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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
\ndeaths and disruption of livelihood. Damage to coastal ecosystems was less than
\nanticipated, especially in comparison with reported impacts from unsustainable
\ndevelopment. This research examines tsunami related damage against a background of
\nanthropogenic pressures. Fishery changes were determined through interview of three
\ngenerations of fishers targeting frigate tuna. Significantly higher values for best day’s
\ncatch and largest specimen ever caught were obtained by older fishers than younger ones.
\nValues were also significantly higher during early years, providing clear evidence of
\nresource decline and the ‘shifting baseline syndrome’. Most fishers reported posttsunami
\ndecline in frigate tuna, but mainly from a larger new generation of fishers, rather
\nthan extra boats provided by aid money or (direct or indirect) biophysical impacts from
\nthe tsunami. The number of boats post-tsunami increased significantly in all research
\nareas, which could result in further catch decline.
\nThe perceptions of 500 Sri Lankan fishers about the influence of risk factors on tsunami
\ndeath toll and house damage are quantified). Mangroves, coral reefs and sand dunes
\nafforded protection against tsunami damage (67–94% of fisher responses), as did
\nhousing and roads. Fishers believed rivers/estuaries, concave coastlines and hotels
\nexacerbated impacts. For comparison, multi-variable models for death toll, housing
\ndamage, inundation area and distance are built, incorporating both natural and
\ndevelopmental risk factors. Bathymetry is the only factor significantly associated with
\nall indicators of impact. Mangroves and marsh were not a significant factor in final
\nmultivariable models. However, in terms of inundation, sand dunes were identified as
\nprotective, while bodies of water exacerbated damage. The extent of agreement and
\nvariance between modelling results and the opinions of fisher questionnaires is critically
\nexamined.
\nResearch findings highlight the need for better coastal management. While the role
\nmangroves in tsunami protection remains equivocal, their known role in providing many
\nother ecosystem services suggests that mangroves warrant greater conservation attention
\nin Sri Lanka, in the face of coastal development pressures. Coastal policy and
\nconservation priorities should be influenced by scientific research (e.g. the tsunami
\nmodel in this thesis) as well as traditional ecological knowledge and opinions from indigenous people. Factors shown to provide tsunami protection often cannot be altered
\nby human intervention (e.g. topography and bathymetry). However, sand dunes could
\npotentially be preserved to reduce future impacts. Tsunamis are rare events and further
\nresearch should be carried out to determine which risk factors are important for more
\nfrequent events (e.g. monsoon). The needs of coastal communities should always remain
\nparamount in considerations of future tsunami and environmental policies.

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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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 teacher head, not a consensus.

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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