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opencc-zeroAug 2020View details →

Dynamic shifts in social network structure and composition within a breeding hybrid population

1. Mating behavior and the timing of reproduction can inhibit genetic exchange between closely related species; however, these reproductive barriers are challenging to measure within natural populations. Social network analysis provides promising tools for studying the social context of hybridization, and the exchange of genetic variation, more generally. 2. We test how social networks within a hybrid population of California (Callipepla californica) and Gambel's quail (Callipepla gambelii) change over discrete periods of a breeding season. We assess patterns of phenotypic and genotypic assortment, and ask whether altered associations between individuals (association rewiring), or changes to the composition of the population (individual turnover) drive network dynamics. We use genetic data to test whether social associations and relatedness between individuals correlate with patterns of parentage within the hybrid population. 3. To achieve these aims, we combine RFID association data, phenotypic data, and genomic measures with social network analyses. We adopt methods from the ecological network literature to quantify shifts in network structure and to partition changes into those due to individual turnover and association rewiring. We integrate genomic data into networks as node-level attributes (ancestry) and edges (relatedness, parentage) to test links between social and parentage networks. 4. We show that rewiring of associations between individuals that persist across network periods, rather than individual turnover, drives the majority of the changes in network structure throughout the breeding season, and that the traits involved in phenotypic/genotypic assortment were highly dynamic over time. Social networks were randomly assorted based upon genetic ancestry, suggesting weak behavioral reproductive isolation within this hybrid population. Finally, we show that the strength of associations within the social network, but not levels of genetic relatedness, predict patterns of parentage. 5. Social networks play an important role in population processes such as the transmission of disease and information, yet there has been less focus on how networks influence the exchange of genetic variation. By integrating analyses of social structure, phenotypic assortment, and reproductive outcomes within a hybrid zone, we demonstrate the utility of social networks for analyzing links between social context and gene flow within wild populations. 08-Jul-2020

opencc-zeroAug 2020View details →

Drivers and dynamics of a massive adaptive radiation in cichlid fishes

Adaptive radiation is the likely source of much of the ecological and morphological diversity of life. How adaptive radiations proceed and what determines their extent remains elusive in most cases. Here we report the in-depth examination of the spectacular adaptive radiation of cichlid fishes in African Lake Tanganyika. Based on whole-genome phylogenetic analyses, multivariate morphological measurements of three ecologically relevant trait complexes (body shape, upper oral jaw morphology, and lower pharyngeal jaw shape), scoring of pigmentation patterns, and approximations of the ecology of virtually all ~240 cichlid species endemic to Lake Tanganyika, we show that the radiation occurred within the confines of the lake and that morphological diversification proceeded in consecutive trait-specific pulses of morphospace expansion. We provide empirical support for two theoretical predictions on how adaptive radiations proceed, the 'early-burst' scenario (for body shape) and the stages model (for all traits investigated). Through the analysis of two genomes per species and by taking advantage of the uneven distribution of species in subclades of the radiation, we further show that species richness scales positively with per individual heterozygosity, but is not correlated with transposable element content, number of gene duplications, or genome-wide levels of selection in coding sequences.

opencc-by-4.0May 2020View details →

Dataset for "Seasonal dynamics of the COS and CO2 exchange of a managed temperate grassland"

Data of measurements and model output of the publication "Seasonal dynamics of the COS and CO2 exchange of a managed temperate grassland". https://doi.org/10.5194/bg-2020-27 Data consists of micrometeorological data, COS and CO2 flux measurements for a managed temperate mountain grassland in Austria. For additional information please contact: <a href="mailto:Georg.Wohlfahrt@uibk.ac.at">Georg.Wohlfahrt@uibk.ac.at</a> changes in version 2: includes extrapolated COS mixing ratios & includes the ustar filter for the flux data changes in version 3: corrected every instance of mixing ratio with mole fraction

opencc-zeroAug 2020View details →

Integrating floral trait and flowering time distribution patterns help reveal a more dynamic nature of co-flowering community assembly processes

