Aim: Decisions on wildlife conservation, management, and epidemiological risk are best based on robust evidence. The continual improvement of species distributions, such that they can be relied upon in decision-making, is important. Here we seek to refine aspects of a generic modelling approach and improve the utility of species distribution maps.
Location: Great Britain (GB).
Methods: We applied a modeling framework based on hierarchical Bayesian species distribution models exploiting opportunistic occurrence records from citizen science datasets to predict both current and potential distributions for each of the six deer species known to be present in GB. Using the resulting maps, we performed a simple analysis of the overlap between species to illustrate possible contact, which we interpret as the relative risk of potential disease spread given an introduction.
Results: Predicted distribution maps showed good agreement with the broader scale occurrence reported by a recent national deer survey with an average True Skill Statistics and AUC of 0.69 and 0.89, respectively. Aggregation of the maps for all species highlighted regions of central and eastern England as well as parts of Scotland where extensive areas of range overlap could result in interspecific contact with consequences for risk assessments for diseases of deer. However, if populations are allowed to expand to their predicted potential, then areas of overlap, and therefore disease interspecific transmission risk, will become extensive and widespread across all of mainland Britain.
Main Conclusions: The generic modeling approach outlined performed well across all of the deer species tested, offering a robust and reliable tool through which current and potential animal distributions can be estimated and presented. Our application, intended to inform quantitative risk assessments, demonstrates the practical use of such outputs to generate the valuable evidence required to inform policy decisions on issues such as management strategy.
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http://dx.doi.org/10.1002/ece3.5424 | DOI Listing |
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China Medical University, Shenyang, Liaoning, China.
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Michael Grätzel Center for Mesoscopic Solar Cells Wuhan National Laboratory for Optoelectronics Key Laboratory of Materials Chemistry for Energy Conversion and Storage of Ministry of Education, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, P. R. China.
Carbon-based printable mesoscopic solar cells (p-MPSCs) offer significant advantages for industrialization due to their simple fabrication process, low cost, and scalability. Recently, the certified power conversion efficiency of p-MPSCs has exceeded 22%, drawing considerable attention from the community. However, the key challenge in improving device performance is achieving uniform and high-quality perovskite crystallization within the mesoporous structure.
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View Article and Find Full Text PDFMol Cancer
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The last decade has witnessed unprecedented succusses with the use of immune checkpoint inhibitors in treating cancer. Nevertheless, the proportion of patients who respond favorably to the treatment remained rather modest, partially due to treatment resistance. This has fueled a wave of research into potential mechanisms of resistance to immune checkpoint inhibitors which can be classified into primary resistance or acquired resistance after an initial response.
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