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Record W2110712869 · doi:10.1139/cjfr-2014-0219

Evaluation of water use of <i>Caragana korshinskii</i> and <i>Hippophae rhamnoides</i> in the Chinese Loess Plateau

2014· article· en· W2110712869 on OpenAlexvenueno aff
Shengqi Jian, Chuanyan Zhao, Shumin Fang, Kai Yu

Bibliographic record

VenueCanadian Journal of Forest Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsTranspirationHippophae rhamnoidesPhotosynthetically active radiationVapour Pressure DeficitEnvironmental scienceShrubWater contentCaraganaSoil waterVegetation (pathology)Water useAgronomyHydrology (agriculture)BotanySoil scienceBiologyPhotosynthesisGeology

Abstract

fetched live from OpenAlex

Understanding the water-use strategy of trees and shrubs is crucial for developing effective vegetation restoration in regions that are subjected to water scarcity. We studied the water-use strategy of Caragana korshinskii Kom. and Hippophae rhamnoides L. in the Chinese Loess Plateau to evaluate the adaption strategies of these two shrubs, which are both commonly used in the restoration programs in this region. We extrapolated the measurements of water use by individual plants to determine the area-averaged transpiration of the shrublands. There was a good agreement between transpiration estimated by the Penman–Monteith method and by the sap-flow method, which suggests that that the sap-flow method can provide reliable estimates of shrub transpiration at the stand level. Stand transpiration was mainly influenced by environmental factors such as photosynthetically active radiation, vapor pressure deficit, and soil water content. When the soil water content was sufficient, photosynthetically active radiation and vapor pressure deficit were the dominant factors; however, soil water content was the primary factor under low soil moisture levels. Stand transpiration ranged from 0.52 to 4.21 mm·day −1 with a mean of 1.42 mm·day −1 for C. korshinskii and ranged from 0.57 to 3.99 mm·day −1 with a mean of 1.94 mm·day −1 for H. rhamnoides. During the experimental period (from June to September 2013), cumulative transpirations were 173.4 and 236.6 mm for C. korshinskii and H. rhamnoides, respectively, which accounted for up to 88.2% of the rainfall registered during this period. We calculated the soil water balance and measured the water potential of stems and leaves for C. korshinskii and H. rhamnoides. Hippophae rhamnoides had a lower net soil water storage, indicating that it consumed more soil water than C. korshinskii. There were some negative water potential drops between stems and leaves for H. rhamnoides, suggesting the lack of a safety margin for H. rhamnoides. Our results indicated that C. korshinskii is more suitable for afforestation than H. rhamnoides in the Loess Plateau.

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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

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

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 head0.074
GPT teacher head0.314
Teacher spread0.239 · 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
Published2014
Admission routes1
Has abstractyes

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