10.7939/r3-5skr-fd90

Adaptation of white spruce populations to extreme climate events: implications for assisted migration practices in Western Canada

2019· article· en· W3136014982 on OpenAlexaboutno aff
Jaime Sebastian‐Azcona

Bibliographic record

VenueUniversity of Alberta Library · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)White (mutation)GeographyClimate changeEcologyBiology

Abstract

fetched live from OpenAlex

The movement of seed sources from south to north has been proposed as a tool to mitigate the effect of climate change on forest productivity and mortality. Southern provenances, coming from warmer regions are expected to better utilize the extended growing seasons expected under climate warming. But even if temperatures are warming overall, early fall frost events or late spring frost events may still occur at similar or even increased frequencies relative to the growth phenology of plants. If trees are not correctly adapted to the length of the growing season, and they release dormancy to early or stop growing too late, they will suffer frost damage. To find the best adapted provenances I studied here different physiological adaptations to climate that should help delineate safe transfer distances of white spruce (Picea glauca [Moench] Voss), using a range-wide provenance trial in Central Alberta. I measured physiological and anatomical traits related to drought resistance and cold hardiness, and implemented a novel tree ring approach to detect xylem anomalies induced by past climate events. My results showed tradeoffs between fall cold hardiness and tree growth primarily along a latitudinal cline. Southern provenances showed higher growth but a later onset of cold hardiness. Latitude of source origin was the most influential environmental variable for both tree height and cold hardiness, suggesting a strong effect of day length regimes in the control of the length of the growing season. Provenances from southern latitudes of origin and from eastern maritime climate conditions showed high productivity, but were also more susceptible to the occurrence of abnormally thin cell wall thickness and unlignified tracheids in the latewood during cold years, indicating a mismatch of growth phenology with the available growing season. Provenances from maritime and warm source environments also had higher mortality rates despite showing good growth. In contrast, provenances from the northern part of the distribution were more vulnerable to late spring frosts when grown in at a warmer test site than their origin climate. The physiological traits related to drought resistance and anatomy measured in this study did not show any significant difference throughout the range of the species, although we found some tradeoffs between hydraulic safety and efficiency. Based on population differentiation observed in this study, hardiness zones could also be used to limit the distance of seed transfers within the species range. The results of this study support moderate northward movement of populations to address climate trends that have already occurred over the last decades. The best performing provenances in this trial came from the southern central part of the distribution (South East Manitoba), about 500 km south and 1,500 km east of the test site and a region with warmer summers and similar winter temperatures and precipitation. These climatic conditions are consistent with expected climate change, and therefore assisted migration prescriptions northward and upward in elevation to moderately cooler temperature (–1 to –2°C difference) seem well supported by this study.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.023
GPT teacher head0.216
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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