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Application of classification trees to model the distribution pattern of a new exotic species Azolla filiculoides (Lam.) at Selkeh Wildlife Refuge, Anzali wetland, Iran

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  • Sadeghi, Roghayeh
  • Zarkami, Rahmat
  • Sabetraftar, Karim
  • Van Damme, Patrick

Abstract

Alien species have the abilities to alter the ecosystems they invade. We used classification trees (CTs) to predict the distribution of an exotic species, Azolla filiculoides (Lam.), at Selkeh Wildlife Refuge located in Anzali wetland, northern Iran. Cover percentages of Azolla were modeled using 33 physico-chemical and structural habitat variables. In total, 7 sampling sites were considered for abiotic and biotic sampling which resulted in 84 datasets. The predictive power of CTs was assessed based on two performance criteria: the percentage of Correctly Classified Instances (CCI %) and Cohen's kappa statistics (k). Different Pruning Confidence Factors (PCFs) were tested in order to improve the predictive results with regard to the complexity and accuracy of the predictions. The obtained results showed that Azolla distribution prediction was reliable in terms of both performance criteria (CCI>70% and k>0.40). Of the 33 variables presented to the model, the validity of 9 variables was confirmed for the prediction of habitat requirement of Azolla. A logical relationship was found between the distribution of Azolla and structural habitat variables such as air temperature, humidity, light intensity and depth of wetland. Besides, orthophosphate and nitrate were found to be two important nutrients for the prediction. The CTs allowed the selection of the most important variables and thus provided critical information to support the implementation of an Azolla management programme in Anzali wetland. More specifically, this kind of models can be used to select parameters that should be sampled at Selkeh wetland in the future.

Suggested Citation

  • Sadeghi, Roghayeh & Zarkami, Rahmat & Sabetraftar, Karim & Van Damme, Patrick, 2012. "Application of classification trees to model the distribution pattern of a new exotic species Azolla filiculoides (Lam.) at Selkeh Wildlife Refuge, Anzali wetland, Iran," Ecological Modelling, Elsevier, vol. 243(C), pages 8-17.
    • Handle: RePEc:eee:ecomod:v:243:y:2012:i:c:p:8-17
    DOI: 10.1016/j.ecolmodel.2012.06.011
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    1. S. T. Buckland & D. L. Borchers & A. Johnston & P. A. Henrys & T. A. Marques, 2007. "Line Transect Methods for Plant Surveys," Biometrics, The International Biometric Society, vol. 63(4), pages 989-998, December.
    2. Zarkami, Rahmat & Sadeghi, Roghayeh & Goethals, Peter, 2012. "Use of fish distribution modelling for river management," Ecological Modelling, Elsevier, vol. 230(C), pages 44-49.
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    1. Sadeghi, Roghayeh & Zarkami, Rahmat & Sabetraftar, Karim & Van Damme, Patrick, 2013. "Application of genetic algorithm and greedy stepwise to select input variables in classification tree models for the prediction of habitat requirements of Azolla filiculoides (Lam.) in Anzali wetland,," Ecological Modelling, Elsevier, vol. 251(C), pages 44-53.
    2. Argaw Ambelu & Seblework Mekonen & Magaly Koch & Taffere Addis & Pieter Boets & Gert Everaert & Peter Goethals, 2014. "The Application of Predictive Modelling for Determining Bio-Environmental Factors Affecting the Distribution of Blackflies (Diptera: Simuliidae) in the Gilgel Gibe Watershed in Southwest Ethiopia," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-10, November.
    3. Roghayeh Sadeghi Pasvisheh & Marie Anne Eurie Forio & Long Tuan Ho & Peter L. M. Goethals, 2021. "Evidence-Based Management of the Anzali Wetland System (Northern Iran) Based on Innovative Monitoring and Modeling Methods," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    4. Sadeghi, Roghayeh & Zarkami, Rahmat & Van Damme, Patrick, 2014. "Modelling habitat preference of an alien aquatic fern, Azolla filiculoides (Lam.), in Anzali wetland (Iran) using data-driven methods," Ecological Modelling, Elsevier, vol. 284(C), pages 1-9.

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