Large Spatial Gradients Research Articles

Climate‐associated variation in the within‐season dynamics of juvenile ticks in California

AbstractChanging climate has driven shifts in species phenology, influencing a range of ecological interactions from plant–pollinator to consumer–resource. Phenological changes in host–parasite systems have implications for pathogen transmission dynamics. The seasonal timing, or phenology, of peak larval and nymphal tick abundance is an important driver of tick‐borne pathogen prevalence through its effect on cohort‐to‐cohort transmission. Tick phenology is tightly linked to climatic factors such as temperature and humidity. Thus, variation in climate within and across regions could lead to differences in phenological patterns. These differences may explain regional variation in tick‐borne pathogen prevalence of the Lyme disease‐causing Borrelia bacteria in vector populations in the United States. For example, one factor thought to contribute to high Lyme disease prevalence in ticks in the eastern United States is the asynchronous phenology of ticks there, where potentially infected nymphal ticks emerge earlier in the season than uninfected larval ticks. This allows the infected nymphal ticks to transmit the pathogen to hosts that are subsequently fed upon by the next generation of larval ticks. In contrast, in the western United States where Lyme disease prevalence is generally much lower, tick phenology is thought to be more synchronous with uninfected larvae emerging slightly before, or at the same time as, potentially infected nymphs, reducing horizontal transmission potential. Sampling larval and nymphal ticks, and their host‐feeding phenology, both across large spatial gradients and through time, is challenging, which hampers attempts to conduct detailed studies of phenology to link it with pathogen prevalence. In this study, we demonstrate through intensive within‐season sampling that the relative abundance and seasonality of larval and nymphal ticks are highly variable along a latitudinal gradient and likely reflect the variable climate in the far western United States with potential consequences for pathogen transmission. We find that feeding patterns were variable and synchronous feeding of juvenile ticks on key blood meal hosts was associated with mean temperature. By characterizing within‐season phenological patterns of the Lyme disease vector throughout a climatically heterogeneous region, we can begin to identify areas with high potential for tick‐borne disease risk and underlying mechanisms at a finer scale.

Investigation of the Sigma Approximation Technique for the Solution of the Time Spectral Equation System

Abstract The time spectral method is commonly utilized to analyze periodic unsteady flows within turbomachines. However, the time spectral solutions in regions with large temporal and spatial gradients, such as wakes, shocks, and boundary layers, can be plagued with unphysical oscillations, known as the Gibbs phenomenon. This paper presents an investigation into the sigma approximation technique, which is capable of significantly attenuating the Gibbs phenomenon by dampening high-frequency nonlinear components in the time spectral solutions. However, the optimal combination of the sigma factors remains to be ascertained considering the trade-off between the accuracy of solutions and the reduction of unphysical oscillations. In this study, a two-row compressor configuration is first selected, and numerical simulations are performed to evaluate the efficacy of this technique under near peak-efficiency and near-stall operating conditions. It is found that Gibbs-type unphysical oscillations can be effectively mitigated without notably compromising solution accuracy through an optimal combination of sigma factors. The NASA Stage 35 case study further verifies the effectiveness of the proposed optimal sigma factor combination in preserving the accuracy of time spectral solutions based on the data from test rig. Moreover, the von Neumann analysis reveals that the sigma approximation technique can enhance the numerical stability of the time spectral equation system, thereby allowing the use of aggressive numerical parameters to accelerate convergence. The stability analysis results are verified by a two-dimension bump under two different flow conditions and further assessed using the two-row compressor.