Species' floral traits and flowering times are known to be the major drivers of pollinator-mediated plant-plant interactions in diverse co-flowering communities. However, their simultaneous role in mediating plant community assembly and plant-pollinator interactions is still poorly understood. Since not all species flower at the same time, inference of facilitative and competitive interactions based on floral trait distribution patterns should account for fine phenological structure (intensity of flowering overlap) within co-flowering communities. Such an approach may also help reveal the simultaneous action of competitive and facilitative interactions in structuring co-flowering communities. Here we used modularity within a co-flowering network context, as a novel approach to detect convergent and/or over-dispersed patterns in floral trait distribution and pollinator sharing. Specifically, we evaluate differences in floral trait and pollinator distribution patterns within (high temporal flowering overlap) and among co-flowering modules (low temporal flowering overlap). We further evaluate the consistency of observed floral trait and pollinator sharing distribution patterns across space (three geographic regions) and time (dry and rainy seasons). We found that floral trait similarity was significantly higher in plant species within co-flowering modules than in species among them. This suggests pollinator facilitation may lead to floral trait convergence, but only within co-flowering modules. However, our results also revealed seasonal and spatial shifts in the underlying interactions (facilitation or competition) driving co-flowering assembly, suggesting that the prevalent dominant interactions are not static. Synthesis: Overall, we provide strong evidence showing that the use of flowering time and floral trait distribution alone may be insufficient to fully uncover the role of pollinator-mediated interactions in community assembly. Integrating this information along with patterns of pollinator sharing will greatly help reveal the simultaneous action of facilitative and competitive pollinator-mediated interactions in co-flowering communities. The spatial and temporal variation in flowering and trait distribution patterns observed further emphasize the importance of adopting a more dynamic view of community assembly processes.

opencc-by-4.0Sep 2020View details →

Molecular dynamics simulations data for "Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes".

Molecular dynamics simulation data created and used in "Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes".

VTFT_Demography: global ageclass simulation data from the LPJ-wsl v2.0 Dynamic Global Vegetation Model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in most global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to fill this gap in understanding by presenting the technical developments of a computationally-efficient approach for representing age-class dynamics within a global ecosystem model, the LPJ-wsl v2.0 Dynamic Global Vegetation Model. The modeled age-classes are initially created by fire feedbacks, wood harvesting, and abandonment of managed land, otherwise aging naturally until a stand-clearing disturbance is simulated or prescribed. In this paper, we show that the age-module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that patterns of ecosystem function follow classic responses with age. We also present a few scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a ~45-year difference in ages between boreal (50N-90N) and tropical (23S-23N) latitudes. Land use change and land management was responsible for an additional decrease in zonal age by -6 years in boreal and by -21 years in temperate (23N-50N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped reduced LPJ-wsl complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature and age-class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C m-2 yr-1 but as high as 0.60 kg C m-2 yr-1 where the effect was greatest. In eastern forests of North America, the demographic effect was of similar magnitude, or greater than, the effects of climate; demographic effects were similarly important in large regions of every vegetated continent. Spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40-Pg C increase in turnover from age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. This LPJ-based age-module therefore simulates the upper limit of age-class distributions on Earth and represents another step forward towards understanding the role of demography in global ecosystems.

Data from: Settling dynamics of nanoparticles in simple and biological media

The biological response of organisms exposed to nanoparticles is often studied in vitro using adherent monolayers of cultured cells. In order to derive accurate concentration-response relationships, it is important to determine the local concentration of nanoparticles to which the cells are actually exposed rather than the nominal concentration of nanoparticles in the cell-culture medium. In this study, the sedimentation–diffusion process of different sized and charged gold nanoparticles has been investigated in vitro by evaluating their settling dynamics and by developing a theoretical model to predict the concentration depth-profile of nanoparticles in solution over time. Experiments were carried out in water and in cell-culture media at a range of controlled temperatures. The optical phenomenon of caustics was exploited to track nanoparticles in real-time in a conventional optical microscope without any requirement for fluorescent labelling that potentially affects the dynamics of the nanoparticles. The results obtained demonstrate that size, temperature and the stability of the nanoparticles play a pivotal role in regulating settling dynamics of nanoparticles. For gold nanoparticles larger than 60 nm in diameter, the initial nominal concentration did not accurately represent the concentration of nanoparticles local to the cells.

