Small Spatio-temporal Scales Research Articles

The biogeographic and evolutionary processes shaping population divergence in Laupala.

Speciation generates biodiversity and the mechanisms involved are thought to vary across the tree of life and across environments. For example, well-studied adaptive radiations are thought to be fuelled by divergent ecological selection, but additionally are influenced heavily by biogeographic, genomic and demographic factors. Mechanisms of non-adaptive radiations, producing ecologically cryptic taxa, have been less well-studied but should likewise be influenced by these latter factors. Comparing among contexts can help pinpoint universal mechanisms and outcomes, especially if we integrate biogeographic, ecological and evolutionary processes. We investigate population divergence in the swordtail cricket Laupala cerasina, a wide-spread endemic on Hawai'i Island and one of 38 ecologically cryptic Laupala species. The nine sampled populations show striking population genetic structure at small spatio-temporal scales. The rapid differentiation among populations and species of Laupala shows that neither a specific geographical context nor ecological opportunity are pre-requisites for rapid divergence. Spatio-temporal patterns in population divergence, population size change, and gene flow are aligned with the chronosequence of the four volcanoes on which L. cerasina occurs and reveal the composite effects of geological dynamics and Quaternary climate change on population dynamics. Spatio-temporal patterns in genetic variation along the genome reveal the interplay of genetic and genomic architecture in shaping population divergence. In early phases of divergence, we find elevated differentiation in genomic regions harbouring mating song loci. In later stages of divergence, we find a signature of linked selection that interacts with recombination rate variation. Comparing our findings with recent work on complementary systems supports the conclusion that mostly universal factors influence the speciation process.

Multi-scale analysis of satellite, reanalysis and muti-source precipitation estimates over the Tibetan Plateau

Due to the important hydrological and meteorological significance, the performance of different kinds of precipitation products for the Tibetan Plateau (TP) has been evaluated in previous studies. However, the performance of the products on a high spatial-temporal scale has not been clearly shown. Based on the Chinese Meteorological Administration (CMA) ground rain gauge observations during 2017–2018 over the TP, this paper analyzes the multi-scale performance of four satellite-based datasets (IMERG_Uncal, IMERG_Cal, GSMaP_MVK, and GSMaP_Gauge), two reanalysis datasets (ERA5 and ERA5-L), and one multi-source merged dataset (CMFD) for different precipitation intensities with a special attention to the characterization of spatiotemporal variability of heavy precipitation. Firstly, this study examines how the quality of precipitation products varies with time scale and precipitation intensity. CMFD generally shows the best quality and has the most stable quality at all temporal scales. Satellite products perform better in summer while reanalysis products show better results in cold seasons. Another significant issue is the impact of gauge-based calibration. GSMaP_Gauge with daily-scale gauge calibration is often considered to outperform other products. However, our study finds that GSMaP_Gauge is problematic at smaller spatiotemporal scales, especially in capturing heavy precipitation. The long-term performance of multi spatiotemporal scale comparison of different precipitation products is the focus of this study, which can help with their application and improvement.

Spatiotemporal Characteristics of the Near-Surface Turbulent Cascade at the Submesoscale in the Drake Passage

Abstract Submesoscale currents and internal gravity waves achieve an intense turbulent cascade near the ocean surface [depth of 0–O(100) m], which is thought to give rise to significant energy sources and sinks for mesoscale eddies. Here, we characterize the contributions of nonwave currents (NWCs; including eddies and fronts) and internal gravity waves (IGWs; including near-inertial motions, lee waves, and the internal wave continuum) to near-surface submesoscale turbulence in the Drake Passage. Using a numerical simulation, we combine Lagrangian filtering and a Helmholtz decomposition to identify NWCs and IGWs and to characterize their dynamics (rotational versus divergent). We show that NWCs and IGWs contribute in different proportions to the inverse and forward turbulent kinetic energy cascades, based on their dynamics and spatiotemporal scales. Purely rotational NWCs cause most of the inverse cascade, while coupled rotational–divergent components of NWCs and coupled NWC–IGWs cause the forward cascade. The cascade changes direction at a spatial scale at which motions become increasingly divergent. However, the forward cascade is ultimately limited by the motions’ spatiotemporal scales. The bulk of the forward cascade (80%–95%) is caused by NWCs and IGWs of small spatiotemporal scales (L < 10 km; T < 6 h), which are primarily rotational: submesoscale eddies, fronts, and the internal wave continuum. These motions also cause a significant part of the inverse cascade (30%). Our results highlight the requirement for high spatiotemporal resolutions to diagnose the properties and large-scale impacts of near-surface submesoscale turbulence accurately, with significant implications for ocean energy cycle study strategies.

