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An annotated checklist of amphibians in and around Dampa Tiger Reserve, Mizoram, India

2021· article· en· W3153273106 on OpenAlexfundno aff
Ht. Decemson, Sushanto Gouda, Lalbiakzuala, Lalmuansanga, Gospel Zothanmawia Hmar, Hmar Tlawmte Lalremsanga

Bibliographic record

VenueJournal of Threatened Taxa · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of CanadaDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsIUCN Red ListThreatened speciesEcologyHabitatAmphibianTigerHabitat destructionGeographyBiologyFishery

Abstract

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Amphibians are an integral part of the ecosystem and act as an ecological indicator. As several species are added to the list of threatened species every year due to loss of habitat, it is important to understand the role of unmanaged landscape for sustenance of amphibian diversity. In this study, 28 amphibian species were recorded from different modified habitat including 19 new records for Dampa Tiger Reserve (DTR) and its surrounding areas. Further, six species, Amolops indoburmanensis, Limnonectes khasianus, Microhyla mukhlesuri, M. mymensinghensis, Raorchestes rezakhani, and Sylvirana lacrima are new distribution records for the state of Mizoram and out of these, two species, Raorchestes rezakhani and Sylvirana lacrima, are new country records for India. Amongst the recorded species, four species are Data Deficient, two Vulnerable, 14 Least Concern, and eight species are not assessed as per the IUCN Red List. Within the core and buffer areas of DTR, we found that natural perennial stream, puddles, canals, natural ponds, fish ponds, roadside, primary forest, secondary forest, paddy fields, and human settlement areas are excellent microhabitats for amphibian population and need to be conserved for their rich ecological niches.

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 score0.129
Threshold uncertainty score0.552

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)0.0010.000

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 head0.011
GPT teacher head0.252
Teacher spread0.240 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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