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Publikasjoner

NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2018

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Sammendrag

Due to the increasing relevance of analyzing water consumption along product life cycles, the water accounting and vulnerability evaluation model (WAVE) has been updated and methodologically enhanced. Recent data from the atmospheric moisture tracking model WAM2-layers is used to update the basin internal evaporation recycling (BIER) ratio, which denotes atmospheric moisture recycling within drainage basins. Potential local impacts resulting from water consumption are quantified by means of the water deprivation index (WDI). Based on the hydrological model WaterGAP3, WDI is updated and methodologically refined to express a basin’s vulnerability to freshwater deprivation resulting from the relative scarcity and absolute shortage of water. Compared to the predecessor version, BIER and WDI are provided on an increased spatial and temporal (monthly) resolution. Differences compared to annual averages are relevant in semiarid and arid basins characterized by a high seasonal variation of water consumption and availability. In order to support applicability in water footprinting and life cycle assessment, BIER and WDI are combined to an integrated WAVE+ factor, which is provided on different temporal and spatial resolutions. The applicability of the WAVE+ method is proven in a case study on sugar cane, and results are compared to those obtained by other impact assessment methods.

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Sammendrag

Aim: Revisits of non-permanent, relocatable plots first surveyed several decades ago offer a direct way to observe vegetation change and form a unique and increasingly used source of information for global change research. Despite the important insights that can be obtained from resurveying these quasi-permanent vegetation plots, their use is prone to both observer and relocation errors. Studying the combined effects of both error types is important since they will play out together in practice and it is yet unknown to what extent observed vegetation changes are influenced by these errors. Methods: We designed a study that mimicked all steps in a resurvey study and that allowed determination of the magnitude of observer errors only vs the joint observer and relocation errors. Communities of vascular plants growing in the understorey of temperate forests were selected as study system. Ten regions in Europe were covered to explore generality across contexts and 50 observers were involved, which deliberately differed in their experience in making vegetation records. Results: The mean geographic distance between plots in the observer+relocation error data set was 24 m. The mean relative difference in species richness in the observer error and the observer+relocation data set was 15% and 21%, respectively. The mean “pseudo-turnover” between the five records at a quasi-permanent plot location was on average 0.21 and 0.35 for the observer error and observer+relocation error data sets, respectively. More detailed analyses of the compositional variation showed that the nestedness and turnover components were of equal importance in the observer data set, whereas turnover was much more important than nestedness in the observer+relocation data set. Interestingly, the differences between the observer and the observer+relocation data sets largely disappeared when looking at temporal change: both the changes in species richness and species composition over time were very similar in these data sets. Conclusions: Our results demonstrate that observer and relocation errors are nonnegligible when resurveying quasi-permanent plots. A careful interpretation of the results of resurvey studies is warranted, especially when changes are assessed based on a low number of plots. We conclude by listing measures that should be taken to maximally increase the precision and the strength of the inferences drawn from vegetation resurveys.