Small-scale Variability Research Articles

NC92Soil: A computer code for deterministic and stochastic 1D equivalent linear seismic site response analyses

The extensive evaluation of the impact of local seismo-stratigraphic configurations on seismic ground motion presents significant challenges due to the necessity of considering the combined effects of uncertainty and small-scale lateral variability of the relevant parameters. To effectively explore these sources of uncertainty, a new Python-based computer program is proposed for one-dimensional seismic site response simulations, adopting the equivalent linear viscoelastic approach in the frequency domain. With respect to existing software, the code introduces new pre- and post-processing features, which also meet the specific requirements of seismic microzonation studies. Within the code, the complete spectrum of uncertainties related to local seismo-stratigraphic configurations, including lithotype successions, layer thicknesses, and seismic and geotechnical properties for the considered lithotypes, is managed by considering user-defined constraints and statistical properties of the relevant parameters. Additionally, a batch approach is offered, enabling the application of the procedure to an unlimited number of different scenarios. To demonstrate the potentiality of the proposed code, a comprehensive set of 90,000 local seismic site response analyses was conducted, showing a clear correlation between the amplification factors, the mean shear wave velocity in the upper 30 m, the fundamental frequency of the deposit and the depth to the seismic bedrock.

Using microdialysis with a deuterium oxide tracer to estimate water exchange, water content and active surface area of the probe

Microdialysis is a useful tool for measuring in situ fluxes of soil compounds with minimal disturbance of soil structure and function. Fluxes of sampled compounds are commonly calculated per unit of membrane surface area, assuming that the entire membrane surface is capable of exchange – which is unlikely given varying soil moisture and the occlusion of membrane pores by the soil solid phase. We present a method to quantify the degree of connectivity of the microdialysis probe membrane to the surrounding soil by means of water exchange between a microdialysis perfusate and soil solution using deuterium (2H2O; equilibrated to DHO) as an internal standard. We applied the method to a range of probe membrane surface areas and soil moisture conditions to generate empirical models that estimate membrane surface area active in exchange. Our results suggest that even in a saturated sandy soil, active membrane surface areas reach only 40.3% of the probe surface area, perhaps due to occlusion by soil particles. However, when accounting for volumetric water content of the soil, active surface areas approached 80–90% of the area likely in contact with water, indicating that sampling efficiency of water-filled pores may still be high, particularly at slow flow rates. Furthermore, our method enables assessment of local soil water content around the probe. Models estimating soil water content were applied to field measurements of DHO exchange in three soil horizons (Organic, B1, B2) at two boreal sites, and in situ estimates were similar to those from conventional soil moisture methods when models were calibrated with the same soil type. We present DHO exchange as a powerful method for improving microdialysis flux interpretations in future studies, and for exploring small-scale water variability in relatively undisturbed soils.

Ultra-high NA optical image differentiator based on dielectric metasurfaces

Metasurface-based optical differentiators have recently attracted attention for their potential advantages in real-time and high-throughput image processing technology. However, the existing differentiators suffer from limitations in numerical aperture (NA). Here, we propose a differential metasurface based on silicon clusters covered with polydimethylsiloxane, achieving a remarkable NA of 0.7. We numerically demonstrate the proposed differentiator can perform second-order differentiation on a 1D spatial function and high NA can accurately compute smaller-scale variations. We further demonstrate its ability to achieve edge detection on 2D images. Our results advance the development of ultra-high numerical aperture optical differentiator and provide new opportunities for image processing.

Dissecting a 30 kpc galactic outflow at z ~ 1.7

ABSTRACT We present the spatially resolved measurements of a cool galactic outflow in the gravitationally lensed galaxy RCS0327 at z ≈ 1.703 using VLT/MUSE IFU observations. We probe the cool outflowing gas, traced by blueshifted Mg ii and Fe ii absorption lines, in 15 distinct regions of the same galaxy in its image-plane. Different physical regions, 5 – 7 kpc apart within the galaxy, drive the outflows at different velocities (Vout ∼ −161 to −240 km s−1), and mass outflow rates ($\dot{M}_{out} \sim 183$ – 527 ${\rm M}_{\odot }\, \mathrm{yr}^{-1}$). The outflow velocities from different regions of the same galaxy vary by 80 km s−1, which is comparable to the variation seen in a large sample of star-burst galaxies in the local universe. Using multiply lensed images of RCS0327, we probe the same star-forming region at different spatial scales (0.5–25 kpc2), we find that outflow velocities vary between ∼ −120 and −242 km s−1, and the mass outflow rates vary between ∼37 and 254 ${\rm M}_{\odot }\, \mathrm{yr}^{-1}$. The outflow momentum flux in this galaxy is ≥ 100% of the momentum flux provided by star formation in individual regions, and outflow energy flux is ≈ 10% of the total energy flux provided by star formation. These estimates suggest that the outflow in RCS0327 is energy driven. This work shows the importance of small scale variations of outflow properties due to the variations of local stellar properties of the host galaxy in the context of galaxy evolution.

