Temporal Time Scales Research Articles

Therapeutic doses of ketamine acutely attenuate the aversive effect of losses during decision-making.

The discovery of rapid-acting antidepressant, ketamine has opened a pathway to a new generation of treatments for depression, and inspired neuroscientific investigation based on a new perspective that non-adaptive changes in the intrinsic excitatory and inhibitory circuitry might underlie the pathophysiology of depression. Nevertheless, it still remains largely unknown how the hypothesized molecular and synaptic levels of changes in the circuitry might mediate behavioral and neuropsychological changes underlying depression, and how ketamine might restore adaptive behavior. Here, we used computational models to analyze behavioral changes induced by therapeutic doses of ketamine, while rhesus macaques were iteratively making decisions based on gains and losses of tokens. When administered intramuscularly or intranasally, ketamine reduced the aversiveness of undesirable outcomes such as losses of tokens without significantly affecting the evaluation of gains, behavioral perseveration, motivation, and other cognitive aspects of learning such as temporal credit assignment and time scales of choice and outcome memory. Ketamine's potentially antidepressant effect was separable from other side effects such as fixation errors, which unlike outcome evaluation, was readily countered with strong motivation to avoid errors. We discuss how the acute effect of ketamine to reduce the initial impact of negative events could potentially mediate longer-term antidepressant effects through mitigating the cumulative effect of those events produced by slowly decaying memory, and how the disruption-resistant affective memory might pose challenges in treating depression. Our study also invites future investigations on ketamine's antidepressant action over diverse mood states and with affective events exerting their impacts at diverse time scales.

Therapeutic doses of ketamine acutely attenuate the aversive effect of losses during decision-making

The discovery of rapid-acting antidepressant, ketamine has opened a pathway to a new generation of treatments for depression, and inspired neuroscientific investigation based on a new perspective that non-adaptive changes in the intrinsic excitatory and inhibitory circuitry might underlie the pathophysiology of depression. Nevertheless, it still remains largely unknown how the hypothesized molecular and synaptic levels of changes in the circuitry might mediate behavioral and neuropsychological changes underlying depression, and how ketamine might restore adaptive behavior. Here, we used computational models to analyze behavioral changes induced by therapeutic doses of ketamine, while rhesus macaques were iteratively making decisions based on gains and losses of tokens. When administered intramuscularly or intranasally, ketamine reduced the aversiveness of undesirable outcomes such as losses of tokens without significantly affecting the evaluation of gains, behavioral perseveration, motivation, and other cognitive aspects of learning such as temporal credit assignment and time scales of choice and outcome memory. Ketamine’s potentially antidepressant effect was separable from other side effects such as fixation errors, which unlike outcome evaluation, was readily countered with strong motivation to avoid errors. We discuss how the acute effect of ketamine to reduce the initial impact of negative events could potentially mediate longer-term antidepressant effects through mitigating the cumulative effect of those events produced by slowly decaying memory, and how the disruption-resistant affective memory might pose challenges in treating depression. Our study also invites future investigations on ketamine’s antidepressant action over diverse mood states and with affective events exerting their impacts at diverse time scales.

Validation of Rotating Detonation Combustor Computational Fluid Dynamics Simulations for Predicting Unsteady Supersonic–Subsonic Flow Field at the Exit

Abstract Rotating detonation combustors (RDCs) have gained increased interest for integration with power-generating gas turbines due to the potential to increase thermal efficiency. The unsteady flow field exiting the RDC is fundamentally different compared to traditional swirl-stabilized combustors. Successful integration of RDC with gas turbines will depend on the ability to properly condition the unsteady flow to achieve performance levels comparable to swirl-stabilized combustors. RDC simulations require significant computational resources due to the small spatial and temporal time scales required to resolve the detonation phenomenon. Furthermore, traditional steady-state computational fluid dynamics (CFD) analyses are not possible for RDC simulations. The present study develops and validates a computationally efficient approach for predicting unsteady flow fields exiting the combustor using 2D, transient reacting CFD with periodic boundary conditions in the combustor and a downstream plenum. Validation is performed by comparing the CFD results to various experimental measurements: (i) wave speed obtained from high-speed ion probe and dynamic pressure data, (ii) average wall static pressure measurements, and (iii) time-resolved particle image velocimetry (PIV) at 100 kHz at the RDC exit. Results indicate good agreement between CFD and experiments with respect to velocity field exiting the RDC, detonation wave speed, and static pressure distribution.

