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- Potapov, Anton M., et al.
(författare)
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Globally invariant metabolism but density-diversity mismatch in springtails
- 2023
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning.
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| 2. |
- Wu, Q., et al.
(författare)
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Freight train air brake models
- 2021
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Ingår i: International Journal of Rail transportation. - : Informa UK Limited. - 2324-8378 .- 2324-8386.
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Tidskriftsartikel (refereegranskat)abstract
- This paper is an outcome of an international collaborative research initiative. Researchers from 24 institutions across 12 countries were invited to discuss the state-of-the-art in railway train air brake modelling with an emphasis on freight rains. Discussed models are classified as empirical, fluid dynamics and fluid-empirical dynamics models. Empirical models are widely used, and advanced versions have been used for train dynamics simulations. Fluid dynamics models are better models to study brake system behaviour but are more complex and slower in computation. Fluid-empirical dynamics models combine fluid dynamics brake pipe models and empirical brake valve models. They are a balance of model fidelity and computational speeds. Depending on research objectives, detailed models of brake rigging, friction blocks and wheel-rail adhesion are also available. To spark new ideas and more research in this field, the challenges and research gaps in air brake modelling are discussed.
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| 3. |
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| 4. |
- Fronzek, Stefan, et al.
(författare)
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Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
- 2018
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Ingår i: Agricultural Systems. - : Elsevier BV. - 0308-521X. ; 159, s. 209-224
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Tidskriftsartikel (refereegranskat)abstract
- Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9°C) and precipitation (-50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses.The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern.The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description.Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index.Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
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