Multiple Temporal Scales Research Articles

Ecological quality assessment: A framework to report ecosystems quality and their dynamics from reference conditions

AbstractWorldwide, ecosystems are suffering important taxonomic and functional modifications in response to anthropogenic disturbances, operating at multiple spatial and temporal scales. Awareness on biodiversity losses has led to the adoption of conservation policies and the development of programs devoted to the conservation and the restoration of terrestrial, freshwater, and marine ecosystems. The assessment of the ecological health of ecosystems requires measuring and characterizing restoration or degradation dynamics and their consequences on the ecological quality with respect to reference conditions defined pragmatically as conservation targets. Methodological innovations, in terms of data collection, analysis, and visualization, have an important influence on the ability of ecologists to understand biodiversity changes. The assessment of the quality of ecosystems with respect to reference conditions requires to address, notably, three main challenges: the definition of reference conditions, the assessment of the degree of achievement of conservation objectives, and the qualitative and quantitative characterization of recovering and departing patterns. We propose here the ecological quality assessment (EQA) framework as a data‐driven approach to track ecological quality focusing on the distance of the tested stations with respect to a chosen reference envelope using fuzzy logic and trajectory analysis. We take advantage of those analytical tools to propose a general and flexible multivariate framework by quantifying the achievement of reference conditions, measuring restoration and degradation dynamics when temporal series are available, and representing and synthesizing this information. To take into account the natural spatiotemporal variability of sites considered as reference, we gave two variants to our framework: a state‐based variant when no temporal replications are available and a trajectory‐based variant specially devoted to compare whole trajectories to a trajectory reference envelope defined by a set of reference trajectories. These two complementary approaches were illustrated through two terrestrial and marine ecological applications using the R package “ecotraj” in order to evidence ecological observations that meet conservation objectives from those that do not meet them. EQA constitutes a flexible framework for the assessment and reporting of ecosystem quality, including restoration and degradation dynamics adaptable to multiple questions in the different fields of ecology and conservation.

Multiscale Cumulative Residual Dispersion Entropy with Applications to Cardiovascular Signals.

Heart rate variability (HRV) is used as an index reflecting the adaptability of the autonomic nervous system to external stimuli and can be used to detect various heart diseases. Since HRVs are the time series signal with nonlinear property, entropy has been an attractive analysis method. Among the various entropy methods, dispersion entropy (DE) has been preferred due to its ability to quantify the time series' underlying complexity with low computational cost. However, the order between patterns is not considered in the probability distribution of dispersion patterns for computing the DE value. Here, a multiscale cumulative residual dispersion entropy (MCRDE), which employs a cumulative residual entropy and DE estimation in multiple temporal scales, is presented. Thus, a generalized and fast estimation of complexity in temporal structures is inherited in the proposed MCRDE. To verify the performance of the proposed MCRDE, the complexity of inter-beat interval obtained from ECG signals of congestive heart failure (CHF), atrial fibrillation (AF), and the healthy group was compared. The experimental results show that MCRDE is more capable of quantifying physiological conditions than preceding multiscale entropy methods in that MCRDE achieves more statistically significant cases in terms of p-value from the Mann-Whitney test.

Rainfall characteristics of sediment connectivity activation from plot to watershed scales on the Loess Plateau

