Resonant hierarchies: a multiscale framework for oscillatory dynamics in the brain

Subtropical mode waters (STWMs) are water masses formed in winter by convective mixing on the equatorward side of western boundary currents in the subtropical gyres. After the return of the seasonal stratification in spring, it is found at the stratification minimum between the seasonal and main pycnoclines. By characterizing STMW primarily at the density gradient minimum, previous studies were limited in their ability to describe STMW properties over large temporal and spatial scales. Rather than using a density-based characterization, the North Atlantic STMW layer was identified here by its much smaller temperature gradient relative to the more stratified seasonal and main thermocline, its temperature, and its large thickness. By using this temperature-based characterization, this study was able to develop a climatology using the large number of XBTs deployed between 1968 and 1988 and contained in the World Ocean Atlas 1994 historical hydrographic database and to use this climatology to examine STMW properties on large spatial and long temporal scales. Three different characterizations were used to assess the degree of convective renewal of the STMW layer during the 1968–88 winters. Two characterizations were based on comparing the winter mixed layer properties to the STMW layer properties in the previous fall, while the third characterization involved comparing the temperature gradient through the STMW layer in the spring to the STMW layer temperature gradient in the previous fall. Based on these characterizations, there was considerable spatial and temporal variability in the renewal of the STMW layer's vertical homogeneity from 1968 to 1988. Basinwide renewal occurred in 1969, 1970, 1977, 1978, 1981, and 1985, with more localized renewal, usually east of 55°W, in the other years. While STMW is nearly vertically homogeneous immediately after renewal, the temperature gradient through the layer increases with time following renewal. The annual rate of increase in the temperature gradient in the year following renewal is ∼5–6 (× 10−4°C per 100 m per day), while the interannual rate of increase is ∼2.0 × 10−4°C per 100 m per day following winters with no renewal of the STMW layer.

Enhancing soil carbon storage for carbon remediation: potential contributions and constraints by microbes

8 Marine Technology Unit (UTM-CSIC), Passeig Maritim de la Barceloneta 37-49, 08003 Barcelona, Spain ABSTRACT: An important aspect of marine research is to quantify the areal coverage of benthic communities. It is technically feasible to efficiently obtain images of marine environments at differ- ent depths and benthic habitats over large spatial and temporal scales. Currently, there is a large and growing library of digital images to analyze, representing a valuable benthic ecological archive. Benthic coverage is the basis of studies on biodiversity, characterization of communities and evaluation of changes over temporal and spatial scales. However, there is still a lack of auto- matic or semi-automatic analytical methods for deriving ecologically relevant data from these images. We introduce a software program named Seascape to obtain semi-automatically seg- mented images (patch outlines) from underwater photographs of benthic communities, where each individual patch (species/categories) is routinely associated to its area cover and perimeter. Seascape is an analog to the classical and better known discipline of landscape ecology approach, which focuses on the concept that communities can be observed as a patch mosaic at any scale. The process starts with a hierarchical segmentation, using a color space criteria adapted to the problem of segmenting complex benthic images. As an endproduct, we obtain a set of images segmented into classified homogenous regions at different resolution levels (hierarchical seg - mentation). To illustrate the versatility and capacity of Seascape, we analyzed 4 digital images from different habitats and depths: coral reefs (Pacific Ocean), coralligenous communities (NW Mediterranean Sea), deep-water coral reefs (NW Mediterranean Sea) and the Antarctic continental shelf (Weddell Sea). The development of this semi-automatic outline tool and its use for classifica- tion constitute an important step forward in the analysis and processing time of underwater seabed images at any scale.

The relative impact of top-down control by herbivores and bottom-up control by environmental conditions on vegetation is a subject of debate in ecology. In this study, we hypothesize that top-down control by goose foraging and bottom-up control by sediment accretion on vegetation composition within an ecosystem can co-occur but operate at different spatial and temporal scales. We used a highly dynamic marsh system with a large population of the Greylag goose (Anser anser) to investigate the potential importance of spatial and temporal scales on these processes. At the local scale, Greylag geese grub for below-ground storage organs of the vegetation, thereby creating bare patches of a few square metres within the marsh vegetation. In our study, such activities by Greylag geese allowed them to exert top-down control by setting back vegetation succession. However, we found that the patches reverted back to the initial vegetation type within 12 years. At large spatial (i.e. several square kilometres) and temporal scales (i.e. decades), high rates of sediment accretion surpassing the rate of local sea-level rise were found to drive long-term vegetation succession and increased cover of several climax vegetation types. In summary, we conclude that the vegetation composition within this tidal marsh was primarily controlled by the bottom-up factor of sediment accretion, which operates at large spatial as well as temporal scales. Top-down control exerted by herbivores was found to be a secondary process and operated at much smaller spatial and temporal scales.

