Length-Weight Relationship Modeling Applications in Aquatic Species Biomass Estimation Methods

Omar Siddiqui

doi:10.71222/9nmep839

Authors

Omar Siddiqui University of Dhaka, Dhaka, Bangladesh Author

DOI:

https://doi.org/10.71222/9nmep839

Keywords:

length-weight relationships, biomass estimation, aquatic species, allometric modeling, morphometric analysis, ecosystem monitoring

Abstract

Length-weight relationships represent fundamental biometric tools in aquatic ecology, providing essential methods for biomass estimation across diverse marine and freshwater species. These allometric relationships enable researchers to convert easily measured morphometric parameters into biomass values, facilitating population assessments and ecosystem monitoring. Contemporary approaches integrate traditional morphometric measurements with advanced technologies including metabarcoding, machine learning, and in situ imaging systems. The application of length-weight models spans multiple taxonomic groups, from zooplankton communities to large crustaceans and fish populations. Recent developments emphasize spatiotemporal modeling approaches that account for environmental variability and seasonal dynamics in aquatic systems. Machine learning algorithms have enhanced biomass estimation accuracy by incorporating multiple morphometric variables beyond simple length measurements. Metabarcoding techniques now enable species-specific biomass calculations from genetic material, revolutionizing plankton community assessments. The integration of these methodologies addresses critical challenges in aquatic biodiversity monitoring and fisheries management. This review synthesizes current applications of length-weight relationship modeling, examining methodological advances in biomass estimation techniques across aquatic ecosystems. The analysis encompasses traditional regression approaches, contemporary technological innovations, and emerging computational methods that improve estimation precision. Understanding these relationships remains crucial for sustainable fisheries management, ecosystem health assessment, and biodiversity conservation in aquatic environments.

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