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Three Gorges Dam: Impact of Water Level Changes on the Density of Schistosome-Transmitting Snail Oncomelania hupensis in Dongting Lake Area, China

2015· article· en· W796357161 on OpenAlexaff
Jinyi Wu, Yibiao Zhou, Yue Chen, Song Liang, Linhan Li, Sheng-Bang Zheng, Shao-Ping Zhu, Guanghui Ren, Xiuxia Song, Qingwu Jiang

Bibliographic record

VenuePLoS neglected tropical diseases · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsOncomelania hupensisSnailWater levelSchistosoma japonicumEcologyGeographyHabitatWetlandSchistosomiasisElevation (ballistics)OncomelaniaEnvironmental scienceBiologyHelminthsCartographyZoology

Abstract

fetched live from OpenAlex

BACKGROUND: Schistosomiasis remains an important public health issue in China and worldwide. Oncomelania hupensis is the unique intermediate host of schistosoma japonicum, and its change influences the distribution of S. japonica. The Three Gorges Dam (TGD) has substantially changed the ecology and environment in the Dongting Lake region. This study investigated the impact of water level and elevation on the survival and habitat of the snails. METHODS: Data were collected for 16 bottomlands around 4 hydrological stations, which included water, density of living snails (form the Anxiang Station for Schistosomiasis Control) and elevation (from Google Earth). Based on the elevation, sixteen bottomlands were divided into 3 groups. ARIMA models were built to predict the density of living snails in different elevation areas. RESULTS: Before closure of TGD, 7 out of 9 years had a water level beyond the warning level at least once at Anxiang hydrological station, compared with only 3 out of 10 years after closure of TGD. There were two severe droughts that happened in 2006 and 2011, with much fewer number of flooding per year compared with other study years. Overall, there was a correlation between water level changing and density of living snails variation in all the elevations areas. The density of living snails in all elevations areas was decreasing after the TGD was built. The relationship between number of flooding per year and the density of living snails was more pronounced in the medium and high elevation areas; the density of living snails kept decreasing from 2003 to 2014. In low elevation area however, the density of living snails decreased after 2003 first and turned to increase after 2011. Our ARIMA prediction models indicated that the snails would not disappear in the Dongting Lake region in the next 7 years. In the low elevation area, the density of living snails would increase slightly, and then stabilize after the year 2017. In the medium elevation region, the change of the density of living snails would be more obvious and would increase till the year 2020. In the high elevation area, the density of living snails would remain stable after the year 2015. CONCLUSION: The TGD influenced water levels and reduced the risk of flooding and the density of living snails in the study region. Based on our prediction models, the density of living snails in all elevations tends to be stabilized. Control of S. japonica would continue to be an important task in the study area in the coming decade.

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 score0.445
Threshold uncertainty score0.505

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 head0.053
GPT teacher head0.280
Teacher spread0.227 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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