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Record W3155012700 · doi:10.1111/geb.13291

Multi‐decade tree mortality in temperate old‐growth forests of Europe and North America: Non‐equilibrial dynamics and species‐individualistic response to disturbance

2021· article· en· W3155012700 on OpenAlexfundno aff
Kerry D. Woods, Thomas A. Nagel, Bogdan Brzeziecki, C. Mark Cowell, Dejan Firm, Peter Jaloviar, Stanislav Kucbel, Yiching Lin, Zbigniew Maciejewski, Jerzy Szwagrzyk, Jaroslav Vencúrik

Bibliographic record

VenueGlobal Ecology and Biogeography · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersVedecká Grantová Agentúra MŠVVaŠ SR a SAVAgentúra na Podporu Výskumu a VývojaJavna Agencija za Raziskovalno Dejavnost RSMinistry of Business, Innovation and EmploymentMcGill University
KeywordsTemperate rainforestEcologyTemperate forestTemperate climateForest dynamicsDisturbance (geology)GeographyAbundance (ecology)Old-growth forestBiologyEcosystem

Abstract

fetched live from OpenAlex

Abstract Aim Old‐growth, mesic temperate forests are often assumed to be structured by gap‐phase processes, resulting in quasi‐equilibrial long‐term dynamics. This assumption influences management focused on simulation of natural disturbance dynamics and is embedded in most models of forest successional dynamics. We use multi‐decade monitoring of permanent plots in old‐growth forests to assess demographic assumptions directly with respect to tree mortality rates. Location Sixteen sites in mesic, temperate old‐growth forests in eastern North America and Europe with multi‐decade monitoring. Time period Variable across sites, spanning c. 20–78 years from 1936 to 2014. Major taxa studied Tree species of late‐successional, cool‐temperate forests of Europe and eastern North America. Methods We calculated and compared the annualized mortality rates (m), with confidence intervals, by species, size class and measurement interval, for tree species of sufficient abundance. Results Retrospective analysis shows dynamic and diverse demographic properties across populations and sites. Stand‐scale mortality rates of 0.7–2.5%/year average higher than previous estimates for old‐growth temperate forests. Variations among species, over time and among size classes, suggest that gap‐phase models are inadequate to explain stand dynamics, implying instead that rare disturbance events of moderate severity have long‐lasting effects in old‐growth forests and that indirect anthropogenic influences affect old‐growth, unlogged forests. Main conclusions Multi‐decade baseline data, essential for understanding community assembly and long‐term dynamics in these “slow systems,” are rare and poorly integrated. Our analysis demonstrates the value of the few long‐term, “legacy” data sets. Results suggest that differences in life history interact with complex disturbance histories, resulting in non‐equilibrial dynamics in old‐growth temperate tree communities, and that changes in disturbance patterns through anthropogenic climate change might, therefore, be an important driver of ecosystem change.

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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.233
Teacher spread0.225 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

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