A Geostatistical Framework Predicting Zooplankton Abundance in a Large River: Management Implications towards Potamoplankton Sustainability

The zooplankton community is a widely used bioindicator for the biological assessment of riverine aquatic ecosystems. Phyto-zooplankton interaction and spatially varying river environment parameters perceivably govern their spatial distribution in a large river. This invites the challenge of predict...

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Bibliographic Details
Published in:Environmental management (New York) 2023-05, Vol.71 (5), p.1037-1051
Main Authors: Sahu, Sanjeev Kumar, Das Sarkar, Soma, Gogoi, Pranab, Naskar, Malay
Format: Article
Language:English
Subjects:
Abundance
Animals
Aquatic ecosystems
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Bioindicators
Biomonitoring
Decoupling
Earth and Environmental Science
Ecology
Ecosystem
Environment
Environmental Management
Forestry Management
Geostatistics
India
Indicator species
Nature Conservation
Plankton
Rivers
Seasons
Spatial distribution
Sustainability
Variability
Waste Water Technology
Water Management
Water Pollution Control
Zooplankton
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Summary:The zooplankton community is a widely used bioindicator for the biological assessment of riverine aquatic ecosystems. Phyto-zooplankton interaction and spatially varying river environment parameters perceivably govern their spatial distribution in a large river. This invites the challenge of predicting zooplankton abundance along the river channel. The present article has proposed a geostatistical framework to predict zooplankton abundance along the river course while decoupling phyto-zooplankton relationship from spatial dependency. The strength of secondary data on the river Narmada—a large tropical river in India—has been utilised to accomplish the goal. The nonlinear logistic regression kriging has been found to be the most effective framework. The phyto-zooplankton relationship captured 66% of zooplankton variability, having moderate (37%) residual spatial dependence. The results have shown longitudinally fluctuating spatial variability, which supports the river serial discontinuity concept. The proposed framework has generated smooth zooplankton abundance and sustainability predictive maps that have allowed detection of the change point locations of zooplankton abundance. The map has precisely identified the most productive zone of zooplankton sustainability. The study also has appraised obtaining approximate data in the areas where sampling is infeasible, which will be helpful for location-specific management strategies on a lower spatial scale.
ISSN:0364-152X
1432-1009
DOI:10.1007/s00267-023-01784-2