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Long- and short-term monitoring of a dam in response to seasonal changes and ground motion loading
(2021)
An experimental multi-parameter structural monitoring system has been installed on the Kurpsai dam, western Kyrgyz Republic. This system consists of equipment for seismic and strain measurements for making longer- (days, weeks, months) and shorter- (minutes, hours) term observations, dealing with, for example seasonal (longer) effects or the response of the dam to ground motion from noise or seismic events. Fibre-optic strain sensors allow the seasonal and daily opening and closing of the spaces between the dam's segments to be tracked. For the seismic data, both amplitude (in terms of using differences in amplitudes in the Fourier spectra for mapping the modes of vibration of the dam) and their time-frequency distribution for a set of small to moderate seismic events are investigated and the corresponding phase variabilities (in terms of lagged coherency) are evaluated. Even for moderate levels of seismic-induced ground motion, some influence on the structural response can be detected, which then sees the dam quickly return to its original state. A seasonal component was identified in the strain measurements, while levels of noise arising from the operation of the dam's generators and associated water flow have been provisionally identified.
Lost in Germania
(2021)
Tacitus’ Germania is notable for its absences: lacking a preface and programmatic statements, and being the only ethnographic monograph to have survived from Greco-Roman antiquity, readers have often leapt to fill in its perceived blanks. This chapter aims at redressing the effects of overdetermined readings by interpreting the text’s absences as significant in their own right.
Centroid moment tensor (CMT) parameters can be estimated from seismic waveforms. Since these data indirectly observe the deformation process, CMTs are inferred as solutions to inverse problems which are generally underdetermined and require significant assumptions, including assumptions about data noise. Broadly speaking, we consider noise to include both theory and measurement errors, where theory errors are due to assumptions in the inverse problem and measurement errors are caused by the measurement process. While data errors are routinely included in parameter estimation for full CMTs, less attention has been paid to theory errors related to velocity-model uncertainties and how these affect the resulting moment-tensor (MT) uncertainties. Therefore, rigorous uncertainty quantification for CMTs may require theory-error estimation which becomes a problem of specifying noise models. Various noise models have been proposed, and these rely on several assumptions. All approaches quantify theory errors by estimating the covariance matrix of data residuals. However, this estimation can be based on explicit modelling, empirical estimation and/or ignore or include covariances. We quantitatively compare several approaches by presenting parameter and uncertainty estimates in nonlinear full CMT estimation for several simulated data sets and regional field data of the M-1 4.4, 2015 June 13 Fox Creek, Canada, event. While our main focus is at regional distances, the tested approaches are general and implemented for arbitrary source model choice. These include known or unknown centroid locations, full MTs, deviatoric MTs and double-couple MTs. We demonstrate that velocity-model uncertainties can profoundly affect parameter estimation and that their inclusion leads to more realistic parameter uncertainty quantification. However, not all approaches perform equally well. Including theory errors by estimating non-stationary (non-Toeplitz) error covariance matrices via iterative schemes during Monte Carlo sampling performs best and is computationally most efficient. In general, including velocity-model uncertainties is most important in cases where velocity structure is poorly known.
Successful conservation efforts have led to recent increases of large mammals such as European bison Bison bonasus, moose Alces alces and grey wolf Canis lupus and their return to former habitats in central Europe.
While embraced by some, the recovery of these species is a controversial topic and holds potential for human-wildlife conflicts.
Involving the public has been suggested to be an effective method for monitoring wildlife and mitigating associated conflicts.
To assess two interrelated prerequisites for engaging people in Citizen Science (CS)-knowledge of returning species and respondents' readiness to participate in CS activities for monitoring and managing these species-we conducted a survey (questionnaire) in two wildlife parks located in different states of Germany.
Based on 472 complete questionnaires, we developed generalized linear models to understand how sociodemographic variables and exposure to the species affected visitors' knowledge of each species, and to investigate if sociodemographic variables and knowledge influenced the likelihood of visitors to participate in CS activities.
Almost all visitors were aware of the returning wolf population, while knowledge and awareness about bison and moose were significantly lower.
Knowledge of the two herbivores differed geographically (higher knowledge of moose in the north-eastern state), possibly indicating a positive association between exposure to the species and knowledge.
However, models generally performed poorly in predicting knowledge about wildlife, suggesting that such specific knowledge is insufficiently explained by sociodemographic variables. Our model, which explained stated willingness in CS indicated that younger participants and those with higher knowledge scores in the survey were more willing to engage in CS activities.
Overall, our analyses highlight how exposure to large mammals, knowledge about wildlife and human demographics are interrelated-insights that are helpful for effectively recruiting citizen scientists for wildlife conservation.
