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Record W4413143309 · doi:10.1016/j.ecolind.2025.114014

The role of wetland vegetation and water connectivity in shaping waterbird populations under human disturbance

2025· article· en· W4413143309 on OpenAlex
Yirong Wan, Linling Tang, Xuejiao Hou, Hui‐Chen Lin, Xiaobin Cai, Zihao Huang, Qiangqiang Xu, Yuhong He

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

VenueEcological Indicators · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsDisturbance (geology)WetlandEcologyVegetation (pathology)Environmental scienceGeographyBiology

Abstract

fetched live from OpenAlex

• Under low human disturbance, rich abundance and diversity of waterbirds were observed. • Wetland vegetation coverage and water connectivity were the primary factors significantly impacting waterbird populations. • Wetland vegetation coverage had a more substantial influence on waterbirds in areas of low disturbance intensity. • The impact of water connectivity on waterbirds was complex under different intensities of human disturbance. The floodplain wetland of Poyang Lake, one of the largest stopover sites for overwintering waterbirds along the East Asian–Australasian Flyway, is experiencing rising human disturbance and rapid landscape changes. However, the impacts of these two factors on waterbird populations at three biological levels (i.e., the species, foraging guild, and community levels) remain poorly understood. Using multi-source remote sensing data and annual winter waterbird survey data (2013–2018), combined with statistical methods such as one-way ANOVA, generalized linear models, and redundancy analysis, we investigated landscape patterns influencing waterbird populations at three biological levels under human disturbance. Results indicated that most waterbird populations, excluding those specializing in invertebrate consumption, thrived greatly under low human disturbance intensity. Wetland vegetation and water connectivity played the most significant role among landscape metrics in shaping waterbird populations at three biological levels. The expanded wetland vegetation coverage strongly promoted waterbird populations, especially under low human disturbance intensity. Expanding main lakes with high water connectivity tended to suppress waterbird populations, while the newly formed shallow sub-lakes with limited connectivity promoted them. The role of water connectivity showed complexity across different intensities of human disturbance. Additionally, larger cropland patches benefited tuber- and seed-eating birds under low-moderate human disturbance, whereas built-up expansion harmed the waterbird community in highly disturbed areas. These findings offer useful insights for conserving overwintering waterbird populations and informing habitat management strategies in floodplain wetlands.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.525

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 studies0.0000.000
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 head0.022
GPT teacher head0.267
Teacher spread0.246 · 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