Fine Temporal Scales Research Articles

Fine scale hydrologic modelling of bioretention using DRAINMOD-urban: Verifying performance across multiple systems

Urbanization causes fundamental shifts in hydrologic partitioning within watersheds, leading to excess runoff being quickly routed to nearby conveyances. This leads to a host of concerns, from flooding to water quality impairments. To combat these effects, bioretention systems are implemented to restore more natural hydrology in the urban environment. To better understand and predict the effectiveness of these interventions, there is a need for reliable hydrology models to assess the performance of bioretention cells prior to installation. DRAINMOD-Urban was recently developed to produce hydrographs with a high temporal resolution, showing substantial promise during initial testing. Unfortunately, the dataset originally used for testing was limited, having minimal occasions of overflow and only consisting of one bioretention location. To achieve a more robust analysis of the model, DRAINMOD-Urban was evaluated using two years of monitoring data for four bioretention cells in North Carolina. The modeled bioretention cells had variable media depths, surface storage volumes, site conditions, and propensity for overflow. DRAINMOD-Urban model parameters were calibrated for a Nash-Sutcliff efficiency (NSE) from 0.14 to 0.60 for drainage and from 0.49 to 0.89 for overflow across the sites using six months of monitoring data. Model validation confirmed these results, producing drainage and overflow hydrographs with accurate timing, duration, and a range of NSEs from 0.19 to 0.60 and from 0.49 to 0.81, respectively, across the four sites. Model performance varied across sites; high drainage and overflow rates are well predicted compared to extended low rates caused by clogging issues or small storms. This study highlights the potential of DRAINMOD-Urban in modeling bioretention hydrology at a fine temporal scale under varying design configurations.

ST3DNetCrime: Improved ST-3DNet Model for Crime Prediction at Fine Spatial Temporal Scales

Crime prediction is crucial for sustainable urban development and protecting citizens’ quality of life. However, there exist some challenges in this regard. First, the spatio-temporal correlations in crime data are relatively complex and are heterogenous in time and space, hence it is difficult to model the spatio-temporal correlation in crime data adequately. Second, crime prediction at fine spatial temporal scales can be applied to micro patrol command; however, crime data are sparse in both time and space, making crime prediction very challenging. To overcome these challenges, based on the deep spatio-temporal 3D convolutional neural networks (ST-3DNet), we devise an improved ST-3DNet framework for crime prediction at fine spatial temporal scales (ST3DNetCrime). The framework utilizes diurnal periodic integral mapping to solve the problem of sparse and irregular crime data at fine spatial temporal scales. ST3DNetCrime can, respectively, capture the spatio-temporal correlations of recent crime data, near historical crime data and distant historical crime data as well as describe the difference in the correlations’ contributions in space. Extensive experiments on real-world datasets from Los Angeles demonstrated that the proposed ST3DNetCrime framework has better prediction performance and enhanced robustness compared with baseline methods. In additon, we verify that each component of ST3DNetCrime is helpful in improving prediction performance.

Piscine predation rates vary relative to habitat, but not protected status, in an island chain with an established marine reserve

Establishing marine reserves can increase biomass and diversity relative to surrounding areas. However, such changes presumably alter species compositions, interactions, and associated demographic processes such as predation. We investigated relative predation pressure by fish inside and outside of a well-established no-take reserve using standardized predation tether units: Squidpops. We deployed Squidpops (N = 990) monitored by cameras to examine predation, as estimated by consumption rates, between paired seagrass and patch reef habitat sites proximate to the Exuma Cays Land and Sea Park, a well-enforced no-take Bahamian reserve since 1986. Surprisingly, there was no significant park effect on consumption nor observed diversity. Significantly higher consumption rates were found at patch reef sites relative to seagrass sites, occurred in association with higher fish diversity and with longer soak times. Observed fish diversity was predicted by habitat and distance inshore with more species found on patch reefs and further from the deep water Exuma Sound. Recorded fish bites were positively associated with patch reef habitat, with reef dwelling fish, and increased as the species became more commonly encountered. Deployment-specific factors, including temperature, depth, and time of day had little impact on measured predation, an expected result as the experiments occurred in similar locations over a fine temporal scale. In our experiment, ecosystem-based factors outweighed the place-based management effects that we expected from being within the oldest well-enforced no-take marine reserve in the Caribbean versus the surrounding actively fished waters. Despite well-documented increases in abundances across trophic levels from primary consumers to apex predators within the reserve, predation rates were not significantly different than adjacent areas. Evaluating the efficacy of a marine reserve in protecting vital ecosystem processes requires studies beyond abundance and diversity surveys. By focusing on predation on two of the most ubiquitous habitats throughout the region and on common species, rather than on exceptional sites and charismatic species, we reveal a process that seems relatively unchanged by strict marine conservation management.

