Patterning habitat preference of avifaunal assemblage on the Nakdong River estuary (South Korea) using self-organizing map

Abstract A comprehensive monitoring of the avifaunal assemblage to observe patterning changes was attempted for an estuarine system in South Korea. The current work identifies the importance of conserving habitat for migratory birds especially in the studied Nakdong River estuary. This estuarine system has been recognized as one of the most important stopover sites on the East Asia–Australasian Flyway, and supports a high level of biodiversity. The installation of an estuarine barrage in 1987 resulted in the habitat being partitioned into freshwater and brackish areas; however, there has been no systematic monitoring throughout the estuary. In the original survey program, the entire system (ca. 100 km2) was divided into eight sites and monthly or biweekly monitoring was implemented for the 3 years from April 2003 to March 2006. 227 species of birds were observed, with the dominant species being mallard (Anas platyrhynchos Linnaeus) (relative abundance, RA, 17.2%). Assemblage parameters showed avifauna biodiversity possessed a strong seasonality with some species groups dominating the estuary. A non-linear patterning self-organizing map (SOM) algorithm was applied to the avifaunal data set to identify patterns in avifaunal distribution. The trained SOM model (quantization error, 3.375; topographic error, 0.000) clearly classified the bird data set into two clusters. These clusters could be characterized by two factors: i.e., seasonal distribution of avifaunal assemblage and/or habitat properties. High dissimilarity between clusters was due to seasonality, while the brackish area (i.e., the cluster 1) was mostly occupied by cold season data while the reverse was true for cluster 2. By comparing bird data from the sub-zones, it was found that the center of the brackish area had a mixed pattern of bird distribution, which implied this area could be more important in terms of habitat preference with respect to migratory bird distribution. From the results, it is strongly suggested that a strict management strategy for the estuarine area to conserve the avifauna throughout the migratory flyway be prepared. The strategy could be seasonally and species specific.

[1]  Teuvo Kohonen,et al.  The self-organizing map , 1990, Neurocomputing.

[2]  C. T. Achuthankutty,et al.  Monsoonal impact on planktonic standing stock and abundance in a tropical estuary (Cochin backwaters – India) , 2007 .

[3]  G J Joo,et al.  Modelling community changes of cyanobacteria in a flow regulated river (the lower Nakdong River, S. Korea) by means of a Self-Organizing Map (SOM) , 2005 .

[4]  Peter A. Whigham,et al.  Winter diatom blooms in a regulated river in South Korea: explanations based on evolutionary computation , 2007 .

[5]  T. Penczak,et al.  Patterning of impoundment impact on chironomid assemblages and their environment with use of the self-organizing map (SOM) , 2006 .

[6]  Mi-Young Song,et al.  Characterization of benthic macroinvertebrate communities in a restored stream by using self-organizing map , 2006, Ecol. Informatics.

[7]  S. Lek,et al.  Spatio-temporal patterns of fish assemblages in coastal West African rivers: a self-organizing map approach , 2006 .

[8]  S. McWilliams,et al.  Waterfowl–habitat associations during winter in an urban North Atlantic estuary , 2006 .

[9]  David C. Duffy,et al.  Where have all the birds gone , 1990 .

[10]  Neil D. Burgess,et al.  Bird Census Techniques , 1992 .

[11]  Young-Seuk Park,et al.  Community patterns of benthic macroinvertebrates collected on the national scale in Korea , 2007 .

[12]  Iván Machón González,et al.  Self-organizing map and clustering for wastewater treatment monitoring , 2004, Eng. Appl. Artif. Intell..

[13]  Jangho Lee,et al.  Classification of breeding bird communities along an urbanization gradient using an unsupervised artificial neural network , 2007 .

[14]  R. Ricklefs,et al.  Competition and the structure of bird communities. , 1975, Monographs in population biology.

[15]  Young-Seuk Park,et al.  Fish assemblages in the large lowland Narew River system (Poland): Application of the self-organizing map algorithm , 2007 .

[16]  Sovan Lek,et al.  A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination , 2001 .

[17]  K. Root.  A Primer of Conservation Biology , 2009 .

[18]  Kuolin Hsu,et al.  Satellite‐based precipitation estimation using watershed segmentation and growing hierarchical self‐organizing map , 2006 .

[19]  Sovan Lek,et al.  Fish zonation and indicator species for the evaluation of the ecological status of rivers: example of the Loire basin (France) , 2007 .

[20]  C. S. George Lee,et al.  Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems , 1996 .

[21]  Jin-Young Park,et al.  A field guide to the birds of Korea , 2000 .

[22]  Li-Chiu Chang,et al.  Enforced self-organizing map neural networks for river flood forecasting , 2007 .

[23]  M. Sanders.  Enhancing food supplies for waders: inconsistent effects of substratum manipulations on aquatic invertebrate biomass , 2000 .

[24]  Young-Seuk Park,et al.  Determining temporal pattern of community dynamics by using unsupervised learning algorithms , 2000 .

[25]  A. M. Kalteh,et al.  Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application , 2008, Environ. Model. Softw..

[26]  C. R. Velásquez.  Managing Artificial Saltpans as a Waterbird Habitat: Species' Responses to Water Level Manipulation , 1992 .

[27]  R. Hughes,et al.  Development of a Bird Integrity Index: Using Bird Assemblages as Indicators of Riparian Condition , 2002, Environmental management.

[28]  J. Terborgh,et al.  Where Have All the Birds Gone? , 1989 .

[29]  Young‐Seuk Park,et al.  Collembolan communities in a peat bog versus surrounding forest analyzed by using self-organizing map , 2007 .

[30]  Tae-Soo Chon,et al.  Multivariate analysis and self-organizing mapping applied to analysis of nest-site selection in Black-tailed Gulls , 2006 .

[31]  Kwang-Seuk Jeong,et al.  Delayed influence of dam storage and discharge on the determination of seasonal proliferations of Microcystis aeruginosa and Stephanodiscus hantzschii in a regulated river system of the lower Nakdong River (South Korea). , 2007, Water research.

[32]  Shang-Lien Lo,et al.  Diagnosing reservoir water quality using self-organizing maps and fuzzy theory. , 2002, Water research.