2023
DOI: 10.1111/ddi.13767
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Range reshuffling: Climate change, invasive species, and the case of Nothofagus forests in Aotearoa New Zealand

Shar Mathias,
Laura G. van Galen,
Scott Jarvie
et al.

Abstract: AimThe impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native Nothofagus and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invas… Show more

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Cited by 4 publications
(1 citation statement)
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“…Additionally, future climate variables were obtained from the 6 th assessment report of the Intergovernmental Panel on Climate Change (IPCC AR6) for two distinct Shared Socioeconomic Pathways scenarios (SSP-126 and SSP-585). These climate projections were derived using the Global Circulation Model (GCM) of GFDL-ESM4 (Shaban et al, 2023;Mathias et al, 2023) and span two temporal scales: 2041-2070 and 2071-2100. To address collinearity issues among these variables, hierarchical cluster analysis was employed with Pearson's correlation coefficient (with a cutoff set at 0.7) (Gallego-Narbón et al, 2023).…”
Section: Predictor Variablesmentioning
confidence: 99%
“…Additionally, future climate variables were obtained from the 6 th assessment report of the Intergovernmental Panel on Climate Change (IPCC AR6) for two distinct Shared Socioeconomic Pathways scenarios (SSP-126 and SSP-585). These climate projections were derived using the Global Circulation Model (GCM) of GFDL-ESM4 (Shaban et al, 2023;Mathias et al, 2023) and span two temporal scales: 2041-2070 and 2071-2100. To address collinearity issues among these variables, hierarchical cluster analysis was employed with Pearson's correlation coefficient (with a cutoff set at 0.7) (Gallego-Narbón et al, 2023).…”
Section: Predictor Variablesmentioning
confidence: 99%