2 resultados para Grid-based clustering approach

em Publishing Network for Geoscientific


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The majority of benthic marine invertebrates have a complex life cycle, during which the pelagic larvae select a suitable substrate, attach to it, and then metamorphose into benthic adults. Anthropogenic ocean acidification (OA) is postulated to affect larval metamorphic success through an altered protein expression pattern (proteome structure) and post-translational modifications. To test this hypothesis, larvae of an economically and ecologically important barnacle species Balanus amphitrite, were cultured from nauplius to the cyprid stage in the present (control) and in the projected elevated concentrations of CO2 for the year 2100 (the OA treatment). Cyprid response to OA was analyzed at the total proteome level as well as two protein post-translational modification (phosphorylation and glycosylation) levels using a 2-DE based proteomic approach. The cyprid proteome showed OA-driven changes. Proteins that were differentially up or down regulated by OA come from three major groups, namely those related to energy-metabolism, respiration, and molecular chaperones, illustrating a potential strategy that the barnacle larvae may employ to tolerate OA stress. The differentially expressed proteins were tentatively identified as OA-responsive, effectively creating unique protein expression signatures for OA scenario of 2100. This study showed the promise of using a sentinel and non-model species to examine the impact of OA at the proteome level.

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Physiognomic traits of plant leaves such as size, shape or margin are decisively affected by the prevailing environmental conditions of the plant habitat. On the other hand, if a relationship between environment and leaf physiognomy can be shown to exist, vegetation represents a proxy for environmental conditions. This study investigates the relationship between physiognomic traits of leaves from European hardwood vegetation and environmental parameters in order to create a calibration dataset based on high resolution grid cell data. The leaf data are obtained from synthetic chorologic floras, the environmental data comprise climatic and ecologic data. The high resolution of the data allows for a detailed analysis of the spatial dependencies between the investigated parameters. The comparison of environmental parameters and leaf physiognomic characters reveals a clear correlation between temperature related parameters (e.g. mean annual temperature or ground frost frequency) and the expression of leaf characters (e.g. the type of leaf margin or the base of the lamina). Precipitation related parameters (e.g. mean annual precipitation), however, show no correlation with the leaf physiognomic composition of the vegetation. On the basis of these results, transfer functions for several environmental parameters are calculated from the leaf physiognomic composition of the extant vegetation. In a next step, a cluster analysis is applied to the dataset in order to identify "leaf physiognomic communities". Several of these are distinguished, characterised and subsequently used for vegetation classification. Concerning the leaf physiognomic diversity there are precise differences between each of these "leaf physiognomic classes". There is a clear increase of leaf physiognomic diversity with increasing variability of the environmental parameters: Northern vegetation types are characterised by a more or less homogeneous leaf physiognomic composition whereas southern vegetation types like the Mediterranean vegetation show a considerable higher leaf physiognomic diversity. Finally, the transfer functions are used to estimate palaeo-environmental parameters of three fossil European leaf assemblages from Late Oligocene and Middle Miocene. The results are compared with results obtained from other palaeo-environmental reconstructing methods. The estimates based on a direct linear ordination seem to be the most realistic ones, as they are highly consistent with the Coexistence Approach.