0130 Reduced Entropy in EEG During Rapid Eye Movement Sleep in Men with Depression

Abstract Introduction Depression is an increasingly prevalent mental health condition. Patients with depression have disrupted rapid eye movement (REM) sleep as characterized by shortened REM latency, increased REM sleep duration, and increased REM density. However, it is unknown whether the dynamic patterns of EEG within REM episodes are altered in these patients. Here we investigated the complexity of EEG during REM sleep using the analysis of irregularity on multiple temporal time scales and compared the difference in such a nonlinear property of EEG between patients with depression and controls. Methods We analyzed the overnight EEG recordings (256 Hz) collected from the left central channel in 19 older men with depression and 19 age-matched otherwise healthy control men in the Osteoporotic Fractures in Men Study (MrOS) obtained from the National Sleep Research Resource (NSRR). To quantify the irregularity/complexity in EEG fluctuations during REM, a Multiscale Entropy (MSE) analysis was performed on each 30-second epoch to calculate the entropy at different time scales between ~0.004 and ~0.078 seconds (i.e., 1/256, 2/256, …, 20/256 seconds). Results As compared to control men, men with depression had significantly lower entropy values at multiple time scales between 0.023-0.031 seconds (time scale =6/256 second: 0.363□0.008 [SE] for depression, 0.408□0.009 for controls; time scale =7/256 second: 0.295□0.009 for depression, 0.342□0.008 for controls; time scale =8/256 second: 0.225□0.009 for depression, 0.269□0.008 for controls; all FDR-adjusted P-values< 0.001), indicating reduced temporal irregularity/complexity in EEG fluctuations. The differences were not statistically significant at smaller or larger time scales. Conclusion EEG complexity/irregularity within REM sleep were altered in patients with depression. Our results indicate the capability of MSE analysis in capturing important complexity features of EEG fluctuations, which might be missed using those entropy algorithms focused on EEG fluctuations at a single time scale. Support (if any) RF1AG059867, RF1AG064312. The National Heart, Lung, and Blood Institute provided funding for the ancillary MrOS Sleep Study, "Outcomes of Sleep Disorders in Older Men," under the following grant numbers: R01 HL071194, R01 HL070848, R01 HL070847, R01 HL070842, R01 HL070841, R01 HL070837, R01 HL070838, and R01 HL070839. The NSRR was supported by the National Heart, Lung, and Blood Institute (R24 HL114473, 75N92019R002).

Dynamics and stage-specificity of between-population gene expression divergence in the Drosophila melanogaster larval fat body

Gene expression variation is pervasive across all levels of organismal organization, including development. Few studies, however, have examined variation in developmental transcriptional dynamics among populations, or how it contributes to phenotypic divergence. Indeed, the evolution of gene expression dynamics when both the evolutionary and temporal timescale are comparatively short remains relatively uncharacterized. Here, we examined coding and non-coding gene expression in the fat body of an ancestral African and a derived European Drosophila melanogaster population across three developmental stages spanning ten hours of larval development. Between populations, expression divergence was largely stage-specific. We detected higher expression variation during the late wandering stage, which may be a general feature of this stage. During this stage, we also detected higher and more extensive lncRNA expression in Europe, suggesting that lncRNA expression may be more important in derived populations. Interestingly, the temporal breadth of protein-coding and lncRNA expression became more restricted in the derived population. Taken together with the signatures of potential local adaptation that we detected at the sequence level in 9-25% of candidate genes (those showing evidence of expression divergence between populations), this finding suggests that gene expression becomes more developmental stage-specific during adaptation to new environments. We further used RNAi to identify several candidate genes that likely contribute to known phenotypic divergence between these populations. Our results shed light on the evolution and dynamics of expression variation over short developmental and evolutionary timescales, and how this variation contributes to population and phenotypic divergence.

