58 research outputs found

    Species trait shifts in vegetation and soil seed bank during fen degradation

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    Fens in Central Europe are characterised by waterlogged organic substrate and low productivity. Human-induced changes due to drainage and mowing lead to changes in plant species composition from natural fen communities to fen meadows and later to over-drained, degraded meadows. Moderate drainage leads to increased vegetation productivity, and severe drainage results in frequent soil disturbances and less plant growth. In the present article, we analyse changes in plant trait combinations in the vegetation and the soil seed bank as well as changes in the seed bank types along gradient of drainage intensity. We hypothesize that an increase in productivity enhances traits related to persistence and that frequent disturbance selects for regeneration traits. We use multivariate statistics to analyse data from three disturbance levels: undisturbed fen, slightly drained fen meadow and severely drained degraded meadow. We found that the abundance of plants regenerating from seeds and accumulating persistent seed banks was increasing with degradation level, while plants reproducing vegetatively were gradually eliminated along the same trajectory. Plants with strong resprouting abilities increased during degradation. We also found that shifts in trait combinations were similar in the aboveground vegetation and in soil seed banks. We found that the density of short-term persistent seeds in the soil is highest in fen meadows and the density of long-term persistent seeds is highest in degraded meadows. The increase in abundance of species with strong regeneration traits at the cost of species with persistence-related traits has negative consequences for the restoration prospects of severely degraded sites

    Modelling historical landscape changes

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    Context: Historical maps of land use/land cover (LULC) enable detection of landscape changes, and help to assess drivers and potential future trajectories. However, historical maps are often limited in their spatial and temporal coverage. There is a need to develop and test methods to improve re-construction of historical landscape change. Objectives: To implement a modelling method to accurately identify key land use changes over a rural landscape at multiple time points. Methods: We used existing LULC maps at two time points for 1930 and 2015, along with a habitat time-series dataset, to construct two new, modelled LULC maps for Dorset in 1950 and 1980 to produce a four-step time-series. We used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool to model new LULC maps. Results: The modelled 1950 and 1980 LULC maps were cross-validated against habitat survey data and demonstrated a high level of accuracy (87% and 84%, respectively) and low levels of model uncertainty. The LULC time-series revealed the timing of LULC changes in detail, with the greatest losses in neutral and calcareous grassland having occurred by 1950, the period when arable land expanded the most, whilst the expansion in agriculturally-improved grassland was greatest over the period 1950–1980. Conclusions: We show that the modelling approach is a viable methodology for re-constructing historical landscapes. The time-series output can be useful for assessing patterns and changes in the landscape, such as fragmentation and ecosystem service delivery, which is important for informing future land management and conservation strategies
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