Identifying the social context of single- and mixed-species group formation in large African herbivores.

Despite continued interest in mixed-species groups, we still lack a unified understanding of how ecological and social processes work across scales to influence group formation. Recent work has revealed ecological correlates of mixed-species group formation, but the mechanisms by which concomitant social dynamics produce these patterns, if at all, is unknown. Here, we use camera trap data for six mammalian grazer species in Serengeti National Park. Building on previous work, we found that ecological variables, and especially forage quality, influenced the chances of species overlap over small spatio-temporal scales (i.e. on the scales of several metres and hours). Migratory species (gazelle, wildebeest and zebra) were more likely to have heterospecific partners available in sites with higher forage quality, but the opposite was true for resident species (buffalo, hartebeest and topi). These findings illuminate the circumstances under which mixed-species group formation is even possible. Next, we found that greater heterospecific availability was associated with an increased probability of mixed-species group formation in gazelle, hartebeest, wildebeest and zebra, but ecological variables did not further shape these patterns. Overall, our results are consistent with a model whereby ecological and social drivers of group formation are species-specific and operate on different spatio-temporal scales. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'.

Long-term insect censuses capture progressive loss of ecosystem functioning in East Asia.

Insects provide critical ecosystem services such as biological pest control, in which natural enemies (NE) regulate the populations of crop-feeding herbivores (H). While H-NE dynamics are routinely studied at small spatiotemporal scales, multiyear assessments over entire agrolandscapes are rare. Here, we draw on 18-year radar and searchlight trapping datasets (2003-2020) from eastern Asia to (i) assess temporal population trends of 98 airborne insect species and (ii) characterize the associated H-NE interplay. Although NE consistently constrain interseasonal H population growth, their summer abundance declined by 19.3% over time and prominent agricultural pests abandoned their equilibrium state. Within food webs composed of 124 bitrophic couplets, NE abundance annually fell by 0.7% and network connectance dropped markedly. Our research unveils how a progressive decline in insect numbers debilitates H trophic regulation and ecosystem stability at a macroscale, carrying implications for food security and (agro)ecological resilience during times of global environmental change.

Advancing understanding of land-atmosphere interactions by breaking discipline and scale barriers.

Vegetation and atmosphere processes are coupled through a myriad of interactions linking plant transpiration, carbon dioxide assimilation, turbulent transport of moisture, heat and atmospheric constituents, aerosol formation, moist convection, and precipitation. Advances in our understanding are hampered by discipline barriers and challenges in understanding the role of small spatiotemporal scales. In this perspective, we propose to study the atmosphere-ecosystem interaction as a continuum by integrating leaf to regional scales (multiscale) and integrating biochemical and physical processes (multiprocesses). The challenges ahead are (1) How do clouds and canopies affect the transferring and in-canopy penetration of radiation, thereby impacting photosynthesis and biogenic chemical transformations? (2) How is the radiative energy spatially distributed and converted into turbulent fluxes of heat, moisture, carbon, and reactive compounds? (3) How do local (leaf-canopy-clouds, 1 m to kilometers) biochemical and physical processes interact with regional meteorology and atmospheric composition (kilometers to 100 km)? (4) How can we integrate the feedbacks between cloud radiative effects and plant physiology to reduce uncertainties in our climate projections driven by regional warming and enhanced carbon dioxide levels? Our methodology integrates fine-scale explicit simulations with new observational techniques to determine the role of unresolved small-scale spatiotemporal processes in weather and climatemodels.