Spatial and temporal variability of martian water-ice cloud effective radius in EMIRS thermal infrared observations

New analyses of thermal infrared spectra obtained from the Emirates Mars Infrared Spectrometer (EMIRS) allow for retrieval of water-ice cloud effective radius, reff,ice, in the lower atmosphere of Mars across spatial, seasonal, and daytime diurnal scales. Using a one Martian-year observational dataset the mean retrieved reff,ice is 3.1 μm (standard deviation, σ = 1.5 μm) for an assumed effective variance, νeff,ice = 0.1, and with most individual values between 1 and 10 μm. Sensitivity analyses show the uncertainty associated with reff,ice is largely inversely proportional to water-ice cloud optical depth, τice. As a result, our retrieval is generally applicable to water-ice clouds with τice of at least ∼0.02 to 0.08 at 825 cm−1. Seasonal results show mean reff,ice values of 4.3 μm (σ = 1.9 μm) during aphelion season (Ls = 40°–140°), associated with larger particle sizes in the aphelion cloud belt (ACB), and 2.5 μm (σ = 0.8 μm) during perihelion season (Ls = 225°–360°). Diurnal analyses between roughly 06:00 and 20:00 local true solar time indicate the largest variability occurs in ACB clouds, with effective radii tending to be smaller during midday (zonal-mean reff,ice of 4–5 μm) as compared to the mornings and afternoons (zonal-mean reff,ice of 6–7 μm). Relatively large spatial gradients in reff,ice within the ACB are observed, including a seasonal mean reff,ice of ∼8 μm in the Tharsis region and regions in the southern mid-latitudes with seasonal mean reff,ice of ∼2 μm. Spatial variability in reff,ice tends to be smaller throughout the rest of the year, though with some similar patterns. This includes several time periods between regional dust storms when a low-latitude band of water-ice clouds formed in the afternoons near Tharsis, which grew in both optical depth and effective radius to maxima in the early evenings. Lastly, changes in reff,ice are found to be generally positively correlated with changes in τice and negatively correlated with estimated cloud height, though reff,ice distributions also show this to be a more complex relationship than simple averages might suggest.

Risk overbounding for ionospheric gradient monitor using geometry-free double differenced carrier phase measurements

Ionosphere anomaly can cause large spatial gradients in the double-differenced carrier phase (DDCP) measurements. Taking advantage of this characteristic, the ionospheric gradient monitor (IGM) is designed with multiple ground reference stations to detect threatening ionospheric gradients for safety of life applications. An optimal IGM should be most sensitive to ionospheric gradients and least sensitive to other errors. However, current IGM suffers from the influence of tropospheric error, which can degrade monitor performance under extreme weather conditions by causing risks of false alarms and missed detections. To address this issue, an alternative IGM is proposed using the geometry-free combination of DDCP as the test statistic. Ambiguity resolution procedure is designed for estimating the ambiguity term in the test statistic. The risk induced by the wrong ambiguity fix and tropospheric error are analyzed and bounded with required averaging period and minimum baseline length. The results show that the proposed theoretical IGM is capable of achieving probability of false alarm of 10–8 and probability of missed detection of 10–6 with a filtering period of 612 s and baseline length of 371.7 m or a filtering period of 544 s and baseline length of 384.4 m. The experimental results using data collected from Hong Kong Satellite Positioning Reference Station Network demonstrate that the performance of the proposed theoretical IGM is comparable to that of the existing detection algorithm.

Relationship between GIX, SIDX, and ROTI ionospheric indices and GNSS precise positioning results under geomagnetic storms

Ionospheric indices give information about ionospheric perturbations, which may cause absorption, diffraction, refraction, and scattering of radio signals, including those from global navigation satellite systems (GNSS). Therefore, there may be a relationship between index values and GNSS positioning results. A thorough understanding of ionospheric indices and their relationship to positioning results can help monitor and forecast the reliability and accuracy of GNSS positioning and support the precision and safety of life applications. In this study, we present the relationship between three indices: Gradient Ionosphere indeX (GIX), Sudden Ionospheric Disturbance indeX (SIDX), and Rate of Total electron content Index (ROTI) in relation to precise positioning results. We used two approaches: precise point positioning (PPP) and relative positioning for long baselines. We focus on GNSS stations located in Europe for two selected geomagnetic storms: March 17, 2015, and May 22, 2015. Our results show that in the case of PPP, positioning degradation occurred mainly at high latitudes and was mostly caused by rapid small-scale changes in ionospheric electron content represented by SIDX and ROTI. We also showed a significant correlation between cycle slips of GNSS signals and ROTI (0.88). The most significant degradations for relative positioning for low and medium latitudes were associated with large spatial gradients reflected by the GIX.

