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Record W7057190463

IMPACT OF CLIMATE VARIABILITY AND FOREST MANAGEMENT REGIMES ON WATER AND ENERGY FLUXES IN TEMPERATE FORESTS IN THE GREAT LAKE REGION

2024· dissertation· en· W7057190463 on OpenAlexfundaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
FundersGlobal Water FuturesMinistry of EnvironmentOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaMcMaster UniversityOntario Innovation TrustOntario Ministry of Natural Resources and ForestrySocial Sciences and Humanities Research Council of CanadaMinistry of Natural Resources
KeywordsEvapotranspirationEddy covarianceTemperate rainforestClimate changeGreenhouse gasTemperate forestTemperate deciduous forestCarbon sequestrationForest ecologyTemperate climate
DOInot available

Abstract

fetched live from OpenAlex

Forest ecosystems cover about 30% (42 million km²) of the Earth's land surface and 25% of these forests are located in temperate climate zone. Forests play a crucial in global carbon cycle and provide numerous goods and services. Due to warmer temperatures caused by increasing greenhouse gas emissions, forest ecosystems have become an important player in withdrawing carbon dioxide from the atmosphere and providing natural climate solutions. While the role of forests in carbon sequestration is well-recognized, less emphasis has been placed on their role in water and energy exchanges, particularly in the context of climate change and extreme weather events. Understanding these exchanges is crucial for assessing the cooling potential of forests through carbon sequestration and evapotranspiration, which significantly influence the carbon and water cycles, respectively. This study analyzed long term eddy covariance measurements of water and energy fluxes from 2012 to 2021 at five forest sites in Southern Ontario, Canada, which are part of the Turkey Point Environmental Observatory. These temperate forests, which grow under similar climatic and edaphic conditions, included four conifer forests comprising three white pine plantations of different ages (83, 48, and 20 years old) and an 81-year-old red pine plantation forest that underwent four different variable retention harvesting (VRH) treatments and a >90-year-old naturally regenerated but managed deciduous forest. The analysis of evapotranspiration (ET) and water use efficiency (WUE) in the deciduous forest revealed impacts of extreme weather events and environmental variables. At daily timescale, ET was primarily controlled by photosynthetically active radiation (PAR) and air temperature (Tair). The mean annual ET was 419 ± 45 mm year-1 from 2012 to 2020. The highest annual ET of 521 mm occurred in 2020, a year characterized by hot and dry conditions, while the lowest annual ET of 359 mm was recorded in 2014, a wet year with more cloudy conditions. Concurrent hot and dry conditions generally increased ET. On average, ET represented 38% of precipitation (P) for the study period. The highest annual WUE (the ratio of Gross Ecosystem Productivity (GEP) to ET) of 4.4 g C kg H₂O⁻¹ was observed in the cool year of 2014, whereas the lowest values of 3.0 and 3.1 g C kg H₂O⁻¹ were found in the hot and dry year of 2012 and the dry year of 2020, respectively. WUE increased from 2012 to 2014, then decreased from 2015 to 2020, where each year (except 2019) experienced extreme weather conditions (e.g., hot, dry, or hot-dry). Dry conditions were defined as periods when the Relative Extractable Water (REW) was below 0.4, while hot conditions were identified when the daily maximum temperature (Tmax) reached or exceeded 27.5°C. This temperature threshold corresponds to the 90th percentile of daily Tmax over the 30-year reference period (1971–2000), based on data from the ECCC weather station in Delhi, Ontario. The results showed the impacts of consecutive and concurrent extreme weather events on the forest water and carbon cycle and the WUE. Overall, WUE was mainly regulated by vapour pressure deficit (VPD). ET and WUE in the conifer (white pine) forests showed differences among stands due to their ages. The mean annual ET values were 465 ± 41, 466 ± 32, and 403 ± 21 mm yr⁻¹ in the 83-, 48-, and 20-year-old stands, respectively, from 2008 to 2021. The two oldest forests exhibited higher annual ET values than the youngest forest and the deciduous stand. On average, ET accounted for 43% of total annual precipitation in the two older forests and 38% in the youngest forest, with the ET/P ratio in the latter being similar to that of the deciduous forest. The mean annual WUE values were 3.4 ± 0.4, 3.6 ± 0.4, and 4.0 ± 0.8 g C kg H₂O⁻¹ in the 83-, 48-, and 20-year-old stands, respectively, indicating overall higher WUE compared to the mean annual WUE of 3.3 ± 0.4 g C kg H₂O⁻¹ in the deciduous forest. Similar to the deciduous forest, Tair emerged as the dominant factor controlling ET and WUE across all three conifer stands of varying ages, but specifically at the monthly timescale. The oldest conifer forest exhibited lower sensitivity to drought, suggesting its higher resilience to dry conditions, likely due to its well-established rooting system and more open and diverse species composition in the understory due to management practices. Moreover, a decline in the ET/P ratio was observed in all three conifer stands over three consecutive drought years from 2015 to 2017. WUE during these drought years increased, with the youngest stand generally exhibiting the highest WUE. Such an increase in WUE was also observed in the deciduous forest over the same period. Lastly, the analysis of sap flow velocity (SV) in the 81-year-old red pine trees was conducted across four different VRH treatments: 33% dispersed basal area retention (33D), 55% dispersed retention (55D), 33% aggregated retention (33A), and 55% aggregated retention (55A), along with an unharvested control (CN) plot. The results illustrated that the 55D treatment was the most optimal forest management practice to promote forest growth, as indicated by the higher transpiration rates. PAR was identified as the primary driver of daily sap flow across VRH treatments, followed by Tair. However, vapor pressure deficit (VPD) assumed greater importance on hourly timescale. Overall, studies conducted in this dissertation have enhanced our understanding of water and energy exchange dynamics in temperate conifer and deciduous forests, particularly in response to interannual variability and extreme weather events. The studies have also contributed to valuable insights into the impact of forest management practices on the resilience of the forests to drought events. This work will help to develop strategies for enhancing forest growth, carbon uptake and water use efficiency, which are vital for forest ecosystems adapting to climate change. These findings will aid stakeholders in adopting effective forest management regimes to promote sustainability and resilience to climatic stresses in forest ecosystems.

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)0.000
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 score0.518
Threshold uncertainty score0.958

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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
Published2024
Admission routes2
Has abstractyes

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