Read the free Plain Language Summary for this article on the Journal blog.
This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system.
Fatty acids are widely used to study trophic interactions in food web assemblages. Generally, it is assumed that there is a very small modification of fatty acids from one trophic step to another, making them suitable as trophic biomarkers. However, recent literature provides evidence that many fishes possess genes encoding enzymes with a role in bioconversion, thus the capability for bioconversion might be more widespread than previously assumed. Nonetheless, empirical evidence for biosynthesis occurring in natural populations remains scarce. In this study, we investigated different feeding types of perch (Perca fluviatilis) that are specialized on specific resources with different levels of highly unsaturated fatty acids (HUFAs), and analyzed the change between HUFA proportions in perch muscle tissue compared to their resources. Perch showed matching levels to their resources for EPA, but ARA and especially DHA were accumulated. Compound-specific stable isotope analyses helped us to identify the origin of HUFA carbon. Our results suggest that perch obtain a substantial amount of DHA via bioconversion when feeding on DHA-poor benthic resources. Thus, our data indicate the capability of bioconversion of HUFAs in a natural freshwater fish population.
Circular economy
(2021)
In a circular economy, the use of recycled resources in production is a key performance indicator for management. Yet, academic studies are still unable to inform managers on appropriate recycling and pricing policies. We develop an optimal control model integrating a firm's recycling rate, which can use both virgin and recycled resources in the production process. Our model accounts for recycling influence both at the supply- and demandsides. The positive effect of a firm's use of recycled resources diminishes over time but may increase through investments. Using general formulations for demand and cost, we analytically examine joint dynamic pricing and recycling investment policies in order to determine their optimal interplay over time. We provide numerical experiments to assess the existence of a steady-state and to calculate sensitivity analyses with respect to various model parameters. The analysis shows how to dynamically adapt jointly optimized controls to reach sustainability in the production process. Our results pave the way to sounder sustainable practices for firms operating within a circular economy.
Cirrus is the only cloud type capable of inducing daytime cooling or heating at the top of the atmosphere (TOA) and the sign of its radiative effect highly depends on its optical depth. However, the investigation of its geometrical and optical properties over the Arctic is limited. In this work the long-term properties of cirrus clouds are explored for the first time over an Arctic site (Ny-Alesund, Svalbard) using lidar and radiosonde measurements from 2011 to 2020. The optical properties were quality assured, taking into account the effects of specular reflections and multiple-scattering. Cirrus clouds were generally associated with colder and calmer wind conditions compared to the 2011-2020 climatology. However, the dependence of cirrus properties on temperature and wind speed was not strong. Even though the seasonal cycle was not pronounced, the winter-time cirrus appeared under lower temperatures and stronger wind conditions. Moreover, in winter, geometrically- and optically-thicker cirrus were found and their ice particles tended to be more spherical. The majority of cirrus was associated with westerly flow and westerly cirrus tended to be geometrically-thicker. Overall, optically-thinner layers tended to comprise smaller and less spherical ice crystals, most likely due to reduced water vapor deposition on the particle surface. Compared to lower latitudes, the cirrus layers over Ny-Alesund were more absorbing in the visible spectral region and they consisted of more spherical ice particles.
MALDI-TOF-MS-based identification of monoclonal murine Anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
Ancient genome provides insights into the history of Eurasian lynx in Iberia and Western Europe
(2022)
The Eurasian lynx (Lynx lynx) is one of the most widely distributed felids in the world. However, most of its populations started to decline a few millennia ago. Historical declines have been especially severe in Europe, and particularly in Western Europe, from where the species disappeared in the last few centuries. Here, we analyze the genome of an Eurasian lynx inhabiting the Iberian Peninsula 2500 ya, to gain insights into the phylogeographic position and genetic status of this extinct population. Also, we contextualize previous ancient data in the light of new phylogeographic studies of the species. Our results suggest that the Iberian population is part of an extinct European lineage closely related to the current Carpathian-Baltic lineages. Also, this sample holds the lowest diversity reported for the species so far, and similar to that of the highly endangered Iberian lynx. A combination of historical factors, such as a founder effect while colonizing the peninsula, together with intensified human impacts during the Holocene in the Cantabrian strip, could have led to a genetic impoverishment of the population and precipitated its extinction. Mitogenomic lineages distribution in space and time support the long-term coexistence of several lineages of Eurasian lynx in Western Europe with fluctuating ranges. While mitochondrial sequences related to the lineages currently found in Balkans and Caucasus were predominant during the Pleistocene, those more closely related to the lineage currently distributed in Central Europe prevailed during the Holocene. The use of ancient genomics has proven to be a useful tool to understand the biogeographic pattern of the Eurasian lynx in the past.