Modulating selective ionic enrichment and depletion zones in straight nanochannels via the interplay of surface charge modulation and electric field mediated fluid-thickening.

We report the possibilities of achieving highly controlled segregation of ion-enriched and ion-depleted regions in straight nanochannels. This is achieved via harnessing the interplay of an axial gradient of the induced transverse electric field on account of electrical double layer phenomenon and the localized thickening of the fluid because of intensified electric fields due to the large spatial gradients of the electrical potential in extreme confinements. By considering alternate surface patches of different charge densities over pre-designed axial spans, we illustrate how these effects can be exploited to realize selectively ion-enriched and ion-depleted zones. Physically, this is attributed to setting up of an axial concentration gradient that delves on the ionic advection due to the combined effect of an externally applied electric field and induced back-pressure gradient along the channel axis and electro-migration due to the combinatorial influences of the applied and the induced electrostatic fields. With an explicit handle on the pertinent parameters, our results offer insights on the possible means of imposing delicate controls on the solute-enrichment and depletion phenomena, a paradigm that remained unexplored thus far.

Effect of defects on flux expulsion of pure niobium superconducting radio frequency cavities via spatial temperature gradient

Since flux vortices are easily pinned by defects in superconducting radio frequency (SRF) cavities, trapped magnetic flux increases the surface resistance of the SRF cavity. It has been experimentally demonstrated that trapped magnetic flux can be expelled by cooling down a superconducting cavity under a large spatial temperature gradient. In this paper, we use the time-dependent Ginzburg–Landau (TDGL) theory to theoretically investigate the effect of defects on the flux expulsion ability of pure niobium superconducting cavities with an applied spatial temperature gradient. It is shown that the residual flux vortex density displays a notable stepwise decreasing trend with increasing temperature gradient at smaller residual fields, while it shows a stepwise rising with increasing defect size. Both larger defect number and size make vortices difficult to be expelled. Moreover, long cooling time is beneficial for vortices to be expelled, and the cooling time has nearly no significant effect on flux expulsion under conditions of large cooling times. The results in this paper provide some theoretical guidelines for improving the performance of superconducting cavities in practical situations.

Evaporation of alcohol droplets on surfaces in moist air

Droplets of alcohol-based formulations are common in applications from sanitizing sprays to printing inks. However, our understanding of the drying dynamics of these droplets on surfaces and the influence of ambient humidity is still very limited. Here, we report the drying dynamics of picoliter droplets of isopropyl alcohol deposited on a surface under controlled humidity. Condensation of water vapor in the ambient environment onto alcohol droplets leads to unexpectedly complex drying behavior. As relative humidity (RH) increases, we observed a variety of phenomena including enhanced spreading, nonmonotonic changes in the drying time, the formation of pancake-like shapes that suppress the coffee-ring effect, and the formation of water-rich films around an alcohol-rich drop. We developed a lubrication model that accounts for the coupling between the flow field within the drop, the shape of the drop, and the vapor concentration field. The model reproduces many of the experimentally observed morphological and dynamic features, revealing the presence of unusually large spatial compositional gradients within the evaporating droplet and surface-tension-gradient-driven flows arising from water condensation/evaporation at the surface of the droplet. One unexpected feature from the simulation is that water can evaporate and condense concurrently in different parts of the drop, providing fundamental insights that simpler models based on average fluxes lack. We further observed rim instabilities at higher RH that are well-described by a model based on the Rayleigh-Plateau instability. Our findings have implications for the testing and use of alcohol-based disinfectant sprays and printing inks.