The impact of climate change and wildfire on decadal alpine vegetation dynamics

Context Climate-induced changes of alpine vegetation diversity, cover and composition have been recorded globally, but most insights have been gleaned from field studies over small spatiotemporal scales. Aims We assess dynamics in climate and vegetation of Australia’s highest and most biologically diverse alpine area that surrounds Mount Kosciuszko (~455 km2), as well as recovery following the 2003 wildfires. Methods Climatic changes were analysed using gridded climate data for mean annual temperature (1910–2019) and seasonal precipitation (1900–2019), and changes in snow cover were assessed from snow course records (1954–2021). A vegetation cover time series (1990, 2000, 2010, 2020) was modelled with an optimised random forest classification using recursive feature selection, and the LandTrendr algorithm was used to detect areas burnt during wildfires. Key results Over time, temperatures and summer precipitation increased, whereas snow cover and winter precipitation decreased. Subsequently, vegetation dynamics were dominated by the densification of subalpine woodlands at lower elevations, replacing dry and wet heathlands. There was treeline stasis but upslope advancement of dry and wet shrublines but grassland vegetation types were relatively stable. However, in burnt areas there was suppressed upslope advancement of shrublines, treeline recession and relatively less expansion of subalpine woodlands. Conclusions Alpine vegetation may be impacted by climate change incrementally through relatively gradual changes in climatic conditions, and transformatively through landscape-level disturbance from wildfires. Implications Higher temperatures and altered precipitation regimes increase the frequency and severity of wildfires, which may be amplified by increasing fuel loads and dryness from the proliferation and advance of woody vegetation in alpine areas.

Impact of hydrological processes on wetland landscapes and wintering migratory birds in a large floodplain lake (Poyang Lake, China)

AbstractHydrological processes are an important factor influencing the wetland landscapes and the quality of wintering migratory birds habitat in Poyang Lake. However, most of the research on a small spatiotemporal scale and there is a lack of studies on the impact of hydrological processes on migratory bird habitats. This study analysed the response of the Poyang Lake wetland landscape to low water levels from 1990 to 2016 and determined the relationship between hydrological processes, wetland landscape characteristics and migratory bird habitats. According to the results, the number of days during the study period when the maximum water level was higher than the current water level (MaxDay) and the average water level from the 40th to 50th day prior to the current day (D50) are two critical factors affecting the area of grassland in Poyang Lake. In particular, a D50 value of 9.5–11.0 m is important for maintaining the grassland area and growth of wetland vegetation. Besides, the water level should not exceed 11 m from mid–late October to early November and should be maintained between 7.58 and 7.97 m in mid–late December that can maximize the habitat area of migratory birds. Furthermore, this study used ecological threshold to propose the optimal inundation period of Cyperus rotundus L. community, Leersia japonica community, Polygonum criopolitanum community, Phragmites australis community, Triarrhena lutarioriparia community, Carex spp. community and Phalaris arundinacea community, which are 124–174, 31–101, 199–249, 65–147, 51–121, 110–190 and 175–253 days, respectively.

Modeling of chromospheric features and dynamics in solar plage

The chromosphere is a dynamic and complex layer where all the relevant physical processes happen on very small spatio-temporal scales. A few spectral lines that can be used as chromospheric diagnostics give us convoluted information that is hard to interpret without realistic theoretical models. What are the key ingredients that these models need to contain? The magnetic field has a paramount effect on chromospheric structuring. This is obvious from the ubiquitous presence of chromospheric dynamic fibrilar structures visible on the solar disk and at the limb. The numerical experiments presented in this manuscript illustrate the present state of modeling. They showcase to what extent our models reproduce various chromospheric features and their dynamics. The publication describes the effect different ingredients have on chromospheric models and provides a recipe for building one-to-one models. Combining these models with observations will provide insight into the physical processes that take place in the solar atmosphere.

The role of wind, mesoscale dynamics, and coastal circulation in the interannual variability of the South Vietnam Upwelling, South China Sea – answers from a high-resolution ocean model

