4.1 Article

Quantifying plant species diversity in coastal dunes: a piece of help from spatially constrained rarefaction

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FOLIA GEOBOTANICA
卷 51, 期 2, 页码 129-141

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SPRINGER
DOI: 10.1007/s12224-016-9249-9

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biodiversity; coastline dynamic processes; coastal dune vegetation; Natura 2000; rarefaction curves; spatial autocorrelation

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Since coastal dunes are one of the most vulnerable landscapes in Europe, their maintenance requires specific conservation and monitoring programmes. In this paper, the coastal dune systems of two natural parks located in central Italy were analyzed aiming at: (1) assessing diversity patterns of all vascular species, endemic and alien taxa in plant communities along the coast-to-inland gradient; (2) comparing these patterns between coastal sections characterized by different dynamical processes (accreting, stable and erosive coasts); and (3) testing the differences induced by the methodological approach used to characterize these patterns. Twenty-one transects were randomly positioned perpendicular to the shoreline in the whole coastal area (30 km in length), and the full spectrum of plant communities was sampled. Patterns of plant diversity were assessed using spatially explicit methods, namely spatial constrained rarefaction (SCR), able to avoid the confounding effect of spatial autocorrelation. The results show that species richness varied significantly between plant communities along the coast-to-inland gradient with the highest values at the level of mobile dunes and transition dunes. Species richness was significantly higher in stable coastal dunes than those found in accreting and in erosive dunes. In fact, sand dynamics (accumulation as well as erosion) create periodic vegetation disturbances affecting composition variability and succession. The SCR methodology avoided overestimation of species richness when compared to classical rarefaction curves. Our findings pinpointed that coastal plant communities create a highly spatially structured mosaic in which mobile dunes represent the highest compositional heterogeneity. Local managers are encouraged to consider these results for planning adequate conservation strategies.

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