Fine-scale Dynamics Research Articles

A Small Nimble In Situ Fine-Scale Flux Method for Measuring Tree Stem Greenhouse Gas Emissions and Processes (S.N.I.F.F)

Tree stem methane emissions are gaining increasing attention as an overlooked atmospheric source pathway. Existing methods for measuring tree stem greenhouse gas fluxes and isotopes may provide robust integrated emission estimates, but due to their coarse resolution, the capacity to derive insights into fine-scale dynamics of tree stem emissions is limited. We demonstrate and field test an alternative method that is Small, Nimble, In situ and allows for Fine-scale Flux (‘SNIFF’) measurements, on complex and contrasting stem surfaces. It is lightweight and therefore suitable to remote field locations enabling real-time data observations allowing for field-based, data driven sampling regimes. This method facilitated novel results capturing fine-scale vertical and radial methane flux measurements (5 cm increments) and revealed: (1) 86–89% of methane emissions emanated from the lower 30 cm of sampled wetland tree species; (2) clear vertical and horizontal trends in δ13C-CH4 possibly due to fractionation associated with oxidation and/or mass-dependant fractionation during diffusive transport; and (3) the occurrence of substantial radial heterogeneity. We also compared a variety of up-scaling approaches to estimate methane flux per tree, including novel smartphone 3D photogrammetry that resulted in substantially higher stem surface area estimations (> 16 to 36%) than traditional empirical methods. Utilising small chambers with high radial and vertical resolution capabilities may therefore facilitate more robust future assessments into the drivers, pathways, oxidation sinks and magnitude of tree stem greenhouse gas emissions, and compliment previous broad-scale sampling techniques.

More Flexible Integration of Functional Systems After Musical Training in Young Adults.

Musical training, because it involves the interaction and integration of diverse functional systems, is an excellent model to investigate training-induced brain plasticity. The human brain functions in a network architecture in which dynamic modules and subgraphs are considered to enable efficient information communication. However, it remains largely unknown how the dynamic integration of functional systems changes with musical training, which may provide new insight into musical training-induced brain plasticity and further the use of music therapy for neuropsychiatric disease and brain injury. Here, 29 healthy young adult novices who received 24 weeks of piano training, and another 27 novices without any intervention were scanned at three time points-before and after musical training and 12 weeks after training. We used nonnegative matrix factorization to identify a set of subgraphs and their corresponding time-dependent coefficients from a concatenated functional network of all the subjects in sliding time windows. The energy and entropy of the time-dependent coefficients were computed to quantify the subgraph's dynamic changes in expression. The training group showed a significantly increased energy of the time-dependent coefficients of 3 subgraphs after training. Furthermore, one of the subgraphs, comprised of primary functional systems and cingulo-opercular task control and salience systems, showed significantly changed entropy in the training group after training. Our results suggest that the integration of functional systems undergoes increased flexibility in fine-scale dynamics after musical training, which reveals how brain functional systems engage in musical performance. The efficacy of musical training induced brain plasticity may provide new therapeutic strategies for brain injury and neuropsychiatric disorders.

Developing a longline/jig sentinel survey program for an area with limited monitoring and fishing efforts

Areas, such as coastal eastern Gulf of Maine (GOM), perceived to have low density of target fish species and having high density fixed gear, are often subject to low fishing pressure and not well monitored. This can lead to a shortage of information regarding the fine scale dynamics of groundfish populations. Sentinel surveys are commonly developed for such areas with little monitoring and commercial fishing activity as a cost effective way to collect relevant data for monitoring the dynamics of fish stocks. In this study, we outline an approach that utilizes information from other survey programs and pilot study for designing a survey that satisfies both the wish of fishermen participants to contribute their knowledge and experience in determining groundfish abundance and distribution and the statistical rigor required for stock assessments. Through an analysis of spatial and density distribution of groundfish populations based on data from pilot seasons of the sentinel survey and other monitoring programs, we designed a survey that has good spatial and temporal coverage and captures the spatial variability in species composition and size structure of key species. The spatially explicit data collected in the program can contribute to a better understanding of groundfish stock status in the eastern GOM. The approach, although developed for the coastal eastern GOM, is also applicable to other areas with similar issues.

