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<p>The present study was carried out to evaluate the physicochemical characteristics of seven selected mangrove systems along the Kerala Coast (Southwest coast of India) on a seasonal basis. The data matrix was presented with different multivariate statistical analysis such as two-way ANOVA, cluster analysis, canonical discriminant factor analysis, and also elucidates the spatiotemporal variations and their disseminations. The study discovered that the hydrographic parameters and nutrient concentrations were influenced by seasonal changes. Cluster Analysis results determined the unique features of the area. Discriminant factor analysis showed that the distributions of variables were significantly affected regionally and not seasonally. The results of Two-way ANOVA reported significant differences (<i>p</i> &lt; 0.05) with stations and seasons in parameters like pH, salinity, EC, TDS, temperature, hardness, ORP, nitrate, phosphate and silicate. This study presents the usefulness of multivariate statistical techniques for analyzing spatial and temporal variations of the hydrographic physico-chemical parameters and successfully managing the water quality in the selected mangrove forests.</p>

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Seasonal distribution of physico-chemical parameters in the tropical mangrove environments of Kerala, Southwest coast of India: a comparative evaluation using statistical approach

  • 期刊论文

  • 发表日期：

    2026年2月20日

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  • Jennees Mathew,
  • Anu Gopinath,
  • G. Anusha

摘要

The present study was carried out to evaluate the physicochemical characteristics of seven selected mangrove systems along the Kerala Coast (Southwest coast of India) on a seasonal basis. The data matrix was presented with different multivariate statistical analysis such as two-way ANOVA, cluster analysis, canonical discriminant factor analysis, and also elucidates the spatiotemporal variations and their disseminations. The study discovered that the hydrographic parameters and nutrient concentrations were influenced by seasonal changes. Cluster Analysis results determined the unique features of the area. Discriminant factor analysis showed that the distributions of variables were significantly affected regionally and not seasonally. The results of Two-way ANOVA reported significant differences (p < 0.05) with stations and seasons in parameters like pH, salinity, EC, TDS, temperature, hardness, ORP, nitrate, phosphate and silicate. This study presents the usefulness of multivariate statistical techniques for analyzing spatial and temporal variations of the hydrographic physico-chemical parameters and successfully managing the water quality in the selected mangrove forests.