TREND ANALYSIS OF RESEARCH ON PHYTOPLANKTON TRAITS AS ECOLOGICAL INDICATORS

This study employs bibliometric analysis to identify trends and research hotspots in the use of phytoplankton traits as ecological indicators.We analyzed 3352 articles published in the Web of Science Core Collection database from 2000 to 2023, focusing on phytoplankton traits, their role as indicators, and their application in aquatic ecosystem monitoring.This study reveals a significant increase in publications on this topic, particularly since 2010.The United States, China, and Germany emerged as leading contributors in this field.Our analysis identifies four major research clusters: (1) using phytoplankton traits to indicate environmental changes in rivers, lakes, and oceans, (2) using phytoplankton traits as bioindicators for specific environmental factors like nutrients and pollutants, (3) exploring the molecular mechanisms of phytoplankton trait variations and new species discoveries, and (4) investigating the relationship between phytoplankton traits and the food web dynamics.Research on phytoplankton traits is rapidly advancing, with significant potential to enhance understanding and monitoring of aquatic ecosystems.Future research directions include further investigating the molecular mechanisms of trait changes, developing more robust bioindicators for specific pollutants, and exploring the ecological implications of trait variations in food webs.

Authors

Publication Details

Journal
Applied Ecology and Environmental Research
Published
2025-01-01
DOI
https://doi.org/10.15666/aeer/2302_23432363
Citations
1
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
1.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

TREND ANALYSIS OF RESEARCH ON PHYTOPLANKTON TRAITS AS ECOLOGICAL INDICATORS

Ting Hu, Yongzhan Mai, Chengzhi Hu, Chengshu Wang et al.
1 citations
Applied Ecology and Environmental Research
Water Quality Monitoring and Analysis
1.00
article

TREND ANALYSIS OF RESEARCH ON PHYTOPLANKTON TRAITS AS ECOLOGICAL INDICATORS

Ting Hu, Yongzhan Mai, Chengzhi Hu, Chengshu Wang, Q.F. LIU, Juan Sun
article en
1 citations

Abstract

This study employs bibliometric analysis to identify trends and research hotspots in the use of phytoplankton traits as ecological indicators.We analyzed 3352 articles published in the Web of Science Core Collection database from 2000 to 2023, focusing on phytoplankton traits, their role as indicators, and their application in aquatic ecosystem monitoring.This study reveals a significant increase in publications on this topic, particularly since 2010.The United States, China, and Germany emerged as leading contributors in this field.Our analysis identifies four major research clusters: (1) using phytoplankton traits to indicate environmental changes in rivers, lakes, and oceans, (2) using phytoplankton traits as bioindicators for specific environmental factors like nutrients and pollutants, (3) exploring the molecular mechanisms of phytoplankton trait variations and new species discoveries, and (4) investigating the relationship between phytoplankton traits and the food web dynamics.Research on phytoplankton traits is rapidly advancing, with significant potential to enhance understanding and monitoring of aquatic ecosystems.Future research directions include further investigating the molecular mechanisms of trait changes, developing more robust bioindicators for specific pollutants, and exploring the ecological implications of trait variations in food webs.

Applied Ecology and Environmental ResearchVol. 23(2)
Chinese Academy of Sciences, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Institute of Oceanology, Chinese Academy of Sciences, State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Central Public-interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences
Openalex Percentile: Top 23%
Water Quality Monitoring and Analysis
1.00
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.