Longitudinal and temporal assemblage patterns of benthic macroinvertebrates in snow melt stream waters of the Jhelum River Basin of Kashmir Himalaya (India)

Abstract

AbstractThis article tries to understand the dynamics involving benthic macroinvertebrate studies over 18 watersheds for a period of 2 years in the Jhelum River Basin (JRB) of Kashmir Himalaya, India. We aimed to understand this by recognizing spatio‐temporal patterns of macroinvertebrates and their relation to some environmental factors across the whole JRB. A total of 93 taxa pertaining to 3 phyla, 7 classes and 55 families were observed. Our observations revealed that taxa richness, Shannon diversity, total density and percentage of Ephemeroptera, Plecoptera and Trichoptera (EPT) metrics considerably declined towards downstream regions. Summer and spring seasons have higher influence on richness, diversity and abundance of most percentage indices. Macrobenthic assemblage structure reflected significant variability with space and time having clear segregation of the downstream sites from upper and midstream reaches in canonical ordination plots. Variation partitioning models [distance‐based redundancy analysis (dbRDA)] showed water discharge and temperature as the main drivers of variation in community structure during summer, whereas fine substrate composition (% sand) and pH were revealed to define the variability in the biology of streams during other seasonal times. Pertinently, much of the variability in benthic faunal assemblages could not be deciphered by environmental drivers and therefore may be linked to other hydrochemical variables (like alkalinity, hardness, chloride and dissolved organic matter) and nutrients (nitrogen and phosphorus). Given the apprehension of future climatic changes, understanding spatial and seasonal influences on the macroinvertebrate assemblage structure remains highlighted here, which is crucial for baseline information as well as management of lotic Himalayan systems spanning longitudinal gradients and climatic variability.