Sediment connectivity is a fundamental concept for understanding sediment dynamics within watersheds, serving as a crucial component in watershed management and soil and water conservation. However, quantifying sediment connectivity remains a challenging task due to its complexity and the difficulties associated with direct measurements of sediment flux at multiple temporal and spatial scales. Our research aims to address this challenge by monitoring functional sediment connectivity at various scales using two key indicators: sediment yield and sediment marks. Sediment yield is monitored at slope plots, slope-channel cascades, and watershed outlets, while sediment marks provide additional insight into functional sediment connectivity along the sediment transport path, particularly in slope-channel cascades and channels following rainfall events. To record sediment marks, we used wooden sticks wrapped with clean gauze as an alternative to assessing functional connectivity. Our results revealed that the activation of sediment connectivity was influenced by rainfall amount, intensity, and type, with the highest activation observed at the slope plot, followed by the outlet of the slope-channel cascade and the watershed outlet. Notably, strong sediment connectivity at slope plots, slope-channel cascades, and main channels exhibits a weak correlation with sediment connectivity at the watershed outlet. In upper contribution areas with lower vegetation coverage and higher human disturbance, rainfall amount and I60 values associated with sediment connectivity activation tend to be lower. Furthermore, our research indicates that medium-duration and moderate-intensity rainfall events have a more significant impact on sediment connectivity at slope plots, while rainfall types characterized by longer durations, lower intensity, and larger amounts have a more pronounced effect on sediment transport paths. This suggests that the identification of sediment connectivity switch nodes can be achieved by considering both rainfall characteristics and underlying surface features. Looking ahead, future research can leverage long-term observations and data-driven models to explore rainfall thresholds for sediment connectivity at various scales, ultimately improving sediment transport prediction within watersheds.

The seabed and the South: from stock stories to new histories of international lawmaking

Centring the career of Cameroonian diplomat Paul Bamela Engo during the negotiation of the UN Convention on the Law of the Sea, this article makes a methodological intervention in the historiography of multilateral treaty-making. It reads through and against the grain of dominant narratives of oceanic constitution-making, and offers counter-narratives that serve as conceptual and mobilizational resources in contemporary struggles. It examines how the ‘stock story’ of the emergence of the resource regime for seabed minerals as the common heritage of mankind erases the radical alternatives that were proposed by Third World actors and their efforts to write them into law, and sorts these actors into trope-laden categories of ‘extremist’ and ‘moderate’. Against this, and building on critical race theorist Richard Delgado’s exploration of counterstorytelling, this article traces histories that position Third World diplomats and lawyers as intellectual innovators and rival worldmakers. Extending the field of international intellectual history, and examining international lawmaking conferences as a political form, these histories link UNCLOS to wider anticolonial and worldmaking projects. Connecting analyses at multiple spatial and temporal scales, such histories also offer an empirically-grounded approach to the agency and structural constraints of Third World actors negotiating international legal orders, and illuminate international lawmaking as a promising site for global history.

The Development and Operational Use of an Integrated Numerical Weather Prediction System in the National Center for Meteorology of the Kingdom of Saudi Arabia

Abstract The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.

Full‐scale modeling of chemical experiments

AbstractComputational chemistry methods are playing an increasingly pivotal role in chemical experiments. From quantum chemistry simulations to finite element simulations, researchers can always find an appropriate simulation method to elucidate the specific mechanisms at a certain resolution scale. However, in organic or inorganic synthesis, the synthesis mechanisms span multiple spatial and temporal scales of chemical experiments. Furthermore, the intricate nature of these mechanisms renders it impossible for any single simulation method to provide a comprehensive depiction of the entire process. In this perspective, using zeolite and polymer synthesis simulations as examples, we stress the significance of full‐scale modeling techniques for chemical experiments and urge the corresponding sophisticated simulation platform.

Integration of multimodal data for large-scale rapid agricultural land evaluation using machine learning and deep learning approaches