Predicting Carbonate Chemistry on the Northwest Atlantic Shelf Using Neural Networks

AbstractThe Northwest Atlantic Shelf (NAS) region has experienced accelerated warming, heatwaves, and is susceptible to ocean acidification, yet also suffers from a paucity of carbonate chemistry observations, particularly at depth. We address this critical data gap by developing three different neural network models to predict dissolved inorganic carbon (DIC) and total alkalinity (TA) in the NAS region from more readily available hydrographic and satellite data. The models predicted DIC withr2between 0.913–0.963 and root mean square errors (RMSE) between 15.4–23.7 (μmol kg−1) and TA withr2between 0.986–0.983 and RMSE between 9.0–10.4 (μmol kg−1) on an unseen test data set that was not used in training the models. Cross‐validation analysis revealed that all models were insensitive to the choice of training data and had good generalization performance on unseen data. Uncertainty in DIC and TA were low (coefficients of variation 0.1%–1%). Compared with other predictive models of carbonate system variables in this region, a larger and more diverse data set with full seasonal coverage and a more sophisticated model architecture resulted in a robust predictive model with higher accuracy and precision across all seasons. We used one of the models to generate a reconstructed seasonal distribution of carbonate chemistry fields based on DIC and TA predictions that shows a clear seasonal progression and large spatial gradients consistent with observations. The distinct models will allow for a range of applications based on the predictor variables available and will be useful to understand and address ocean sustainability challenges.

New species of <i>Lepanthes</i> (Orchidaceae: Pleurothallidinae) to honour “Bachué”, the mythological mother of the indigenous Muisca people.

In an expedition of 341 plots across a large elevation (1,100-3,880 m) and spatial gradient (~270 km) in the eastern cordillera we found a new species of the genus Lepanthes in Santuario de Fauna y Flora de Iguaque, Boyaca, Colombia. We propose L. bachue as a new species. It is most similar to L. papallactae but it can be distinguished by its proliferous plants (vs. non proliferous), the petals with the upper lobe 2.5 mm long, the lower lobe 4.5 mm long, larger than the upper one, and the margins fimbriate (vs. lobes subequal, 4.5 mm long and shortly pubescent) and the lip with the blades oblong, sub-sigmoid, adnate to the middle of the column with a short oblong, bifid, yellow appendix hiding in the middle (vs. blades narrowly elliptical-oblong, connate to the column above the middle with a recurved, pedunculate, biglandular appendix). Our large elevational and geographical sampling suggest that the species is geographically restricted and have high habitat specialization, thus urging to protect its natural habitat and population.

Infectious disease ecology and evolution in a changing world.

Infectious disease ecology and evolution in a changing world.

Exploring within-ecodistrict lake organic matter variability and identifying possible environmental contaminant biomarkers using sedimentomics

Sedimentomics methods offer insight into the physiological parameters that influence freshwater sediment organic matter (sedOM). To date, most sedimentomics studies characterized variations across large spatial and environmental gradients; here we examine whether sedimentomics methods capture subtle sedOM variations within a relatively homogeneous study area in southwestern Nova Scotia, Canada. Additionally, we explore the lake sedimentome for candidate biomarkers related to ongoing carnivorous animal farming in the region. Sediment cores were recovered from seven lakes across a trophic (oligo- to eu- trophic) and anthropogenic land use gradient (carnivorous animal farming in catchment, downstream of farming, no farming nearby). Subsamples that dated prior to 1910 (pre-carnivorous animal farming) and later than 2010 (during carnivorous animal farming) were analyzed using UHPLC-HRMS in both negative (ESI−) and positive (ESI+) electrospray ionization modes. Cluster analysis (k-means) showed replicate samples from a given lake clustered distinctly from one another in both ESI modes, indicating sedOM captured subtle variations between lake systems. PCA combined with multiple linear regression indicated carnivorous animal farming and OM source explained most of the observed variation in lake sedOM. Principal component analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) of ESI− and ESI+ data sets identified 103 unique candidate biomarkers. Ten strong candidate biomarkers were identified using graphical methods; more research is required for biomarker verification and molecular characterization. Our results indicate sedimentomics could be used in environmentally homogeneous areas, offering insight into the controls of sedOM cycling. Additionally, we identified prospective biomarkers related to carnivorous animal farming that could be used to understand relative contributions of farming to ongoing eutrophication issues in southwestern Nova Scotia.

