Invasive non-native species management under climatic and anthropogeni pressure: Application of a modelling framework

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Abstract

Mitigation of impacts from already established invasive non-native species (INNS) relies on reducing species abundance and onward spread. However, there is limited understanding regarding the effectiveness of INNS management approaches in the short and long term, in particular in the marine environment. Further, the interplay between management and key population drivers is not well explored. The Pacific oyster Crassostrea gigas Thunberg, 1793, also known as Magallana gigas Thunberg, 1793, is native to the north-eastern Pacific coast of Asia and has been introduced in the UK for aquaculture purposes, with wild populations now widely established along the South coast. Concern over the potential impact of this species has led to trial of its management, yet clear evidence to support management decisions around this species is still lacking. This study applied a modelling framework, based on differential equations representing C. gigas life stages, to explore the effect of adult oyster population management on population persistence and density, under changing temperatures and external larval recruitment. The outputs highlight that population control may be possible and intuitively population density is negatively correlated with management frequency and effort. However, the exact relationship between population density and management is influenced by spawning and external recruitment. Specifically, outputs indicate that while the effects of climate change could be counterbalanced by an increase in management effort, the impact of external recruitment can only be reduced through management, rather than reversed. The wider application of this framework to inform INNS management decisions is discussed.

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Alves, M. T., & Tidbury, H. J. (2022). Invasive non-native species management under climatic and anthropogeni pressure: Application of a modelling framework. Management of Biological Invasions, 13(2), 259–273. https://doi.org/10.3391/mbi.2022.13.2.01

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