In opportunistic networking, characterizing contact patterns between mobile users is essential for assessing feasibility and performance of opportunistic applications. There has been significant efforts in deriving this characterization, based on observations and trace analyses; however, most of the findings arise from studying contact opportunities at large spatial and temporal scales. Moreover, the user population is considered to be constant: no users can join or leave the system. Yet, there are many examples of scenarios which do not fully adhere to the previous assumption and cannot be accurately described at large scales. Urban environments, such as smaller city districts, are characterized by highly dynamic user populations. We believe that scenarios with varying population requires further investigation. In this paper, we present a novel modeling approach to study operation of opportunistic applications in scenarios where the population size is subjected to frequent changes, that is, it exhibits churn. We also propose an application for estimating the size of a mobile crowd, which we then use to validate our model in four scenarios: a city area, subway station, a conference and a scenario with a synthetic mobility model. We show that the model provides good representations of the investigated scenarios.

Monitoring biodiversity over large spatial and temporal scales is crucial to assess the impact of global changes and environmental mitigation measures. However, large-scale monitoring of invertebrates remains poorly developed despite the importance of these organisms in ecosystem functioning. The development of new recording techniques and new methods of automatic species recognition based on sound detection and easily applicable within a citizen-science framework, offers interesting possibilities. However, the value of such protocols has not been tested for the study of temporal trends on a large spatial scale.We used an acoustic region-wide citizen-monitoring program of Orthoptera, conducted along roads, to assess the relevance of automatic species recognition methods to detect temporal trends while taking into account spatial and seasonal patterns of two Orthoptera species activity (Tettigonia viridissima Linnaeus, 1758, and Ruspolia nitidula Scopoli, 1786) at a large scale. Additionally, we tested the effect of climate and land-use variables on spatio-temporal abundance patterns using generalized linear mixed models. We found negative temporal trends for the two species across the survey period (2006–2012). The spatial variations were largely explained by the geoclimatic conditions and, to a lesser extent, by land use (negative effects of urbanization). The temporal variations were highly correlated to the climatic conditions of the year, and of the previous year (nonlinear effect of temperature, precipitation).To our knowledge, this paper describes the first successful attempt to calculate large-scale temporal trends of insect populations on the basis of an automatic identification process of acoustic data. We argue that acoustic monitoring along roads, coupled with the automatic recognition of species sounds, offers several advantages for assessing Orthoptera biodiversity response to global changes and environmental measures.

Biodiversity monitoring at large spatial and temporal scales is greatly needed in the context of global changes. Although insects are a species-rich group and are important for ecosystem functioning, they have been largely neglected in conservation studies and policies, mainly due to technical and methodological constraints. Sound detection, a nondestructive method, is easily applied within a citizen-science framework and could be an interesting solution for insect monitoring. However, it has not yet been tested at a large scale. We assessed the value of a citizen-science program in which Orthoptera species (Tettigoniidae) were monitored acoustically along roads. We used Bayesian model-averaging analyses to test whether we could detect widely known patterns of anthropogenic effects on insects, such as the negative effects of urbanization or intensive agriculture on Orthoptera populations and communities. We also examined site-abundance correlations between years and estimated the biases in species detection to evaluate and improve the protocol. Urbanization and intensive agricultural landscapes negatively affected Orthoptera species richness, diversity, and abundance. This finding is consistent with results of previous studies of Orthoptera, vertebrates, carabids, and butterflies. The average mass of communities decreased as urbanization increased. The dispersal ability of communities increased as the percentage of agricultural land and, to a lesser extent, urban area increased. Despite changes in abundances over time, we found significant correlations between yearly abundances. We identified biases linked to the protocol (e.g., car speed or temperature) that can be accounted for ease in analyses. We argue that acoustic monitoring of Orthoptera along roads offers several advantages for assessing Orthoptera biodiversity at large spatial and temporal extents, particularly in a citizen science framework.

In situ filtering rate variability in egg and larval surveys off the Pacific coast of Japan: Do plankton nets clog or over-filter in the sea?