Spatial variation in key functional traits of Mediterranean fucoid algae: Insights from Cystoseira sensu lato intertidal canopies

Cystoseira sensu lato are fucoid algae that form dense stands on intertidal and subtidal rocky reefs sustaining species-rich associated assemblages. The increasing human pressure is causing the decline of these marine forests, raising wide concerns on the ecological consequences of their loss. Yet, little is known about functional trait variables of Cystoseira s.l. species, which are essential to a deeper understanding of their contribution to the functioning of coastal ecosystems. We analysed the intraspecific spatial variation of the total organic matter, Corg, N and P contents in Ericaria amentacea from intertidal rocky shores in the W Mediterranean Sea. Specifically, we quantified spatial patterns of variation of traits at large (100s km), small (1000s m), and local (100s cm) scale. We also explored potential interspecific variation by comparing the combined functional profile of trait variables between E. amentacea and Cystoseira compressa, an often co-occurring or vicariant species. Tissue contents of organic matter, Corg, N and P, were consistent among E. amentacea stands, supporting the hypothesis of a large-scale (100s km) spatial homogeneity of such key traits in this species. Overlapping functional profiles between E. amentacea and C. compressa also suggested putative interspecific trait congruencies. However, a small-scale (1000s m) significant variability was found for all trait variables in E. amentacea. Variance components at small (1000s m) and local (100s cm) scale accounted for the largest contribution to the total spatial variation for all traits, recommending caution in the use of small and local-scale trait values to generalize functional performances of Cystoseira s.l. forests over large areas. This study represents one of the first attempts to shed light on the variability of key functional attributes of Cystoseira s.l. species at a range of spatial scales, which could assist more reliable assessments of their functional role and improve their management and conservation.

Retrieval of sub-kilometer resolution solar irradiance from Fengyun-4A satellite using a region-adapted Heliosat-2 method

It is, now, universally accepted that modern solar resource assessment should proceed with acquiring satellite-derived irradiance; the underlying problem is one of retrieval. The Advanced Geostationary Radiation Imager (AGRI), which is one of the main payloads of China’s latest-generation geostationary satellite series, namely, Fengyun-4 (FY-4), offers such an opportunity, albeit its full potential remains largely unexplored. On this account, a region-adapted semi-empirical model based on Heliosat-2 is herein developed to estimate global horizontal irradiance (GHI) at the native resolution of FY-4 satellite (0.5 km, 15 min), using AGRI reflectance measurement at 640 nm. The adaptation of Heliosat-2 parameters to China’s climatology and geography is based on a research-grade ground-based radiometry network with 38 stations evenly distributed across the country. Model validation is conducted against ground-based observations made at 34 unseen stations, over the course of one year (2018). As compared to the 5-km Himawari-8 radiation product, the developed product not only has a 10-fold refinement in resolution, which can clearly depict those small-scale variations in solar resources that are not observable from the Himawari-8 product, but also attains a substantially lower bias (1.4% versus 7.6% under clear skies and –0.3% versus 9.5% under cloudy skies). This ultra-high-resolution product is of vital importance to solar resource assessment on a scale consistent with the size of typical utility-scale photovoltaic plants. The product is also of great value for agricultural and ecological studies, which often depends upon high-quality solar radiation at a high spatio-temporal resolution.

Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia

In this work, we perform the recalibration of Pan-STARRS1 (PS1) photometry by correcting for position-dependent systematic errors using the spectroscopy-based stellar color regression (SCR) method, the photometry-based SCR method, and the Gaia BP/RP synthetic photometry method. We confirm the significant large-scale and small-scale spatial variation of the magnitude offsets for all the grizy filters. We show that the PS1 photometric calibration precisions in the grizy filters are around 5–7 mmag when averaged over 14′ regions. We note a much larger calibration error up to 0.04 mag in the Galactic plane, which is probably caused by the systematic errors of the PS1 magnitudes in crowded fields. The results of the three methods are consistent with each other within 1–2 mmag or better for all the filters. We provide 2D maps and a Python package to correct for position-dependent magnitude offsets of PS1, which can be used for high-precision investigations and as a reference to calibrate other surveys.

Influence of small-scale spatial variability of soil properties on yield formation of winter wheat

BackgroundWith the increasing development of sophisticated precision farming techniques, high-resolution application maps are frequently discussed as a key factor in increasing yield potential. However, yield potential maps based on multiple soil properties measurements are rarely part of current farming practices. Furthermore, small-scale differences in soil properties have not been taken into account.MethodsTo investigate the impact of soil property changes at high resolution on yield, a field trial has been divided into a sampling grid of 42 plots. The soil properties in each plot were determined at three soil depths. Grain yield and yield formation of winter wheat were analyzed at two sites.ResultsMultiple regression analyses of soil properties with yield measures showed that the soil contents of organic carbon, silt, and clay in the top and subsoil explained 45–46% of the variability in grain yield. However, an increasing clay content in the topsoil correlated positively with grain yield and tiller density. In contrast, a higher clay content in the subsoil led to a decrease in grain yield. A cluster analysis of soil texture was deployed to evaluate whether the soil´s small-scale differences caused crucial differences in yield formation. Significant differences in soil organic carbon, yield, and yield formation were observed among clusters in each soil depth.ConclusionThese results show that small-scale lateral and vertical differences in soil properties can strongly impact crop yields and should be considered to improve site-specific cropping techniques further.

Estimation and characterisation of the wave-induced turbulent kinetic energy and turbulent dissipation from ADCP data

Turbulence in the water flow causes small-scale variations in the mechanical stress acting on submerged tidal turbines. As such it increases their fatigue loading and impacts greatly their lifetime. It is therefore essential for engineers to have an accurate knowledge and characterisation of turbulence at a given site as they design the structures to be deployed. The strength of the tidal currents is the main parameter influencing the intensity of turbulence through their friction with the sea bed. However, most potential tidal energy sites are located in a coastal environment with shallow enough water depths so that the direct impact of waves on turbulence can not be overlooked. Steepness-induced wave breaking is indeed observed to increase the turbulent mixing for such applications. In this context, we propose to estimate the contribution of surface processes to the total turbulence in Alderney Race, France, the most energetic tidal site in western Europe. The turbulent kinetic energy (TKE) specifically induced by waves and wind is characterised using measurements from a 5-beams ADCP deployed between 27/02/2018 and 06/07/2018.Analytical profiles are fitted to the data, the only fitting parameter of the model is an evaluation of the turbulence penetration depth, it determines how deep surface processes impact the water column. Its dependence towards mean wave and current parameters is studied. The results do not allow to conclude on the nature of turbulence observed in the mid water column.

Observations and simulations of caustic formation due to oceanographic fine structure.

An at-sea experiment in deep water was conducted to explore the impact of small-scale sound-speed variability on mid-frequency (1-10 kHz) acoustic propagation. Short-range (1-5 km) acoustic transmissions were sent through the upper ocean (0-200 m) while oceanographic instruments simultaneously measured the ocean environment within 2 km of the single upper turning points of the acoustic transmissions. During these transmissions, acoustic receptions over a 7.875 m vertical line array show closely spaced, sometimes interfering arrivals. Ray and full-wave simulations of the transmissions using nearby sound-speed profiles are compared deterministically to the received acoustic signals. The sensitivity of the acoustic arrivals to the vertical scales of ocean sound speed is tested by comparing the observed and simulated arrival intensity where the sound-speed profile used by the simulation is smoothed to varying scales. Observations and modeling both suggest that vertical fine-scale structures (1-10 m) embedded in the sound-speed profile have strong second derivatives which allow for the formation of acoustic caustics as well as potentially interfering acoustic propagation multipaths.