Rapid and accurate agricultural land evaluation provides essential guidance for the supervision and allocation of agricultural land resources; it also helps to ensure food security. Previous work has mainly evaluated the land quality at the county level by using field sampling data and based on a factor approach. However, it is difficult to achieve uniform, large-scale agricultural land evaluation via conventional approaches because of its spatial heterogeneity, as well as the large temporal and economic costs associated with data acquisition. In this study, we integrated publicly available multimodal data (i.e., satellite remote sensing, environmental, and socioeconomic data) into the Google Earth Engine (GEE) platform, selected the best indicators from each modality using the geodetector, on the basis of which different combinations of input models were designed. And then we developed machine learning (random forest, RF) and deep learning (deep neural network, DNN) models to evaluate the land quality in paddy field and dry land systems in 2013 throughout Guangdong Province, China. The results showed that the performance of our combination of variables decreased in the following order: multimodal > bimodal > unimodal. With the best input combination, the RF model (R2 = 0.91, RMSE = 97.56, and CCC = 0.95) outperformed the DNN model (R2 = 0.89, RMSE = 108.72, and CCC = 0.94) in terms of predicting the quality of paddy field. The RF model (R2 = 0.90, RMSE = 104.27, and CCC = 0.95) also outperformed the DNN model (R2 = 0.86, RMSE = 124.38, and CCC = 0.93) in terms of predicting the quality of dry land. The agricultural land quality estimates obtained using the RF and DNN models were more accurate for paddy field than for dry land systems because of greater land quality homogeneity in paddy fields. This research proposed a simple, low-cost for rapid and accurate agricultural land evaluation at the provincial scale using publicly available multimodal data, which can help to achieve control of the agricultural land grade at multiple spatial and temporal scales.

How do conservation policies, climate and socioeconomic changes impact Hyrcanian forests of northern Iran?

Sustainable forest management (SFM) practices are required to conserve forest ecosystem services. International agreements and national management plans have been developed to avoid deforestation and increase forest sustainability. Due to the high rate of deforestation and its increasing trend in the past, the most important conservation policy (the Forest Rest Plan) in Hyrcanian forests (HFs) has been in place since 2016 to conserve the HFs, which are a UNESCO World Heritage site. The aim of the Forest Rest Plan (FRP) is to increase the crown cover, resilience, and production of HFs. Here, we apply a robust methodology based on Landsat-8-derived spectral-temporal features, spatial analysis, stepwise multilevel logistic regression, and scientific forest management knowledge to determine how the FRP, climate change, anthropogenic activities, and the environmental conditions influence deforestation and forest recovery. We identified and evaluated 18 explanatory variables, including socioeconomic, climatic, and physiographic factors, to determine the key drivers of forest cover change. Our findings revealed complex interactions between distinct land features that occur at multiple spatial and temporal scales in HFs as connected human–natural systems. Further, we found a decreasing trend in deforestation and a growing trend in forest recovery resulting from implementation of the FRP. Additionally, our stepwise multilevel logistic regression identified impacts of climate change, human pressure, and some physiographic factors, such as forest density, on deforestation and forest recovery. We conclude that while some positive impacts can already be identified, additional adaptive, preventative, and restorative strategies must be developed to reach all FRP objectives.

Towards an interdisciplinary agenda for teaching in the climate crisis: reflections from the humanities and social sciences

The current anthropogenic climate crisis presents unique challenges to the higher education classroom. Pedagogy in the context of climate change must be attuned to complex and varied student experiences that can contend with feelings of anxiety, disconnection, distress and hopelessness. As educators and researchers, we collate our pedagogical approaches in the humanities and social sciences to progress ongoing discussions about climate pedagogy and highlight possibilities for action from Australia. Drawing on the inherent interconnectedness of our disciplines, we offer an interdisciplinary agenda for teaching in the climate crisis that is attuned to framing, positionality and reflexivity; multiple temporal and spatial scales; other ways of living and knowing; and creative action and activism to cultivate an affective classroom.

Evaluation of multiple gridded snowfall datasets using gauge observations over high mountain Asia

Snowfall is an important component of the High Mountain Asia (HMA) cryosphere; its changes affect the regional energy and water balance. Snowfall data from numerous gridded products provide the basis for conducting climate-change studies; however, the applicability of these datasets in HMA has not been assessed comprehensively in terms of precipitation. This study comprehensively evaluates the applicability of the following widely used gridded datasets in HMA for the period 1991–2014: fifth generation of European ReAnalysis (ERA5), Global Land Data Assimilation System (GLDAS), High Asia Refined analysis (HAR), Multi-Source Weather (MSWX), National Centers for Environmental Prediction (NCEP), and China Meteorological Forcing Dataset (CMFD). The accuracy features of each dataset were evaluated based on observations from 148 gauges at various temporal scales (i.e., annual, monthly, and daily), elevations, sub-regions, and snowfall intensities. The results show that CMFD performs better at multiple temporal scales (i.e., annual, cool season, monthly, and daily) than other snowfall data. In addition, the CMFD accuracy has good stability, even at different elevations. CMFD is advantageous regarding interpreting the frequency and amount of different levels of (even extreme) snowfall events. The slightly inferior MSWX also performs well at different timescales, spatial scales, and elevations, and constitutes an attractive alternative to CMFD. HAR captures better light and moderate snowfall, and is the most accurate of the three sets of gridded products that contain direct snowfall data. This study constitutes an important reference for selecting suitable snowfall datasets for future scientific research.

Visualizing multi-physical spatiotemporal evolution of dielectric breakdown in high-performance polymeric capacitors

Pulse power has many important technological applications, for which the dielectric capacitors are essential. It is imperative to understand the breakdown mechanism to improve the dielectric energy storage density, yet the breakdown process involves multi-physical coupling spanning multiple spatial and temporal scales, making its characterization very challenging. Recognizing local field concentration results in local strain concentration through Maxwell's stress, we develop an effective method to visualize the dielectric breakdown process via optic strain measurement. Utilizing high-performance biaxially oriented polypropylene as a demonstration, we find dielectric breakdown is an ultrafast process with breakdown current rising and dropping in just tens of nanoseconds. Rapid temperature rise is observed after breakdown as well due to Joule heating, though both current measurement and temperature mapping offer little insight before breakdown actually occurs. Nevertheless, substantial strain concentration is observed before breakdown, reflecting electric field concentration that eventually leads to breakdown. A well-defined upper bound on the electric field concentration is also noted.

Towards time and cost‐efficient habitat assessment: Challenges and opportunities for benthic ecology and management

Abstract To the untrained eye, soft‐sediment habitats are often viewed as vast expanses of featureless sand and mud. With new technology, it is finally possible to begin to map the ecological heterogeneity of these ecosystems to reveal their importance for ecosystem service provision and open up new opportunities to manage their use and protect them. When compared with terrestrial or marine vegetated habitats, the characterization of unvegetated soft sediments still lacks rapid and cost‐effective practices that allow the direct collection of ecological data at multiple spatial and temporal scales facilitating direct relevance to conservation and management. New technologies that allow for the building of maps that incorporate multiple scales of heterogeneity also provide new ways of upscaling necessarily detailed and small‐scale process studies. The study of the relationship between benthic structure, biodiversity and ecosystem functioning can benefit from a range of established and novel techniques and creates new opportunities to empirically test generalities and predictions based on theory or small‐scale experimental studies. The capacity to map ecological changes rapidly and at scale and to link small‐scale experiments to landscapes uncovers new insights for seafloor conservation including rapid response to disturbance events, broad‐scale ecologically meaningful mapping and assessments of biodiversity–ecosystem function and biodiversity–ecosystem services relationships. As technology advances and becomes more accessible to all, it offers promising new avenues of research to expand our current capabilities, and the adoption of nested approaches, with a synergy of different samplings simultaneously covering several scales and resolutions, is likely to have the most benefit, supporting decision‐making with ecologically insightful data, as well as the timely assessment of the outcomes of conservation actions.

