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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
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Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Rule-based analysis of throughfall kinetic energy to evaluate biotic and abiotic factor thresholds to mitigate erosive powerGoebes, Philipp, Schmidt, Karsten, Stumpf, Felix, von Oheimb, Goddert, Scholten, Thomas, Härdtle, Werner, Seitz, Steffen 17 September 2019 (has links)
Below vegetation, throughfall kinetic energy (TKE) is an important factor to express the potential of rainfall to detach soil particles and thus for predicting soil erosion rates. TKE is affected by many biotic (e.g. tree height, leaf area index) and abiotic (e.g. throughfall amount) factors because of changes in rain drop size and velocity. However, studies modelling TKE with a high number of those factors are lacking. This study presents a new approach to model TKE. We used 20 biotic and abiotic factors to evaluate thresholds of those factors that can mitigate TKE and thus decrease soil erosion. Using these thresholds, an optimal set of biotic and abiotic factors was identified to minimize TKE. The model approach combined recursive feature elimination, random forest (RF) variable importance and classification and regression trees (CARTs). TKE was determined using 1405 splash cup measurements during five rainfall events in a subtropical Chinese tree plantation with five-year-old trees in 2013.
Our results showed that leaf area, tree height, leaf area index and crown area are the most prominent vegetation traits to model TKE. To reduce TKE, the optimal set of biotic and abiotic factors was a leaf area lower than 6700mm2, a tree height lower than 290 cm combined with a crown base height lower than 60 cm, a leaf area index smaller than 1, more than 47 branches per tree and using single tree species neighbourhoods. Rainfall characteristics, such as amount and duration, further classified high or low TKE. These findings are important for the establishment of forest plantations that aim to minimize soil erosion in young succession stages using TKE modelling.
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Identifiers in e-Science platforms for the ecological sciencesNadrowski, Karin, Seifarth, Daniel, Ratcliffe, Sophia, Wirth, Christian, Maicher, Lutz 14 December 2012 (has links) (PDF)
In the emerging Web of Data, publishing stable and unique identifiers promises great potential in using the web as common platform to discover and enrich data in the ecologic sciences. With our collaborative e-Science platform “BEFdata”, we generated and published unique identifiers for the data repository of the Biodiversity – Ecosystem Functioning Research Unit of the German Research Foundation (BEF-China; DFG: FOR 891). We linked part of the identifiers to two external data providers, thus creating a virtual common platform including several ecological repositories. We used the Global Biodiversity Facility (GBIF) as well the International Plant Name Index (IPNI) to enrich the data from our own field observations. We conclude in discussing other potential providers for identifiers for the ecological research domain. We demonstrate the ease of making use of existing decentralized and unsupervised identifiers for a data repository, which opens new avenues to collaborative data discovery for learning, teaching, and research in ecology.
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Identifiers in e-Science platforms for the ecological sciencesNadrowski, Karin, Seifarth, Daniel, Ratcliffe, Sophia, Wirth, Christian, Maicher, Lutz January 2012 (has links)
In the emerging Web of Data, publishing stable and unique identifiers promises great potential in using the web as common platform to discover and enrich data in the ecologic sciences. With our collaborative e-Science platform “BEFdata”, we generated and published unique identifiers for the data repository of the Biodiversity – Ecosystem Functioning Research Unit of the German Research Foundation (BEF-China; DFG: FOR 891). We linked part of the identifiers to two external data providers, thus creating a virtual common platform including several ecological repositories. We used the Global Biodiversity Facility (GBIF) as well the International Plant Name Index (IPNI) to enrich the data from our own field observations. We conclude in discussing other potential providers for identifiers for the ecological research domain. We demonstrate the ease of making use of existing decentralized and unsupervised identifiers for a data repository, which opens new avenues to collaborative data discovery for learning, teaching, and research in ecology.
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