Inversion géostatistique par itérations de la tomographie de résistivité électrique

AbstractElectrical resistivity tomography (ERT) is a geophysical method used to create an image of the subsurface due to its sensitivity to porosity, water saturation, and pore fluid salinity. This geophysical method has been widely applied in the investigation of mineral and groundwater resources, as well as in archaeological, environmental, and engineering studies. The prediction of subsurface properties, such as electrical conductivity, from measured ERT data requires solving a challenging geophysical inversion problem. This work proposes an iterative geostatistical resistivity inversion method using stochastic sequential simulation and co-simulation as stochastic model perturbation and update techniques. Electrical resistivity models are generated conditioned to a target histogram, often retrieved from available resistivity borehole data, and assuming a spatial continuity pattern described by a variogram model. From the electrical resistivity models, a finite-volume approximation of Poisson’s equation is used to compute synthetic ERT data. The misfit between predicted and observed data drives the convergence of an iterative procedure and conditions the co-simulation of new models in the subsequent iterations. This methodology is applied to a two-dimensional synthetic case, and a set of two-dimensional profiles obtained from an ERT survey carried out in southern Portugal. In both application examples, the final models predict ERT data that match the observed ones while reproducing borehole data and imposed variogram models. The results obtained in both data sets are compared against a commercial deterministic ERT inversion methodology, showing the ability of the proposed method to model small-scale variability and assess spatial uncertainty.

Temporal and small-scale spatial variation in spatfall of the mussel Mytilus edulis platensis: Basis for culture management at San Jorge Gulf, Patagonia Argentina

Despite the commercial potential of mussel populations along the Patagonian coast of Argentina, studies on mussel farming and fisheries to the south of parallel 42° S are clearly insufficient thus far. In this study, variations in mussel settlement (between sites and across depths) were monitored for 12 months at two contrasting sites in San Jorge Gulf, Argentina. The effect of depth on spat density was evaluated through monthly samples taken from artificial collectors at three depths (3, 7 and 11 m). The temporal settlement pattern was consistent at both sites, with the maximum spatfall recorded in early March (late summer), coinciding with the peak of sea water temperature. Settlement also correlated with Chl a and particulate organic carbon peak values, typically manifesting 2–3 months later and followed the initial decline in mussel condition during late spring and early summer. Significant differences between localities were detected in settlement abundance. The optimal temporal gap for mussel settlement was observed in mid / late summer, suggesting that this is the optimal time to deploy spat collectors in the field. Settlement was uniform between depths, thereby implying that the specific depth of collector placement did not appear to emerge as a key factor of settlement success.

Influence of Groundwater on the Very Shallow Geothermal Potential (vSGP) in the Area of a Large-Scale Geothermal Collector System (LSC)

The water balance in the very shallow subsurface can be influenced by capillary rise due to a high groundwater table. Since moisture content is an important factor for the thermal conductivity of soils, this can also have an influence on the very shallow geothermal potential (vSGP). For this reason, the effect of spatial and seasonal variations in groundwater tables on moisture content in essential depth layers was investigated at a large-scale geothermal collector system (LSC) in Bad Nauheim, Germany. Quasi-one-dimensional simulations using the FEFLOW® finite-element simulation system were employed to determine site-dependent and seasonally varying moisture contents, from which thermal conductivities were derived. The model setup was previously validated based on recorded moisture contents. The simulations resulted in groundwater-related maximum seasonal and spatial differences in thermal conductivity of 0.14 W/(m∙K) in the LSC area. Larger differences of up to 0.21 W/(m∙K) resulted for different soil textures at the same depth due to different thermal properties. The results indicate that an efficient design of LSCs requires a sufficiently detailed subsurface exploration to account for small-scale variations in grain size distribution and groundwater level.

Geological characterization and controlling factors of small-scale variations in the cobalt-rich ferromanganese crust deposits

Cobalt-rich ferromanganese crusts (CRC) are potential resources for Co, Ni, Pt, and other strategic metals. The CRC thickness varies from a few mm to more than 100 mm at various distance scales over the rock outcrops in the seamounts. However, their variation patterns and controlling factors are not well understood. We conducted a comprehensive small-scale survey, including shipboard acoustic measurements, seafloor observations, and rock drilling over the Xufu Guyot of the Marcus-Wake seamounts in the Northwestern Pacific to characterize the thickness variations on a scale of several kilometers with the topography and geological evolution of the guyot. Rock drilling revealed that thicker CRC (>100 mm) tend to occur on the margins and flat areas on the guyot, while thinner CRC are associated with carbonate reef mounds over the volcanic pinnacles and seamount slopes. The microstratigraphic description indicated that the CRC thickness is strongly related to the geological evolution of the guyot, mainly the stability of the substrate rocks and coverage with calcareous pelagic sedimentation.