Sex and diel period influence patterns of resource selection in elk

AbstractResource selection and space use are important aspects of an animal's ecology and understanding these behaviors is necessary for proper wildlife management. We used mixed‐effect integrated step‐selection models to evaluate seasonal variation in resource selection between male and female elk (Cervus canadensis) and diel periods in central Pennsylvania, USA. Resource selection varied seasonally, between sexes, and across diel periods. These results demonstrate strong seasonal sexual segregation in resource use, and movements between habitats throughout the day, highlighting the dynamic nature of resource selection by elk and underscoring the importance of considering sexual variation at multiple temporal scales when designing ungulate management strategies. Finally, we developed habitat suitability maps for male and female elk in the Pennsylvania Elk Management Area. Wildlife ecologists and managers must consider multiple sources of variation in habitat use and resource selection, particularly for large mobile species such as elk.

The medial septum controls hippocampal supra-theta oscillations

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.

Identifying potential measures of stress and disturbance during a captive to wild African elephant reintegration.

There is increasing evidence of compromised welfare for elephants managed in captivity. Should such facilities eventually close, more elephants will need to be rehabilitated and reintegrated into the wild. The goal of such reintegration would be to restore any physical or psychological aspects of the elephant that may have been compromised in captivity, followed by introduction into a free-roaming system where they can interact with other elephants. However, to achieve this goal, the reintegration methods implemented need to be assessed to ensure that welfare remains the priority. The objective of this study was to test whether parameters generally associated with stress and disturbance in African elephants, respond to changes in potentially stressful environmental conditions, assessed at multiple temporal scales ranging from minutes to months. The main changes in environmental conditions that were investigated included the different phases of reintegration of a group of elephants from captivity into the wild. Stress and disturbance related parameters used for comparisons included physiological responses, namely the extent of temporal gland secretions (eTGS) and faecal glucocorticoid metabolite (fGCM) levels as well as behavioural responses, namely the display of stereotype and stress-related behaviours. Results showed that eTGS significantly increased during the initial release of the elephants compared to when in captivity. Stereotypic behaviours were only recorded during the captive phase and immediately ceased after release. Faecal GCM levels spiked in the first year after release before decreasing back to pre-reintegration levels during the third year. These findings indicate that fGCM levels, the eTGS and disturbance related behaviours all proved effective in explaining the changes in stress and disturbance experienced by elephants during the initial years after being reintegrated from captivity into the wild.

The Interplay Between Supply Chain Resilience and Climate Change

Supply chains – a web of organisations and actors from raw material to consumption – are no longer linear; they instead make up a network of interconnected and overlapping global suppliers. Simultaneously, climate change has become one of, if not the greatest challenge of the modern world, materialised by increasing temperatures and sea levels, and intensified extreme weather events. This era of increased turbulence needs new ways of thinking to build resilience strategies in the face of such disruptions. Supply chain resilience (SCR) strategies have typically been based on an equilibrium-seeking system whereby the goal is to bounce back to the pre-disruption state or bounce forward to a better state. This research borrows the Complex Adaptive Systems (CAS) perspective which acknowledges the environment as a continuously evolving system that responds to multiscale interactions and feedback between different actors. This CAS perspective of SCR seeks to maintain the core functionality by adapting, evolving, and transforming to the dynamic environment. This research aims to explore the interrelationship between SCR and climate change across multiple temporal and spatial scales through multiple case studies. In this presentation, I will display initial findings from the pilot study focusing on three cases of New Zealand multinationals. These findings are formed exclusively through secondary data collected from case study, company reports and documents, press releases and databases, which will later be used to complement interviews and focus groups with companies’ executives. I will demonstrate how increased collaboration and agility along the supply chain is needed in the face of increasing climate related disruptions. Given that supply chain interactions are a major contributor to climate change, this presentation also intends to explore ways in which supply chains can operate more sustainability as part of a continuously evolving process of resiliency.

