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Stakeholders are critical environmental managers in human-dominated landscapes. In some contexts, stakeholders can be forced to personally act following their own observations and risk perception instead of science recommendation. In particular, biological invasions need rapid control actions to reduce potential socio-ecological impacts, while science-based risk assessments are rather complex and time-delayed. Although they can lead to important detrimental effects on biodiversity, potential time-delayed disconnections between stakeholders' action and science recommendations are rarely studied. Using the case study of western European beekeepers controlling the invasive Asian hornet Vespa velutina nigrithorax for its suspected impact on honey bee colonies, we analysed mechanisms underlying personal actions of stakeholders and how they evolved in science disconnection. Personal actions of stakeholders were causal-effect linked with their risk observation but disconnected to time-delayed science predictions and recommendations. Unfortunately, these science-disconnected actions also led to dramatic impacts on numerous species of the local entomofauna. These results highlight the need to improve mutual risk communication between science and action in the early-stages of management plans to improve the sustainably of stakeholders' practices., Competing Interests: Declaration of competing interest No conflict of interest was reported by the authors., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies-with independent data-are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be-at least partially-climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology.