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Record W2923607901

Aquatic bird assemblages of a tropical African man-made lake

2018· article· en· W2923607901 on OpenAlexaboutno aff
Moshood Keke Mustapha, E.O. Aiyeleso

Bibliographic record

VenueUkrainian Journal of Ecology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsSpecies richnessEcologySpecies evennessDominance (genetics)Species diversityBiologyMacrophyteGuildGeographyHabitat
DOInot available

Abstract

fetched live from OpenAlex

Aquatic birds are important biotic components of Lake Ecosystem serving as indicator of pollution, sources of protein, fishing agent, income, recreation, tourism, sport and pest control. The aim of this study was to provide a baseline data and checklist of the bird assemblages in Asa Lake, Ilorin, Nigeria. Bird sampling was conducted weekly for 24 weeks, by walking 10 mS-1 along a line transect on the bank of the lake. The populations were classified as rare, frequently seen and common based on the number of sightings, and abundance. Diversity indices such as dominance, evenness, Simpson diversity, Shanon-Weiner diversity, Marglef’s richness were estimated. 13682 birds consisting of 17 species in 9 families were recorded in the lake. Species were found in highest number during the rains. Water fowl was the most abundant species 42.21%. African jacana was the least abundant constituting 0.67%. Family Ardeidae was the most abundant in terms of species diversity. Three species were commonly seen, four frequently seen, while nine were rare. Diversity indices of the bird species were; (D) 0.045, (1-D) 0.95; (e^H/S) 0.96, Margalef richness 3.67 and (H) 2.99. The assemblage of bird species in the lake was high due to the availability of food, submerged aquatic macrophytes seeds and foliage, large volume of water, surface area and depth of the lake and absence of large predators. Morphological characteristics and behavioural tactics of the birds were attributed to the high occurrence of some of the birds. For continued residency of the birds in the lake, lake best management practices (LBMP) should be implemented. Continuous monitoring of the birds (bio monitor) in the lake should also be done to give an insight into the ecological conditions of the lake and at the same time serving as aesthetic organisms in the lake. Keywords: Birds; assemblages; lake; foraging; diversity; macrophytes; waterfowl References: Ali, S. (1943). The book of Indian birds. The Bombay Natural History Society; Bombay, India. Araoye, P. A. (2009). The seasonal variation of pH and dissolved oxygen (DO2) concentration in Asa lake Ilorin, Nigeria. International Journal of Physical Sciences, 4(5), 271-274. Bibby, C. J., Burgess, N. D., Hill, D. A., & Mustoe, S. (2000). Bird census techniques. Elsevier. Brasil. Ministry of Environment, Water Resources and Legal Amazon (Brasilia, DF). (1997). Conservation Plan of the Upper Paraguay Basin (Pantanal) -PCBAP: integrated and prognostic analysis of the Upper Paraguay Basin. Colwell, M. A., & Taft, O. W. (2000). Waterbird communities in managed wetlands of varying water depth. Waterbirds, 23, 45-55. Donatelli, R. J., Posso, S. R., & Toledo, M. C. B. (2014). Distribution, composition and seasonality of aquatic birds in the Nhecolândia sub-region of South Pantanal, Brazil. Brazilian Journal of Biology, 74(4), 844-853. Evans, M. I. (1994). Important bird's areas in the Middle East. Bird Life International, p. 410. Garay, G. L. A. D. Y. S., Johnson, W. E., & Franklin, W. L. (1991). Relative abundance of aquatic birds and their use of wetlands in the Patagonia of southern Chile. Revista Chilena de Historia Natural, 64, 127-137. Gaston, A. J. (1975). Methods for estimating bird populations. Journal of the Bombay Natural History Society, 72(2), 271-283. Grimmett, R., Inskipp, C., Inskipp, T., & Byers, C. (1999). Pocket guide to the birds of the Indian subcontinent. Oxford University Press, p. 384. Grimmett, R., & Inskipp, T. (2018). Birds of northern India. Bloomsbury Publishing, New Delhi, India, p. 240. Hammer, O., Harper, D. A. T., & Ryan, P. D. (2001). PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica, 4: 9. Hoyer, M. V., & Canfield, D. E. (1994). Bird abundance and species richness on Florida lakes: influence of trophic status, lake morphology, and aquatic macrophytes. In Aquatic birds in the trophic web of lakes. Springer, Dordrecht, pp. 107-119. Hoyer, M. V. (2013). Lake Management and Aquatic Birds. 17, 17-20. Knapton, R. W., & Petrie, S. A. (1999). Changes in distribution and abundance of submerged macrophytes in the Inner Bay at Long Point, Lake Erie: implications for foraging waterfowl. Journal of Great Lakes Research, 25(4), 783-798. MaGuarran, A. (1988). Ecological diversity and its measurement. Princeton University Press. New Jersey, p. 178. Malizia, L. R. (2001). Seasonal fluctuations of birds, fruits, and flowers in a subtropical forest of Argentina. The Condor, 103(1), 45-61. Mustapha, M. K. (2011). Perspectives in the Limnology of Shallow Tropical African Reservoirs in Relation to Their Fish and Fisheries. Journal of Transdisciplinary Environmental Studies, 10(1). Oliveira, D. M. M. D. (2006). Efeitos bioticos e abioticos de ambientes alagaveis nas assembleias de aves aquaticas e piscivoras no Pantanal, Brasil. Paszkowski, C. A., & Tonn, W. M. (2000). Community concordance between the fish and aquatic birds of lakes in northern Alberta, Canada: the relative importance of environmental and biotic factors. Freshwater Biology, 43(3), 421-437. Rajpar, M. N., & Zakaria, M. (2011). Bird species abundance and their correlationship with microclimate and habitat variables at Natural Wetland Reserve, Peninsular Malaysia. International Journal of Zoology, 2011. Serle, W., Morel, G. J., & Hartwig, W. (1992). Birds of West Africa. Collins Publication, London, p. 351. Shirihai, H., & Christie, D. (1996). The Macmillan birder's guide to European and Middle Eastern birds: including North Africa. Macmillan Pub Limited. Suter, W. (1994). Overwintering waterfowl on Swiss lakes: how are abundance and species richness influenced by trophic status and lake morphology?. In Aquatic Birds in the Trophic Web of Lakes. Springer, Dordrecht, pp. 1-14.

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 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 score0.009
Threshold uncertainty score0.991

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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