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Record W4398786206 · doi:10.1360/sste-2023-0106

中国亚热带地区<bold>2000~2019</bold>年森林海拔分布特征及其时空动态

2024· article· zh· W4398786206 on OpenAlex
振灿 郑, 留文 庄, 国芳 缪, 涵 刘, 志强 程, 纹宇 李, 荣 商, 鹏 宫, 镜明 陈

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.

Bibliographic record

VenueSCIENTIA SINICA Terrae · 2024
Typearticle
Languagezh
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInternal medicineEndocrinologyChemistryMedicine

Abstract

fetched live from OpenAlex

中国亚热带地区拥有丰富的森林资源, 且具有多山特征. 在自21世纪之初开始的天然林保护和退耕还林等政策实施以及气候变化背景下, 该区域的森林资源较历史时期已发生显著变化; 同时, 森林资源多分布于山地也意味着这些变化可能随海拔高度而呈现显著差别. 为探讨自2000年以来中国亚热带地区森林分布的时空动态变化, 尤其随海拔高度的变化趋势, 本研究利用两类土地覆被产品, 从森林覆被与森林类型两个角度逐步开展分析; 研究采用分级方式, 利用不确定性相对小的粗分类森林覆被数据, 对不确定性更大的森林类型数据作一定程度的约束, 以实现在获取更细节的信息与减小数据的不确定性之间达到合理平衡. 首先将森林覆被数据拆解为稳定及变化两大类, 随后以森林覆被结果为基础, 进一步分析森林类型数据中的稳定与变化状况. 分析结果显示, 中国自实施森林资源生态工程和管理政策以来, 亚热带地区54%面积的森林覆被属性在近20年来一直处于稳定状态, 可作为生态环境处于良好状态的表征之一; 结果同时也显示出长期存在的森林与耕地等基本生产需求的动态转换. 随海拔高度的动态变化分析则进一步显示, 700m以下的低海拔地区以森林与耕地间的动态转换为主; 700~1500m中海拔地区以森林与灌丛的转换为主; 2000m以上的高海拔地区则以与草地的转换为主. 在森林覆被属性稳定的区域, 96%的森林类型也处于不变状态, 其中海拔1700m以下常绿阔叶林分布面积最大, 海拔1700m以上则以常绿针叶林为主; 该区域也仍有较大面积的常绿针叶林和常绿阔叶林存在与林灌草混交带和自然植被农田混交带这两种过渡森林类型间的动态转换, 其中常绿针叶林在1000m以下的低海拔地区基本单向地转出为林灌草混交带, 而在1000m以上的中高海拔地区则主要由自然植被农田混交带转入而来; 常绿阔叶林在低海拔地区有一定面积减少而转出为林灌草混交带, 但在中低海拔地区的面积增加则均来自于自然植被农田混交带的转入. 这些随海拔高度呈现的变化特征, 可能包含特定人为活动和气候变化的影响, 将为未来更深入探讨中国亚热带地区森林资源的生态系统服务功能演变提供垂直维度的信息和视角.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.005
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0650.114

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 head0.084
GPT teacher head0.397
Teacher spread0.313 · 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