Influence of Physically Constrained Initial Perturbations on the Predictability of Mei-Yu Heavy Precipitation

Abstract Based on the conditional nonlinear optimal perturbation (CNOP) approach, the predictability of mei-yu heavy precipitation and its underlying physical processes is investigated. As an extension of our previous work, the practical predictability of heavy precipitation events is studied using more realistic initial perturbations than previously considered. The initial perturbation reflects certain physical connections among multiple variables, including zonal and meridional winds, potential temperature (T), and water vapor mixing ratio (Q). Two types of initial perturbations for the CNOP are identified, with similar spatial distributions but opposite signs and resulting effects. The accumulated precipitation is strengthened with mostly positive perturbations in the T and Q components for the CNOP and weakened by negative perturbations. Comparing downscaling (DOWN) perturbations and random perturbations (RPs) with the CNOP, it is found that the CNOP and DOWN perturbations exhibit particularly large- and mesoscale spatial structures, respectively, while the RPs yield a spatial distribution with mostly convective-scale features. Also, the CNOP results in the largest error growth and forecast uncertainty, especially for Q, followed by the DOWN perturbations; those in the RPs are the smallest. These results provide important implications for optimizing the initial perturbations of convection-permitting ensemble prediction systems, especially precipitation forecasts. Moreover, it is suggested that small-scale related variables, that is, those associated with vertical motion and microphysical processes, are much less predictable than thermodynamic variables, and the errors grow through distinct physical processes for the three types of initial perturbations, that is, those with flow-dependent features.

Assessing Contaminant Mass Discharge Uncertainty With Application of Hydraulic Conductivities Derived From Geoelectrical Cross‐Borehole Induced Polarization and Other Methods

AbstractA new methodology was developed to support contaminant mass discharge (CMD)‐based risk assessment of groundwater contamination downgradient of point source zones. Geoelectrical cross‐borehole induced polarization (IP) data were collected at a site undergoing in situ remediation of chlorinated solvents for determining 2D hydraulic conductivity (K) distributions with an inversion model resolution of 0.15 m (vertically) x 0.50 m (horizontally) in three control planes from 10 to 20 m depth. Additionally, 18 slug tests and 31 grain size distribution analyses (GSA) from the control planes, were used for K‐estimation. The geometric means and variance of the IP, slug test, and GSA derived K‐estimates were consistent with previously studied sandy aquifers. Furthermore, the vertical variation in K between two geological settings, a sandy till and a meltwater sand formation, was clearly identified by the IP K‐estimates. The vertical variation was backed up by hydraulic profiling tool (HPT) measurements. Random realizations of CMD were simulated based on the cross‐borehole IP derived K‐values. For comparison, the CMD was also estimated with a geostatistical conditional simulation approach, using the data from slug tests and GSAs. The high IP resolution captured the small scale variations in K across the transects and led to CMD predictions with a narrow uncertainty interval, whereas slug test and GSA either under‐ or overestimated the magnitude of the areas with the highest CMD. Applying the geophysical cross‐borehole method for estimating K‐distributions in addition to traditional methods would improve CMD‐based risk assessment and evaluation of remediation performance at contaminated sites.

Wave Groups and Small Scale Variability of Wave Heights Observed by Altimeters

AbstractRecent satellite altimeter retracking and filtering methods have considerably reduced the noise level in estimates of the significant wave height (Hs), allowing to study processes with smaller spatial scales. In particular, previous studies have shown that wave‐current interactions may explain most of the variability of Hs at scales 20–100 km. As the spatial scale of the measurement is reduced, random fluctuations emerge that should be associated to wave groups. Here we quantify the magnitude of this effect, and the contribution of wave groups to the uncertainty in Hs measurements by altimeters, with a particular focus on extreme extra‐tropical storms. We take advantage of the low orbit altitude of the China‐France Ocean Satellite (CFOSAT), and the low noise level of the nadir beam of the SWIM instrument. Our estimate of wave group effects uses directional wave spectra measured by off‐nadir beams on SWIM, and signal processing theory that gives statistical properties of the wave envelope, and thus the local wave heights, from the shape of the wave spectrum. We find that the standard deviation of Hs associated to wave groups is a function of satellite altitude, wave height and spectral peakedness. For CFOSAT these fluctuations generally account for about 25% of the variance measured over a 80 km distance. This fraction is largest in storms and in the presence of long swells. When the estimated effect of wave groups is subtracted from the variance of Hs measurements, the remaining variability is higher in regions of strong currents.