Revealing Senior Mobility Patterns and Activities in Urban Transit Systems

Urban mobility plays a crucial role in maintaining seniors’ well-being and quality of life, with urban transit systems serving as their primary mode of travel. This study focuses on revealing seniors’ travel patterns and activities and predicting their demands in transit systems. We propose a spatio-temporal travel pattern model that extends the structural topic model from text mining, to detect senior mobility patterns from trip sequences at the rail station level and discover their activities hidden in passively collected data from a probabilistic generative procedure. The proposed model can incorporate a wide range of spatio-temporal covariates that help estimate the relative importance of travel patterns across stations and over time. Numerical experiments are conducted using transit smart card data collected in Nanjing, China. The results demonstrate that our proposed methodology successfully transforms massive mobility records into informative travel patterns, each of which characterizes a distinct distribution of trip attributes. We combine land use characteristics of station areas with detected patterns to explore seniors’ behavioral strategies and activities at multiple spatial and temporal scales. Moreover, by applying prior detected patterns to the station-level ridership prediction, we significantly improve the predictive performance of direct ridership models. This study contributes to detecting seniors’ travel patterns, discovering latent activities, predicting station-level travel demands, and creating senior-friendly mobility systems.

Framework to develop an open‐source forage data network to improve primary productivity and enhance system resiliency

AbstractData repositories using legacy data are needed to minimize research redundancy, enable knowledge synthesis, and optimize productivity and resiliency of agricultural systems. However, a framework is needed to develop an online searchable database to identify optimum systems for sustainable agricultural intensification and diversification, particularly for forages. Therefore, this paper outlines the development of a community‐driven forage database (Forage Data Hub) using legacy datasets encompassing multiple temporal and spatial scales and species to analyze system functionality and resiliency. Specific steps outlined included (1) developing minimum and preferred data requirements; (2) data standardization, structuring, and compilation; (3) creating a data thesaurus, data shapes, and data model; and (4) creating a web‐based system interface to facilitate database access. We demonstrate utility of curating these diverse datasets by quantifying forage system resiliency during extreme weather occurrences (relationship between standardized yields and yields during years receiving 25th percentile of the 30‐year normal precipitation) for three systems (monocrop annual, monocrop perennial, and mixed perennial) spanning 52,997 data entries (108 unique locations and 51 years). Overall, during low‐precipitation years, monocrop annual systems achieved 67% of their expected yield, while monocrop perennial systems achieved 93% and mixed perennial systems achieved 112% of potential yields. Therefore, diverse perennial systems were more resilient to climate‐related stresses compared to annual forage systems. Development of the US Forage Data Hub underscores the benefits of community‐driven data sharing and curation for a given commodity to provide system‐level sustainability assessments for identifying practices that promote ecological intensification and resiliency to climatic stochasticity.

Grassland cover dynamics and their relationship with climatic factors in China from 1982 to 2021

China possesses abundant grassland resources, making it imperative to comprehend the influence of climate change on Chinese grassland ecosystems. Nonetheless, the impact pathways and lag effects of climate factors on various grassland types in this region at multiple temporal scales are still to be investigated in long-term sequences. This study investigated the dynamics of grassland FVC (fractional vegetation cover), temperature, precipitation, and drought from 1982 to 2021 using trend analysis, multiple linear regression, path analysis, and correlation analysis and explored the dominant, direct, indirect, and time-lag effects of climate factors on different grassland types at multiple time scales. Precipitation-grassland correlation pathways dominated the annual-scale grassland FVC. The correlation path of temperature to grassland FVC and the direct path of temperature dominated spring grassland FVC. The correlation path of drought to grassland FVC and the direct path of drought dominated summer grassland FVC. The correlation path of temperature to grassland FVC and the direct path of temperature dominated autumn and winter grassland FVC. The effects of temperature and precipitation on alpine and subalpine meadows, desert grasslands, and alpine and subalpine plains grasslands had a 1-month lag. The response to drought exhibited a 1-month lag in desert grasslands, a 2-month lag in alpine and subalpine meadows, plains grasslands, meadows, and alpine and subalpine plains grasslands, and a 3-month lag in sloped grasslands. This study seeks to provide a scientific reference to reveal the impact of climate change on grasslands and to protect grassland ecosystems.

The spatial and temporal structure of neural activity across the fly brain

What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.