Modelling the habitat preferences of the swan mussel ( Anodonta cygnea ) using data-driven model
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Modelling the habitat preferences of the swan mussel (Anodonta cygnea) using data-driven model Rahmat Zarkami & Shohreh Kia & Roghayeh Sadeghi Pasvisheh
Received: 7 July 2020 / Accepted: 30 September 2020 # Springer Nature Switzerland AG 2020
Abstract The Anzali wetland (located in northern Iran) and many parts of its catchment are considered important habitats for the swan mussel (Anodonta cygnea). The habitat of this native bioindicator mussel is being threatened in many locations of the catchment due to various anthropogenic activities. The present study aimed to apply a classification tree model (J48 algorithm) to predict the habitat preferences of A. cygnea in 12 sampling sites based on various water quality and physical-habitat variables. The species was present in 50% of sampling sites, while it was absent in the remaining of the sampling sites. In total, 144 samples of A. cygnea (72 presence and 72 absence instances) were monthly measured together with the abiotic variables during 1-year study period (2017–2018). For the CT model, two-thirds of datasets (96 instances) served as a training and the remainder was employed for the validation set (48 instances). Among 25 environmental variables introduced to the model (with pruning confidence factor = 0.10, threefold cross-validation and 5 times randomization effort), the validity of 6 variables was confirmed by the model in all three subsets. Water R. Zarkami (*) : S. Kia Department of Environmental Science, Faculty of Natural Resources, University of Guilan, P.O. Box 1144, Sowmeh Sara, Guilan, Iran e-mail: [email protected] R. S. Pasvisheh Department of Plants and Crops, Faculty of Bio-Science Engineering, Ghent University, Coupure Links, 653, 9000 Ghent, Belgium
salinity, flow velocity, water depth and water turbidity were jointly predicted by the model in three subsets. The model predicted that the absence of A. cygnea might be associated with increasing flow velocity, total phosphate and water turbidity. In contrast, the presence of A. cygnea might be related to decreased water depth and increased calcium concentration. The model also confirmed that all predicted variables for the species might be completely dependent on the water salinity. According to the chi-square test (x2 = 26.53, p < 0.05), the habitat condition of A. cygnea is influenced by significant variations in the spatio-temporal patterns. Keywords Anodonta cygnea . Classification tree . Datadriven model . Habitat preferences . Presence/absence . Swan mussel
Introduction Many Iranian wetlands are designated as wetlands of international importance according to the Ramsar list (Hamedani et al. 2017). Nevertheless, some of the wetlands such as Anzali wetland are in a critical condition designated on the Montreux Record (Sadeghi et al. 2017). Anzali wetland is an important habitat for many native flora and fauna. Bivalve molluscs are one of the valuable aquatic animals inhabiting Anzali wetland as well as in some parts of the surrounding catchment. These benthic organisms play a key role
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