Optimistic Optimization of Gaussian Process Samples

Bayesian optimization is a popular formalism for global optimization, but its computational costs limit it to expensive-to-evaluate functions. A competing, computationally more efficient, global optimization framework is optimistic optimization, which exploits prior knowledge about the geometry of the search space in form of a dissimilarity function. We investigate to which degree the conceptual advantages of Bayesian Optimization can be combined with the computational efficiency of optimistic optimization. By mapping the kernel to a dissimilarity, we obtain an optimistic optimization algorithm for the Bayesian Optimization setting with a run-time of up to $\mathcal{O}(N \log N)$. As a high-level take-away we find that, when using stationary kernels on objectives of relatively low evaluation cost, optimistic optimization can be strongly preferable over Bayesian optimization, while for strongly coupled and parametric models, good implementations of Bayesian optimization can perform much better, even at low evaluation cost. We argue that there is a new research domain between geometric and probabilistic search, i.e. methods that run drastically faster than traditional Bayesian optimization, while retaining some of the crucial functionality of Bayesian optimization.Comment: 10 pages, 6 figure

Organic Matter in the Surface Microlayer: Insights From a Wind Wave Channel Experiment

The surface microlayer (SML) is the uppermost thin layer of the ocean and influencing interactions between the air and sea, such as gas exchange, atmospheric deposition and aerosol emission. Organic matter (OM) plays a key role in air-sea exchange processes, but studying how the accumulation of organic compounds in the SML relates to biological processes is impeded in the field by a changing physical environment, in particular wind speed and wave breaking. Here, we studied OM dynamics in the SML under controlled physical conditions in a large annular wind wave channel, filled with natural seawater, over a period of 26 days. Biology in both SML and bulk water was dominated by bacterioneuston and -plankton, respectively, while autotrophic biomass in the two compartments was very low. In general, SML thickness was related to the concentration of dissolved organic carbon (DOC) but not to enrichment of DOC or of specific OM components in the SML. Pronounced changes in OM enrichment and molecular composition were observed in the course of the study and correlated significantly to bacterial abundance. Thereby, hydrolysable amino acids, in particular arginine, were more enriched in the SML than combined carbohydrates. Amino acid composition indicated that less degraded OM accumulated preferentially in the SML. A strong correlation was established between the amount of surfactants coverage and γ-aminobutric acid, suggesting that microbial cycling of amino acids can control physiochemical traits of the SML. Our study shows that accumulation and cycling of OM in the SML can occur independently of recent autotrophic production, indicating a widespread biogenic control of process across the air-sea exchange

Competition for nutrients and light: testing advances in resource competition with a natural phytoplankton community

A key challenge in ecology is to understand how nutrients and light affect the biodiversity and community structure of phytoplankton and plant communities. According to resource competition models, ratios of limiting nutrients are major determinants of species composition. At high nutrient levels, however, species interactions may shift to competition for light, which might make nutrient ratios less relevant. The "nutrient-load hypothesis" merges these two perspectives, by extending the classic model of competition for two nutrients to include competition for light. Here, we test five key predictions of the nutrient-load hypothesis using multispecies competition experiments. A marine phytoplankton community sampled from the North Sea was inoculated in laboratory chemostats provided with different nitrogen (N) and phosphorus (P) loads to induce either single resource limitation or co-limitation of N, P, and light. Four of the five predictions were validated by the experiments. In particular, different resource limitations favored the dominance of different species. Increasing nutrient loads caused changes in phytoplankton species composition, even if the N:P ratio of the nutrient loads remained constant, by shifting the species interactions from competition for nutrients to competition for light. In all treatments, small species became dominant whereas larger species were competitively excluded, supporting the common view that small cell size provides a competitive advantage under resource-limited conditions. Contrary to expectation, all treatments led to coexistence of diatoms, cyanobacteria and green algae, resulting in a higher diversity of species than predicted by theory. Because the coexisting species comprised three phyla with different photosynthetic pigments, we speculate that niche differentiation in the light spectrum might play a role. Our results show that mechanistic resource competition models that integrate nutrient-based and light-based approaches provide an important step forward to understand and predict how changing nutrient loads affect community composition

Towards representing thermokarst processes in land surface models

Large-scale Earth system and land surface models often lack an adequate representation of subgrid-scale processes in permafrost landscapes. Small-scale processes such as thermokarst formation might, however, considerably impact the energy and carbon budgets in way which is not resolved within large-scale models. Since a spatially high-resolved simulation of such processes is not feasible, novel techniques for up-scaling subgrid processes are demanded. Within this work a one-dimensional model of the ground thermal regime of land surfaces, CryoGrid 3, is employed to conceptually represent small-scale features of permafrost landscapes, particularly those related to thermokarst. For example, the model has been shown to adequately describe the degradation of permafrost underneath waterbodies in a warming climate. Using tiling approaches such point-wise realizations can be up-scaled in a statistical way in order to represent larger land surface units. The model development is closely linked to field campaigns to the Lena River Delta in Siberia which offers very diverse land surface features such as polygonal tundra and thermos-erosional valleys. These features are related to the region’s diverse soil stratigraphies, in particular the occurrence of ice-rich ground. Combining field measurements with modelling ultimately allows an improvement in the qualitative and quantitative understanding of the typical geomorphological processes in permafrost landscapes and their representation in large-scale models