Abstract. The South Vietnam Upwelling (SVU) develops in the South China Sea (SCS) under the influence of southwest monsoon winds. To study the role of small spatiotemporal scales on the SVU functioning and variability, a simulation was performed over 2009–2018 with a high-resolution configuration (1 km at the coast) of the SYMPHONIE model implemented over the western region of the SCS. Its capability to represent ocean dynamics and water masses from daily to interannual scales and from coastal to regional areas is quantitatively demonstrated by comparison with available satellite data and four in situ datasets. The SVU interannual variability is examined for the three development areas already known: the southern (SCU) and northern (NCU) coastal upwelling areas and the offshore upwelling area (OFU). Our high-resolution model, together with in situ observations and high-resolution satellite data, moreover shows for the first time that upwelling develops over the Sunda Shelf off the Mekong Delta (MKU). Our results confirm for the SCU and OFU and show for the MKU the role of the mean summer intensity of wind and cyclonic circulation over the offshore area in driving the interannual variability of the upwelling intensity. They further reveal that other factors contribute to SCU and OFU variability. First, the intraseasonal wind chronology strengthens (in the case of regular wind peaks occurring throughout the summer for SCU or of stronger winds in July–August for OFU) or weakens (in the case of intermittent wind peaks for SCU) the summer average upwelling intensity. Second, the mesoscale circulation influences this intensity (multiple dipole eddies and associated eastward jets developing along the coast enhance the SCU intensity). The NCU interannual variability is less driven by the regional-scale wind (with weaker monsoon favoring stronger NCU) and more by the mesoscale circulation in the NCU area: the NCU is prevented (favored) when alongshore (offshore) currents prevail.

A terrain treadmill to study animal locomotion through large obstacles.

A challenge to understanding locomotion in complex three-dimensional terrain with large obstacles is to create tools for controlled, systematic experiments. Recent terrain arenas allow observations at small spatiotemporal scales (∼10 body lengths or cycles). Here, we created a terrain treadmill to enable high-resolution observation of animal locomotion through large obstacles over large spatiotemporal scales. An animal moves through modular obstacles on an inner sphere, while a rigidly attached, concentric, transparent outer sphere rotates with the opposite velocity via closed-loop feedback to keep the animal on top. During sustained locomotion, a discoid cockroach moved through pillar obstacles for up to 25 min (2500 cycles) over 67 m (1500 body lengths). Over 12 trials totaling ∼1 h, the animal was maintained within a radius of 1 body length (4.5 cm) on top of the sphere 90% of the time. The high-resolution observation enables the study of diverse locomotor behaviors and quantification of animal-obstacle interaction.

A Dataset of Overshooting Cloud Top from 12-Year CloudSat/CALIOP Joint Observations

A strong convective storm is a disastrous weather system with a small spatio-temporal scale. It often occurs suddenly and can cause huge disasters. Thus, it is necessary to improve the forecast accuracy of strong convective storms. Overshooting cloud top (OT) is the product of strong updrafts in convective storms, which can penetrate the tropopause and enter the lower stratosphere. OT is closely related to severe weather and can influence water vapor transport and the material exchange between the troposphere and stratosphere. Therefore, the timely detection of OT can help improve the accuracy of forecasting. In this study, we develop a new objective OT detection algorithm based on geostationary satellite observations from 2006 to 2017. The accuracy of the new algorithm in identifying OT is verified by manually comparing it with the radar echo images and the cloud images of MODIS 250 m. Then, the OT is statistically analyzed in a long time series. It is found that OT events are mainly concentrated in equatorial and low latitude regions, with higher frequency in summer. There are obvious differences between OT events on land and sea. Additionally, this dataset also reveals the close connection between the seasonal shift of OT and the seasonal average precipitation distribution around the globe. This study provides a scientific basis for determining the geographical characteristics of OT frequency and explores the application of this OT objective detection algorithm in the operational forecast of strong convective weather. We hope this study can benefit OT monitoring in operational weather forecasting.

Comparing spatial metrics of extreme precipitation between data from rain gauges, weather radar and high-resolution climate model re-analyses

The representation of extreme precipitation at small spatio-temporal scales is of major importance in urban hydrology. The present study compares point and radar observations to reanalyse climate model output data for a period of 14 years where there is full spatial and temporal overlap between datasets. The datasets are compared with respect to seasonality of occurrence, intensity levels and spatial structure of the extreme events. All datasets have similar seasonal distributions and comparable intensity levels. There are, however, clear differences in the spatial correlation structure of the extremes. Seemingly, the radar data is the best representation of a “real” spatial structure for extreme precipitation, even though challenges appear in data when moving far from the physical radar. The spatial correlation in point observations is a valid representation of the spatial structure of extreme precipitation. The convective-permitting climate model seems to represent the spatial structure of extreme precipitation much more realistically, compared to the coarser convective parameterized model. However, there is still room for improvement of the convective-permitting climate model for the shortest rainfall durations and smallest spatial scales in comparison with point and radar data.

