Aquatic Ecology

, Volume 53, Issue 1, pp 49–60 | Cite as

Application of deterministic and stochastic geo-statistical tools for analysing spatial patterns of fish density in a tropical monsoonal estuary

  • G. B. SreekanthEmail author
  • S. K. Chakraborty
  • A. K. Jaiswar
  • Bappa Das
  • E. B. Chakurkar


In this paper, we compared the efficiency of advanced deterministic and stochastic geo-statistical techniques to predict spatial patterns of fish density in the tropical monsoonal estuary, Zuari, using the following environmental descriptors: temperature, salinity, dissolved oxygen, transparency and geographic coordinates. The methods applied in this study were multiple linear regression, Cubist, support vector regression, random forest regression, universal kriging and regression kriging. Fish abundance and environmental data were collected from September, 2013 to August, 2016 in 48 sampling stations distributed along the estuarine gradient. Ranking procedure of various regression methods showed that the Cubist model was the best performing model based on prediction accuracy in the development phase and prediction consistency in the validation phase. Latitude, temperature, salinity and dissolved oxygen had positive influence on fish abundance, while longitude and transparency showed negative impacts. This study offers scope for refining the employed currently models to predict spatial densities of fish populations using a wide range of available biotic and abiotic variables, which will enable to develop an efficient management framework for tropical monsoonal estuaries.


Tropical monsoonal estuary Zuari Machine learning tools Geo-statistics Multiple linear regression Cubist Support vector regression Random forest regression Universal kriging Regression kriging 



The authors acknowledge the guidance, support and encouragement from the Director and staff of Central Institute of Fisheries Education and Central Coastal Agricultural Research Institute [research institutes under Indian Council of Agricultural Research (ICAR)] for this study. The authors also express heartfelt thanks to the fishermen of Zuari estuary for their kind cooperation with the fishing experiments and collection of data, in particular, the members of Shree Shantadurga Fishermen’s Association, Goa.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • G. B. Sreekanth
    • 1
    Email author
  • S. K. Chakraborty
    • 2
  • A. K. Jaiswar
    • 2
  • Bappa Das
    • 1
  • E. B. Chakurkar
    • 1
  1. 1.ICAR-Central Coastal Agricultural Research InstituteOld GoaIndia
  2. 2.ICAR-Central Institute of Fisheries EducationMumbaiIndia

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