Infrared thermography monitoring of rock faces – Potential and pitfalls

Rock surface temperatures are of fundamental importance for studies on weathering, rockfall and permafrost. Point temperature measurements may not reflect the small-scale variability of temperature as a function of micro-topography. To close this gap, infrared thermography (IRT) seems to be a simple and promising approach. However, there are several pitfalls in terms of interpretation, as radiation temperatures depend on emissivity and reflectivity of the rock, which in turn are influenced by rock type, surface roughness, wetness, surrounding weather conditions, and angle to the camera axis.We performed laboratory and exemplary field experiments in order to estimate the magnitude of possible errors. We used rough and smooth (sawn) specimen of six different stone types in wet and dry condition and took IRT images at different tilt angles between camera axis and rock surface. Furthermore, we applied the approach to a small rock outcrop (approx. 3 × 3 m) and to a rockwall (approx. 100 × 100 m).The results of the laboratory measurements show that the temperature error increases with increasing tilt angle of the rock surface. Depending on the nature of the reflected surroundings, radiation temperatures can be warmer or cooler than sensor temperatures. In typical settings, the error is low (<0.5 K) up to a tilt of 40° but it may increase to >1 K at tilt angles of 50° and more. Smooth and wet surfaces tend to be more prone to deviations.The field examples confirm the results of the laboratory tests. But they show that spatial differences in temperature can still be detected as the “true” differences are usually larger than the magnitude of error. We suggest to reduce the error of the IRT image by correcting temperatures using a high-resolution surface model.

Small-scale variation in available water capacity of the soil influences height growth of single trees in Southern Germany

Aim of study: Detecting possible small-scale soil effects on height growth of single trees in monospecific stands of three important tree species (Abies alba, Fagus sylvatica, and Picea abies).&#x0D; Area of study: 37 mature stands along an ecological gradient in Southern Germany from the cold and wet “optimal niche zone” to warmer and drier niche zones, including gravelly soils with poor water supply.&#x0D; Material and methods: Measurement of achieved height and age of 15 to 20 sample trees per stand. Estimation of the available water capacity of the soil (AWC) in close proximity to sample trees based on soil texture following the German soil survey guidelines. Examining height growth depending on niche zone and AWC. &#x0D; Main results: On sites (stand level) with the lowest water regime, height growth increased significantly with AWC of microsites. The estimated effect on height growth over the whole range of AWC values was almost 8 m at those sites. In contrast, the effect was negative on optimal sites. For intermediate and marginal sites, the effect was positive, albeit not significant for marginal sites.&#x0D; Research highlights: To our knowledge this is the first study about small-scale effects of AWC on height growth of single trees in temperate European forests. Small-scale soil variability should be considered in future scientific studies and practical evaluation, involving single tree performance at stands with low water regime. This seems particularly important in genetic environmental associations studies and in the process of selecting trees for breeding purposes in such stands.

Weak evidence of trade-offs modulated by seed mass among a guild of closely related winter annuals

Plant-plant interactions are integral to the establishment and persistence of diversity in plant communities. For annual plant species that depend on seeds to regenerate, seed characteristics that confer fitness advantages may mediate processes such as plant-plant interactions. Seed mass is known to vary widely and has been shown to associate with species’ differences in stress tolerance and competitive effects. However, understanding of how seed mass influences species’ responses to competition is less well understood. Using natural assemblages of six closely related annual plant species in Western Australia, we implemented a thinning study to assess how seed mass influences the outcomes of plant-plant interactions. We found relatively weak evidence for competition or facilitation among species. Our strongest results indicated that heavy-seeded species had lower survivorship than light-seeded species when interacting with heterospecifics. Seed mass was also negatively related to overall survival, counter to expectations. These findings indicate some evidence for trade-offs mediated by seed mass in this system. However, we acknowledge that other factors may have influenced our results, such as the use of natural assemblages (rather than using sowing experiments) and the presence of important small-scale environmental variation not captured with our choice of abiotic variables. Further research is required to clarify the role of seed mass in this diverse annual system, ideally including many focal species, and using sowing experiments.