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Record W4414225148 · doi:10.24124/2025/30583

Climate and biological resilience at the northern limit of British Columbia’s Inland Temperate Rainforest

2025· dissertation· en· W4414225148 on OpenAlexaboutno aff
Nathan Malcomb

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsTemperate rainforestRainforestTemperate climateProductivityClimate changeBiomass (ecology)DendroclimatologyEcosystemTemperate forestLatitude

Abstract

fetched live from OpenAlex

,Climate-mediated shifts in forest productivity hold uncertain impacts for temperate rainforest ecosystems. While considerable focus has been devoted to detecting, monitoring, quantifying, and modeling ecological change, variable tree responses across biogeographic gradients complicate ongoing research. In British Columbia, arid montane forests are dynamically reorganizing to meet evolving environmental conditions, as evidenced by large-scale disturbance processes such as mega-fires and insect outbreaks. Less is known about the more subtle climate responses impacting the Inland Temperate Rainforest. As these forests are among the most productive in the world, shifts in forest growth may have lasting implications for global climate and ecological, economic, and cultural systems. This thesis documents the influence of the recent climate variability on an ITR ecosystem in the northern Rocky Mountains of British Columbia. Findings complement the existing body of limited research in this biologically rich but relatively understudied region by producing multi-species tree-ring chronologies from high- and low-elevation sites. Using multiple analytical techniques, results from tree-ring, biomass, and dendroclimatic analyses highlight the role of biogeography in mediating climate sensitivity and tree growth across species and elevation gradients. Stand-level biomass estimates reveal the significant carbon storage potential of lower-elevation forests, rivaling productive temperate rainforests in the coastal Pacific Northwest. Dendroclimatic analysis highlights the role of temperature and snow in limiting tree growth, with the highest productivity periods occurring during years with slightly above-average temperatures, below-average snowpack, and average precipitation. As expected at this northern latitude site, low growth occurs during cold years with heavy snowpack. Still, trees also display negative growth responses to above-average temperatures and drought, particularly at low elevations. Despite near-normal precipitation in the recent decade, thermal stress during periodic "heat domes" is becoming an overarching driver of reduced biomass accumulation in old-growth western red cedar, an iconic keystone species and dominant carbon pool in the ITR. Intervals of reduced growth throughout the 121-year study period have been followed by notable plasticity across cedar and other co-dominant species, showing potential for increased productivity under projected climate scenarios. The long-term trajectory of the ITR will hinge on species-level adaptations to nonanalog warming conditions projected for the next century and conservation measures that protect the structural and compositional resiliency of these globally significant ecosystems. Remarkable adaptability is evident in study species which thrive from the Northern Rockies (Engelmann spruce and subalpine fir) to the Sierra Madre of central Mexico (Douglas-fir) and along the Pacific Northwest coast to northern California (western hemlock, western red cedar, Douglas-fir). Dedicated research and conservation efforts across these ranges are essential for enabling the forests of the ITR to adapt to changing environmental conditions. This thesis underscores the ITR’s critical role as a globally significant carbon sink and biodiversity reservoir. Building on existing conservation efforts, it calls for the creation of the Great Caribou Rainforest Initiative. Modeled after the Great Bear Rainforest Framework, this initiative aligns scientific evidence with cultural and economic values to create best-practice climate change mitigation strategies safeguarding the ITR’s adaptive capacity, carbon storage, and biodiversity.

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)0.000
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 score0.040
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.203
Teacher spread0.198 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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