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How does the local population represent the possible changes in riparian vegetation over time?
Such zones may be determined by assessing the biological productivity response of adjacent vegetation over time.
Table 1 Vegetation recovery indices used to document the recovery of vegetation over time after the eruption.
The aim of the present research was to investigate the bioengineering effects of vegetation over time in an area prone to debris flows in Gansu province, China.
In perennial and natural vegetation systems, monitoring changes in vegetation over time is of fundamental interest for identifying and quantifying impacts of management and natural processes.
Of the two scale factors examined, grain size was more consistent than MMU in terms of identifying relative change in composition and configuration of wetland marsh vegetation over time.
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Also of interest were: whether the extraordinarily high species richness present in the early study was maintained and if input of species continued despite the presence of established vegetation; how the seed bank and vegetation developed over time; how persistence of species varied in the seed bank and vegetation; and how invasive species contributed to species dynamics.
We assessed changes in rainfall, area of vegetation types, and transect coverage per vegetation type over time as potential factors that could influence both population trends and general trends in overall bird density.
Since we did not have data on changes in vegetation cover over time, we used only the presence or absence of vegetation as binary data in the model to avoid an unjustified accuracy.
Mediterranean-type vegetation (evergreen oaks and Pinus pinaster-halepensis types) showed the fastest post-fire vegetation dynamics over time.
This has proved a very useful methodological framework, not only for local and regional overviews of vegetation types (Schaminée et al. 2009), but also for thorough analyses of vegetation changes over time (Jandt et al. 2011; Jantsch et al. 2013; Chytrý et al. 2014).
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