Spatiotemporal characteristics and temporal stability of soil water in an alpine meadow on the northern Tibetan Plateau
Bibliographic record
Abstract
The spatiotemporal characteristics of soil water content (SWC) have a significant influence on vegetation degradation and growth in alpine meadow ecosystems. The spatiotemporal variability and temporal stability (TS) of SWC, however, have rarely been studied on the northern Tibetan Plateau owing to the rugged and hostile sampling environment. The objective of this study was to analyze the spatiotemporal variability and the TS of SWC in various layers of the soil, to a depth of 50 cm in a 33.5 hm2 plot, with the data obtained from 113 measuring locations collected on 22 sampling occasions during the growing seasons of 2015 and 2016. The SWC was moderately variable both in time (two consecutive growing seasons) and horizontal space (plot). The variabilities, however, did not vary consistently with increasing depth for the various dominant influencing factors. The SWC in the undeveloped, shallow, and stony alpine meadow soil was temporally stable; TS did not depend on depth due to disturbances by grass roots and stones. The best representative location of TS at each depth could be determined, and all accurately estimated the field mean SWC. Vegetation coverage, soil organic carbon, gravel and stone contents, and saturated hydraulic conductivity were the main factors influencing TS. This study provides useful information for the management of alpine meadows and provides an effective method for studying SWC at a hectometre scale on the Tibetan 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".