Trait–environment relationships of hydroids (Cnidaria: Hydrozoa) across large spatial and environmental gradients in the Atlantic Ocean

AbstractAimThe aim was to test trait–environment relationships in hydroids across large spatial and environmental gradients and to evaluate associations between traits, environmental variables, space and phylogeny.LocationAtlantic Ocean and adjacent polar seas.Time periodPresent day.Major taxa studiedHydrozoa.MethodsTrait–environment relationships and their spatial and phylogenetic contexts were assessed in hydroids by using a combination of a fourth‐corner test and extended‐RLQ approach, in a multivariate ordination method that uses five matrices: (1) species across sites, (2) environmental data across sites, (3) traits across species, (4) latitude and longitude for each site, and (5) phylogenetic distance among species. We based our analyses on 3680 records of 431 species distributed at 1440 sites, 16 species traits, nine environmental variables and a phylogenetic tree of the studied species.ResultsHydroid traits are significantly correlated with environmental variables and geographical space, and hydroid phylogeny is correlated with the environment and geographical space. More evidently, we observed an increased presence of larger species (taller, more branched, with greater base diameter and polysiphonic) at sites richer in nitrate and silicate, with higher dissolved oxygen, lower temperatures, lower salinities and lower current velocities. The observation of phylogenetically related species with similar traits and distributions corroborates that historical processes interact with the environment in determining community assembly and explaining patterns of distribution of species traits.Main conclusionsSeveral environmental variables combined affect the distribution of hydroid traits, which are also influenced by spatial and historical factors. In the first analysis of its kind for hydrozoans, we have provided an overview of how hydroids are distributed across environments according to their traits and revealed the spatial and phylogenetic components of these trait–environment relationships.

Beyond physical control: Macrofauna community diversity across sandy beaches and its relationship with secondary production

Our understanding of the response of macrofauna diversity patterns to the variability of sandy beaches across spatial scales is limited. Defining relationships between diversity and ecosystem productivity is key to understanding the ecological consequences of the current global rates of biodiversity loss. Here, we conducted a study across a large spatial gradient of 39 sandy beaches involving a wide range of environmental conditions and macrobenthic diversity to (1) explore macrofauna diversity patterns (2) estimate secondary production and (3) quantify how much of the variability in beach secondary production can be explained by macrofauna diversity. Beach macrofauna showed a clear increase in α-diversity across a beach geographic gradient linked to oceanographic conditions. Partitioning of β-diversity implied the replacement of some species by others between beaches (i.e. spatial turnover) instead of a process of species loss (or gain) from beach to beach (i.e. nestedness). Variance partitioning analyses revealed that environmental and oceanographic variables (i.e., sea surface temperature, beach size, slope, and exposure rate), but also macrofauna diversity (i.e., species richness and Shannon index), largely determine beach secondary production. We showed that an increase in macrofauna diversity enhances beach secondary production, promoting energy transfer across trophic levels. The positive exponential relationship between macrofauna diversity and secondary production supports the idea that macrofauna plays an essential role in maintaining beaches as productive coastal ecosystems. Consequently, macrofauna diversity loss due to the ongoing shoreline recession and coastal occupation, exacerbated by climate change might cause exponential reductions in beach secondary production, which would affect the functioning of these sea-land interface areas.

Modern approaches for leveraging biodiversity collections to understand change in plant-insect interactions

Research on plant-pollinator interactions requires a diversity of perspectives and approaches, and documenting changing pollinator-plant interactions due to declining insect diversity and climate change is especially challenging. Natural history collections are increasingly important for such research and can provide ecological information across broad spatial and temporal scales. Here, we describe novel approaches that integrate museum specimens from insect and plant collections with field observations to quantify pollen networks over large spatial and temporal gradients. We present methodological strategies for evaluating insect-pollen network parameters based on pollen collected from museum insect specimens. These methods provide insight into spatial and temporal variation in pollen-insect interactions and complement other approaches to studying pollination, such as pollinator observation networks and flower enclosure experiments. We present example data from butterfly pollen networks over the past century in the Great Basin Desert and Sierra Nevada Mountains, United States. Complementary to these approaches, we describe rapid pollen identification methods that can increase speed and accuracy of taxonomic determinations, using pollen grains collected from herbarium specimens. As an example, we describe a convolutional neural network (CNN) to automate identification of pollen. We extracted images of pollen grains from 21 common species from herbarium specimens at the University of Nevada Reno (RENO). The CNN model achieved exceptional accuracy of identification, with a correct classification rate of 98.8%. These and similar approaches can transform the way we estimate pollination network parameters and greatly change inferences from existing networks, which have exploded over the past few decades. These techniques also allow us to address critical ecological questions related to mutualistic networks, community ecology, and conservation biology. Museum collections remain a bountiful source of data for biodiversity science and understanding global change.