Coastal Alaska forests under climate change: What to expect?

Coastal Alaska forests consist of 2.6 million hectares of productive timberland and constitute the largest terrestrial carbon reservoir in the state. It has become increasingly urgent to understand potential climate-induced changes in forest structural and species composition in this region. Based on in situ data from 544 permanent sample plots (PSPs) for calibration and 244 PSPs for validation, we developed a climate-sensitive density-dependent, species-, and size-specific matrix model (CSMatrix-AK), to predict fine-scale dynamics of coastal Alaska forests from the present to Year 2100 under three climate scenarios – Representative Concentration Pathway (RCP) 4.5, RCP6.0, and RCP8.5. With post-sample validation, we showed that the CSMatrix-AK model was more accurate than other existing models for the region. Under low-intensity and high-frequency stochastic shocks which represented natural disturbances typical for the region, we projected a gradual decline of Sitka spruce, a major commercial species in the region, and a significantly lower level of total stand basal area under all three climate scenarios. The results suggest that timber industry, landowners and managers, policymakers, and local communities will need to prepare for substantial impacts of climate change on Coastal Alaska forests and the regional forestry sector. Our CSMatrix-AK model provides a useful tool to better inform the stakeholders of such changes and lays the foundation for adaptive forest management to sustain forests and associated ecosystem services in the region.

Patchiness in old-growth oriental beech forests across development stages at multiple neighborhood scales

The patch mosaic–development stage model posits the unity of patches and development stages in primeval temperate forests and links patchiness to the synchronized, coarse-scale canopy senescence, and breakup processes that initiate the demographic transition to new regeneration patches that then asynchronously progress through sequential development stages. Subtle structural differences and inconsistent transitions among development stages observed in primeval forests such as Oriental beech (Fagus orientalis Lipsky) set expected coarse-scale canopy senescence against observed, predominantly fine-scale canopy-gap dynamics. Applying a multi-scale approach to quantify the extent to which stages are characterized by the interspersion of neighborhoods of variously sized trees (i.e., patch types), we investigated patchiness and structural differences in nine Oriental beech stands classified into Initial, Optimum, and Decay stages. Differences among stages in patch type richness and composition occurred primarily at the finest scales and diminished rapidly with increasing scale. Most patch types were ubiquitous and the few patch types unique to a particular stage occurred at very low abundances. Patch types composed of advance regeneration were most prevalent in the Initial stage, but were absorbed into the matrix structure at scales > 500 m2. In all three stages, the most heterogeneous patch type encompassed > 90% of all trees at scales > 100 m2. To portray fine-scale dynamics resulting in similar patch type compositions and structures across development stages, we introduce and discuss the new patch mosaic–gap reabsorption model that avoids the unity of patch and “demographic” stage to focus instead on “structural” stages.

Bilberry vs. cowberry in a scots pine boreal forest. II. Alternate modes of prediction

The bilberry-vs.-cowberry fine-scale dynamics has been modelled by a discrete Markov chain of transitions among the four observable statuses of permanent sample plots: bilberry (Vaccinium myrtillus) alone, cowberry (V. vitis-idaea) alone, both species, and species-free (Logofet and Maslov, 2019). Six successive examinations of spp. presence/absence on 20 × 20 cm quadrats located along permanent transects in a Scots pine boreal forest were initiated in 1980, 26 years after a forest fire in 1954, and repeated in every 5 years, thus scoping the 25 years of post-fire succession (Maslov, 1989). Those data have provided the exact calibration of 5 one-step transition matrices forming a nonautonomous Markov-chain model. Its basic prediction (forward forecast) has been obtained as the limiting distribution of states generated by the geometric average of transition matrices featured increase in the share species coexistence.Presented in this paper, the alternate modes of prediction are the validation forecast and the backward prediction. The former is implemented as the geometric average of the first 4 one-step matrices and its dominant eigenvector as the limiting distribution of quadrate states. It appears to hit a 5% vicinity of the distribution observed in 2005, thus certifying a success of model validation.As regards the backward prediction, I propose a technique that realizes the idea of backward prediction by means of reversing the time dimension in the observation data. The ensuing formula for the average backward transition matrix looks somewhat different from that for the forward one but enables calculating the matrix as reliable as the forward formula does. Although the 1955 distribution back-predicted from the observed 1980 one cannot be quantitatively interpreted as a community that might form just 1 year after the fire, it does qualitatively confirm (together with the backward limiting distribution) the directionality revealed earlier in the forward dynamics.

