Challenges in supplying empirical proof for predictions derived from Species Distribution Models (SDMs): the case of an invasive cyanobacterium.

Species distribution models (SDMs) calibrated with bioclimatic variables revealed a high probability for range expansion of the invasive toxin producing cyanobacterium, Raphidiopsis raciborskii to Sweden, where no reports of its presence have hitherto been recorded. While predictions focused on the importance of climate variables for possible invasion, other barriers to dispersal and successful colonization need to be overcome by the species for successful invasion. In this study, we combine field-based surveys of R. raciborskii (microscopy and molecular analysis using species-specific primers) of 11 Swedish lakes and in-silico screening of environmental DNA using 153 metagenomic datasets from lakes across Europe to validate the SDMs prediction. Field-based studies in lakes with high/low predicted probability of occurrence did not detect the presence of R. raciborskii, and in-silico screening only detected hints of its presence in 5 metagenomes from lakes with probability ranging from 0.059 to 0.825. The inconsistencies between SDMs results and both field-based/in-silico monitoring could be due to either sensitivity of monitoring approaches in detecting early invasions or uncertainties in SDMs that focused solely on climate drivers. However, results highlight the necessity of proactive monitoring with high temporal and spatial frequency.

Species distribution models as a tool for early detection of the invasive Raphidiopsis raciborskii in European lakes.

In freshwater habitats, invasive species and the increase of cyanobacterial blooms have been identified as a major cause of biodiversity loss. The invasive cyanobacteria Raphidiopsis raciborskii a toxin-producing and bloom-forming species affecting local biodiversity and ecosystem services is currently expanding its range across Europe. We used species distribution models (SDMs) and regional bioclimatic environmental variables, such as temperature and precipitation, to identify suitable areas for the colonization and survival of R. raciborskii, with special focus on the geographic extent of potential habitats in Northern Europe. SDMs predictions uncovered areas of high occurrence probability of R. raciborskii in locations where it has not been recorded yet, e.g. some areas in Central and Northern Europe. In the southeastern part of Sweden, areas of suitable climate for R. raciborskii corresponded with lakes of high concentrations of total phosphorus, increasing the risk of the species to thrive. To our knowledge, this is the first attempt to predict areas at high risk of R. raciborskii colonization in Europe. The results from this study suggest several areas across Europe that would need monitoring programs to determine if the species is present or not, to be able to prevent its potential colonization and population growth. Regarding an undesirable microorganism like R. raciborskii, authorities may need to start information campaigns to avoid or minimize the spread.