Strong Ionospheric Spatial Gradient Events Induced by Signal Propagation Paths Aligned With Equatorial Plasma Bubbles

Low-latitude ionospheric behavior directly interferes with a wide range of applications dependent on signals and information from satellites. The most severe and variable events are plasma bubbles and ionospheric scintillation. During plasma bubble events, large and steep plasma density gradients may intersect transionospheric signal from satellites, especially around the equatorial anomaly region. Large ionospheric spatial gradients (or decorrelations) are a critical component of ionospheric threat models for global navigation satellite systems augmentation systems; however, the models cannot assimilate abrupt changes in ionospheric behavior. In this article, an investigation of the relationship between plasma depletions, the occurrence of scintillation, and strong ionospheric spatial decorrelation events was conducted. The results indicate that strong scintillations occur when large gradients are verified. Additionally, the most critical ionospheric spatial gradients were verified mostly under certain conditions: when satellite signals are aligned with the plasma bubble propagation along geomagnetic field lines. Therefore, even though amplitude scintillation may degrade communications, the critical gradient events seem to be related to a particular configuration of satellite signal across the ionosphere. Thus, it is recommended that ionospheric threat models for augmentation systems in low-latitude regions consider this alignment aspect.

XIGA: An eXtended IsoGeometric analysis approach for multi-material problems

Multi-material problems often exhibit complex geometries along with physical responses presenting large spatial gradients or discontinuities. In these cases, providing high-quality body-fitted finite element analysis meshes and obtaining accurate solutions remain challenging. Immersed boundary techniques provide elegant solutions for such problems. Enrichment methods alleviate the need for generating conforming analysis grids by capturing discontinuities within mesh elements. Additionally, increased accuracy of physical responses and geometry description can be achieved with higher-order approximation bases. In particular, using B-splines has become popular with the development of IsoGeometric Analysis. In this work, an eXtended IsoGeometric Analysis (XIGA) approach is proposed for multi-material problems. The computational domain geometry is described implicitly by level set functions. A novel generalized Heaviside enrichment strategy is employed to accommodate an arbitrary number of materials without artificially stiffening the physical response. Higher-order B-spline functions are used for both geometry representation and analysis. Boundary and interface conditions are enforced weakly via Nitsche’s method, and a new face-oriented ghost stabilization methodology is used to mitigate numerical instabilities arising from small material integration subdomains. Two- and three-dimensional heat transfer and elasticity problems are solved to validate the approach. Numerical studies provide insight into the ability to handle multiple materials considering sharp-edged and curved interfaces, as well as the impact of higher-order bases and stabilization on the solution accuracy and conditioning.

Consistency and Variation in the Kelp Microbiota: Patterns of Bacterial Community Structure Across Spatial Scales.

Kelp species are distributed along ~ 25% of the world's coastlines and the forests they form represent some of the world's most productive and diverse ecosystems. Like other marine habitat-formers, the associated microbial community is fundamental for host and, in turn, wider ecosystem functioning. Given there are thousands of bacteria-host associations, determining which relationships are important remains a major challenge. We characterised the associated bacteria of two habitat-forming kelp species, Laminaria hyperborea and Saccharina latissima, from eight sites across a range of spatial scales (10s of metres to 100s of km) in the northeast Atlantic. We found no difference in diversity or community structure between the two kelps, but there was evidence of regional structuring (across 100skm) and considerable variation between individuals (10s of metres). Within sites, individuals shared few amplicon sequence variants (ASVs) and supported a very small proportion of diversity found across the wider study area. However, consistent characteristics between individuals were observed with individual host communities containing a small conserved "core" (8-11 ASVs comprising 25 and 32% of sample abundances for L. hyperborea and S. latissima, respectively). At a coarser taxonomic resolution, communities were dominated by four classes (Planctomycetes, Gammaproteobacteria, Alphaproteobacteria and Bacteroidia) that made up ~ 84% of sample abundances. Remaining taxa (47 classes) made up very little contribution to overall abundance but the majority of taxonomic diversity. Overall, our study demonstrates the consistent features of kelp bacterial communities across large spatial scales and environmental gradients and provides an ecologically meaningful baseline to track environmental change.