Frontiers in Fine-Scale in situ Studies: Opportunities During the SWOT Fast Sampling Phase

Conceived as a major new tool for climate studies, the Surface Water and Ocean Topography (SWOT) satellite mission will launch in late 2021 and will retrieve the dynamics of the oceans upper layer at an unprecedented resolution of a few kilometers. During the calibration and validation (CalVal) phase in 2022, the satellite will be in a 1-day-repeat fast sampling orbit with enhanced temporal resolution, sacrificing the spatial coverage. This is an ideal opportunity – unique for many years to come – to coordinate in situ experiments during the same period for a focused study of fine scale dynamics and their broader roles in the Earth system. Key questions to be addressed include the role of fine scales on the ocean energy budget, the connection between their surface and internal dynamics, their impact on plankton diversity, and their biophysical dynamics at the ice margin.

Bilberry vs. cowberry in a Scots pine boreal forest: Exclusion or coexistence in a post-fire succession?

Although the famous competition exclusion principle was thoroughly elaborated in the framework of multispecies population models, its illustrations with field data were facing certain obstacles. The data we deal with were collected by 6 consecutive examinations of bilberry (Vaccinium myrtillus) and cowberry (V. vitis-idaea) presence/absence in 20 × 20 cm quadrats located along permanent transects in a Scots pine boreal forest. These data feature a great sample size (2000 quadrats×6 examinations) and a 5-year interval for each pair of examination/re-examination, and the data have enabled us to construct a Markov chain model for the fine-scale dynamics of these dominant species at the later stages of post-fire succession. The discrete-time nonautonomous model consists of the five time-dependent, one-step transition matrices that describe changes occurring in the quadrat status for the 5 years in the following 4 terms: species-free quadrat; bilberry alone, cowberry alone, both species. Calibrated on the data, each one-step transition matrix transforms the current distribution of quadrats among their statuses exactly to the next one observed and yields a steady-state distribution as its (time-specific) positive eigenvector. Step-by-step variations in the elements of transition matrices do affect the components of the corresponding eigenvectors, but do not change the dominance relationships among them.Calculated as the 5-th power matrix root from the product of those five transition matrices (in the chronological order within their product), the geometric average, treated again as a transition matrix, provides for the spatial and temporal characteristics of the observed dynamics summarizing the whole observation period. We reveal the expected terminal stable outcome of species dynamics to be a distribution where 37% of quadrats are occupied by the bilberry alone, 11% by cowberry alone, 38% by the both species, and 14% be species-free. It is shown for the first time that the share of cowberry-alone quadrats decreases notably in the course of succession, whereas the share of species coexistence quadrats increase.The averaged characteristics of cyclicity and status duration in the fine-scale dynamics enable us to estimate the total time of the secondary post-fire succession as 46–50 years (till reaching a distribution close to the terminal one). Of the four statuses considered, the cowberry-alone quadrats have the least mean duration time (9 years), while the bilberry-and-cowberry quadrats have the longest time (18 years), which are explainable by different life spans of the shoots in proper species.

Fine-scale spatial and temporal dynamics of kdr haplotypes in Aedes aegypti from Mexico