On the Local Rain-Rate Extreme Associated with a Mesovortex over South China: Observational Structures, Characteristics, and Evolution

Abstract Extreme short-term hourly rainfall accumulations are shown to be commonly attendant with rotation-featured mesovortices. This study aims to document the detailed aspects of mesovortex-related extreme rain rates in a record-breaking event that occurred over South China on 7 May 2017 through high-resolution observations, and to reveal how the mesoscale storm contributes to the extreme rain rates, with special attention given to the minute rain-rate enhancement episode (MREE). The event accumulation possesses highly local distribution, with a spatial rainfall core. Extreme rain rates are dictated by a meso-γ-scale storm, and it is found that the observed rain rate is well correlated to storm-related maximum reflectivity in the lowest 2 km above ground level (AGL) as well as its reflectivity centroid (i.e., reflectivity factor exceeding 50 dBZ) depth. The cross section reveals that the storm structure evolves progressively into a single centroid, which subsequently descends to the near surface, resulting in the rain-rate peak (4.8 mm min−1). Extremely weak environmental mean flow interacts with the near-opposite storm propagation that determines the slow storm movement, prolonging local rainfall. Rainfall-induced cold outflow surges ahead unevenly, leading to an inhomogeneous mesoscale outflow boundary (IMOB) at low levels. A mesovortex subsequently develops along the IMOB in the lowest ∼5.5 km AGL, with a horizontal radius of 1.5–3 km. A mesoscale low-level jet observed over the upstream of the storm increases the low-level shear despite short duration, which provide potential dynamics for the storm and mesovortex development. These results help us better understand the generation of extreme rain rates in small spatiotemporal scale. Significance Statement Despite many extreme short-duration rainfall events linking to low-level rotation phenomenon, we are still exploring how these rotations develop within extreme-rainfall-producing storms. While past studies have found that these low-level rotations within such storms are conducive to enhancing rainfall, rotation characteristics are less understood. In this study, we examine how the rotations develop during an episode of observed-rainfall rise. The results reveal that the cold airflows resulted from the storm-inducing rainfall impinge unevenly on warm moist southerly wind, leading to such low-level rotation. The rainfall observed per minute is found to associate well with low-level rotation that develops upward. These results further motivate exploration of extreme short-duration rainfall and storm-related rotation.

An assessment of tropopause characteristics of the ERA5 and ERA-Interim meteorological reanalyses

Abstract. The tropopause layer plays a key role in manifold processes in atmospheric chemistry and physics. Here we compare the representation and characteristics of the lapse rate tropopause according to the definition of the World Meteorological Organization (WMO) as estimated from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Our study is based on 10-year records (2009 to 2018) of ECMWF's state-of-the-art reanalysis ERA5 and its predecessor ERA-Interim. The intercomparison reveals notable differences between ERA5 and ERA-Interim tropopause data, in particular on small spatiotemporal scales. The monthly mean differences of ERA5 minus ERA-Interim tropopause heights vary between −300 m at the transition from the tropics to the extratropics (near 30∘ S and 30∘ N) to 150 m around the Equator. Mean tropopause temperatures are mostly lower in ERA5 than in ERA-Interim, with a maximum difference of up to −1.5 K in the tropics. Monthly standard deviations of tropopause heights of ERA5 are up to 350 m or 60 % larger than for ERA-Interim. Monthly standard deviations of tropopause temperatures of ERA5 exceed those of ERA-Interim by up to 1.5 K or 30 %. The occurrence frequencies of double-tropopause events in ERA5 exceed those of ERA-Interim by up to 25 percentage points at middle latitudes. We attribute the differences between the ERA5 and ERA-Interim tropopause data and the larger, more realistic variability of ERA5 to improved spatiotemporal resolution and better representation of geophysical processes in the forecast model as well as improvements in the data assimilation scheme and the utilization of additional observations in ERA5. The improved spatiotemporal resolution of ERA5 allows for a better representation of mesoscale features, in particular of gravity waves, which affect the temperature profiles in the upper troposphere and lower stratosphere (UTLS) and thus the tropopause height estimates. We evaluated the quality of the ERA5 and ERA-Interim reanalysis tropopause data by comparisons with COSMIC and MetOp Global Positioning System (GPS) satellite observations as well as high-resolution radiosonde profiles. The comparison indicates an uncertainty of the first tropopause for ERA5 (ERA-Interim) of about ±150 to ±200 m (±250 m) based on radiosonde data and ±120 to ±150 m (±170 to ±200 m) based on the coarser-resolution GPS data at different latitudes. Consequently, ERA5 will provide more accurate information than ERA-Interim for future tropopause-related studies.

