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...
| Publicado en: | Environmental Management Vol. 71; no. 5; pp. 1037 - 1052 |
|---|---|
| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2023
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162993182&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162993182 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0364152X O5H jtl: Environmental Management issn: 0364152X maglogo: N pubinfo: dt: May2023 vid: 71 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 162993182 161169552 10.1007/s00267-023-01784-2 162993182 ppf: 1037 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Geostatistical Framework Predicting Zooplankton Abundance in a Large River: Management Implications towards Potamoplankton Sustainability. aug: au: Sahu, Sanjeev Kumar Das Sarkar, Soma Gogoi, Pranab Naskar, Malay affil: ICAR-Central Inland Fisheries Research Institute Barrackpore, 700120, Kolkata, West Bengal, India sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|