BackgroundAs resistance to insecticides increases in disease vectors, it has become exceedingly important to monitor populations for susceptibility. Most studies of field populations of Aedes aegypti have largely characterized resistance patterns at the spatial scale of the city or country, which may not be completely informative given that insecticide application occurs at the scale of the house or city block. Phenotypic resistance to pyrethroids dominates in Ae. aegypti, and it has been partially explained by mutations in the voltage-gated sodium channel gene. Here, we assess community-level patterns of four knockdown resistance (kdr) haplotypes (C1534/I1016, F1534/I1016, C1534/V1016 and F1534/V1016) in Ae. aegypti in 24 randomly chosen city blocks from a city in Yucatán State, Mexico, during both the dry and wet season and over two years.ResultsThree of the four haplotypes, C1534/I1016, C1534/V1016 and F1534/V1016 were heterogeneous between city blocks at all four sampling time points, and the double mutant haplotype, C1534/I1016, showed a significant increase following the wet season. The F1534/I1016 haplotype was rarely detected, similar to other studies. However, when haplotype frequencies were aggregated to a coarser spatial scale, the differences in space and time were obscured.ConclusionsOur results provide empirical evidence that the selection of kdr alleles is occurring at fine spatial scales, indicating that future studies should include this scale to better understand evolutionary processes of resistance in natural populations.

Destabilization of an Oceanic Meddy-Like Vortex: Energy Transfers and Significance of Numerical Settings

Abstract The increase of computational capabilities led recent studies to implement very high-resolution simulations that gave access to new scale interaction processes, particularly those associated with the transfer of energy from the oceanic mesoscales to smaller scales through an interior route to dissipation, which is still underexplored. In this context, we study spindown simulations of a mesoscale interior vortex, unstable to a mixed baroclinic–barotropic instability. Even though the global energy is almost conserved, some energy is transferred down to dissipation scales during the development of instabilities. However, in our parameter regime, there is no substantial forward energy cascade sustained by unbalanced dynamics. Rather than exploring the physical parameter range, we clarify numerical discretization issues that can be detrimental to the physical solutions and our interpretation of finescale dynamics. Special care is given to determining the effective resolution of the different simulations. We improve it by a factor of 2 in our primitive equation (PE) finite-difference Coastal and Regional Ocean Community (CROCO) model by implementing a fifth-order accurate horizontal advection scheme. We also explore a range of grid aspect ratios dx/dz and find that energy spectra converge for aspect ratios that are close to N/f, the ratio of the stratification N over the Coriolis parameter f. However, convergence is not reached in the PE model when using a fourth-order centered scheme for vertical tracer advection (standard in ROMS-family codes). The scheme produces dispersion errors that trigger baroclinic instabilities and generate spurious submesoscale horizontal features. This spurious instability shows great impact on submesoscale production and energy cascade, emphasizing the significance of numerical settings in oceanic turbulence studies.

Analyzing the Fine-Scale Dynamics of Two Dominant Species in a Polytrichum–Myrtillus Pine Forest. I. A Homogeneous Markov Chain and Cyclicity Indices

Using long-term direct observations in a Polytrichum-Myrtillus pine forest, we have constructed and verified a homogeneous Markov chain model for two dominant species (Vaccinium myrtillus and V. vitis-idaed) at the late stages of succession. The sampling design features a large sample size (2000 quadrats) on permanent transects, several re-examinations with the interval of 5 years, and the use of species rooted frequency. As a model of the process under concern, the discrete Markov chain accounts for the following four states: both species being absent on the quadrat, one of them being present alone, and the joint presence of the both; the model time step coincides with the time interval between observations. The model is calibrated on the data of two successive examinations and verified on that of one more examination. All possible transitions between the states are revealed to realize in quadrats for one time interval, as well as the absence of transitions at each state, which results in the complete digraph (directed graph) of transitions. Major model results are obtained by the formulae of finite Markov chain theory: the steady-state square distribution, cyclicity characteristics, and the mean durations of stages in the fine-scale dynamics. As a steady-state (stable) outcome of succession, the distribution among quadrats is expected where 30% of quadrats are occupied by V. myrtillus alone, 11% by V. vitis-idaea alone, both species are present on 18% of quadrats, and 41% of quadrats are 'empty'. This demonstrates a possibility for V. myrtillus and V. vitis-idaea to coexist stably at the latest stages of succession, with the clear predominance of V. myrtillus, yet without competitive exclusion. The quantitative characteristics of cyclicity and the durations of stages in the fine-scale dynamics enable us to estimate the total duration of secondary post-fire succession as about 45 years (to reach a distribution of states that differs less than 5% from the steady-state one). Out of the four states specified, the quadrats with V. vitis-idaea alone persist for the least time (8 years) on the average, while 'empty' ones persist for the greatest time (18 years). Forecasting the dynamics for one model time step forward and comparing the forecast with the real square distribution have revealed the measure of difference to be 5.4%. This illustrates the efficiency of the (time-)homogeneous Markov chain as a short-term forecast tool, yet leaves open the question whether the homogeneity hypothesis be true in the longer term.

