Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

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European mushroom assemblages are darker in cold climates
Krah, Franz Sebastian ; Büntgen, Ulf ; Schaefer, Hanno ; Müller, Jörg ; Andrew, Carrie ; Boddy, Lynne ; Diez, Jeffrey ; Egli, Simon ; Freckleton, Robert ; Gange, Alan C. ; Halvorsen, Rune ; Heegaard, Einar ; Heideroth, Antje ; Heibl, Christoph ; Heilmann-Clausen, Jacob ; Høiland, Klaus ; Kar, Ritwika ; Kauserud, Håvard ; Kirk, Paul M. ; Kuyper, Thomas W. ; Krisai-Greilhuber, Irmgard ; Norden, Jenni ; Papastefanou, Phillip ; Senn-Irlet, Beatrice ; Bässler, Claus - \ 2019
Nature Communications 10 (2019). - ISSN 2041-1723

Thermal melanism theory states that dark-colored ectotherm organisms are at an advantage at low temperature due to increased warming. This theory is generally supported for ectotherm animals, however, the function of colors in the fungal kingdom is largely unknown. Here, we test whether the color lightness of mushroom assemblages is related to climate using a dataset of 3.2 million observations of 3,054 species across Europe. Consistent with the thermal melanism theory, mushroom assemblages are significantly darker in areas with cold climates. We further show differences in color phenotype between fungal lifestyles and a lifestyle differentiated response to seasonality. These results indicate a more complex ecological role of mushroom colors and suggest functions beyond thermal adaption. Because fungi play a crucial role in terrestrial carbon and nutrient cycles, understanding the links between the thermal environment, functional coloration and species’ geographical distributions will be critical in predicting ecosystem responses to global warming.

A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations : An example from the Amazon region
Rammig, Anja ; Heinke, Jens ; Hofhansl, Florian ; Verbeeck, Hans ; Baker, Timothy R. ; Christoffersen, Bradley ; Ciais, Philippe ; Deurwaerder, Hannes De; Fleischer, Katrin ; Galbraith, David ; Guimberteau, Matthieu ; Huth, Andreas ; Johnson, Michelle ; Krujit, Bart ; Langerwisch, Fanny ; Meir, Patrick ; Papastefanou, Phillip ; Sampaio, Gilvan ; Thonicke, Kirsten ; Randow, Celso von; Zang, Christian ; Rödig, Edna - \ 2018
Geoscientific Model Development 11 (2018)12. - ISSN 1991-959X - p. 5203 - 5215.

Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.

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