Pesticides are Substantially Transported in Particulate Phase, Driven by Land use, Rainfall Event and Pesticide Characteristics—A Runoff and Erosion Study in a Small Agricultural Catchment

Agriculture on sloping lands is prone to processes of overland flow and associated soil detachment, transportation, and deposition. The transport of pesticides to off-target areas related to runoff processes and soil erosion poses a threat of pollution to the downstream environment. This study aimed to quantify transport of pesticides both dissolved in water and in the particulate phase in transported sediments. Particulate phase transport of pesticides on short temporal time scales from agricultural fields is scarcely studied. During two growing seasons (2019 and 2020) rainfall—runoff events were monitored in a catchment of 38.5 ha. We selected 30 different pesticides and one metabolite based on interviews with the farmers on the application pattern. Concentrations for these 31 residues were analyzed in runoff water (dissolved phase–DP) and sediment (particulate phase–PP) and in soil samples taken in the agricultural fields. In all runoff events active substances (AS) were detected. There was a clear difference between DP and PP with 0–5 and 8–18 different AS detected in the events, respectively. Concentrations in PP were higher than in DP, with factors ranging from 12 to 3,700 times. DP transport mainly occurs in the first days after application (69% within 10 days), and PP transport occurs over the long term with 90% of transported mass within 100 days after application. Potato cultivation was the main source of runoff, erosion, and pesticide transport. Cereals and apples with grassed inter-rows both have a very low risk of pesticide transport during overland flow. We conclude that for arable farming on sloping lands overland transport of pesticide in the particulate phase is a substantial transport pathway, which can contribute to pollution over longer time periods compared to transport in water. This process needs to be considered in future assessments for pesticide fate and environmental risk.

Self-healing epoxidized natural rubber with ionic/coordination crosslinks

Self-healing polymers with strong mechanical robustness and superior self-healing ability are of interest in coatings, electronics, structural components, etc. However, it is difficult to realize these properties simultaneously, owing to the mutually exclusive requirements: the mechanical robustness of materials needs strong bonds to form robust network, but a strong bond leads to weak self-healing capability. In this work, we report the rational design of epoxidized natural rubber (ENR) incorporating with ionic and coordination supramolecular hybrid bond network, in which these two kinds of bonds possess identical cross-linking point yet contrasting bond strength. The optical microscope pictures and the temperature-dependent infrared spectra analysis show that ionic bonds rapidly shorten the spatial distance of the ENR chains located on both sides of the ionic bond to assemble into a stable network with lower energy state owing to its short temporal timescale for reconstruction, and simultaneously promote the reconstruction of coordination bond as a result of their sharing the same cross-linking point. The cooperative collaboration of these two bonds lead to a tensile stress of 1.33 MPa, a strain of 600%, and a healing efficiency of 92% after healing for 3 h at ambient temperature. This novel self-healing material is promising for various applications, especially when the component is difficult to disassemble or with limited enviroment conditions.

Leveling with Tinbergen: Four levels simplified to causes and consequences.

In 1963, Niko Tinbergen published his foundational manuscript identifying the four questions we ask in animal behavior-how does the behavior emerge across the lifespan (development); how does it work (mechanism); how and why did it evolve (evolution); and why is it adaptive (function). Tinbergen clarified that these 'levels of analysis' are complementary, not competing, thereby avoiding many fruitless scientific debates. However, the relationships among the four levels was never established. Here, we propose 'leveling' Tinbergen's questions to a single temporal timescale divided into causes (encompassing mechanism, development, and evolution) and consequences (encompassing function). Scientific advances now seamlessly link evolution, development, and mechanism into a continuum of 'causes'. The cause-consequence distinction separates the processes that precede (and lead to) a behavior, from the processes that come after (and result from) a behavior. Even for past behaviors, the functional outcomes are (historical) consequences of the causes that preceded them.

Recreational fishers’ perceptions of climate change

Abstract Shifts in marine species distributions associated with climate change occur across large spatial areas and long time periods. Marine recreational fishing occurs in most countries with many participants interacting regularly with the environment, yet there have been few studies on the views of recreational fishers towards climate change. This study aims to assess perceptions of climate change for a boat-based recreational fishery in Western Australia, where fishing occurs across a wide latitudinal range, from tropical to temperate waters. Perceptions of climate change were assessed by fisher demographics and fishing behaviour. One in two respondents noticed changes in species types and distributions, with metropolitan residents and avid fishers more likely to notice these changes. Two out of three respondents considered climate change is occurring, recognition of which was higher amongst metropolitan residents, females, and younger respondents. Males and older respondents, on the other hand considered themselves to have more knowledge of climate change science. This study provides a baseline to assist in informing policy changes that might be required to address the impacts of climate change. Studies of this kind can also build support for citizen science programs to enhance data collection across the spatial and temporal time scales required to observe climate change.

