Iranian Journal of Ichthyology

Monthly catch assessment of Labeo rohita (Hamilton, 1822) at Khambo landing site, Keenjhar Lake, Sindh: A year-long study

ATIA BATOOL — 2026-10-15

This study presents a comprehensive analysis of monthly catch data for Labeo rohita (Rohu) collected from the Khambo landing site at Keenjhar Lake over a 12-month period (January to December 2025). A total of 20 boats were sampled monthly from an operational fleet of 250 boats, with fishing activity occurring 9-10 days per month. Catch per unit effort (CPUE) was calculated for both number of fish and weight (kg). The results indicate significant seasonal variation in Rohu catch, with peak abundance observed during the post-monsoon period (September-November). The lowest catches were recorded during the pre-monsoon months (March-April). The highest monthly catch (both in number and weight) occurred in November (920 fish, 659kg), while the lowest was recorded in March (489 fish, 380 kg). The mean weight per fish varied throughout the year (0.484-1.136kg), with larger specimens caught during the pre-monsoon period (February-April) and smaller fish dominating the post-monsoon catch (July-October). Statistical analysis revealed significant seasonal differences in both the number (ANOVA, F=6.23, P<0.01) and weight (ANOVA, F=4.87, P<0.05) of fish caught. These findings provide crucial baseline data for sustainable fisheries management and highlight the need for seasonal fishing regulations, particularly mesh-size restrictions during the post-monsoon recruitment period, to ensure the long-term viability of the Rohu fishery in Keenjhar Lake.

Projecting habitat suitability changes of Caranx ignobilis (Forsskål, 1775) in the Persian Gulf using ensemble species distribution models

Hamed MOUSAVI-SABET — 2026-10-01

Understanding the impacts of climate change on marine habitats is essential for predicting future species distribution patterns and supporting sustainable fisheries management, particularly for commercially important apex predators. In this study, we used occurrence records from global databases (GBIF and OBIS) and published field surveys, combined with Bio-ORACLE environmental predictors, to model current and future habitat suitability of Caranx ignobilis (Forsskål, 1775) in the Persian Gulf. We implemented six individual modeling algorithms and three ensemble modeling techniques using the biomod2 platform. The ensemble model EMwmean (AUC= 0.992, TSS= 0.923) was selected for final projections because it integrates multiple algorithms and reduces model-specific bias. Based on variable importance analysis, sea surface temperature (SST), salinity, and primary production were identified as the most influential environmental predictors shaping habitat suitability. Future projections under SSP2-4.5 and SSP5-8.5 indicated progressive contraction of suitable habitat in the southeastern Persian Gulf, accompanied by a northwestward displacement of the habitat centroid. Specifically, the modelled area classified as suitable habitat is projected to decline from 48.49×10³km² under current conditions to zero by the 2090s under both SSP2-4.5 and SSP5-8.5, reflecting zero modelled suitable habitat under the applied threshold rather than biological extirpation. These findings provide spatially explicit information to support adaptive fisheries management and conservation planning, thereby enhancing the long-term resilience of this ecologically and commercially important reef-associated predator under future climate change in the Persian Gulf.

How ensemble species distribution modelling under climate change reveals habitat loss for a Tigris–Euphrates’ endemic fish (Luciobarbus xanthopterus Heckel, 1843) in Iran?

Mohammad Reza Nodrat — 2026-10-24

Climate change is expected to alter the distribution and persistence of freshwater fishes, particularly endemic species with geographically restricted ranges. An ensemble species distribution modelling (SDM) framework implemented in biomod2 to estimate current habitat suitability for the vulnerable yellowfin barbel (Luciobarbus xanthopterus) and to project changes under future climate scenarios. After spatial filtering, 42 occurrence records were retained. Nineteen bioclimatic variables, elevation, and human footprint were initially considered; after reducing multicollinearity, six predictors were retained: annual mean temperature, annual precipitation, temperature seasonality, precipitation of the wettest quarter, elevation, and human footprint. Six algorithms (ANN, RF, GLM, GBM, FDA, and MARS) were fitted and evaluated using AUC, TSS, and Cohen’s kappa. The ensemble model identified approximately 68,000km² of currently suitable habitat, corresponding to about 40% of the Iranian portion of the Tigris basin. Under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 (low, intermediate, high, and very high greenhouse gas emissions, respectively), projected habitat loss by 2070 was 24%, 25%, 33%, and 49%, respectively, whereas habitat gains were 15%, 14%, 8%, and 5%. Net habitat change ranged from -9% under SSP1-2.6 to -44% under SSP5-8.5. Annual mean temperature, annual precipitation, temperature seasonality, and human footprint were the most influential predictors. These results indicate that climate change may substantially reduce the suitable range of L. xanthopterus and highlight the value of identifying climate refugia, maintaining river connectivity, and reducing non-climatic pressures in the Tigris–Euphrates system.