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Record W1566012978

Environmental assessment of the south coast of Sri Lanka, with special reference to the 2004 tsunami

2010· dissertation· en· W1566012978 on OpenAlexfundno aff
A. J. Venkatachalam

Bibliographic record

VenueWarwick Research Archive Portal (University of Warwick) · 2010
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and environmental studies
Canadian institutionsnot available
FundersUniversity of OxfordInternational Development Research Centre
KeywordsGeographyMangroveLivelihoodFisheryCoral reefCoastal erosionDeforestation (computer science)Environmental protectionSocioeconomicsAgriculture
DOInot available

Abstract

fetched live from OpenAlex

Following the 2004 tsunami in Sumatra, Sri Lanka experienced >30,000 confirmed deaths and disruption of livelihood. Damage to coastal ecosystems was less than anticipated, especially in comparison with reported impacts from unsustainable development. This research examines tsunami related damage against a background of anthropogenic pressures. Fishery changes were determined through interview of three generations of fishers targeting frigate tuna. Significantly higher values for best day’s catch and largest specimen ever caught were obtained by older fishers than younger ones. Values were also significantly higher during early years, providing clear evidence of resource decline and the ‘shifting baseline syndrome’. Most fishers reported posttsunami decline in frigate tuna, but mainly from a larger new generation of fishers, rather than extra boats provided by aid money or (direct or indirect) biophysical impacts from the tsunami. The number of boats post-tsunami increased significantly in all research areas, which could result in further catch decline. The perceptions of 500 Sri Lankan fishers about the influence of risk factors on tsunami death toll and house damage are quantified). Mangroves, coral reefs and sand dunes afforded protection against tsunami damage (67–94% of fisher responses), as did housing and roads. Fishers believed rivers/estuaries, concave coastlines and hotels exacerbated impacts. For comparison, multi-variable models for death toll, housing damage, inundation area and distance are built, incorporating both natural and developmental risk factors. Bathymetry is the only factor significantly associated with all indicators of impact. Mangroves and marsh were not a significant factor in final multivariable models. However, in terms of inundation, sand dunes were identified as protective, while bodies of water exacerbated damage. The extent of agreement and variance between modelling results and the opinions of fisher questionnaires is critically examined. Research findings highlight the need for better coastal management. While the role mangroves in tsunami protection remains equivocal, their known role in providing many other ecosystem services suggests that mangroves warrant greater conservation attention in Sri Lanka, in the face of coastal development pressures. Coastal policy and conservation priorities should be influenced by scientific research (e.g. the tsunami model in this thesis) as well as traditional ecological knowledge and opinions from indigenous people. Factors shown to provide tsunami protection often cannot be altered by human intervention (e.g. topography and bathymetry). However, sand dunes could potentially be preserved to reduce future impacts. Tsunamis are rare events and further research should be carried out to determine which risk factors are important for more frequent events (e.g. monsoon). The needs of coastal communities should always remain paramount in considerations of future tsunami and environmental policies.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2010
Admission routes1
Has abstractyes

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