Seeing the locust in the swarm: accounting for spatiotemporal hierarchy improves ecological models of insect populations

Ecological phenomena operate at different spatial scales and are not uniform across landscapes or through time. One ecological theory that attempts to account for scaling and spatiotemporal variances is hierarchical patch dynamics. It introduces a hierarchical patch network with smaller spatiotemporal scales being nested within larger scales. However, few studies have modeled its presence within animal population dynamics. Locusts are an excellent model for investigating the spatiotemporal hierarchy of animal population dynamics, due to their high migratory capacity, large geographic ranges that extend across widely differing environments, and available long‐term data on distributions. Here, we investigated the influence of preceding vegetation growth on desert locust Schistocerca gregaria and Australian plague locust Chortoicetes terminifera outbreaks on three spatial levels (species range > geographic region > land unit) and between seasons. Both species are dryland herbivores with population dynamics linked to habitat productivity pulses after rain. We used NDVI data (MODIS imagery) as a measure of vegetation growth in hierarchical generalized additive models at different scales. Locust outbreaks were either preceded by vegetation growth between 78 and 32 days (Australian plague locusts) or 32 and 20 days before (desert locust) the observation. Although prior vegetation growth characterized outbreaks of both species, the temporal pattern of NDVI differed between spatiotemporal levels. All model selection criteria selected for a similar spatial hierarchy for both species: geographic region > land unit which supports the hierarchical patch dynamics paradigm. Further, it illuminates important timing differences between geographic regions and land units for preceding vegetation growth and locust outbreaks which can help locust managers identify when and where outbreaks occur. By acknowledging the spatiotemporal patterning of locust abundance, we account for heterogeneity of population dynamics throughout species ranges. Our findings demonstrate the importance of incorporating spatiotemporal variation in population models of insects and other animals.

Bending of the concentration discharge relationship can inform about in-stream nitrate removal

Abstract. Nitrate (NO3-) excess in rivers harms aquatic ecosystems and can induce detrimental algae growths in coastal areas. Riverine NO3- uptake is a crucial element of the catchment-scale nitrogen balance and can be measured at small spatiotemporal scales, while at the scale of entire river networks, uptake measurements are rarely available. Concurrent, low-frequency NO3- concentration and streamflow (Q) observations at a basin outlet, however, are commonly monitored and can be analyzed in terms of concentration discharge (C–Q) relationships. Previous studies suggest that steeper positive log (C)–log (Q) slopes under low flow conditions (than under high flows) are linked to biological NO3- uptake, creating a bent rather than linear log (C)–log (Q) relationship. Here we explore if network-scale NO3- uptake creates bent log (C)–log (Q) relationships and when in turn uptake can be quantified from observed low-frequency C–Q data. To this end we apply a parsimonious mass-balance-based river network uptake model in 13 mesoscale German catchments (21–1450 km2) and explore the linkages between log (C)–log (Q) bending and different model parameter combinations. The modeling results show that uptake and transport in the river network can create bent log (C)–log (Q) relationships at the basin outlet from log–log linear C–Q relationships describing the NO3- land-to-stream transfer. We find that within the chosen parameter range the bending is mainly shaped by geomorphological parameters that control the channel reactive surface area rather than by the biological uptake velocity itself. Further we show that in this exploratory modeling environment, bending is positively correlated to percentage of NO3- load removed in the network (Lr.perc) but that network-wide flow velocities should be taken into account when interpreting log (C)–log (Q) bending. Classification trees, finally, can successfully predict classes of low (∼4 %), intermediate (∼32 %) and high (∼68 %) Lr.perc using information on water velocity and log (C)–log (Q) bending. These results can help to identify stream networks that efficiently attenuate NO3- loads based on low-frequency NO3- and Q observations and generally show the importance of the channel geomorphology on the emerging log (C)–log (Q) bending at network scales.