Coral reef erosion: In situ measurement on different dead coral substrates on a Caribbean reef

AbstractWidespread mortality of reef‐building coral substantially reduces the capacity for reef growth and makes available extensive bare substrate areas that in the absence of coral recovery will be eroded by a variety of external and internal bioeroders. Here, we analyze rates of external erosion on six different types of carbonate substrates under in situ conditions over a 2‐yr period. We measure vertical changes in the surface elevation of four species of recently dead corals afflicted by the stony coral tissue loss disease outbreak, and other two common types of calcareous substrates, long‐dead Acropora palmata fronds and bare calcareous hardground, as a reference for “bare” carbonate substrates that occur widely in Caribbean reefs. The surface of the recently dead colonies experienced significant erosion after 2 yr of exposure, but at different rates depending on the species. Dead skeletons of Orbicella faveolata experienced the greatest rates of erosion after 2 yr at −9.9 mm (±3.2 mm); Dendrogyra cylindrus eroded −3.6 mm (±2.8 mm), Pseudodiploria strigosa −3.3 mm (±3.7 mm), and Siderastrea siderea −1.2 mm (±0.9 mm), while long‐dead substrates remained unchanged. There was significant erosion in the presence of parrotfish grazing scars and of short algal turf mats, while crustose coralline algae cover and sand‐and‐high turf mats were not associated with significant changes in elevation, arguably indicating a protective effect. This study provides new insights into how and at what rates external carbonate erosion is shaping contemporary reefs at fine spatial and temporal scales.

On the move: spatial ecology and habitat use of red fox in the Trans-Himalayan cold desert.

Red fox (Vulpes vulpes) is the most widespread wild carnivore globally, occupying diverse habitats. The species is known for its adaptability to survive in dynamic anthropogenic landscapes. Despite being one of the most extensively studied carnivores, there is a dearth of information on red fox from the Trans-Himalayan region. We studied the home range sizes of red fox using the different estimation methods: minimum convex polygon (MCP), kernel density estimator (KDE), local convex hull (LoCoH) and Brownian-bridge movement model (BBMM). We analysed the daily movement and assessed the habitat selection with respect to topographic factors (ruggedness, elevation and slope), environmental factor (distance to water) and anthropogenic factors (distance to road and human settlements). We captured and GPS-collared six red fox individuals (three males and three females) from Chiktan and one female from Hemis National Park, Ladakh, India. The collars were programmed to record GPS fixes every 15-min. The average BBMM home range estimate (95% contour) was 22.40 ± 12.12 SD km2 (range 3.81–32.93 km2) and the average core area (50% contour) was 1.87 ± 0.86 SD km2 (range 0.55–2.69 km2). The estimated average daily movement of red fox was 17.76 ± 8.45 SD km/d (range 10.91–34.22 km/d). Red fox significantly selected lower elevations with less rugged terrain and were positively associated with water. This is the first study in the Trans-Himalayan landscape which aims to understand the daily movement of red fox at a fine temporal scale. Studying the movement and home range sizes helps understand the daily energetics and nutritional requirements of red fox. Movement information of a species is important for the prioritisation of areas for conservation and can aid in understanding ecosystem functioning and landscape management.

Food availability alters community co-occurrence patterns at fine spatiotemporal scales in a tropical masting system.

Patterns of co-occurrence among species can help reveal the structure and assembly of ecological communities. However, studies have been limited by measuring co-occurrence in either space or time but not both simultaneously. This is especially problematic in systems such as masting forests where resources are highly variable, meaning that spatial use and co-occurrence patterns can change on fine spatiotemporal scales. We develop an analytical framework for assessing species co-occurrence at fine spatial and temporal scales simultaneously and apply these models to a camera trapping dataset from Borneo. We sought to determine how substantial variation in food availability across space and time affects co-occurrence among terrestrial vertebrates. We detect many significant, mostly positive, co-occurrence patterns among species, but almost entirely in unlogged forest and during dipterocarp mast years. The most strongly co-occurring pair of species, bearded pig (Sus barbatus) and sambar (Rusa unicolor), only positively co-occur in areas and years when fruit is locally abundant. Species occurrences in logged forest and non-mast years are mostly random with respect to other species. This suggests that frugivore-granivore species positively co-occur when resources are plentiful (i.e., large trees are present and fruiting), likely because they use the same resources; these patterns disappear when food availability is lower. Our approach demonstrates the utility of measuring co-occurrence in space and time together and highlights the importance of resource abundance for driving the co-occurrence structure of communities. Furthermore, our method could be broadly applied to other systems to assess fine-scale spatiotemporal patterns across a range of taxa.

