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faculteit: "FNWI" en publicatiejaar: "2012"
| Auteurs||R.C.C. Hsu, W.L.M. Tamis, N. Raes, G.R. de Snoo, J.H.D. Wolf, G. Oostermeijer, S.H. Lin|
|Titel||Simulating climate change impacts on forests and associated vascular epiphytes in a subtropical island of East Asia|
|Tijdschrift||Diversity and distributions|
|Faculteit||Faculteit der Natuurwetenschappen, Wiskunde en Informatica|
|Instituut/afd.||FNWI: Institute for Biodiversity and Ecosystem Dynamics (IBED)|
|Samenvatting||Aim: This study aims to assess the impact of climate change on forests and vascular epiphytes, using species distribution models (SDMs).|
Location: Island of Taiwan, subtropical East Asia.
Methods: A hierarchical modelling approach incorporating forest migration velocity and forest type–epiphyte interactions with classical SDMs was used to model the responses of eight forest types and 237 vascular epiphytes for the year 2100 under two climate change scenarios. Forest distributions were modelled and modified by dominant tree species’ dispersal limitations and hypothesized persistence under unfavourable climate conditions (20 years for broad-leaved trees and 50 years for conifers). The modelled forest projections together with 16 environmental variables were used as predictors in models of epiphyte distributions. A null method was applied to validate the significance of epiphyte SDMs, and potential vulnerable species were identified by calculating range turnover rates.
Results: For the year 2100, the model predicted a reduction in the range of most forest types, especially for Picea and cypress forests, which shifted to altitudes c. 400 and 300 m higher, respectively. The models indicated that epiphyte distributions are highly correlated with forest types, and the majority (77–78%) of epiphyte species were also projected to lose 45–58% of their current range, shifting on average to altitudes c. 400 m higher than currently. Range turnover rates suggested that insensitive epiphytes were generally lowland or widespread species, whereas sensitive species were more geographically restricted, showing a higher correlation with temperature-related factors in their distributions.
Main conclusions: The hierarchical modelling approach successfully produced interpretable results, suggesting the importance of considering biotic interactions and the inclusion of terrain-related factors when developing SDMs for dependant species at a local scale. Long-term monitoring of potentially vulnerable sites is advised, especially of those sites that fall outside current conservation reserves where additional human disturbance is likely to exacerbate the effect of climate change.
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