Feminist Forms and Borderless Landscapes in Ali Smith’s Seasonal Quartet

Pioneering Scottish novelist Ali Smith experiments with literary form and, in response to the contemporary climate crisis, she plants environmental themes into her poetic prose. Smith’s seasonal quartet includes four stand-alone but interconnected novels that capture the critical and cyclical changes that come with an industrial, post-Brexit world. This change includes the ever-growing borders that divide people and places. Smith crosses and removes borders in her four published volumes—Autumn (2016), Winter (2017), Spring (2019), and Summer (2020)—to reunite Europeans with their fragmented, common land. Her third volume, Spring, demands particular attention for its archive of feminist and ecological forms. Spring exhibits the work of British visual artist Tacita Dean (1965—), whose 2018 exhibition at the Royal Academy, titled Landscape, implores the viewer to consider their place in temporal and geological time scales. Dean’s form-breaking style resists modern art’s limitations and, like Smith’s experimental fiction, refuses to conform to borders or, in this case, genre conventions. A practice well versed in the politics of exclusion, feminist art has the capacity to model a borderless world. Smith’s gallery of feminist art further incites us to remediate marginalized subjects and restore our relationship with the wider ecosystem.

Road accidents analytics with data visualization: a case study in Shah Alam Malaysia

Road accident has become a serious problem of concern due to the increasing trend of the occurrences in line with the increase in the number of registered vehicles in Malaysia year by year. Causes of road accidents may come from various factors. Information on the causes is important to increase knowledge in assisting various responsible bodies with the theory and framework for establishing appropriate regulation, policy as well as for intervention planning and purposes in controlling and managing road accidents problem. Thus, this study aims to produce a road accidents profile of Shah Alam based on secondary data from MIROS and PDRM using descriptive and inferential data analytics. The application of data visualization methodology and techniques have shown that among all states in Malaysia, Selangor having the highest frequency of road accidents. For the cases of Shah Alam, there exist a temporal time scale pattern of road accidents occurrence. More number of accidence happened during the day compared to night. The most critical time the accidence took place is during busy hours; between 8.00 to 10.00 am in the morning, during evening hours between 4.00 to 6.00 pm and night hours after 6.00 pm until 8.00 pm. The accidental death cases were found mostly come from motorbike with (90-250cc), followed by car and lorry and were found mostly occurred at straight-ahead road as well as municipal road. The most type of collision is straying, digressing, or skidding followed by back collision and side collision. The severity of accidents impact is found associated with drivers demographic factors in which accidental death cases involving male is higher than female with age group between 21 to 25 years old.

FMRI-Indexed neural temporal tuning reveals the hierarchical organsiation of the face and person selective network

Recognising and knowing about conspecifics is vital to human interaction and is served in the brain by a well-characterised cortical network. Understanding the temporal dynamics of this network is critical to gaining insight into both hierarchical organisation and regional coordination. Here, we combine the high spatial resolution of fMRI with a paradigm that permits investigation of differential temporal tuning across cortical regions. We cognitively under- and overload the system using the rapid presentation (100–1200msec) of famous faces and buildings. We observed an increase in activity as presentation rates slowed and a negative deflection when inter-stimulus intervals (ISIs) were extended to longer periods. The primary distinction in tuning patterns was between core (perceptual) and extended (non-perceptual) systems but there was also evidence for nested hierarchies within systems, as well as indications of widespread parallel processing. Extended regions demonstrated common temporal tuning across regions which may indicate coordinated activity as they cooperate to manifest the diverse cognitive representation accomplished by this network. With the support of an additional psychophysical study, we demonstrated that ISIs necessary for different levels of semantic access are consistent with temporal tuning patterns. Collectively, these results show that regions of the person-knowledge network operate over different temporal timescales consistent with hierarchical organisation.

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

AbstractGeophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

Mobile Ions in Composite Solids.