Non-Native Plant Invasions in Prairie Grasslands of Alberta, Canada

Native prairie grasslands are a fundamental part of Canada's natural heritage, but these formerly extensive ecosystems have undergone declines due to grassland conversion and fragmentation. In addition, remaining native grasslands are threatened by invasive non-native plants, which can outcompete native flora and negatively impact ecological functioning. Although several studies have reported invasions in northern prairie grasslands, only some have investigated patterns across a large spatial gradient, and few have tested their relationship with environmental predictors and anthropogenic disturbance. We surveyed 139 plots across a 938-km spatial gradient in Alberta to 1) identify the most frequent and abundant non-native species, 2) test whether levels of non-native plant invasions are linked to environmental factors or anthropogenic disturbance, and 3) inspect whether relationships differ between mesic and semiarid grasslands. Data were analyzed using generalized additive models and commonality analysis.Our results show that Kentucky bluegrass (Poa pratensis subsp. angustifolia), commonly used for agronomic purposes, is by far the most frequent and abundant non-native plant in Alberta grasslands. Across all plots, abundance and richness of non-native plants were positively linked to a shared effect by aridity, soil texture, and agricultural activity. Furthermore, the importance of predictors differed between mesic and semiarid grasslands. In mesic grasslands, non-native plant abundance and richness were highest in areas with high agricultural activity and fine-textured soils. In the semiarid prairie, topography accounted for most explained variation in the levels of invasion. In summary, climatic conditions, and to some extent agricultural activity and topography, best explain the patterns of non-native plant invasions. A priority for future research is to identify the mechanisms underlying the differences in invasion across mesic and semiarid prairie grasslands. To counteract invasions, practitioners need to diminish the propagule pressure by invasive agronomic grasses, protect and restore grasslands remnants in the mesic region, and proactively control new invaders.

Physical–biological interactions underlying the connectivity patterns of coral‐dependent fishes around the Arabian Peninsula

AbstractAimDistribution patterns of lineages alone do not explain the processes underlying phylogenetic differentiation in fishes observed around the Arabian Peninsula, whose hypotheses traditionally rely on (i) Pleistocene vicariance events, (ii) successive bottlenecks, (iii) recent founder effects (iv) and large spatial gradients in physical conditions. In this study, we test the hypothesis that phylogeographical patterns of coral‐dependent fish species inhabiting the peninsula may be driven by a combination of ocean circulation, larval behaviour and seascape features.LocationArabian Peninsula.TaxaCoral reef fish.MethodsA biophysical modelling system that relies on stochastic Lagrangian framework and Individual‐Based Model was used to simulate larval dispersal through three putative barriers, by tracking three‐dimensional movements of virtual particles in ocean circulation scenarios. We explored the range of dispersal capabilities across reef fish species by creating 72 hypothetical strategies, each representing a unique combination of five biological traits, namely pelagic larval duration, spawning periodicity, mortality rate, reproductive output and vertical migration.ResultsThe strength of the barriers was highly variable as a function of all biological traits (except reproductive output) and indicated high asymmetry of connectivity, and hence gene flow, between adjacent areas. In addition, direction and distance travelled by the virtual larvae varied according to both the geographical position of releasing site and biannual monsoonal winds. On average, larvae released during the summer exhibited a higher potential for dispersal than larvae released during the winter.Main conclusionsOur biophysical models showed that in the Arabian Peninsula, the combination of hydrodynamic, seascape features and larval traits likely affects the distribution of genetic lineages due to the interruption, reduction or asymmetry of larval movements through the putative barriers.