Sailing synthetic seas: Stochastic simulation of benchmark sea state time series

Coastal and offshore engineering relies on the analysis of sea state parameters, such as significant wave height ( H m 0 ), zero-crossing mean wave period ( T m 02 ), and mean wave direction ( Θ m ). Since observed records of these parameters usually span only a few years, proper uncertainty assessment requires the simulation of unobserved but equally plausible time series. This study suggests a simple stochastic method, named SyntheSeas, to generate synthetic sequences that preserve marginal distributions and power spectra along with power cross-spectra of H m 0 , T m 02 , and Θ m . SyntheSeas is a tailored version of the multivariate Iterative Amplitude Adjusted Fourier Transform (IAAFT) method, and has several desirable properties: (i) it relies on minimal assumptions, (ii) it accounts for the limiting steepness condition that constrains the relationship between H m 0 and T m 02 without using ad hoc parametrisation, and (iii) it accounts for the modelling problems due to the circular behaviour of Θ m with satisfactory approximation. Thanks to its simplicity and transparency, SyntheSeas (i) allows the identification of the key properties required to simulate realistic time series of H m 0 , T m 02 , and Θ m , (ii) provides a benchmark to test parametric models and their components, and (iii) enables quick applications, such as preliminary uncertainty and sensitivity analyses, without requiring advanced expertise in stochastic modelling. As a proof of concept, we discuss an application to data recorded from four wave buoys deployed around the United Kingdom. • Fourier-based simulation of sea state time series at fine temporal scales. • Preserving distributions, power cross-spectra, and limiting steepness condition. • Introducing synthetic sea state time series to validate alternative models’ output.

Resource amount and discontinuity influence flight and reproduction in Hippodamia convergens (Coleoptera: Coccinellidae)

AbstractIndustrial‐scale agriculture creates a mosaic of large monocultures in the landscape, where seasonal cropping cycles generate discontinuous resource availability for insect predators both spatially and temporally. In this environment, selection will favor predator movement and reproductive behaviors that optimize the location and effective utilization of resource (prey) pulses that are both patchy and ephemeral in nature. Using a model system to study predator movement and reproduction, we tested how discontinuous periods of food resource access that mimic fluctuating resource populations (aphids) would influence flight behavior and reproduction of a highly mobile predator, Hippodamia convergens (convergent lady beetle), and possibly modify energetic trade‐offs between these behaviors. Adult beetles were provided either short (3 h) or long (6 h) food pulses daily (continuous availability) or short (6 h) or long (12 h) food pulses every other day (discontinuous availability). We measured preoviposition period, fecundity, and fertility during an 18‐day oviposition period, and female tethered flight activity (3 h) before and after the oviposition period. We found that discontinuous food access delayed the onset of oviposition in the high food quantity treatment; fewer females laid eggs overall, and 18‐day fecundity was lower compared with continuous provision of the same food quantity. A longer preoviposition period was associated with fewer reproductive days and lower fitness. Flight distance and fecundity were negatively correlated, suggesting that energetic expenditure in flight can deplete energetic reserves otherwise used for subsequent reproduction. The negative effects of discontinuous resource access at fine temporal scales reveal how gaps in resource availability could influence lady beetle population dynamics and their ecosystem services within the agricultural landscape.

Utilising Sentinel-1’s orbital stability for efficient pre-processing of sigma nought backscatter

