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Record W3164297196 · doi:10.1111/gcb.15728

Tree growth and treeline responses to temperature: Different questions and concepts

2021· letter· en· W3164297196 on OpenAlexaff
J. Julio Camarero, Antonio Gazol, Raúl Sánchez‐Salguero, Alex Fajardo, Eliot J. B. McIntire, Eryuan Liang

Bibliographic record

VenueGlobal Change Biology · 2021
Typeletter
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsNatural Resources Canada
FundersMinisterio de Ciencia e Innovación
KeywordsChinese academy of sciencesLibrary sciencePlateau (mathematics)GeographyArchaeologyChinaComputer science

Abstract

fetched live from OpenAlex

Climate warming is expected to enhance tree growth at alpine treelines. A higher growth rate is forecasted as temperatures rise and growth becomes less dependent on the temperature rise. Since radial growth is just one component of treeline dynamics those forecasts do not necessarily apply to treeline elevation or latitude; treelines can shift upward or poleward or remain stable. In his letter to the editor, Körner (2021) commented on our recent assessment of climate impacts on tree growth at treeline (Camarero et al., 2021). We share some of his opinions such as the nonlinear responses of growth to temperature. We also agree that focusing on temperature-dependent processes such as growth can improve forecasts of treeline responses to climate. However, we disagree on his commentary suggesting that we concluded treeline will no longer be limited by low temperature and that this implies treeline and isotherms will diverge. For the sake of clarity, we must differentiate growth responses to temperature of treeline trees from treeline position responses to temperature. It must be noted that radial growth is just one component of treeline dynamics which consist of other processes, including establishment and mortality. First, our study did not aim to predict shifts in treeline position, rather we aimed to model changes in growth of treeline trees as a function of temperature. Second, non-thermal, local factors can affect growth responses at treeline including, for instance, size and age structures, biotic interactions, soil conditions or precipitation regimes (Camarero et al., 2017; Fajardo & McIntire, 2012; Wang et al., 2016). The explanatory power of growth variation based on temperature models did not evenly increase with elevation confirming threshold growth responses to temperature at treeline (Paulsen et al., 2000). According to Körner (2021), such variation would be explained by differential growth enhancement by climate warming shifting upwards or polewards. He suggests that once a threshold is surpassed, thermal effects diminish, and this would explain our findings because growth of 20th-century treeline trees will not be any more limited by low temperature since they will not form the “climatic treeline.” We reconstructed growth of 20th-century treeline trees and projected their growth rates during the 21st century based on climate scenarios with different warming rates. Our forecasts involved treeline trees, and many recruited during the 19th century, but they should also apply to treeline trees recruited recently, for example, 50 years ago. If isotherms shift upslope or poleward due to climate warming, treeline trees will be exposed to more or less thermal constraints of growth depending on treeline shift rates. Some treelines could shift while others could show lagged or null responses to climate. Isotherms may move upslope, but treeline trees may not; our study focused on trees growing at the altitudinal or latitudinal limits of tree existence today regardless of where the treeline will be in the future. Non-thermal factors such as soil moisture can also impact treeline dynamics by influencing regeneration, growth and mortality rates, thus making treeline shifts less dependent on temperature than expected (Batllori et al., 2009; McIntire et al., 2016; Sidgel et al., 2018). This would explain why many treelines are not shifting upward or poleward in response to climate warming (Harsch et al., 2009). Overall, we conclude that treeline trees showing a high growth limitation by cold temperatures during the 20th century could become less responsive to warmer conditions during the 21st century. Not applicable.

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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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.290
Teacher spread0.248 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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