Trophic fingerprinting of a pristine but rapidly deteriorating downstream region of a Western Ghats River.

Chalakudy River is renowned for its pristine waters and rich ichthyofaunal biodiversity. The downstream area of the river is confronting a series of risks, including pollution, saline water ingression, sand mining, illegal and intensified fishing practices, and invasion of exotic and alien species. A mass balanced ecosystem model was constructed for the downstream region of Chalakudy River (DCR) using Ecopath with Ecosim (EWE), incorporating 12 functional groups to delineate the food web and network flow indices for the period 2020 to 2021. The trophic level (TL) of the ecosystem network ranged from TL-1 (detritus) to TL-3.4 (birds). High fishing pressure is one possible cause for the high ecotrophic efficiency values as evidenced by the fish groups. Both the grazing food chain and detritus food chain (detritivory: herbivory ratio 0.94) contributed more or less equal to the energy transfer between TL. Network analysis of the model indicated a mean transfer efficiency of 12%, with shares from primary producers (14%) and detritus (11%). A mixed trophic impact analysis demonstrated a strong positive impact of primary producers and detritus groups on most of the other ecological groups at higher trophic levels. The DCR model showed a high system throughput (32,464.7 t km-2 year-1), low system omnivory (0.09), low connectance index (0.36), low Finn's cycling index (4.9), and mean path length (2.8), low relative ascendency (37.5%), and high system overhead (62.5%). These indices propound that DCR is an immature and developing ecosystem with moderate strength in reserve to resist external perturbations.

Study of feeding biology and diet-associated microplastic contamination in selected creek fishes of northeastern Arabian Sea: A multi-species approach.

This study investigated the diet composition and microplastic contamination in six fish species collected from the creek area of northeastern Arabian Sea. The results show that the diet of the fish is mainly composed of shrimps, algae, fish, and zooplankton, with microplastics constituting up to 4.83 % (Index of Preponderance) of their diet. The average abundance of microplastics ranges from 5.82 to 7.69 items per fish, and their ingestion is influenced by seasonal variation, gut fullness, and trophic level. Microplastic contamination has no significant effect on the condition factor and hepatosomatic index of the fish species. However, polymer hazard index indicates that microplastic pollution in fish is associated with a low to high risk factor, which might cause potential harm to aquatic lives and higher vertebrates via food chain. Therefore, this study highlights the need for immediate attention and effective regulations to reduce microplastic pollution to protect marine life.

Biodiversity assessment using passive acoustic recordings from off-reef location-Unsupervised learning to classify fish vocalization.

We present the quantitative characterization of Grande Island's off-reef acoustic environment within the Zuari estuary during the pre-monsoon period. Passive acoustic recordings reveal prominent fish choruses. Detailed characteristics of the call employing oscillograms and individual fish call parameters of the segmented data include vocal groups such as Sciaenidae, Terapon theraps, and planktivorous as well as invertebrate sounds, e.g., snapping shrimp. We calculated biodiversity parameters (i) Acoustic Evenness Index (AEI), (ii) Acoustic Complexity Index (ACI), and mean sound pressure level (SPLrms) for three frequency bands such as full band (50-22 050 Hz), the low-frequency fish band (100-2000 Hz), and the high-frequency shrimp band (2000-20 000 Hz). Here, ACI and AEI metrics characterize the location's soundscape data effectively indicating increased biodiversity of fish species for both the low-frequency and high-frequency bands. Whereas variations for SPLrms are prominent for three frequency bands. Moreover, we employ unsupervised classification through a hybrid technique comprising principal component analysis (PCA) and K-means clustering for data features of four fish sound types. Employed PCA for dimensionality reduction and related K-means clustering successfully provides 96.20%, 76.81%, 100.00%, and 86.36% classification during the dominant fish chorus. Overall, classification performance (89.84%) is helpful in the real-time monitoring of the fish stocks in the ecosystem.

Effect of environment on spatio-temporal structuring of fish assemblages in a monsoon-influenced tropical estuary.

This study analyzes the trophic structure of fish assemblages in a well-mixed tropical estuary, Zuari, located in southwest coast of India. A total of 224 fish species were collected between September 2013 and August 2016 from 324 sampling events from 9 sampling stations using surface and bottom set gillnets. The sampling events were designed to cover three major seasons such as the pre-monsoon, monsoon, and post-monsoon. For each sampling event, abiotic variables such as temperature, salinity, dissolved oxygen, and transparency of the water were recorded. The data obtained for abundance of fish species was subjected to cluster analysis and non-metric multidimensional scaling. The results defined six spatio-temporally varying groups (clusters) within Zuari estuary. Canonical correspondence analysis demonstrated that temperature, salinity, dissolved oxygen, and transparency were important in determining the fish assemblages in Zuari. The estuarine resident species were abundant in the inner zone (riverine side) of the estuary, where the salinity and temperature recorded lower dimensions compared to middle and outer zones (marine side). However, the inner shallow zone of the estuary was not a preferred habitat for the migrating marine species. Majority of the fish species preferred middle and outer zones and post-monsoon and pre-monsoon seasons for inhabiting the estuary. The present study furnishes a reference data for the spatio-temporal dynamics of fish assemblages in tropical monsoonal estuaries.