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Record W3029445600

Assessments of physico-chemical parameters of Garaet Hadj Tahar wetland and their effect on waterbirds settlement

2020· article· en· W3029445600 on OpenAlexaboutno aff
Y. Bara, Mouslim Bara, Mourad Bensouilah, Menouar Saheb, Sadek Atoussi, Moussa Houhamdi

Bibliographic record

VenueUkrainian Journal of Ecology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandSettlement (finance)GeographyWaterfowlEcologyEnvironmental scienceEnvironmental protectionHabitatBiology
DOInot available

Abstract

fetched live from OpenAlex

This topic presented the relationship between physicochemical parameters and waterbirds assembling at Garaet Hadj Tahar (occidental Numidia, northeast of Algeria). Our data were collected from January 2018 to December 2018. Five physical parameters and four nutrient parameters, were measured at this wetland. We have noted 35 waterbirds species belonging to eleven family. All waterbirds of this wetland listed as least concern according to IUCN red list, except the three Anatidae key species with a conservation statuts: Aythya nyroca (near threatned), Oxyura leucocephala (endangered species) and Marmaronetta angustirostris  (vulnerable). The maximum values of abundance, species richness, Shannon diversity index and Simpson diversity index were noted in wintering period but not for the Pielou�??s evenness index. Only five physicochemical parameters influenced the waterbirds population assembling at this wetland. Garaet Hadj Tahar wetland must getting more conservation interest and surveys in order to maintain the biodiversity of this hotspot wetland.    Keywords: Wetland; Physicochemical; Numidia; Waterbirds; Garaet Hadj Tahar  References Alonso, J.C., Alonso, J.A., & Carrascal, L.M. (1991). Habitat selection by foraging White Storks, Ciconia ciconia, during the breeding season. Can. J. Zool., 69, 1957-1962. Bara, M., & Segura, N.L. (2019). Effect of Air Temperature and Water Depth on Bird Abundance: A Case Study of Rallidae and Anatidae in the Northeastern Algerian Garaet Hadj Tahar. Pakistan J. Zool., 51 (1), 211-217. Bara, M., Merzoug, S.E., Khelifa, R., Bouslama, Z., & Houhamdi, M. (2014). Aspects of breeding ecology of the purple swamphen Porphyrio porphyrio in the wetland complex of Guerbes-Sanhadja, northeast of Algeria. Ostrich, 85, 185-191. Bezzalla, A., Houhamdi M., Maazi M.C., & Chenchouni, H. (2019). Modelling climate influences on population dynamics and diurnal time budget of the Shelduck (Tadorna tadorna) wintering in Ramsar wetlands of Algeria. Avian Biology Research, 12 (3), 77-95. Blondel, J. (1975). Analyse des peuplements d’oiseaux d’eau. Element d’un diagnostic ecologique. I : La methode des echantillonnages frequentiels progressifs (E.F.P). Terre et Vie, 29, 533-589. Brandolin, P.G, & Blendinger, P.G. (2015). Effect of habitat and landscape structure on waterbird abundance in wetlands of central Argentina. Wetlands Ecol Manage, 24 (1), 93-105. Cody, L.M. (1985). Habitat selection in birds. Academic press, INC. Harcourt Brace Jovanovich, publisher. Carrascal, L.M., Seoane, J. & Villen-Perez, S. (2012). Temperature and Food constraints in wintering birds an experimental approach in montane Mediterranean oakwoods. Commun. Ecol., 13, 221-229. Demaya, S.G., Luiselli, L., Di Vittorio, M., Dendi, D., & Lado, F.T. (2019). Bird community structure across habitats in a protected area of South Sudan. African journal of ecology, 1, 1-5. Dmitrenko, I., Kirillov, S., Eicken, H., & Markova, N. (2005). Wind�?�driven summer surface hydrography of the eastern Siberian shelf. Geophysical research letters, 32 (14), 1-5. Dustan, C.E., & Fox, B.J. (1996). The effects of fragmentation and disturbance of rainforests on ground dwelling small mammals on the Robertson Plateau New south Wales Australia. J. Biogeogr, 23, 187–201. Elafri, A., Halassi, I., & Houhamdi, M. (2016). Diversity patterns and seasonal variation of the waterbird community in Mediterranean wetlands of Northeastern Algeria. Zoology and Ecology, 26 (2), 85-92. Ewers, M.R., & Didham, K.R. (2006). Confounding factors in the detection of species responses to habitat fragmentation. Biological reviews, 81 (1), 117-142. Fahrig, L. (2017). Ecological Responses to Habitat Fragmentation Per Se. Annual reviews, 48, 