2 research outputs found

    Change in habitat suitability of the invasive Snowflake coral (Carijoa riisei) during climate change: An ensemble modelling approach

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    Global species range dynamics are intrinsically influenced by the interplay between human activities and climate compatibility. Snowflake coral (Carijoa riisei) is a soft octacoral species that belongs to the family Clavulariidae and can rapidly grow to colonise new habitats. This species has successfully colonised numerous habitats, displacing native species and disrupting the ecological balance in the introduced habitats. Recent investigations into species invasions in aquatic ecosystems suggest that anthropogenic activities and climate change will accelerate the introduction, establishment, and spread of invasive species to new habitats. In this study, we utilised ensemble species distribution modelling to investigate shifts in the invasive potential of Snowflake coral in current and future climatic settings on a global scale. Future distribution was forecasted using four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) across two periods (2040–2050 and 2090–2100). The results accurately predicted the known distributional range of the species. Temperature, distance to the port, and bathymetry were identified as the three most significant predictor variables. The low and medium habitat suitability regions increased in all scenarios and periods. In the high habitat suitability category, only RCP 4.5 and RCP 6.0 in the 2090–2100 period exhibited an increase in percentage area. Under the worst-case climate scenario, RCP 8.5 (2090–2100), the high-suitability regions displayed a surprising decline in area percentage, which can be attributed to the temperature thresholds of the species. Our findings indicate that the species has a greater potential to spread under current climatic conditions than previously reported, and its expansion may further accelerate in the future. This highlights the urgent need for more intensive surveys employing advanced detection tools and the implementation of proactive management measures to protect vulnerable ecosystems that could be impacted by this species

    Ensemble modelling of Pirarucu (Arapaima gigas) distribution in biodiversity hotspot to understand its invasion risk

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    Invasive species pose a severe threat to biodiversity around the world. Managing the consequences of invasion is difficult in aquatic settings, as the rate at which invaders establish typically outpaces the resources available to eradicate them. For proactive management measures to be implemented, prior knowledge of the probability of invasion is required. In this study, we created a spatial model of the probability of the Pirarucu (Arapaima gigas) invasion in the Western Ghats. The Western Ghats, one of the world's top biodiversity hotspots, is home to numerous endemic species, many of which are now threatened. An ensemble modelling approach using 10 models, including machine learning techniques such as Artificial Neural Network (ANN), Maximum Entropy (MaxEnt), Random Forest (RF), Generalised Boosted Regression Model (GBM) and Classification Tree Analysis (CTA), was adopted. The model was built using the species' occurrence data and nine climate variables. The findings revealed that southern regions of the Western Ghats have a high risk of Pirarucu invasion. Sri Lanka also has a much greater geographical area with a higher percentage of appropriate habitats for the species. The study becomes vital as this exotic species was repeatedly reported from the rivers since the extensive floods in the region in 2018. The developed model will assist managers in prioritising locations and initiating monitoring and management steps to prevent the spread before they establish in the wild. With earlier Pirarucu invasions in Bolivia, Peru and East Asia and recent climatic vagaries in the Western Ghats, the native biodiversity of the region is in grave danger of being displaced