Fast ion conduction in solid-state matrices constitutes the foundation for a wide spectrum of electrochemical systems that use solid electrolytes (SEs), examples of which include solid-state batteries (SSBs), solid oxide fuel cells (SOFCs), and diversified gas sensors. Mixing different solid conductors to form composite solid electrolytes (CSEs) introduces unique opportunities for SEs to possess exceptional overall performance far superior to their individual parental solids, thanks to the abundant chemistry and physics at the new interfaces thus created. In this review, we provide a comprehensive and in-depth examination of the development and understanding of CSEs for SSBs, with special focus on their physiochemical properties and mechanisms of ion transport therein. The origin of the enhanced ionic conductivity in CSEs relative to their single-phase parents is discussed in the context of defect chemistry and interfacial reactions. The models/theories for ion movement in diversified composites are critically reviewed to interrogate a general strategy to the design of novel CSEs, while properties such as mechanical strength and electrochemical stability are discussed in view of their perspective applications in lithium metal batteries and beyond. As an integral component of understanding how ions interact with their composite environments, characterization techniques to probe the ion transport kinetics across different temporal and spatial time scales are also summarized.

Некоторые вопросы теоретической картографии

The article is devoted to current theoretical issues of modern cartography. The paper puts forward the concept of metacartography, which laid as the foundation for the Theory of Cartography as a science. The author of this concept is the outstanding Georgian cartographer Alexander Aslanikashvili, who is the founder of the theory of cartography. This concept, which in a new way comprehended the main categories of cartography (the subject of cognition of science, the method of studying a certain side of reality and language) by means of which cartography examines its subject, made it possible to raise some questions of theoretical cartography for research: 1) temporal synthesis; 2) timescale; 3) dynamic generalization. The temporary synthesis in the article is considered on the basis of the results of a theoretical study of A. Aslanikashvili, cartographic forms of analysis and synthesis. Temporal synthesis is studied by the example of diurnal state maps of natural-territorial complexes (steks). The process of temporary synthesis of the so-called “multi-temporal maps” is carried out for one year at three levels: 1) synthesis of dynamic maps for one month; 2) synthesis of dynamic maps for one season; 3) synthesis of dynamic maps for one year. As a result of the temporary synthesis of stacks maps, one synthetic map is compiled without loss of the initial spatiotemporal information. In the process of mapping there are used the so-called “spatiotemporal” diagrams. A new concept of “mapped time” was introduced. In cartography, two types of scale are investigated: a) the scale of space (degree of abstraction) and b) the scale of content (degree of generalization). The article studies the timescale when mapping stacks. In the work, this concept is defined as the degree of generalization of the essence of the development of the mapped phenomenon. The article explores another issue — dynamic generalization. The study is based on stacks’ maps for one year. It was found that dynamic generalization depends on the “degree of syntheticity” of the stecks maps. Dynamic generalization is in direct correlation with the number of dynamics maps of the spatiotemporal model phenomenon. The issues of temporal synthesis, time scale and dynamic generalization are in close relationship with each other. For example, dynamic generalization is the result of a temporary synthesis, and these processes are carried out with the presence of a time scale.

The Global Influence of Cloud Optical Thickness on Terrestrial Carbon Uptake

Abstract Clouds can modify terrestrial productivity by reducing total surface radiation and increasing diffuse radiation, which may be more evenly distributed through plant canopies and increase ecosystem carbon uptake (the “diffuse fertilization effect”). Previous work at ecosystem-level observational towers demonstrated that diffuse photosynthetically active radiation (PAR; 400–700 nm) increases with cloud optical thickness (COT) until a COT of approximately 10, defined here as the “low-COT regime.” To identify whether the low-COT regime also influences carbon uptake on broader spatial and longer temporal time scales, we use global, monthly data to investigate the influence of COT on carbon uptake in three land-cover types: shrublands, forests, and croplands. While there are limitations in global gross primary production (GPP) products, global COT data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reveal that during the growing season tropical and subtropical regions more frequently experience a monthly low-COT regime (>20% of the time) than other regions of the globe. Contrary to ecosystem-level studies, comparisons of monthly COT with monthly satellite-derived solar-induced chlorophyll fluorescence and modeled GPP indicate that, although carbon uptake generally increases with COT under the low-COT regime, the correlations between COT and carbon uptake are insignificant (p > 0.05) in shrublands, forests, and croplands at regional scales. When scaled globally, vegetated regions under the low-COT regime account for only 4.9% of global mean annual GPP, suggesting that clouds and their diffuse fertilization effect become less significant drivers of terrestrial carbon uptake at broader spatial and temporal scales.