Seasonal genotype dynamics of a marine dinoflagellate: Pelagic populations are homogeneous and as diverse as benthic seed banks.

Genetic diversity is the basis for evolutionary adaptation and selection under changing environmental conditions. Phytoplankton populations are genotypically diverse, can become genetically differentiated within small spatiotemporal scales and many species form resting stages. Resting stage accumulations in sediments (seed banks) are expected to serve as reservoirs for genetic information, but so far their role in maintaining phytoplankton diversity and in evolution has remained unclear. In this study we used the toxic dinoflagellate Alexandrium ostenfeldii (Dinophyceae) as a model organism to investigate if (i) the benthic seed bank is more diverse than the pelagic population and (ii) the pelagic population is seasonally differentiated. Resting stages (benthic) and plankton (pelagic) samples were collected at a coastal bloom site in the Baltic Sea, followed by cell isolation and genotyping using microsatellite markers (MS) and restriction site associated DNA sequencing (RAD). High clonal diversity (98%–100%) combined with intermediate to low gene diversity (0.58–0.03, depending on the marker) was found. Surprisingly, the benthic and pelagic fractions of the population were equally diverse, and the pelagic fraction was temporally homogeneous, despite seasonal fluctuation of environmental selection pressures. The results of this study suggest that continuous benthic–pelagic coupling, combined with frequent sexual reproduction, as indicated by persistent linkage equilibrium, prevent the dominance of single clonal lineages in a dynamic environment. Both processes harmonize the pelagic with the benthic population and thus prevent seasonal population differentiation. At the same time, frequent sexual reproduction and benthic–pelagic coupling maintain high clonal diversity in both habitats.

Spatial Hurst–Kolmogorov Clustering

The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is introduced as a robust means to identify, model and simulate the Hurst–Kolmogorov (HK) dynamics, ranging from small (fractal) to large scales exhibiting the clustering behavior (else known as the Hurst phenomenon or long-range dependence). The HK clustering is an attribute of a multidimensional (1D, 2D, etc.) spatio-temporal stationary stochastic process with an arbitrary marginal distribution function, and a fractal behavior on small spatio-temporal scales of the dependence structure and a power-type on large scales, yielding a high probability of low- or high-magnitude events to group together in space and time. This behavior is preferably analyzed through the second-order statistics, and in the scale domain, by the stochastic metric of the climacogram, i.e., the variance of the averaged spatio-temporal process vs. spatio-temporal scale.

Terrestrial mesopredators did not increase after top-predator removal in a large-scale experimental test of mesopredator release theory

Removal or loss of top-predators has been predicted to cause cascading negative effects for ecosystems, including mesopredator release. However, reliable evidence for these processes in terrestrial systems has been mixed and equivocal due, in large part, to the systemic and continued use of low-inference study designs to investigate this issue. Even previous large-scale manipulative experiments of strong inferential value have been limited by experimental design features (i.e. failure to prevent migration between treatments) that constrain possible inferences about the presence or absence of mesopredator release effects. Here, we build on these previous strong-inference experiments and report the outcomes of additional large-scale manipulative experiments to eradicate Australian dingoes from two fenced areas where dingo migration was restricted and where theory would predict an increase in extant European red foxes, feral cats and goannas. We demonstrate the removal and suppression of dingoes to undetectable levels over 4–5 years with no corresponding increases in mesopredator relative abundances, which remained low and stable throughout the experiment at both sites. We further demonstrate widespread absence of negative relationships between predators, indicating that the mechanism underpinning predicted mesopredator releases was not present. Our results are consistent with all previous large-scale manipulative experiments and long-term mensurative studies which collectively demonstrate that (1) dingoes do not suppress red foxes, feral cats or goannas at the population level, (2) repeated, temporary suppression of dingoes in open systems does not create mesopredator release effects, and (3) removal and sustained suppression of dingoes to undetectable levels in closed systems does not create mesopredator release effects either. Our experiments add to similar reports from North America, Asia, Europe and southern Africa which indicate that not only is there a widespread absence of reliable evidence for these processes, but there is also a large and continually growing body of experimental evidence of absence for these processes in many terrestrial systems. We conclude that although sympatric predators may interact negatively with each other on smaller spatiotemporal scales, that these negative interactions do not always scale-up to the population level, nor are they always strong enough to create mesopredator suppression or release effects.