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Record W1499160066 · doi:10.1029/2007wr006781

Longer‐term effects of pine and eucalypt plantations on streamflow

2008· article· en· W1499160066 on OpenAlexaff
David F. Scott, F. W. Prinsloo

Bibliographic record

VenueWater Resources Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersHans Merensky FoundationWater Research Commission
KeywordsAfforestationStreamflowEnvironmental sciencePinus radiataEucalyptusAgroforestrySubtropicsDrainage basinTropicsAgronomyHydrology (agriculture)GeographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

The longer‐term effects of afforestation with Pinus radiata and Eucalyptus grandis on streamflows were analyzed using data from two paired‐catchment experiments in South Africa. The experiments are rare in that they have been maintained over longer periods than the typical rotation period for industrial timber plantations in the tropics or subtropics. In both experiments the planting treatments led to large reductions in streamflow, which increased with the age of the trees and were positively related to water availability. The pine plantation caused peak reductions in yield over a 5‐year period of 44 mm a −1 or 7.7% a −1 for each 10% of catchment planted when the trees were between 10 and 20 years old. The eucalypt plantation caused peak reductions over a 3‐year period of 48 mm a −1 and 10% a −1 for each 10% of catchment planted. However, as the plantations matured (over 30 years of age in the case of pines and over 15 years of age in the case of eucalypts) the flow reduction trend was reversed, and streamflow effects appear to be tending toward preafforestation levels. The longer‐term effects of planted forests need not be as harmful on the water yield of catchments as has been predicted from shorter‐term studies. The implication of these results is that if trees are grown on very long rotations, they may be used for restoring degraded catchments or as a means of storing carbon without completely denuding available water resources.

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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.487

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 studies0.0000.001
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 head0.028
GPT teacher head0.285
Teacher spread0.257 · 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.

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

Citations137
Published2008
Admission routes1
Has abstractyes

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