A spatially explicit model framework to predict the spread of the noisy miner (Manorina melanocephala)
Pacific Conservation Biology, ISSN: 2204-4604, Vol: 28, Issue: 5, Page: 414-426
2021
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
Context: The noisy miner (Manorina melanocephala) is an aggressive Australian honeyeater that has been strongly implicated in the decline of assemblages of smaller passerine species in eastern Australia. Factors likely to promote the spread of noisy miners throughout modified landscapes have been identified using static correlative models. However, the underlying mechanisms resulting in the patterns of space-use implicit in such models remain largely unknown. Aims: The aim of the study was to develop a modelling context that is better able to capture the underlying mechanisms driving the spread of Noisy Miners than are static correlative modelling techniques. Methods: A spatially explicit, grid-based model framework was derived to estimate the vulnerability of assemblages of bird species to displacement or replacement by noisy miners. Data from an area of suburban and peri-urban Brisbane were used as a case study in the application of the model framework. Key results: The model framework predicted that sensitive bird assemblages, occupying a range of habitats, were far more vulnerable overall to displacement or replacement by noisy miners within the case study landscape than vice versa. The spaces within this landscape occupied by sensitive bird species predicted to be most vulnerable to noisy miner spread were identified. Conclusions: The spatially explicit context within which the model framework is set provides an opportunity to gain insights into the mechanisms underlying the spread of noisy miners that static correlative models have yet to fully identify. Implications: The model framework has potential for application in land use and conservation management planning.
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