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Waterfowls habitat modeling: Simulation of nest site selection for the migratory Little Tern (Sterna albifrons) in the Nakdong estuary

Author

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  • Jeong, Kwang-Seuk
  • Jang, Ji-Deok
  • Kim, Dong-Kyun
  • Joo, Gea-Jae

Abstract

This paper aims to find patterns in nest site selection by Little Terns Sterna albifrons, in the Nakdong estuary in South Korea. This estuary is important waterfowl stopover and breeding habitat, located in the middle of the East Asia-Australasian Flyway. The Little Tern is a common species easily observed near the seashore but their number is gradually declining around the world. We investigated their nests and eggs on a barrier islet in the Nakdong estuary during the breeding season (May to June, 2007), and a pattern for the nest site selection was identified using genetic programming (GP). The GP generated a predictive rule-set model for the number of Little Tern nests (training: R2=0.48 and test: 0.46). The physical features of average elevation, variation of elevation, plant coverage, and average plant height were estimated to determine the influence on nest numbers for Little Tern. A series of sensitivity analyses stressed that mean elevation and vegetation played an important role in nest distribution for Little Tern. The influence of these two variables could be maximized when elevation changed moderately within the sampled quadrats. The study results are regarded as a good example of applying GP to vertebrate distribution patterning and prediction with several important advantages compared to conventional modeling techniques, and can help establish a management or restoration strategy for the species.

Suggested Citation

  • Jeong, Kwang-Seuk & Jang, Ji-Deok & Kim, Dong-Kyun & Joo, Gea-Jae, 2011. "Waterfowls habitat modeling: Simulation of nest site selection for the migratory Little Tern (Sterna albifrons) in the Nakdong estuary," Ecological Modelling, Elsevier, vol. 222(17), pages 3149-3156.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:17:p:3149-3156
    DOI: 10.1016/j.ecolmodel.2011.05.032
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    References listed on IDEAS

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    1. Kim, Dong-Kyun & Cao, Hongqing & Jeong, Kwang-Seuk & Recknagel, Friedrich & Joo, Gea-Jae, 2007. "Predictive function and rules for population dynamics of Microcystis aeruginosa in the regulated Nakdong River (South Korea), discovered by evolutionary algorithms," Ecological Modelling, Elsevier, vol. 203(1), pages 147-156.
    2. Lee, Jangho & Kwak, Inn-Sil & Lee, Eungkyoung & Kim, Kyung A., 2007. "Classification of breeding bird communities along an urbanization gradient using an unsupervised artificial neural network," Ecological Modelling, Elsevier, vol. 203(1), pages 62-71.
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    Cited by:

    1. Hyunbin Jo & Ji-Deok Jang & Keon-Young Jeong & Jeong-An Gim & Gea-Jae Joo & Kwang-Seuk Jeong, 2022. "Prey Identification of the Little Tern, Sternula albifrons (Pallas, 1764), by Applying DNA Barcoding to Fecal Materials," Sustainability, MDPI, vol. 14(19), pages 1-9, September.
    2. Gobeyn, Sacha & Mouton, Ans M. & Cord, Anna F. & Kaim, Andrea & Volk, Martin & Goethals, Peter L.M., 2019. "Evolutionary algorithms for species distribution modelling: A review in the context of machine learning," Ecological Modelling, Elsevier, vol. 392(C), pages 179-195.

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