For already more than seven years, the Sentinel-1 C-band Synthetic Aperture Radar (SAR) mission has been providing indispensable information for monitoring bio-geophysical parameters at fine temporal and spatial scales. As many applications require backscatter datacubes as input, enormous amounts of data have to be radiometrically and geometrically corrected to be in a common, Earth-fixed reference system. Pre-processing workflows accomplishing this task have already been established and are implemented in several software suites. However, typically, these workflows are computationally expensive which may lead to prohibitively large costs when generating multi-year Sentinel-1 datacubes for whole continents or the world. In this paper, we discuss existing approaches for generating sigma nought and projected local incidence angle (PLIA) data and present simplifications of the overall workflow relying on the unprecedented orbital stability of Sentinel-1. Propagating orbital deviations through the complete Sentinel-1 pre-processing pipeline helped us to simulate and identify PLIA as a static layer per relative orbit. The outcome of these simulations also provided the necessary information to replace iterative root-finding algorithms for determining the time of closest approach (TCA), i.o.w. the azimuth index, with a linear one — at no expense of radiometric accuracy. All experiments were performed using an in-house developed toolbox named wizsard, which made it possible to speed up Sentinel-1 pre-processing by approximately 4–5 times with respect to the Sentinel Application Platform (SNAP). This could pave the way for producing quality-curated, large-scale backscatter datacubes at continental and global scales in acceptable time frames.

Catchment response to intense rainfall: Evaluating modelling hypotheses

AbstractFloods resulting from high‐intensity rainfall events are known to be difficult to simulate. The catchment response to such events is very heterogeneous due to complex combinations of hydrological processes at fine temporal and spatial scales. The goal of this study is to find a way to inform the structure of a hydrological model on the variability in catchment response to rainfall events. To that end, rainfall intensity was used as a proxy for the activation of fast heterogeneous runoff processes. We developed three hypotheses that increase the versatility of a hydrological model by modifying the volume and temporal distribution of effective rainfall when high‐intensity rainfall events occur. These modifications were implemented within the GR5H lumped rainfall–runoff model. The different model versions were run on 229 French catchments where 10 652 flood events were selected. Model performance was assessed considering five groups of catchments, and model performance was also evaluated based on three event characteristics. Results showed that introducing a dynamic dependency of fluxes to rainfall intensities at the hourly time step helps to improve the simulation of floods, especially on Mediterranean catchment areas. Generic values of the additional parameters are proposed to limit the increase in calibration complexity.

Globally assessing the hysteresis between sub-diurnal actual evaporation and vapor pressure deficit at the ecosystem scale: Patterns and mechanisms

• Magnitude of the sub-diurnal AET - VPD hysteresis varies with biomes and climates. • Variation of the hysteresis is mostly attributable to evaporative demand limitation. • Soil moisture supply limitation amplifies the hysteresis during the dry season. • We provide some novel features to diagnose limiting mechanisms of the hysteresis. Hysteresis between sub-diurnal actual evaporation ( AET ) (or one of its components, transpiration) and vapor pressure deficit ( VPD ) at the species or individual ecosystem level has been extensively studied, but the global variation and seasonal variability of this hysteresis across biomes and climates is yet to be fully explored and the limiting mechanisms remain unclear. We hypothesize that the sub-diurnal AET - VPD hysteresis results from the interplay between evaporative demand and soil moisture supply limitations. To test our hypothesis, we quantify the sub-diurnal AET - VPD hysteresis across a broad range of biomes and climates based on the observations from the 89 FLUXNET sites (703 site-years) across the globe. We find that the magnitude of hysteresis varies with biomes and climates and is mostly attributable to evaporative demand limitation in all ten sampled biomes. In seasonally dry locations, however, low soil moisture availability amplifies the hysteresis during the dry season. Sensitivity analysis using a hydraulic model suggests that most ecosystems exhibiting seasonal drought display a more isohydric behavior during the dry season, while shift toward a more anisohydric response during the wet season. Our findings have important implications for understanding sub-diurnal dynamics between vegetation and its surrounding environment, reducing uncertainties in AET simulation at fine spatial and temporal scales, and improving understanding of the ecosystem response to hydrologic stress.

Human choices, slope and vegetation productivity determine patterns of traditional alpine summer grazing

Grazing behaviour influences animal productivity and the conservation of grassland ecosystem services. We used GPS tracking and remote sensing (NDVI index) to monitor the grazing patterns of lactating cows on the ‘Malga Ombretta’ summer farm (1,957 m asl) in the Dolomites, eastern Italian Alps, from 5th July to 5th August 2018. The pasture area (35 ha) was grazed by a mixed herd of Simmental and Alpine grey cows (stocking density = 0.6 LU/ha) under traditional management: each morning the farmer led the cows to graze in a selected sub-area of pasture, and during the afternoon he left them free to graze unrestricted until they returned to the barn for the night. GPS positions were collected every minute from 9 Simmental and 4 Alpine Grey cows with low milk production during the time they were outdoors. The farmer’s choice of where to drive the herd to graze in the morning determined the distances the cows walked/day, which varied from 2.0 to 8.9 km, and favoured the use of higher and steeper areas that the cows tended otherwise to avoid. When free in the afternoon, the cows selected areas with higher NDVI values than those selected by the farmer in the morning, and Alpine Grey cows used slightly higher slopes and altitudes than Simmental cows, suggesting better adaptation to mountain pastures. The study revealed highly heterogenous grazing patterns dependent on multiple factors that can be assessed at fine temporal and spatial scales using GPS and remote sensing technologies to improve grazing management. HIGHLIGHTS Daily distances walked and grazing patterns were influenced differently by the farmer’s decisions and the animals’ choices in response to environmental features. The NDVI index of vegetation productivity suggested that cows grazed more productive areas when free than when driven by the farmer. GPS tracking and remote sensing shed light on how human and animal choices regarding grazing are influenced by environmental features.

