MétaCan
Menu
Back to cohort
Record W4281980485 · doi:10.1016/j.foreco.2022.120324

A global synthesis on the effects of thinning on hydrological processes: Implications for forest management

2022· article· en· W4281980485 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueForest Ecology and Management · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Toronto
FundersAgencia Estatal de InvestigaciónUniversitat Politècnica de ValènciaJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsThinningEnvironmental scienceEvapotranspirationThroughfallTranspirationWater contentStemflowForest managementHydrology (agriculture)Forest ecologyClimate changePrecipitationEcosystemSoil waterAgroforestrySoil scienceEcologyForestryGeographyGeologyMeteorologyBiology

Abstract

fetched live from OpenAlex

Forest thinning can significantly affect hydrological processes. However, these effects largely vary with forest types, climate, thinning intensity, and hydrological variables of interest. Understanding these effects and their variations can significantly support thinning treatments' design and selection to ensure desired hydrological benefits. In this global-level review paper, we report the first comprehensive meta-analysis on the effects of thinning on major hydrological processes with an emphasis on rainfall partitioning, soil moisture and evapotranspiration processes. The synthesized and reviewed studies encompass different biophysical conditions (climate and forest ecosystems), silvicultural systems, and time scales (from weeks to decades) across continents. The results showed a significant increase in net precipitation, soil moisture and tree-level water use after thinning (the effect sizes are 1.19, 1.14 and 1.56 relative to the value of the control, respectively), while decreases in stemflow and transpiration (the effect sizes of 0.42 and 0.6 relative to the value of the control, respectively). Thinning intensity of about 50% of the stand density is determined as the threshold at or over which hydrological processes are significantly affected. The duration of thinning effect can be set between 2.6 and 4.3 (throughfall) and 3.1–8.6 years (soil moisture and transpiration), asking for repeated thinning in order to effectively sustain these effects. These global averages can serve as benchmarks for assessment and comparisons, but the effects of thinning depend on local biophysical conditions and thinning treatments. The literature review on the rest of the studied hydrological variables suggests that thinning generally enhance runoff to increase water yield and groundwater recharge. Thinning can also have a positive or limited role in water use efficiency (WUE), but it mitigates the effects of drought through increasing WUE. Moderate adverse effects on water quality can be prevented by adequate forest managements to prevent soil degradation. Nevertheless, more researches at relatively less studied regions are needed to support a more robust analysis of these reviewed hydrological variables. The management implications of the synthesized and reviewed results are suggested and discussed within the context of climate 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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