Eco‐evolutionary dynamics driven by fishing: from single species models to dynamic evolution within complex food webs

Evidence of contemporary evolution across ecological time scales stimulated research on the eco-evolutionary dynamics of natural populations. Aquatic systems provide a good setting to study eco-evolutionary dynamics owing to a wealth of long-term monitoring data and the detected trends in fish life-history traits across intensively harvested marine and freshwater systems. In the present study, we focus on modelling approaches to simulate eco-evolutionary dynamics of fishes and their ecosystems. Firstly, we review the development of modelling from single-species to multispecies approaches. Secondly, we advance the current state-of-the-art methodology by implementing evolution of life-history traits of a top predator into the context of complex food web dynamics as described by the allometric trophic network (ATN) framework. The functioning of our newly developed eco-evolutionary ATNE framework is illustrated using a well-studied lake food web. Our simulations show how both natural selection arising from feeding interactions and size-selective fishing cause evolutionary changes in the top predator and how those feed back to its prey species and further cascade down to lower trophic levels. Finally, we discuss future directions, particularly the need to integrate genomic discoveries into eco-evolutionary projections.

opencc-by-4.0Sep 2020View details →

Raw data : Population Dynamics and Yield Loss Assessment for Pea Aphid (Homoptera: Aphididae) on Lentil in Morocco

Raw data to describes the population fluctuation of pea aphid over different seasons and their effects on yield loss in Morocco.

Stable and dynamic representations of value in the prefrontal cortex

This data set was compiled for the experiments detailed in Enel, P., Wallis, J., & Rich, E. (2019). Stable and dynamic representations of value in the prefrontal cortex. Elife 9 (2020): e54313 <a class="doi__link" href="https://doi.org/10.7554/eLife.54313">10.7554/eLife.54313</a> Optimal decision-making requires that stimulus-value associations are kept up to date by constantly comparing the expected value of a stimulus with its experienced outcome. To do this, value information must be held in mind when a stimulus and outcome are separated in time. However, little is known about the neural mechanisms of working memory (WM) for value. Contradicting theories have suggested WM requires either persistent or transient neuronal activity, with stable or dynamic representations respectively. To test these hypotheses, we recorded neuronal activity in the orbitofrontal and anterior cingulate cortex of two monkeys performing a valuation task. We found that features of all hypotheses were simultaneously present in prefrontal activity, and no single hypothesis was exclusively supported. Instead, mixed dynamics supported robust, time invariant value representations while also encoding the information in a temporally specific manner. We suggest that this hybrid coding is a critical mechanism supporting flexible cognitive abilities.

opencc-by-4.0Sep 2020View details →

Full-field numerical simulations of temperate ice viscoplastic deformation and dynamic recrystallization [Data set]

This data set corresponds to the scientific article Llorens, M.-G., Griera, A., Bons, P.D., Gomez-Rivas, E., Weikusat, I., Prior, D., Kerch, J. and Lebensohn, R.A. Seismic anisotropy of temperate ice in polar ice sheets. Journal of Geophysical Research: Earth Surface. This data set contains (i) the output files with the crystal orientation and phase data of each simulation presented in the article (run using the open-source software platform ELLE; Bons et al., 2008; Piazolo et al., 2019), and (ii) a code to plot the crystallographic orientation density function (ODF) using the open-source code MTEX (Mainprice et al., 2015). For the visualization of seismic wave velocities the information contained in these output files can be loaded (in radians) to the software package AEH-EBSD Analysis Toolbox (Naus-Thijseen, 2011; Vel et al., 2016). The output files are provided for time steps 50 (shear strain of 1), 100 (shear strain of 2), 200 (shear strain of 4), 300 (shear strain of 6) and 400 (shear strain of 8). Each file has eight columns and multiple rows. Each row stores the output data for an unode of the model, and the model has 256x256 unodes. The first three columns correspond to the three Euler angles (α, β, γ) in degrees, the fourth and fifth column are the x and y coordinates of each unode, the sixth and seventh columns contain attributes not used in these simulations and column eight shows the phase number corresponding to each unode (1 for solid ice and 2 for water). Three simulations are presented and analyzed in this article, and thus their results stored in this data set: Simulation 1: purely solid ice (melt fraction ϕ=0) Simulation 2: ice including 5% water (melt fraction ϕ=5) Simulation 3: ice including 15% water (melt fraction ϕ=15)

Simple muscle-lever systems are not so simple: The need for dynamic analyses to predict lever mechanics that maximize speed