Antibiotics reduce genetic diversity of core species in the honeybee gut microbiome.

The gut microbiome plays a key role in animal health, and perturbing it can have detrimental effects. One major source of perturbation to microbiomes, in humans and human-associated animals, is exposure to antibiotics. Most studies of how antibiotics affect the microbiome have used amplicon sequencing of highly conserved 16S rRNA sequences, as in a recent study showing that antibiotic treatment severely alters the species-level composition of the honeybee gut microbiome. But because the standard 16S rRNA-based methods cannot resolve closely related strains, strain-level changes could not be evaluated. To address this gap, we used amplicon sequencing of protein-coding genes to assess effects of antibiotics on fine-scale genetic diversity of the honeybee gut microbiota. We followed the population dynamics of alleles within two dominant core species of the bee gut community, Gilliamella apicola and Snodgrassella alvi, following antibiotic perturbation. Whereas we observed a large reduction in genetic diversity in G.apicola, S.alvi diversity was mostly unaffected. The reduction in G.apicola diversity accompanied an increase in the frequency of several alleles, suggesting resistance to antibiotic treatment. We find that antibiotic perturbation can cause major shifts in diversity and that the extent of these shifts can vary substantially across species. Thus, antibiotics impact not only species composition, but also allelic diversity within species, potentially affecting hosts if variants with particular functions are reduced or eliminated. Overall, we show that amplicon sequencing of protein-coding genes, without clustering into operational taxonomic units, provides an accurate picture of the fine-scale dynamics of microbial communities over time.

Temporal changes in vegetation of a virgin beech woodland remnant: stand-scale stability with intensive fine-scale dynamics governed by stand dynamic events

The aim of this resurvey study is to check if herbaceous vegetation on the forest floor exhibits overall stability at the stand-scale in spite of intensive dynamics at the scale of individual plots and stand dynamic events (driven by natural fine scale canopy gap dynamics). In 1996, we sampled a 1.5 ha patch using 0.25 m² plots placed along a 5 m × 5 m grid in the best remnant of central European montane beech woods in Hungary. All species in the herbaceous layer and their cover estimates were recorded. Five patches representing different stand developmental situations (SDS) were selected for resurvey. In 2013, 306 plots were resurveyed by using blocks of four 0.25 m² plots to test the effects of imperfect relocation. We found very intensive fine-scale dynamics in the herbaceous layer with high species turnover and sharp changes in ground layer cover at the local-scale (< 1 m2). A decrease in species richness and herbaceous layer cover, as well as high species turnover, characterized the closing gaps. Colonization events and increasing species richness and herbaceous layer cover prevailed in the two newly created gaps. A pronounced decrease in the total cover, but low species turnover and survival of the majority of the closed forest specialists was detected by the resurvey at the stand-scale. The test aiming at assessing the effect of relocation showed a higher time effect than the effect of imprecise relocation. The very intensive fine-scale dynamics of the studied beech forest are profoundly determined by natural stand dynamics. Extinction and colonisation episodes even out at the stand-scale, implying an overall compositional stability of the herbaceous vegetation at the given spatial and temporal scale. We argue that fine-scale gap dynamics, driven by natural processes or applied as a management method, can warrant the survival of many closed forest specialist species in the long-run. Nomenclature: Flora Europaea (Tutin et al. 2010) for vascular plants; Soo 1968–1980 for syntaxa

Tree Circumference Dynamics in Four Forests Characterized Using Automated Dendrometer Bands.