Understanding drivers and monitoring changes of biodiversity forms the basis for evidence-based management and policy recommendations that aim to reduce biodiversity loss and to ensure the delivery of ecosystem services on which we rely. Ecoacoustic monitoring can be applied across large spatial and temporal scales, offering the potential for less resource-intensive ecosystem monitoring. Indices of acoustic diversity have been shown to correlate with species richness of various taxa, as well as vegetation and landscape structure. In order to apply ecoacoustic monitoring at large scales we need to improve our understanding of the effects of local and regional land-use on acoustic patterns, and assess how temporal aspects of acoustic patterns can be integrated in these analyses. We hypothesized that land-use intensity and landscape structure affect species richness and composition of birds and orthopteran, and therefore indirectly affect acoustic diversity and composition. To test this, we set up autonomous recording systems in grassland plots along land-use intensity gradients in three regions in Germany. We applied structural equation modelling to analyze the direct and indirect drivers of acoustic diversity and composition, including mowing and grazing intensities, landscape diversity, distance to the nearest road, vascular plant species richness as well as bird and orthopteran species richness and composition. Single indices of acoustic diversity did not reflect changes in bird or orthopteran species richness, making them poor predictors for local land-use related changes in species richness in grassland plots. Acoustic composition (non-metric multidimensional scaling combination of mean monthly acoustic indices at different day phases), however, did relate to differences in landscape structure, land-use intensity, vocalizing species composition and orthopteran species richness. We propose the developed acoustic composition metric as suitable proxy to detect ecosystem changes in grasslands.

Laboratory-scale evaluation of algaecide effectiveness for control of microcystin-producing cyanobacteria from Lake Okeechobee, Florida (USA)

Community ecology and ecosystem ecology seem to have existed in different worlds. Levin (1989) suggests that the gulf between the two is the consequence of the different historical traditions in each. Community ecology, for example, emerged from basic studies, where generalized patterns were sought in the natural interactions among the biota. From the outset, the goal has been to deduce general and simple theory. On the other hand, many of the modelling approaches developed to understand ecosystem dynamics emerged from specific applied problems, where not only biotic but abiotic and human disturbances transformed ecosystem function. That tradition, therefore, is often more complete, but at the price of producing a collection of complex specific examples from which generalization is difficult.

Understanding species' responses to climate change is a critical challenge facing biologists today. Though many species are widespread, few studies of climate-driven shifts in flowering time have examined large continuous spatial scales for individual species. And even fewer studies have examined these shifts at time scales greater than a few decades. We used digitized herbarium specimens and PRISM climate data to produce the spatially and temporally broadest-scale study of flowering time in a single species to date, spanning the contiguous United States and 153 years (1863-2016) for a widespread weedy annual, Triodanis perfoliata (Campanulaceae). We examined factors driving phenological shifts as well as the roles of geographic and temporal scale in understanding these trends. Year was a significant factor in both geospatial and climatic analyses, revealing that flowering time has advanced by ~9 days over the past ~150 years. We found that temperature as well as vapor pressure deficit, an understudied climatic parameter associated with evapotranspiration and water stress, were strongly associated with peak flowering. We also examined how sampling at different spatiotemporal scales influences the power to detect flowering-time shifts, finding that relatively large spatial and temporal scales are ideal for detecting flowering-time shifts in this widespread species. Our results emphasize the importance of understanding the interplay of geospatial factors at different scales to examine how species respond to climate change.

