Browsing by Author "Middleton I"
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- ItemIntroduced alien, range extension or just visiting? Combining citizen science observations and expert knowledge to classify range dynamics of marine fishes(1/07/2021) Middleton I; Aguirre JD; Trnski T; Francis M; Duffy C; Liggins LAim: Despite the unprecedented rate of species redistribution during the Anthropocene, there are few monitoring programmes at the appropriate spatial and temporal scale to detect distributional change of marine species and to infer climate- versus human-mediated drivers of change. Here, we present an approach that combines citizen science with expert knowledge to classify out-of-range occurrences for marine fishes as potential range extensions or human-mediated dispersal events. Innovation: Our stepwise approach includes decision trees, scoring and matrices to classify citizen science observations of species occurrences and to provide a measure of confidence and validation using expert knowledge. Our method draws on peer-reviewed literature, knowledge of the species (e.g. contributing to its detectability, and potential to raft with, or foul, man-made structures or debris) and information obtained from citizen science observations (e.g. life stage, number of individuals). Using a case study of suspected out-of-range marine fishes in Aotearoa New Zealand, we demonstrate our approach to defining species’ ranges, assigning confidence to these definitions and considering the species detectability to overcome the data deficiencies that currently hinder monitoring the range dynamics of these species. Our classification of citizen science observations revealed that six of ten species had out-of-range occurrences; one of these was classified as an extralimital vagrant, four species had potentially extended their ranges and one species occurrence was likely due to human-mediated dispersal. Conclusion: The case study of marine fishes in New Zealand validates our approach combining citizen science observations with expert knowledge to infer species range dynamics in real time. Our stepwise approach helps to identify data deficiencies important in informing scientific inferences and management actions and can be refined to suit other data sources, taxonomic groups, geographic settings or extended with new steps and existing tools.