Here we argue that quasi-static analyses are insufficient to predict the speed of an organism from its skeletal mechanics alone (i.e. lever arm mechanics). Using a musculoskeletal numerical model we specifically demonstrate that 1) a single lever morphology can produce a range of output velocities, and 2) a single output velocity can be produced by a drastically different set of lever morphologies. These two sets of simulations quantitatively demonstrate that it is incorrect to assume a one-to-one relationship between lever arm morphology and organism maximum velocity. We then use a statistical analysis to quantify what parameters are determining output velocity, and find that muscle physiology, geometry, and limb mass are all extremely important. Lastly we argue that the functional output of a simple lever is dependent on the dynamic interaction of two opposing factors: those decreasing velocity at low mechanical advantage (low torque and muscle work) and those decreasing velocity at high mechanical advantage (muscle force-velocity effects). These dynamic effects are not accounted for in static analyses and are inconsistent with a force-velocity tradeoff in lever systems. Therefore, we advocate for a dynamic, integrative approach that takes these factors into account when analyzing changes in skeletal levers.

opencc-zeroOct 2020View details →

Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances

Disturbances play a key role in driving forest ecosystem dynamics, but how disturbances shape wildlife habitat across space and time often remains unclear. A major reason for this is a lack of information about changes in habitat suitability across large areas and longer time periods. Here, we use a novel approach based on Landsat satellite image time series to map seasonal habitat suitability annually from 1986 to 2017. Our approach involves characterizing forest disturbance dynamics using Landsat-based metrics, harmonizing these metrics through a temporal segmentation algorithm, and then using them together with GPS telemetry data in habitat models. We apply this framework to assess how natural forest disturbances and post-disturbance salvage logging affect habitat suitability for two ungulates, roe deer (Capreolus capreolus) and red deer (Cervus elaphus), over 32 years in a Central European forest landscape. We found that red and roe deer differed in their response to forest disturbances. Habitat suitability for red deer consistently improved after disturbances, whereas the suitability of disturbed sites was more variable for roe deer depending on season (lower during winter than summer) and disturbance agent (lower in windthrow versus bark-beetle-affected stands). Salvage logging altered the suitability of bark beetle-affected stands for deer, having negative effects on red deer and mixed effects on roe deer, but generally did not have clear effects on habitat suitability in windthrows. Our results highlight long-lasting legacy effects of forest disturbances on deer habitat. For example, bark beetle disturbances improved red deer habitat suitability for at least 25 years. The duration of disturbance impacts generally increased with elevation. Methodologically, our approach proved effective for improving the robustness of habitat reconstructions from Landsat time series: integrating multi-year telemetry data into single, multi-temporal habitat models improved model transferability in time. Likewise, temporally segmenting the Landsat-based metrics increased the temporal consistency of our habitat suitability maps. As the frequency of natural forest disturbances is increasing across the globe, their impacts on wildlife habitat should be considered in wildlife and forest management. Our approach offers a widely applicable method for monitoring habitat suitability changes caused by landscape dynamics such as forest disturbance

Apparent breeding success drives long-term population dynamics of a migratory swan

The ability of a species to adapt to environmental change is ultimately reflected in its vital rates – i.e., survival and reproductive success of individuals. Together, vital rates determine trends in numbers, commonly monitored using counts of species abundance. Rapid changes in abundance can give rise to concern, leading to calls for research into the biological mechanisms underlying variations in demography. For the NW European population of Bewick's swan (Cygnus columbianus bewickii), there have been major changes in the population trends recorded during nearly five decades of monitoring (1970-2016). The total number of birds increased to a maximum of c. 30,000 in 1995 and subsequently decreased to about 18,000 individuals in 2010. Such large fluctuation in population numbers is rare in long-lived species and understanding the drivers of this population change is crucial for species management and conservation. Using the integrated population model (IPM) framework, we analysed three demographic datasets in combination: population counts, capture-mark-resightings (CMR) and the proportion of juveniles in winter over a period of ~50 years. We found higher apparent breeding success in the years when the population had a positive growth rate compared to years with a negative growth rate. Moreover, no consistent trend in adult and yearling survival, and an increasing trend in juvenile survival was found. A transient life-table response experiment showed that apparent breeding success and adult survival contributed most to the variation in population trend. We explored possible explanatory variables for the different demographic rates and found a significant association between juvenile survival both with the water level in lakes during autumn migration, which affects food accessibility for the swans, and with summer temperatures. Such associations are important for understanding the dynamics of species with fluctuating population sizes, and thus for informing management and conservation decisions.

opencc-zeroOct 2020View details →

Data from: Dispersal patterns in a medium-density Irish badger population: implications for understanding the dynamics of tuberculosis transmission.