Stem diameter is one of the most commonly measured attributes of trees, forming the foundation of forest censuses and monitoring. Changes in tree stem circumference include both irreversible woody stem growth and reversible circumference changes related to water status, yet these fine-scale dynamics are rarely leveraged to understand forest ecophysiology and typically ignored in plot- or stand-scale estimates of tree growth and forest productivity. Here, we deployed automated dendrometer bands on 12–40 trees at four different forested sites—two temperate broadleaf deciduous, one temperate conifer, and one tropical broadleaf semi-deciduous—to understand how tree circumference varies on time scales of hours to months, how these dynamics relate to environmental conditions, and whether the structure of these variations might introduce substantive error into estimates of woody growth. Diurnal stem circumference dynamics measured over the bark commonly—but not consistently—exhibited daytime shrinkage attributable to transpiration-driven changes in stem water storage. The amplitude of this shrinkage was significantly correlated with climatic variables (daily temperature range, vapor pressure deficit, and radiation), sap flow and evapotranspiration. Diurnal variations were typically <0.5 mm circumference in amplitude and unlikely to be of concern to most studies of tree growth. Over time scales of multiple days, the bands captured circumference increases in response to rain events, likely driven by combinations of increased stem water storage and bark hydration. Particularly at the tropical site, these rain responses could be quite substantial, ranging up to 1.5 mm circumference expansion within 48 hours following a rain event. We conclude that over-bark measurements of stem circumference change sometimes correlate with but have limited potential for directly estimating daily transpiration, but that they can be valuable on time scales of days to weeks for characterizing changes in stem growth and hydration.

Fine-Scale Genetic Structure and Reproductive Biology of the Blueberry Pathogen Monilinia vaccinii-corymbosi.

The fungus Monilinia vaccinii-corymbosi, a pathogen of Vaccinium spp., requires asexual and sexual spore production to complete its life cycle. A recent study found population structuring of M. vaccinii-corymbosi over a broad spatial scale in the United States. In this study, we examined fine-scale genetic structuring, temporal dynamics, and reproductive biology within a 125-by-132-m blueberry plot from 2010 to 2012. In total, 395 isolates of M. vaccinii-corymbosi were sampled from infected shoots and fruit to examine their multilocus haplotype (MLH) using microsatellite markers. The MLH of 190 single-ascospore isolates from 21 apothecia was also determined. Little to no genetic differentiation and unrestricted gene flow were detected among four sampled time points and between infected tissue types. Discriminant analysis of principal components suggested genetic structuring within the field, with at least K = 3 genetically distinct clusters maintained over four sampled time points. Single-ascospore progeny from eight apothecia had identical MLH and at least two distinct MLH were detected from 13 apothecia. Tests for linkage disequilibrium suggested that genetically diverse ascospore progeny were the product of recombination. This study supports the idea that the fine-scale dynamics of M. vaccinii-corymbosi may be complex, with genetic structuring, inbreeding, and outcrossing detected in the study area.

On the evolution of flow topology in turbulent Rayleigh-Bénard convection

Small-scale dynamics is the spirit of turbulence physics. It implicates many attributes of flow topology evolution, coherent structures, hairpin vorticity dynamics, and mechanism of the kinetic energy cascade. In this work, several dynamical aspects of the small-scale motions have been numerically studied in a framework of Rayleigh-Bénard convection (RBC). To do so, direct numerical simulations have been carried out at two Rayleigh numbers Ra = 108 and 1010, inside an air-filled rectangular cell of aspect ratio unity and π span-wise open-ended distance. As a main feature, the average rate of the invariants of the velocity gradient tensor (QG, RG) has displayed the so-called “teardrop” spiraling shape through the bulk region. Therein, the mean trajectories are swirling inwards revealing a periodic spin around the converging origin of a constant period that is found to be proportional to the plumes lifetime. This suggests that the thermal plumes participate in the coherent large-scale circulation and the turbulent wind created in the bulk. Particularly, it happens when the plumes elongate substantially to contribute to the large-scale eddies at the lower turbulent state. Supplementary small-scale properties, which are widely common in many turbulent flows have been observed in RBC. For example, the strong preferential alignment of vorticity with the intermediate eigenstrain vector, and the asymmetric alignment between vorticity and the vortex-stretching vector. It has been deduced that in a hard turbulent flow regime, local self-amplifications of straining regions aid in contracting the vorticity worms, and enhance the local interactions vorticity/strain to support the linear vortex-stretching contributions. On the other hand, the evolution of invariants pertained to the traceless part of velocity-times-temperature gradient tensor has also been considered in order to determine the role of thermals in the fine-scale dynamics. These new invariants show an incorporation of kinetic and thermal gradient dynamics that indicate directly the evolution and lifetime of thermal plume structures. By applying an identical approach, the rates of the new invariants have shown a symmetric cycling behaviour decaying towards two skew-symmetric converging origins at the lower Ra number. The trajectories near origins address the hot and cold coherent plumes that travel as an average large-scale heat flux in the sidewall vicinities, and denote a periodic spin period close to the plumes lifetime. At the hard turbulent case, the spiraling trajectories travel in shorter tracks to reveal the reduced lifetime of plumes under the dissipative and mixing effects. The turbulent background kinetic derivatives get self-amplified and the trajectories converge to a zero-valued origin indicating that there is no contribution from the plumes to the average coherent large scales of heat flux. These and other peculiar scrutinies on the small-scale motions in RBC have been enlightened, and may have a fruitful consequence on modelling approaches of buoyancy-driven turbulence.