Dynamics of organic matter and bacterial activity in the Fram Strait during summer and autumn

The Arctic Ocean is considerably affected by the consequences of global warming, including more extreme seasonal fluctuations in the physical environment. So far, little is known about seasonality in Arctic marine ecosystems in particular microbial dynamics and cycling of organic matter. The limited characterization can be partially attributed to logistic difficulties of sampling in the Arctic Ocean beyond the summer season. Here, we investigated the distribution and composition of dissolved organic matter (DOM), gel particles and heterotrophic bacterial activity in the Fram Strait during summer and autumn. Our results revealed that phytoplankton biomass influenced the concentration and composition of semi-labile dissolved organic carbon (DOC), which strongly decreased from summer to autumn. The seasonal decrease in bioavailability of DOM appeared to be the dominant control on bacterial abundance and activity, while no temperature effect was determined. Additionally, there were clear differences in transparent exopolymer particles (TEP) and Coomassie Blue stainable particles (CSP) dynamics. The amount of TEP and CSP decreased from summer to autumn, but CSP was relatively enriched in both seasons. Our study therewith indicates clear seasonal differences in the microbial cycling of organic matter in the Fram Strait. Our data may help to establish baseline knowledge about seasonal changes in microbial ecosystem dynamics to better assess the impact of environmental change in the warming Arctic Ocean

Agar Contact Method as a Valuable Tool to Identify Slaughter Hygiene Deficiencies along the Slaughter Process by Longitudinally Sampling Pig Skin Surfaces

Examinations of total viable counts (TVCs) and Salmonella spp. on the skin of individual pigs during the slaughter process are useful to identify abattoir-specific risk factors for (cross-)contamination. At seven process stages (lairage to before chilling), pigs were bacteriologically investigated by repeatedly sampling the same animals using the agar contact method. The mean TVC of all pigs increased significantly at the first three tested process stages (mean count, after delivery: 5.70 log cfu/cm2, after showering: 6.27 log cfu/cm2, after stunning: 6.48 log cfu/cm2). Significant mean TVC reductions occurred after scalding/dehairing (mean count: 3.71 log cfu/cm2), after singeing/flaming (2.70 log cfu/cm2), and after evisceration (2.44 log cfu/cm2) compared with the respective preceding process stages. At the end of the slaughter line and before chilling, the mean TVC was 2.33 log cfu/cm2, showing that the slaughter process reduced contamination significantly. The slaughter process effectively reduced even very high levels of incoming TVCs, since at the individual animal level, at the end of the slaughter process, there was no difference in the TVCs of animals with initially high and initially low TVCs. Additionally, 12 Salmonella spp. isolates were recovered from 12 different pigs, but only until the stage after scalding/dehairing. Overall, the agar contact method used is valuable for detecting hygiene deficiencies at slaughter, and is animal-equitable, practical, and suitable for use on live animals

From Ecological Stoichiometry to Biochemical Composition: Variation in N and P Supply Alters Key Biosynthetic Rates in Marine Phytoplankton

One of the major challenges in ecological stoichiometry is to establish how environmental changes in resource availability may affect both the biochemical composition of organisms and the species composition of communities. This is a pressing issue in many coastal waters, where anthropogenic activities have caused large changes in riverine nutrient inputs. Here we investigate variation in the biochemical composition and synthesis of amino acids, fatty acids (FA), and carbohydrates in mixed phytoplankton communities sampled from the North Sea. The communities were cultured in chemostats supplied with different concentrations of dissolved inorganic nitrogen (DIN) and phosphorus (DIP) to establish four different types of resource limitations. Diatoms dominated under N-limited, N+P limited and P-limited conditions. Cyanobacteria became dominant in one of the N-limited chemostats and green algae dominated in the one P-limited chemostat and under light-limited conditions. Changes in nutrient availability directly affected amino acid content, which was lowest under N and N+P limitation, higher under P-limitation and highest when light was the limiting factor. Storage carbohydrate content showed the opposite trend and storage FA content seemed to be co-dependent on community composition. The synthesis of essential amino acids was affected under N and N+P limitation, as the transformation from non-essential to essential amino acids decreased at DIN:DIP ≤ 6. The simple community structure and clearly identifiable nutrient limitations confirm and clarify previous field findings in the North Sea. Our results show that different phytoplankton groups are capable of adapting their key biosynthetic rates and hence their biochemical composition to different degrees when experiencing shifts in nutrient availability. This will have implications for phytoplankton growth, community structure, and the nutritional quality of phytoplankton as food for higher trophic levels

Language learning and teaching with Swedish FrameNet++ : Two examples

Peer reviewe

Brief communication: Unravelling the composition and microstructure of a permafrost core using X-ray computed tomography

The microstructure of permafrost ground contains clues to its formation and hence its preconditioning to future change. We applied X-ray computed microtomography (CT) to obtain high-resolution data (Δx=50 µm) of the composition of a 164 cm long permafrost core drilled in a Yedoma upland in north-eastern Siberia. The CT analysis allowed the microstructures to be directly mapped and volumetric contents of excess ice, gas inclusions, and two distinct sediment types to be quantified. Using laboratory measurements of coarsely resolved core samples, we statistically estimated the composition of the sediment types and used it to indirectly quantify volumetric contents of pore ice, organic matter, and mineral material along the core. We conclude that CT is a promising method for obtaining physical properties of permafrost cores which opens novel research potentials