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• W2074288387 abstract "Quantifying spatial and temporal dynamics of organic matter (OM) is critical both for understanding ecosystem functioning and for predicting impacts of landscape change. To determine the influence of different habitats and coarse particulate OM (CPOM) types upon floodplain OM dynamics, we quantified aerial input, lateral surface transfer, and surface storage of CPOM over an annual cycle on the near-natural floodplain of the River Tagliamento in NE-Italy. Using these data, we modelled floodplain leaf dynamics, taking account of the spatial distribution and hydrologic connectivity of habitats, and using leaf storage as a response variable. Mean aerial CPOM input to the floodplain was similar from riparian forest and islands, but surface transfer was greater from islands, supporting the suggestion that these habitats act as “islands of fertility” along braided rivers. Leaves were the lateral conveyor of energy to more open parts of the floodplain, whereas CPOM was mainly stored as small wood in vegetated islands and riparian forest. Simulating the loss of habitat diversity (islands, ponds) decreased leaf storage on the whole floodplain, on exposed gravel and in large wood accumulations. In contrast, damming (loss of islands, ponds and floods plus floodplain overgrowth) greatly increased storage on exposed gravel. A random shuffle of habitats led to a storage increase on exposed gravel, while that in large wood accumulations and ponds declined. These results disentangle some of the complexities of CPOM dynamics in floodplain ecosystems, illustrate the value of models in understanding ecosystem functioning at a landscape level, and directly inform river management practice." @default.
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• W2074288387 date "2012-10-10" @default.
• W2074288387 modified "2023-10-16" @default.
• W2074288387 title "Environmental heterogeneity affects input, storage, and transformation of coarse particulate organic matter in a floodplain mosaic" @default.
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• W2074288387 doi "https://doi.org/10.1007/s00027-012-0277-0" @default.
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