The source characteristics of slow and fast earthquakes can help us interpret the evolution of the mechanics that govern the seismic cycle. The variability of source characteristics can be observed along different tectonic regimes such as strike-slip faults vs megathrusts, across different time scales like earthquakes and slow-slip events. However, on a regional scale, the local tectonic setting can have a significant impact on these parameters as observed in Central Pamir region. In this thesis, I aim to study source parameters of seismic and aseismic events and the impact of the aforementioned spatial and temporal scales on these source parameters. I catalogued 109 slip distributions from 52 earthquakes and 17 slow-slip events on thrust and strike-slip faults in various tectonic settings around the world with slip distributions constrained by geodesy in combination with other data. The width, potency, and potency density of slow and fast earthquakes were determined based on static slip distributions. I define and derive potency density as a ratio of the average slip to the rupture radius, to use as a measure of anelastic deformation unbiased by assumptions regarding the elastic properties of the surrounding medium. From the analysis of the catalogued events, it is observed that strike-slip earthquakes had the highest potency densities amongst all the events while slow slip events(SSE) had the lowest potency densities. Among megathrust events, continental thrust earthquakes and Tsunami earthquakes showed much higher potency densities as well as centroid depths compared to their deeper subduction counterparts with SSEs being the deepest events. The tendency of rupture characteristics to vary with fault type and centroid depth provides a prognosis for future slow and fast earthquakes. To better understand the effect of regional tectonics on specific earthquakes, I focus on the 2015 Mw 7.2 Lake Sarez earthquake sequence that occurred in Tajikistan. The mainshock was the largest crustal event to occur in this region in the past century. The event showed three significant segments along strike that were constrained by pixel-offset tracking of Sentinel-1A SAR imagery. Joint inversion of geodetic and teleseismic waveform data indicated a unilateral rupture towards the northeast. With a rupture speed of ∼3 km/s, a significant portion of the seismic moment distributed at depths < 10 km. To better understand the regional stresses, I estimated the focal mechanisms of 59 aftershocks using regional broadband data. Approximately two-thirds of the aftershocks were strike-slip earthquakes with depths ranging from 10 to 22 km, consistent with the mainshock. The remaining aftershocks exhibited oblique-normal or thrust components, highlight- ing the role of smaller faults in accommodating both the east-west extensional and the north-south compressional tectonic loading. This event helped shed light on a previously unknown fault cutting through the Pamir Plateau. Along with an analysis of the recent seismicity in the Pamir region, I attempt to understand the large-scale tectonics of the Pamir region from a geomorphic and geologic perspective. In chapter 4, I present a detailed analysis of fault traces in and around the Pamir Plateau mapped on high-resolution satellite imagery. I focus on the major fault systems such as the Karakoram, the Main Pamir Thrust, the Darvaz fault, and the Chaman Fault systems and on how these fault systems interact with the Sarez Karakul fault. We also map river and moraine offsets which help constrain the location as well as the slip rate on the fault. Preliminary discrete element analysis of the region was able to reproduce the major fault systems along with the new fault mapped by us, thus highlighting the importance of the new Sarez-Karakul fault in accommodating the overall tectonic stresses of the region.

Detrended fluctuation analysis (DFA) and power spectrum density are applied to verify the presence of temporal scaling behavior and long-range persistence (LRP) of weekly hydrogen ion deposition (WHD), NO3- and SO42- deposition series in National Atmospheric Deposition Program, USA, for the period 1978–2001. The results show a common scaling behavior for all sites analyzed. Two distinct scaling regions are identified by DFA1, one corresponding to 1 month to 1 year and the other to 1 year to 5 years. The WHD series obey power-law in two temporal regimes respectively with mean DFA1 scaling exponents α1≈0.68 and α2≈0.45, implying the presence of LRP in the acid deposition series and there is a tendency for a large deposition event to be followed by another large event, and vice versa. For DFA2–DFA4, however, the annual crossover, which divides the temporal scale into two regimes, disappears gradually with the order q of DFAq increasing, and the two scaling regimes turn to share the same scaling exponent close to α1. The result indicates that the scaling behavior exits in the two regimes with the same scaling exponent α1, and LRP prevails during the examined 1-month to 5-years scale. NO3- and SO42- deposition evolve the same way as WHD does, implying the pollutants involving in acid deposition may share some prominent mechanism controlling their evolutions. We ascribe the long-range power-law scaling of acid deposition evolutions to the self-organized critical behavior of atmosphere under pollution stress and it should be considered in the trend prediction of acid deposition as an important factor.

As important as the intrinsic properties of an individual nervous cell stands the network of neurons in which it is embedded and by virtue of which it acquires great part of its responsiveness and functionality. In this study we have explored how the topological properties and conduction delays of several classes of neural networks affect the capacity of their constituent cells to establish well-defined temporal relations among firing of their action potentials. This ability of a population of neurons to produce and maintain a millisecond-precise coordinated firing (either evoked by external stimuli or internally generated) is central to neural codes exploiting precise spike timing for the representation and communication of information. Our results, based on extensive simulations of conductance-based type of neurons in an oscillatory regime, indicate that only certain topologies of networks allow for a coordinated firing at a local and long-range scale simultaneously. Besides network architecture, axonal conduction delays are also observed to be another important factor in the generation of coherent spiking. We report that such communication latencies not only set the phase difference between the oscillatory activity of remote neural populations but determine whether the interconnected cells can set in any coherent firing at all. In this context, we have also investigated how the balance between the network synchronizing effects and the dispersive drift caused by inhomogeneities in natural firing frequencies across neurons is resolved. Finally, we show that the observed roles of conduction delays and frequency dispersion are not particular to canonical networks but experimentally measured anatomical networks such as the macaque cortical network can display the same type of behavior.