IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v222y2011i8p1522-1533.html
   My bibliography  Save this article

Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS

Author

Listed:
  • Choi, Jong-Kuk
  • Oh, Hyun-Joo
  • Koo, Bon Joo
  • Ryu, Joo-Hyung
  • Lee, Saro

Abstract

To make a macrofaunal (crustacean) habitat potential map, the spatial distribution of ecological variables in the Hwangdo tidal flat, Korea, was explored. Spatial variables were mapped using remote sensing and a geographic information system (GIS) combined with field observations. A frequency ratio (FR) and logistic regression (LR) model were employed to map the macrofauna potential area for the Ilyoplax dentimerosa, a crustacean species. Spatial variables affecting the tidal macrofauna distribution were selected based on abundance and biomass and used within a spatial database derived from remotely sensed data of various types of sensors. The spatial variables included the intertidal digital elevation model (DEM), slope, distance from a tidal channel, tidal channel density, surface sediment facies, spectral reflectance of the near infrared (NIR) bands and the tidal exposure duration. The relation between the I. dentimerosa and each spatial variable was calculated using the FR and LR. The species was randomly divided into a training set (70%) to analyse habitat potential using FR and LR and a test set (30%) to validate the predicted habitat potential map. The relations were overlaid to produce a habitat potential map with the species potential index (SPI) value for each pixel. The potential habitat maps were compared with the surveyed habitat locations such as validation data set. The comparison results showed that the LR model (accuracy is 85.28%) is better in prediction than the FR (accuracy is 78.96%) model. The performance of models gave satisfactory accuracies. The LR provides the quantitative influence of variables on a potential habitat of species; otherwise, the FR shows the quantitative influence of a class in each variable. The combination of a GIS-based frequency ratio and logistic regression models and remote sensing with field observations is an effective method to determine locations favorable for macrofaunal species occurrences in a tidal flat.