1-23. Ferger, S.W., Schleuning, M., Hemp, A., Howell, K.M., & Bohning-Gaese, K. (2014). Food resources and vegetation structure mediate climatic effects on species richness of birds. Glob. Ecol. Biogeogr., 23, 541-549. Fishpool, L.D.C., & Evans, M.I. (2001). Important Bird Areas in Africa and associated islands: priority sites for conservation. BirdLife Conservation Series No. 11, Pisces Publications and BirdLife International, Newsbury and Cambridge, UK. Haddad, M.N., Brudvig, A.L., Clobert, J., Davies, F.K., Gonzalez, A. et col. (2015). Habitat fragmentation and its lasting impact on Earth’s ecosystems. Science advanced, e1500052. Hammer, o, Harper, D.A.T, & Ryan, P.D. (2001). PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4 (1), 9. Hoyer, M.V. (2013). Lake Management and Aquatic Birds. Fish & wildlife management, 17, 17-20. International Organization for Standardization. (1994). Environment: water quality. Chemical methods ISO Standards Compendium, Technical comity/147, Volume 2. 1st edition. International Union for Conservation Nature. (2019). The IUCN red list of threatened species. Available at: http: //www.iucnredlist.org/technicaldocuments/spatial (accessed September 2019). Keke, M.M, & Elizabeth, A.O. (2018). Aquatic bird assemblages of a tropical African man-made lake. Ukrainian Journal of Ecology, 8 (4), 41-45. Lindenmayer, D.B., & Fischer, J. (2006). Habitat Fragmentation and Landscape Change: an Ecological and Conservation Synthesis. Island Press, Washington, D.C. Magurran, A.E. (1988). Ecological diversity and its measurement. Princeton, NJ: Princeton University Press. McKnight, K.S. (1998). Effects of food abundance and environmental parameters on foraging behavior of gadwall sand American coots in winter. Canadian Journal of Zoology, 76 (11), 1993-1998. Metallaoui, S., & Merzoug, A.E. (2009). Wintering observation of red crested pochard Netta rufina beside Skikda (Algeria). Alauda, 77, 57. Metallaoui, S., & Houhamdi, M. (2010). Biodiversity and ecology of aquatic avifauna wintering in Garaet Hadj Tahar (Skikda, northeast of Algeria). Hydroecol. Appl., 17, 1-16. Palacio, X.F., & Montalti, D. (2013). Seasonal variation and effect of non-native invasive vegetation on two bird communities in northeast of Buenos Aires province, Argentina. Ornitologia Neotropical, 24, 157–168. Polak, M., & Kasprzykowski, Z. (2010). Reproduction parameters of the Great Bittern Botaurus stellaris in the fish ponds of eastern Poland. Acta ornithological, 45 (1), 75-81. Relyea, R.A. (2002). Costs of phenotypic plasticity. The American naturalist, 159 (3), 272-282. Rodier, J., Leguebe, B., Merlet, N. et col. (2009). L'analyse de l'eau. Eaux naturelles. Residuaires. Eau de mer. 9eme edition. Dunod. Paris, 1511p. Samraoui, B., & De Belair, G. (1997). The Guerbes- Senhadja wetlands. Part I: An overview. Ecologie, 28, 233–250. Samraoui, F., Alfarhan, A.H., Al-Rasheid, K.A.S., & Samraoui, B. (2011). An appraisal of the status and distribution of waterbirds of Algeria: indicators of global changes? Ardeola, 58 (1), 137-163. Shannon, C.E., & Weaver, W. (1949). The mathematical theory of communication. Urbana, IL: University of Illinois Press. Stewart, P.H. (1968). Quotient pluviothermique et degradation biospherique quelques reflexions. Bull. Soc, Hist Nat, Afr. N., 59, 23-36. Tamisier, A. (1974). Etho-ecological studies of teal wintering in the camargue (Rhone Delta, France). Wildfowl, 25, 123-133. Tamisier, A. (1978). Realites et signification de l'organisation sociale chez les canards en periode hivernale. Bull. Soc. Fr. Etude Comp. Animal, 2, 11-24. Tamisier, A., & Tamisier, M.C. (1981). L'existence d'unites fonctionnelles demontree chez les sarcelles d'hiver en camargue par la bio telemetrie. Rev. Eco., 35, 563-579. Wiens, J.A. (1989). Spatial scaling in ecology. Functional Ecology, 3, 385-397.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.355

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 studies0.0000.000
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 head0.013
GPT teacher head0.256
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.

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".

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Citations3
Published2020
Admission routes1
Has abstractyes

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