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which can be linked to the continuum scale simulation. We illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.

Dynamics in benthic community composition and influencing factors in an upwelling-exposed coral reef on the Pacific coast of Costa Rica.

Seasonal upwelling at the northern Pacific coast of Costa Rica offers the opportunity to investigate the effects of pronounced changes in key water parameters on fine-scale dynamics of local coral reef communities. This study monitored benthic community composition at Matapalo reef (10.539°N, 85.766°W) by weekly observations of permanent benthic quadrats from April 2013 to April 2014. Monitoring was accompanied by surveys of herbivore abundance and biomass and measurements of water temperature and inorganic nutrient concentrations. Findings revealed that the reef-building corals Pocillopora spp. exhibited an exceptional rapid increase from 22 to 51% relative benthic cover. By contrast, turf algae cover decreased from 63 to 24%, resulting in a corresponding increase in crustose coralline algae cover. The macroalga Caulerpa sertularioides covered up to 15% of the reef in April 2013, disappeared after synchronized gamete release in May, and subsequently exhibited slow regrowth. Parallel monitoring of influencing factors suggest that C. sertularioides cover was mainly regulated by their reproductive cycle, while that of turf algae was likely controlled by high abundances of herbivores. Upwelling events in February and March 2014 decreased mean daily seawater temperatures by up to 7 °C and increased nutrient concentrations up to 5- (phosphate) and 16-fold (nitrate) compared to mean values during the rest of the year. Changes in benthic community composition did not appear to correspond to the strong environmental changes, but rather shifted from turf algae to hard coral dominance over the entire year of observation. The exceptional high dynamic over the annual observation period encourages further research on the adaptation potential of coral reefs to environmental variability.

A Hybrid Dynamical–Statistical Downscaling Technique. Part I: Development and Validation of the Technique

Abstract In this study (Part I), the mid-twenty-first-century surface air temperature increase in the entire CMIP5 ensemble is downscaled to very high resolution (2 km) over the Los Angeles region, using a new hybrid dynamical–statistical technique. This technique combines the ability of dynamical downscaling to capture finescale dynamics with the computational savings of a statistical model to downscale multiple GCMs. First, dynamical downscaling is applied to five GCMs. Guided by an understanding of the underlying local dynamics, a simple statistical model is built relating the GCM input and the dynamically downscaled output. This statistical model is used to approximate the warming patterns of the remaining GCMs, as if they had been dynamically downscaled. The full 32-member ensemble allows for robust estimates of the most likely warming and uncertainty resulting from intermodel differences. The warming averaged over the region has an ensemble mean of 2.3°C, with a 95% confidence interval ranging from 1.0° to 3.6°C. Inland and high elevation areas warm more than coastal areas year round, and by as much as 60% in the summer months. A comparison to other common statistical downscaling techniques shows that the hybrid method produces similar regional-mean warming outcomes but demonstrates considerable improvement in capturing the spatial details. Additionally, this hybrid technique incorporates an understanding of the physical mechanisms shaping the region’s warming patterns, enhancing the credibility of the final results.