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From the Cover: Predicting the spread of marine species introduced by global shipping
Authors:Hanno Seebens  Nicole Schwartz  Peter J Schupp  Bernd Blasius
Institution:aInstitute for Chemistry and Biology of the Marine Environment, University of Oldenburg, 26111 Oldenburg, Germany;;bDepartment of Botany and Biodiversity Research, University of Vienna, 1030 Vienna, Austria;;cSenckenberg Biodiversity and Climate Research Centre, 60325 Frankfurt, Germany
Abstract:The human-mediated translocation of species poses a distinct threat to nature, human health, and economy. Although existing models calculate the invasion probability of any species, frameworks for species-specific forecasts are still missing. Here, we developed a model approach using global ship movements and environmental conditions to simulate the successive global spread of marine alien species that allows predicting the identity of those species likely to arrive next in a given habitat. In a first step, we simulated the historical stepping-stone spreading dynamics of 40 marine alien species and compared predicted and observed alien species ranges. With an accuracy of 77%, the model correctly predicted the presence/absence of an alien species in an ecoregion. Spreading dynamics followed a common pattern with an initial invasion of most suitable habitats worldwide and a subsequent spread into neighboring habitats. In a second step, we used the reported distribution of 97 marine algal species with a known invasion history, and six species causing harmful algal blooms, to determine the ecoregions most likely to be invaded next under climate warming. Cluster analysis revealed that species can be classified according to three characteristic spreading profiles: emerging species, high-risk species, and widespread species. For the North Sea, the model predictions could be confirmed because two of the predicted high-risk species have recently invaded the North Sea. This study highlights that even simple models considering only shipping intensities and habitat matches are able to correctly predict the identity of the next invading marine species.The number of alien species transported by human assistance has increased rapidly during the last decades with serious consequences for native flora and fauna (13). These biological invasions are considered to be one of the major drivers of biodiversity changes (46). Once an unwanted alien species has naturalized in the new environment, it is nearly impossible to eradicate the species, and thus the mitigation of further introduction is the most efficient way of combating biological invasions (6, 7). However, a targeted monitoring and an efficient adaptive management requires knowledge about spreading dynamics of the next potential invaders and thus about the distribution of species, their invasiveness, and the likelihood of new introductions. Although all of these topics have been analyzed on their own, the potential to predict the spreading of alien species while combining these components remains to be tested.A large amount of recent introductions can be attributed to the intensified global trade and transport as many species were accidentally or deliberately translocated through the exchange of commodities or the movements of transportation means (8, 9). The amount of exchanged commodities and the intensity of global traffic have therefore been found to be a good predictor to model the global spread of alien species (1012). In most cases, predictions of alien species introductions are difficult to assess as model results could not be validated (i.e., quantitatively assessed using observed data) thoroughly due to the paucity of high-quality distributional data of alien species. Without any model validation, however, it is nearly impossible to assess the quality and the reliability of model predictions, which hampers the application of models for the management of alien species. In recent years, appropriate high-quality data have been made accessible by various online databases, but testing model predictions with these data has still been lacking.Model frameworks to predict the likelihood of new invasions have already been developed (10, 11, 13). However, these were not able to predict the identity of new invaders, but only the likelihood that any new species arrives from a certain source region on Earth. Here, we combined such a model, a slightly modified version of the vector-based model of marine invasion adopted from ref. 10, with datasets about the global distribution of marine alien species, which enabled us to predict the identity of the next species to arrive in a given local habitat. The model is a statistical model that describes how the probability a given species successfully invades a specific location depends on the shipping traffic and the environmental differences (temperature and salinity) between locations.In a first step, to test the accuracy of the model, we used native ranges of 40 marine species from various taxonomic groups, ranging from algae to fish, as initial condition. For each species, we simulated the global spread outside its native range and compared the predicted alien range at each simulation time step with the observed one. This procedure allows the assessment of the quality of model predictions, although the degree of expansion distinctly varied among species, as some species are already widespread, whereas others occupy only a few alien regions either because they just started to spread or there are only a limited number of suitable habitats available.In a second step, we used the reported distribution of 97 marine algal species with a known invasion history and six harmful algal species obtained from AlgaeBase (www.algaebase.org) and determined the species-specific invasion probabilities for each marine ecoregion not occupied by that species. Algae are particularly well suited for such an analysis because they are easily translocated by the exchange of ballast water, and especially invasive seaweeds are of global concerns because over 400 introductions have been reported worldwide (14). Furthermore, seaweeds deeply shape marine ecosystems and they can have strong detrimental ecological and economic impacts (14, 15). Using our model, we identified the likely hot spots of future invasions among 90 marine ecoregions of the world and algal species with the highest probability to arrive next.
Keywords:alien species  model predictions  species identity  marine ecoregion  climate change
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