Mitochondrial DNA markers reveal genetic connectivity among populations of Osteoglossiform fish Chitala chitala

Anthropogenic risk assessment of riverine habitat using geospatial modelling tools for conservation and restoration planning: a case study from a tropical river Pranhita, India

The riverine ecosystem provides multiple benefits to human community and contributes to the sustainable development of the ecoregion. The growing dependency on these ecosystems has largely contributed to aggravating the ecological risks, habitat degradation, and loss of ecosystem services. The present study evaluates the ecological risk emanating from nine anthropogenic stressors including river use, hydro-morphology, catchment pollution, and biological stressor on river Pranhita in Godavari Basin of Peninsular India using InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Habitat Risk Assessment model. The primary field survey, remote sensing, and secondary data-assisted spatial modelling results revealed low ecological risk (R = 0.65 of 3) in river Pranhita due to anthropogenic activities. Sediment loading, the inflow of nitrogen, and habitat fragmentation were the major stressors with relatively higher risk score (> 1); influence on a sizeable portion of riverine habitat (29-75% of the total area under high-risk zone) indicates the mounting threat from catchment activities. The low-risk value observed in protected river reaches as compared to unprotected areas is likely to be influenced by the abundant presence of intact riparian vegetation which mitigate the catchment stressors and minimal anthropogenic activity within protected areas. This study demonstrates the application of InVEST HRA model for ecological risk assessment of riverine ecosystems and fish assemblages along with their input data generation framework. This has the potential for prioritization of sensitive habitats based on computed ecological risk and stressor identification based on their exposure and consequences for developing appropriate mitigation measures. This model is spatially explicit and accommodates user-defined criteria for ecosystem-level assessment at a regional and national scale to facilitate the resource managers and policymakers for conservation and restoration planning and implementation of targeted management measures for sustainable development.

Microsatellite Analysis Revealed Potential DNA Markers for Gestation Length and Sub-Population Diversity in Kari Sheep

Kari sheep inhabiting the Chitral district of Pakistan show variation in gestation length. In this study, we have analyzed the genetic differences between the three subtypes of Kari sheep (based on variation in gestation length) using microsatellite markers. Kari sheep samples were collected from their breeding tract and were characterized for gestation length and genetic diversity using microsatellite markers. A total of 78 Kari ewes were grouped into three categories based on gestation length (GL), i.e., Kari-S (with a shorter GL), Kari-M (with a medium GL), and Kari-L (with a longer GL). DNA from these samples was used to amplify 31 ovine-specific microsatellite loci through PCR. Of the total 78 Kari specimens, 24 were grouped in Kari-S (GL = 100.7 ± 1.8), 26 were from the Kari-M subtype (GL = 123.1 ± 1.0), and 28 were Kari-L (GL = 143.8 ± 1.5). Microsatellite analysis revealed an association of genotypes at two marker sites (MAF214 and ILSTS5) with variation in GL. A total of 158 alleles were detected across the 22 polymorphic loci with an average of 7.18 alleles per locus. Unique alleles were found in all three subtypes. The highest number of unique alleles was observed in Kari-L (15), followed by Kari-S (10) and Kari-M (8). The results indicated that Kari-S is a genetically distinct subtype (with higher genetic differentiation and distance) from Kari-M and Kari-L. The genetic uniqueness of Kari-S is important for further exploration of the genetic basis for shorter gestation length, and exploitation of their unique values.

Phenotypic variation of Chitala chitala (Hamilton, 1822) from Indian rivers using truss network and geometric morphometrics

Chitala chitala (Hamilton, 1822) is an economically important food fish species occurring throughout Indian rivers, which also has ornamental value. This study focuses on morphological variations in C. chitala from seven river basins across India namely; Son, Tons, Ken, Brahmaputra, Ganga, Gomti and Gandak. A truss network was constructed by interconnecting nine landmarks to generate 36 morphometric variables extracted from digital images of specimens sampled from the study locations. Transformed truss measurements were subjected to principal component analysis (PCA), canonical discriminant function analysis (CDFA) and discriminant analyses of principal components (DAPC). DAPC function coefficients performed much better in capturing the variation pattern and discrimination between the rivers which was not achieved using CDFA. Eight truss variables were identified with significant and highest loading for truss variables on principal components and coefficients on discriminant function from DAPC contributing to maximum variation between the rivers. Performance graph and functional distribution of identified truss variables clearly indicated distinction between the rivers. Thin plate spline analysis and procrustes shape analysis further showed the variation in morphology between specimens across the rivers. The significant parameters differentiating specimens from different rivers were linked to dorsal fin origin, the base of the pectoral fin and the perpendicular point on the anal fin from the dorsal fin origin. Variation in the hydrodynamics of the rivers studied might be possibly affecting the fin kinematics and consequently leading to adaption seen as phenotypic variation in C. chitala. The results showcased in the present study shall help in better understanding of intra-specific diversity which is significant for management and conservation of a species.