The water vapor-induced swelling, as well as subsequent phase-transition kinetics, of thin films of a diblock copolymer (DBC) loaded with different amounts of the salt NaBr, is investigated in situ. In dilute aqueous solution, the DBC features an orthogonally thermoresponsive behavior. It consists of a zwitterionic poly(sulfobetaine) block, namely, poly(4-(N-(3'-methacrylamidopropyl)-N, N-dimethylammonio) butane-1-sulfonate) (PSBP), showing an upper critical solution temperature, and a nonionic block, namely, poly(N-isopropylmethacrylamide) (PNIPMAM), exhibiting a lower critical solution temperature. The swelling kinetics in D2O vapor at 15 degrees C and the phase transition kinetics upon heating the swollen film to 60 degrees C and cooling back to 15 degrees C are followed with simultaneous time-of-flight neutron reflectometry and spectral reflectance measurements. These are complemented by Fourier transform infrared spectroscopy. The collapse temperature of PNIPMAM and the swelling temperature of PSBP are found at lower temperatures than in aqueous solution, which is attributed to the high polymer concentration in the thin-film geometry. Upon inclusion of sub-stoichiometric amounts (relative to the monomer units) of NaBr in the films, the water incorporation is significantly increased. This increase is mainly attributed to a salting-in effect on the zwitterionic PSBP block. Whereas the addition of NaBr notably shifts the swelling temperature of PSBP to lower temperatures, the collapse temperature of PNIPMAM remains unaffected by the presence of salt in the films.
Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators. Influencer networks include a small set of highly-connected nodes and can reach synchrony only via strong node interaction. Tonjes et al. show that introducing an optimal amount of noise enhances synchronization of such networks, which may be relevant for neuroscience or opinion dynamics applications.
The mean free path of ionizing photons, lambda(mfp), is a key factor in the photoionization of the intergalactic medium (IGM). At z greater than or similar to 5, however, lambda(mfp) may be short enough that measurements towards QSOs are biased by the QSO proximity effect. We present new direct measurements of lambda(mfp) that address this bias and extend up to z similar to 6 for the first time. Our measurements at z similar to 5 are based on data from the Giant Gemini GMOS survey and new Keck LRIS observations of low-luminosity QSOs. At z similar to 6 we use QSO spectra from Keck ESI and VLT X-Shooter. We measure lambda(mfp) = 9.09(-1.28)(+1.62) proper Mpc and 0.75(-0.45)(+0.65) proper Mpc (68 percent confidence) at z = 5.1 and 6.0, respectively. The results at z = 5.1 are consistent with existing measurements, suggesting that bias from the proximity effect is minor at this redshift. At z = 6.0, however, we find that neglecting the proximity effect biases the result high by a factor of two or more. Our measurement at z = 6.0 falls well below extrapolations from lower redshifts, indicating rapid evolution in lambda(mfp) over 5 < z < 6. This evolution disfavours models in which reionization ended early enough that the IGM had time to fully relax hydrodynamically by z = 6, but is qualitatively consistent with models wherein reionization completed at z = 6 or even significantly later. Our mean free path results are most consistent with late reionization models wherein the IGM is still 20 percent neutral at z = 6, although our measurement at z = 6.0 is even lower than these models prefer.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
The understanding of bidimensional materials dynamics and its electrolyte interface equilibrium, such as graphene oxide (GO), is critical for the development of a capacitive biosensing platform. The interfacial capacitance (C-i) of graphene-based materials may be tuned by experimental conditions such as pH optimization and cation size playing key roles at the enhancement of their capacitive properties allowing their application as novel capacitive biosensors. Here we reported a systematic study of C-i of multilayer GO films in different aqueous electrolytes employing electrochemical impedance spectroscopy for the application in a capacitive detection system. We demonstrated that the presence of ionizable oxygen-containing functional groups within multilayer GO film favors the interactions and the accumulation of cations in the structure of the electrodes enhancing the GO C-i in aqueous solutions, where at pH 7.0 (the best condition) the C-i was 340 mu F mg(-1) at -0.01 V vs Ag/AgCl. We also established that the hydrated cation radius affects the mobility and interaction with GO functional groups and it plays a critical role in the Ci, as demonstrated in the presence of different cations Na+=640 mu F mg(-1), Li+=575 mu F mg(-1) and TMA(+)=477 mu F mg(-1). As a proof-of-concept, the capacitive behaviour of GO was explored as biosensing platform for standard streptavidin-biotin systems. For this system, the C-i varied linearly with the log of the concentration of the targeting analyte in the range from 10 pg mL(-1) to 100 ng mL(-1), showing the promising applicability of capacitive GO based sensors for label-free biosensing.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.