Suggested Citation

  • Choi, Jong-Kuk & Oh, Hyun-Joo & Koo, Bon Joo & Ryu, Joo-Hyung & Lee, Saro, 2011. "Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS," Ecological Modelling, Elsevier, vol. 222(8), pages 1522-1533.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:8:p:1522-1533
    DOI: 10.1016/j.ecolmodel.2010.12.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380010006575
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2010.12.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Merckx, Bea & Goethals, Peter & Steyaert, Maaike & Vanreusel, Ann & Vincx, Magda & Vanaverbeke, Jan, 2009. "Predictability of marine nematode biodiversity," Ecological Modelling, Elsevier, vol. 220(11), pages 1449-1458.
    2. Mouton, Ans M. & De Baets, Bernard & Van Broekhoven, Ester & Goethals, Peter L.M., 2009. "Prevalence-adjusted optimisation of fuzzy models for species distribution," Ecological Modelling, Elsevier, vol. 220(15), pages 1776-1786.
    3. Bandelj, Vinko & Curiel, Daniele & Lek, Sovan & Rismondo, Andrea & Solidoro, Cosimo, 2009. "Modelling spatial distribution of hard bottom benthic communities and their functional response to environmental parameters," Ecological Modelling, Elsevier, vol. 220(21), pages 2838-2850.
    4. Galparsoro, Ibon & Borja, Ángel & Bald, Juan & Liria, Pedro & Chust, Guillem, 2009. "Predicting suitable habitat for the European lobster (Homarus gammarus), on the Basque continental shelf (Bay of Biscay), using Ecological-Niche Factor Analysis," Ecological Modelling, Elsevier, vol. 220(4), pages 556-567.
    5. Hatten, James R. & Parsley, Michael J., 2009. "A spatial model of white sturgeon rearing habitat in the lower Columbia River, USA," Ecological Modelling, Elsevier, vol. 220(24), pages 3638-3646.
    6. Ottaviani, D. & Panzacchi, M. & Jona Lasinio, G. & Genovesi, P. & Boitani, L., 2009. "Modelling semi-aquatic vertebrates’ distribution at the drainage basin scale: The case of the otter Lutra lutra in Italy," Ecological Modelling, Elsevier, vol. 220(2), pages 111-121.
    7. Meixler, Marcia S. & Bain, Mark B. & Todd Walter, M., 2009. "Predicting barrier passage and habitat suitability for migratory fish species," Ecological Modelling, Elsevier, vol. 220(20), pages 2782-2791.
    8. Mouton, Ans M. & De Baets, Bernard & Goethals, Peter L.M., 2010. "Ecological relevance of performance criteria for species distribution models," Ecological Modelling, Elsevier, vol. 221(16), pages 1995-2002.
    9. Fulton, John W. & Wagner, Chad R. & Rogers, Megan E. & Zimmerman, Gregory F., 2010. "Hydraulic modeling of mussel habitat at a bridge-replacement site, Allegheny River, Pennsylvania, USA," Ecological Modelling, Elsevier, vol. 221(3), pages 540-554.
    10. Kocev, Dragi & Džeroski, Sašo & White, Matt D. & Newell, Graeme R. & Griffioen, Peter, 2009. "Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition," Ecological Modelling, Elsevier, vol. 220(8), pages 1159-1168.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Moung-Jin Lee & Wonkyong Song & Saro Lee, 2015. "Habitat Mapping of the Leopard Cat ( Prionailurus bengalensis ) in South Korea Using GIS," Sustainability, MDPI, vol. 7(4), pages 1-21, April.
    2. Holguin-Gonzalez, Javier E. & Boets, Pieter & Alvarado, Andres & Cisneros, Felipe & Carrasco, María C. & Wyseure, Guido & Nopens, Ingmar & Goethals, Peter L.M., 2013. "Integrating hydraulic, physicochemical and ecological models to assess the effectiveness of water quality management strategies for the River Cuenca in Ecuador," Ecological Modelling, Elsevier, vol. 254(C), pages 1-14.
    3. Everaert, Gert & Boets, Pieter & Lock, Koen & Džeroski, Sašo & Goethals, Peter L.M., 2011. "Using classification trees to analyze the impact of exotic species on the ecological assessment of polder lakes in Flanders, Belgium," Ecological Modelling, Elsevier, vol. 222(14), pages 2202-2212.
    4. Mouton, A.M. & Dillen, A. & Van den Neucker, T. & Buysse, D. & Stevens, M. & Coeck, J., 2012. "Impact of sampling efficiency on the performance of data-driven fish habitat models," Ecological Modelling, Elsevier, vol. 245(C), pages 94-102.
    5. Crisci, C. & Ghattas, B. & Perera, G., 2012. "A review of supervised machine learning algorithms and their applications to ecological data," Ecological Modelling, Elsevier, vol. 240(C), pages 113-122.
    6. Fukuda, Shinji & De Baets, Bernard & Mouton, Ans M. & Waegeman, Willem & Nakajima, Jun & Mukai, Takahiko & Hiramatsu, Kazuaki & Onikura, Norio, 2011. "Effect of model formulation on the optimization of a genetic Takagi–Sugeno fuzzy system for fish habitat suitability evaluation," Ecological Modelling, Elsevier, vol. 222(8), pages 1401-1413.
    7. 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.
    8. Martín-García, Laura & González-Lorenzo, Gustavo & Brito-Izquierdo, Isabel T. & Barquín-Diez, Jacinto, 2013. "Use of topographic predictors for macrobenthic community mapping in the Marine Reserve of La Palma (Canary Islands, Spain)," Ecological Modelling, Elsevier, vol. 263(C), pages 19-31.
    9. Mouton, Ans M. & De Baets, Bernard & Goethals, Peter L.M., 2010. "Ecological relevance of performance criteria for species distribution models," Ecological Modelling, Elsevier, vol. 221(16), pages 1995-2002.
    10. Yue Wang & Jihong Xia & Wangwei Cai & Zewen Liu & Jingjiang Li & Jingyun Yin & Jiayi Zu & Chuanbin Dou, 2023. "Response of Fish Habitat Quality to Weir Distribution Change in Mountainous River Based on the Two-Dimensional Habitat Suitability Model," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    11. Caldow, Chris & Monaco, Mark E. & Pittman, Simon J. & Kendall, Matthew S. & Goedeke, Theresa L. & Menza, Charles & Kinlan, Brian P. & Costa, Bryan M., 2015. "Biogeographic assessments: A framework for information synthesis in marine spatial planning," Marine Policy, Elsevier, vol. 51(C), pages 423-432.
    12. Van Looy, K. & Piffady, J. & Cavillon, C. & Tormos, T. & Landry, P. & Souchon, Y., 2014. "Integrated modelling of functional and structural connectivity of river corridors for European otter recovery," Ecological Modelling, Elsevier, vol. 273(C), pages 228-235.
    13. Marcot, Bruce G., 2012. "Metrics for evaluating performance and uncertainty of Bayesian network models," Ecological Modelling, Elsevier, vol. 230(C), pages 50-62.
    14. Muñoz-Mas, Rafael & Marcos-Garcia, Patricia & Lopez-Nicolas, Antonio & Martínez-García, Francisco J. & Pulido-Velazquez, Manuel & Martínez-Capel, Francisco, 2018. "Combining literature-based and data-driven fuzzy models to predict brown trout (Salmo trutta L.) spawning habitat degradation induced by climate change," Ecological Modelling, Elsevier, vol. 386(C), pages 98-114.
    15. An Cao & Xueyi Shi, 2022. "The Effects of Climate Change on Habitat Connectivity: A Case Study of the Brown-Eared Pheasant in China," Land, MDPI, vol. 11(6), pages 1-17, May.
    16. Gacutan, Jordan & Galparsoro, Ibon & Murillas-Maza, Arantza, 2019. "Towards an understanding of the spatial relationships between natural capital and maritime activities: A Bayesian Belief Network approach," Ecosystem Services, Elsevier, vol. 40(C).
    17. Domisch, Sami & Kuemmerlen, Mathias & Jähnig, Sonja C. & Haase, Peter, 2013. "Choice of study area and predictors affect habitat suitability projections, but not the performance of species distribution models of stream biota," Ecological Modelling, Elsevier, vol. 257(C), pages 1-10.
    18. Muñoz-Mas, R. & Martínez-Capel, F. & Alcaraz-Hernández, J.D. & Mouton, A.M., 2015. "Can multilayer perceptron ensembles model the ecological niche of freshwater fish species?," Ecological Modelling, Elsevier, vol. 309, pages 72-81.
    19. Gutiérrez-Estrada, Juan C. & Pulido-Calvo, Inmaculada & Bilton, David T., 2013. "Consistency of fuzzy rules in an ecological context," Ecological Modelling, Elsevier, vol. 251(C), pages 187-198.
    20. Wen Song & Wei Song & Haihong Gu & Fuping Li, 2020. "Progress in the Remote Sensing Monitoring of the Ecological Environment in Mining Areas," IJERPH, MDPI, vol. 17(6), pages 1-17, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:222:y:2011:i:8:p:1522-1533. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.