Large-scale PVA modeling of insects in cultivated grasslands: The role of dispersal in mitigating the effects of management schedules under climate change.

In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60‐year periods (2020–2079) on a fine temporal (daily) and high spatial (250 × 250 m2) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.

Machine learning techniques to characterize functional traits of plankton from image data.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab‐based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Dead-Reckoning Configurations Analysis for Marine Turtle Context in a Controlled Environment

In the past few years, dead-reckoning (DR) has been frequently used to estimate the trajectory of marine animals at a fine temporal scale using bio-logger devices. The precision of the swim sequence trajectory estimation depends on various accumulated errors from external forces, sensors and computation. Trajectory accuracy is hard to estimate due to the difficulty of collecting precisely-known underwater positions. In this paper, we aim at estimating this accuracy at a fine temporal scale using a reference system for positioning. This work focuses on how each sensor frequency and algorithm used for the DR affect trajectory accuracy and the global power consumption of the bio-logger. We develop a dual GPS Real Time Kinematic (RTK) system offering us reference trajectories with 2 cm accuracy on position and 1.6° on heading. The DR algorithms use 3-axis Inertial Measurement Unit (IMU), depth and speed sensor data for orientation and speed determination. For the experimental tests, the GPS module and the bio-logger are attached to a swimmer doing breaststroke imitating turtle movement for different swim sequences between 15 and 40 minutes. Power consumption of the electronics is measured during laboratory tests. Results show that using an adapted speed sensor and correcting for marine current, even roughly, provide us with the best gain in accuracy. The use of the gyroscope or high-frequency sampling of sensors does not increase the accuracy of the trajectory reconstruction to a level that would be critical for slow moving marine animal applications.

Applications of low-cost environmental monitoring systems for fine-scale abiotic measurements in forest ecology

Ecological studies have long examined large-scale geographic gradients in abiotic conditions and their relationship to the structure and function of ecological systems, but many critical processes in forested systems are driven by abiotic gradients that vary at fine spatial and temporal scales. To adequately characterize fine scale microclimatic variability, intensive sampling is required that may be cost-prohibitive with commercially available instrumentation. The expanded availability of inexpensive, and open-source environmental monitoring systems may meet the need to advance mechanistic understanding of fine-scale ecological processes. Here, we (1) present a custom, open-source, and inexpensive environmental monitoring system, (2) evaluate its performance against commercial systems and sensors, and (3) demonstrate its utility in a broad range of forest ecology applications. We demonstrate that temperature and humidity measurements are reliably captured with open-source data loggers and sensors are strongly correlated to research-grade instruments (R2 = 0.97). Further, these systems generate reliable data at 13-80% of the cost of comparable commercial systems primarily due to higher potential for scalability. We demonstrate applications in forest ecology to examine micrometeorology in fire prone ecosystems, microsite variability in dry conifer systems, and climate mediation effects in urban forested systems. The use of open-source data loggers for a broad range of forest ecology applications offer opportunities for more robust environmental characterization especially in forest ecology applications where high spatial and temporal resolution is necessary to understand ecological phenomena such as fire, regeneration, and phenology. Increased use, development, and validation of low-cost instrumentation with commercial options will increase confidence of their use among researchers in these and other applications.

