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Record W1574846308 · doi:10.5539/ijb.v7n3p103

Forms and Trends of Encroachments in Cross River National Park of Nigeria

2015· article· en· W1574846308 on OpenAlexvenueno aff
H. M. Ijeomah, Edem A. Eniang, Shafiu Kilishi Halidu, Albert Nathan Onyejekwe

Bibliographic record

VenueInternational Journal of Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsNational parkPoachingGeographyWildlifeSocioeconomicsBiodiversityLoggingForestryEnvironmental protectionEcologyArchaeology

Abstract

fetched live from OpenAlex

Forms and trends of encroachments were investigated in Cross River National Park (CRNP) of Nigeria with the view of ascertaining the prevailing forms, trends, strategies of poaching and ecological consequences of illegal exploitations on the state of species in the biodiversity hotspot; that is contiguous with Korup and Takamanda national parks of Cameroon. Data for this study were obtained through personal observations, administrative record, structured questionnaires and in depth interview with experienced members of park protection staff who have been in the park for a minimum period of five years and are therefore quite knowledgeable about wildlife management and protection in the park. A set of questionnaire was randomly administered to 40 Park protection staff of CRNP in other to examine the forms, trends, intensity and reasons for encroachment in the park. Data on trend of arrest being an indicator of encroachment was collected from the administrative record of CRNP. Data obtained were analyzed using descriptive statistics in form of percentages and frequency of counts. Hunting (100%) and collection of Non Timber Forest Products (NTFPs) (75%) were implicated as the highest form of encroachment in the park while fuel wood collection (15%) was the least. The highest and lowest forms of arrest between 1991 and 2014 were 12.8% and 0.2% respectively. The least annual arrest (0.2%) recorded between 1991 and 2014 was in 1994 and 1995 respectively. Out of 616 arrests made between 1991 and 2014 34.%, 28.9% and 26.1% were for logging, hunting and collection of NTFPs respectively while aiding and abetting had the least record of only 1.6%. Nevertheless most respondents implicated households of host and enclave communities as encroachers (85.00%) and aiders of encroachments (95.0%) in CRNP. Cross River National Park is porous to non-seasonal encroachment as the anti poaching operations therein are ineffective.

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 score0.010
Threshold uncertainty score0.195

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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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