Global methane emissions from the human body: Past, present and future

Methane (CH4) is a potent greenhouse gas released to the atmosphere by various natural and anthropogenic sources. Numerous studies have been conducted to quantify the major and minor CH4 sources on spatial and temporal time scales. A minor source of the atmospheric global CH4 budget is the direct release of CH4 from the living human body. Based on available data from recent publications, for the first time, CH4 emissions from human breath and flatus are estimated on a global scale taking into account dominant factors influencing emission, such as age, ethnicity, and gender. Human CH4 emissions are compared between preindustrial times (1750), present age (2017) and future prediction (2100) using demographic data based on World Population Prospects 2017 of the United Nations (UN 2017). In preindustrial times the global CH4 release by humans is estimated at 34 ± 28 Gg and then substantially increase by a factor of ten reaching 344 ± 255 Gg by 2017. Emissions are estimated to further increase by almost fourfold to a value of 1221 ± 672 Gg by 2100, even though the rise in population is predicted to only increase by 50%. This nonlinear relationship is related to the predicted change in population structure affecting the number of CH4 producers. In contrast, for the year 2100 the simplified non-weighted estimation which merely considers the expected increase in population would only account for 612 ± 169 Gg. The discrepancy between the simplified non-weighted and weighted estimations of human CH4 emissions emphasises the importance of factor-based calculations in order to compile more accurate data.

Long-term temporal and spatial analysis of SO2 over Gauteng and Mpumalanga monitoring sites of South Africa

This paper focused on the temporal and spatial variability of sulphur dioxide (SO2) from 2004 to 2013 over 36 ground-based (GB) stations located in Gauteng and Mpumalanga provinces of South Africa. The assessment was based on the in situ SO2 data, where the GB stations were sorted into different groups and in addition, kriging-based analysis and OMI SO2 data (2004–2013) were deployed to study their seasonal spatial variability. It was observed that Pretoria west, Witbank and Randwater had high SO2 levels and standard deviations. Although, winter played a major role in having peak SO2 values in most of the stations, it was surpassing that in spring the SO2 levels of Witbank and Pretoria west stations dropped and Randwater had the highest standard deviation of 11.2 ppbv in October. A prominent seasonal variation was seen in all the groups, excluding Mpumalanga power stations (MP) group. This was particularly evident in the Vaal Triangle group. Highveld group ranked topmost level with elevated SO2 values proceeded by the MP group in all the temporal time scales. The spatial based analysis further proved that the highest SO2 levels were centred around major industrial regions of Mpumalanga, regardless of all the seasons.

A framework for priority-setting in climate smart agriculture research

Climate-smart agriculture (CSA) is widely promoted as an approach for reorienting agricultural development under the realities of climate change. Prioritising research-for-development activities is crucial, given the need to utilise scarce resources as effectively as possible. However, no framework exists for assessing and comparing different CSA research investments. Several aspects make it challenging to prioritise CSA research, including its multi-dimensional nature (productivity, adaptation and mitigation), the uncertainty surrounding many climate impacts, and the scale and temporal dependencies that may affect the benefits and costs of CSA adoption. Here we propose a framework for prioritising agricultural research investments across scales and review different approaches to setting priorities among agricultural research projects. Many priority-setting case studies address the short- to medium-term and at relatively local scales. We suggest that a mix of actions that span spatial and temporal time scales is needed to be adaptive to a changing climate, address immediate problems and create enabling conditions for enduring change.

Effects of temporal averaging on short-term irradiance variability under mixed sky conditions

Abstract. Characterizations of short-term variability in solar radiation are required to successfully integrate large numbers of photovoltaic power systems into the electrical grid. Previous studies have used ground-based irradiance observations with a range of different temporal resolutions and a systematic analysis of the effects of temporal averaging on the representation of variability is lacking. Using high-resolution surface irradiance data with original temporal resolutions between 0.01 and 1 s from six different locations in the Northern Hemisphere, we characterize the changes in representation of temporal variability resulting from time averaging. In this analysis, we condition all data to states of mixed skies, which are the most potentially problematic in terms of local PV power volatility. Statistics of clear-sky index k* and its increments Δk*τ (i.e., normalized surface irradiance and changes therein over specified intervals of time) are considered separately. Our results indicate that a temporal averaging time scale of around 1 s marks a transition in representing single-point irradiance variability, such that longer averages result in substantial underestimates of variability. Higher-resolution data increase the complexity of data management and quality control without appreciably improving the representation of variability. The results do not show any substantial discrepancies between locations or seasons.