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Wetland restoration: Predicting vegetation trajectories over 25 years

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DataONE2025-07-16 更新2025-08-16 收录
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Worldwide wetland loss has made the conservation of these ecosystems a policy priority and led to the multiplication of restoration programs. However, the lack of long-term monitoring limits our understanding of the processes influencing the vegetation composition of restored wetlands and our ability to predict outcomes over multiple decades. Here, we assessed the extent to which hydrological regime and planting density of target species, two critical factors driving wetland vegetation and restoration success, can predict restoration outcomes. Using correlation analyses and generalized models, we assessed the role of target species planting density and analogous hydrological conditions (e.g. level, variation, seasonality) to reference wetlands for achieving and predicting restored vegetation similarity to reference plant communities in 12 sedge and/or willow dominated wetlands in Mountain Village, Colorado over 25 years post-restoration. We found a significant positive correlation betwe..., , ## **Wetland restoration: Predicting vegetation trajectories over 25 years** **Dataset DOI**: 10.5061/dryad.sj3tx96gn\ **Associated article**: JAPPL-2024-01003.R2 (in press) ### **Description of the data and file structure** This dataset was collected to assess the long-term effects of hydrological restoration on wetland plant community trajectories over a 25-year period. It includes both raw and derived data from a monitoring program conducted near Telluride, Colorado (USA). The dataset supports the analyses presented in the article *Wetland restoration: Predicting vegetation trajectories over 25 years*. ### **Content** The dataset includes: * **Vegetation data** from permanent plots surveyed in 2003, 2013, and 2023, recording species presence and cover. * **Groundwater table depth measurements** taken weekly during the 2000 growing season. * **A synthesis table** aggregating derived indicators (e.g. Vegetation similarity, hydrological similarity, ...) ### **Files and variables*...,
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2025-07-22
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