Condition‐dependent immune function in a freshwater snail revealed by stable isotopes

Abstract The immune system is costly to maintain and use because it requires a lot of energy. This can make parasite resistance dependent on host nutritional state. The dependence of immune function on host condition can have broad ecological (e.g., disease dynamics) and evolutionary (e.g., expression of trade‐offs related to parasite resistance) consequences. Research on the dependence of immune function on host condition is typically conducted in laboratory experiments that manipulate either the quantity or composition of available resources. Such studies are essential in establishing conceptual frameworks, but their results are difficult to generalise to natural populations because the experimental treatments may deviate from natural variation in host resource level and use. We examined the condition dependence of immune function in a generalist freshwater snail Lymnaea stagnalis by relating the activity of two immune parameters of snail haemolymph, phenoloxidase (PO)‐like and antibacterial activity, to snail resource level and use using field‐collected individuals. We measured several variables that reflect the snails’ quality based on their recent (i.e., within the past few days; amount and stable isotope composition [δ15N and δ13C] of produced faeces) and longer‐term (i.e., weeks to months; stable isotope composition of tissues) resource use. The PO‐like activity of the snails’ haemolymph was condition‐dependent. Snails that had recently consumed food from higher trophic levels, presumably including more animal protein (high δ15N values of faeces), had a stronger defence. Additionally, snails with low energy (i.e., lipid) reserves in their tissues (high δ13C values of tissues) showed higher PO‐like activity. The antibacterial activity of the snails’ haemolymph was not condition dependent. The finding of the importance of the composition of recently consumed food on immune function (namely PO‐like activity) suggests that the parasite resistance of snails may change rapidly depending on the type of resources available in their environment. Thus, environmental variation may influence the outcome of host–parasite interactions on fine spatial and temporal scales. Furthermore, the negative relationship between the snails’ energy reserves and PO‐like activity suggests substantial energetic costs of immune activity in L. stagnalis.

Relationship of leaf elongation rate of young wheat leaves, gross primary productivity and environmental variables in the field with hourly and daily temporal resolution

Plant growth is controlled by an interplay of internal and external factors. The production of biomass via photosynthesis is dependent on the plant response to environmental variables such as temperature, vapour pressure deficit and light intensity. Short-term responses of plant growth to these variables at fine temporal scales of hours are not well investigated, especially under field conditions. The present study explores the relationship between leaf elongation rate (LER) of young wheat leaves in the field in very high temporal resolution (minutes). Turbulent fluxes of CO2 were measured with the eddy covariance technique and used to derive GPP, and environmental variables such as air and soil temperature, short wave radiation and vapour pressure deficit were simultaneously measured.The analysis revealed the importance of different variables on different temporal scales (hourly, daily). On an hourly scale, GPP and shortwave radiation explain most of the variance of LER, however on a daily scale, air temperature is the main driver. A cross-correlation analysis confirmed that the strongest immediate relationship can be found between LER and GPP and incoming shortwave radiation; variables that are determining photosynthesis. In principal, LER also shows the same diurnal patterns as air temperature and soil temperature, however air and soil temperature lag behind LER. Multivariate growth models show that combinations with GPP or incoming shortwave radiation and air temperature perform best. These results indicate that short term growth processes in young wheat leaves in the field are mainly controlled by incoming shortwave radiation, while the magnitude of growth is controlled by temperature.

High-resolution observations of submarine groundwater discharge reveal the fine spatial and temporal scales of nutrient exposure on a coral reef: Faga'alu, AS

High-resolution observations of submarine groundwater discharge reveal the fine spatial and temporal scales of nutrient exposure on a coral reef: Faga'alu, AS

Visually aligned sound generation via sound-producing motion parsing

The task of generating natural sounds from videos is still challenging because the generated sounds should be highly temporal-wise aligned with visual motions. To reach this goal, the model needs to extract the discriminative visual motions correlated to the corresponding sound. In this paper, we propose a novel method of sound-producing motion parsing to explore the discriminative temporal visual embedding, which can distinguish the sound-producing motion from still to facilitate the mapping from visual motion to the corresponding sound. In the proposed method, we first extract the time-redundant visual embedding in a sliding temporal window through video frames to better distinguish the transient visual motion from complex background information. Subsequently, a series of temporal regulators are performed to capture the various tempo-scales of visual motions, and then a cross-modal temporal aligner is introduced to align the visual and sound embeddings in finer temporal scale. Finally, the visual embedding is affined and upsampled to ensure that the generated sound is consistent with real one in the resolution scale. Furthermore in order to make the model more interpretable, we leverage the gradient flowing into the bottleneck layer to produce a coarse temporal activation map, highlighting the important temporal cues in the visual embedding for the sound prediction. To evaluate the effectiveness of our approach, we conduct several experiments on the generated sounds. Extensive evaluation results demonstrate that the proposed method can improve the temporal-wise alignment significantly and obtain the competitive results in sound quality as well. Code will be released here.