Abstract

We assessed the potential for using optical functional types as effective markers to monitor changes in vegetation in floodplain meadows associated with changes in their local environment. Floodplain meadows are challenging ecosystems for monitoring and conservation because of their highly biodiverse nature. Our aim was to understand and explain spectral differences among key members of floodplain meadows and also characterize differences with respect to functional traits. The study was conducted on a typical floodplain meadow in UK (MG4-type, mesotrophic grassland type 4, according to British National Vegetation Classification). We compared two approaches to characterize floodplain communities using field spectroscopy. The first approach was sub-community based, in which we collected spectral signatures for species groupings indicating two distinct eco-hydrological conditions (dry and wet soil indicator species). The other approach was “species-specific”, in which we focused on the spectral reflectance of three key species found on the meadow. One herb species is a typical member of the MG4 floodplain meadow community, while the other two species, sedge and rush, represent wetland vegetation. We also monitored vegetation biophysical and functional properties as well as soil nutrients and ground water levels. We found that the vegetation classes representing meadow sub-communities could not be spectrally distinguished from each other, whereas the individual herb species was found to have a distinctly different spectral signature from the sedge and rush species. The spectral differences between these three species could be explained by their observed differences in plant biophysical parameters, as corroborated through radiative transfer model simulations. These parameters, such as leaf area index, leaf dry matter content, leaf water content, and specific leaf area, along with other functional parameters, such as maximum carboxylation capacity and leaf nitrogen content, also helped explain the species’ differences in functional dynamics. Groundwater level and soil nitrogen availability, which are important factors governing plant nutrient status, were also found to be significantly different for the herb/wetland species’ locations. The study concludes that spectrally distinguishable species, typical for a highly biodiverse site such as a floodplain meadow, could potentially be used as target species to monitor vegetation dynamics under changing environmental conditions.

Highlights

  • Floodplain meadows are highly biodiverse and sensitive ecosystems supporting numerous species of flora and fauna [1,2]

  • We assess if it is possible to identify spectrally distinguishable members of the community. We investigate if their leaf and canopy level biophysical and biochemical properties explain the observed differences in vegetation spectra with the help of radiative transfer model

  • All spectral analysis tests show that the DRY and WET sub-community based classes are spectrally very similar, while for the species based classes results suggest spectral differences between Sanguisorba officinalis (SO) and Carex acuta (CA) or Juncus acutiflorus (JA) with mixed results for differences between CA and JA

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Summary

Introduction

Floodplain meadows are highly biodiverse and sensitive ecosystems supporting numerous species of flora and fauna [1,2]. The biodiversity of these meadows is under constant threat due to changes in hydrological regime, poor management and agricultural intensification. Because of their high ecological significance, they have been given a high conservation priority, and they need to be studied and monitored closely to prevent any further loss of biodiversity. Fritillario–Alopecuretum pratensis with 16 constant species referring to those that are typical members of MG4) including grasses and broad leaf herbaceous species It is one of the most typical floodplain communities in the UK; a semi-natural ecosystem developed as a result of traditional management. This management allows vegetation to grow during spring and summer, which is cut for hay during June–July, followed by grazing in the two months in early autumn

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