European badgers (Meles meles) are group-living mustelids implicated in the spread of bovine tuberculosis (TB) to cattle and act as a wildlife reservoir for the disease. In badgers, only a minority of individuals disperse from their natal social group. However, dispersal may be extremely important for the spread of TB, as dispersers could act as hubs for disease transmission. We monitored a population of 139 wild badgers over seven years in a medium-density population (1.8 individuals/ km2). GPS-tracking collars were applied to 80 different individuals. Of these, we identified 25 dispersers, 14 of which were wearing collars as they dispersed. This allowed us to record the process of dispersal in much greater detail than ever before. We show that dispersal is an extremely complex process, and measurements of straight-line distance between old and new social groups can severely underestimate how far dispersers travel. Assumptions of straight-line travel can also underestimate direct and indirect interactions and the potential for disease transmission. For example, one female disperser which eventually settled 1.5 km from her natal territory travelled 308 km and passed through 22 different territories during dispersal. Knowledge of badgers'ranging behaviour during dispersal is crucial to understanding the dynamics of TB transmission, and for designing appropriate interventions, such as vaccination.

opencc-by-4.0Oct 2020View details →

Calcareous nannofossil size and abundance response to the Messinian Salinity Crisis onset and paleoenvironmental dynamics

The file contains calcareous nannofossils (Helicosphaera carteri, Sphenolithus abies, Umbilicosphaera rotula, Coccolithus pelagicus, Reticulofenestra minuta) biometry data collected in the Messinian Perales section (Sorbas Basin, Spain) and in the Banengo and Pollenzo sections (Piedmont Basin, Italy)

opencc-zeroOct 2020View details →

Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models

Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterised strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVM) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products, but rarely by other vegetation products or by in-situ field observations. In this study, we evaluate the performance of three methods for spatial representation of vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DM), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV). PFT profiles obtained from an independently collected vegetation data set from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVM often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, we suggest implementation of three novel PFT-specific thresholds for establishment in the DGVM. We performed a series of sensitivity experiments to demonstrate that these thresholds improve the performance of the DGVM. The results highlight the potential of using PFT-specific thresholds obtained by DM in development and benchmarking of DGVMs for broader regions. Also, we emphasize the potential of establishing DM as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

opencc-zeroNov 2020View details →

Trophic cascades alter eco-evolutionary dynamics and body size evolution

Trait evolution in predator-prey systems can feed back to the dynamics of interacting species as well as cascade to impact the dynamics of indirectly linked species (eco-evolutionary trophic cascades; EETC). A key mediator of trophic cascades is body mass, as it both strongly influences and evolves in response to predator-prey interactions. Here we use Gillespie Eco-Evolutionary Models to explore EETCs resulting from top predator loss and mediated by body mass evolution. Our four trophic level food chain model uses allometric scaling to link body mass to different functions (ecological pleiotropy) and is realistically parameterized from the FORAGE database to mimic the parameter space of a typical freshwater system. To track real-time changes in selective pressures, we also calculated fitness gradients for each trophic level. As predicted, top predator loss generated alternating shifts in abundance across trophic levels, and depending on the nature and strength in changes to fitness gradients, also altered trajectories of body mass evolution. Although more distantly linked, changes in the abundance of top predators still affected the eco-evolutionary dynamics of the basal producers, in part because of their relatively short generation times. Overall, our results suggest that impacts on top predators can set off transient eco-evolutionary trophic cascades with the potential for widespread indirect impacts on food webs.

opencc-zeroNov 2020View details →

Spatial and temporal dynamics of space use by free-ranging domestic dogs Canis familiaris in rural Africa

Variation in the spatial ecology of animals influences the transmission of infections and so understanding host behaviour can improve the control of diseases. Despite the global distribution of free-ranging domestic dogs Canis familiaris and their role as reservoirs for zoonotic diseases, little is known about the dynamics of their space use. We deployed GPS loggers on free-ranging dogs from six villages in rural Chad, and tracked the movements of 174 individuals in the dry season and 151 in the wet season. We calculated 95% and core home ranges using auto-correlated kernel density estimates (AKDE95 and AKDEcore), determined the degree to which their movements were predictable, and identified correlates of movement patterns. The median AKDE95 range in the dry season was 0.54km2 and in the wet season was 0.31km2, while the median AKDEcore range in the dry season was 0.08km2 and in the wet season was 0.04km2. Seasonal variation was, in part, related to owner activities. Dogs from hunting households had ranges that were five times larger in the dry season. At least 70% of individuals were more predictably 'at home' (<50m from the household) throughout the day in the dry season. 80% of dogs demonstrated periodicity in activity levels (speed) and just over half the dogs exhibited periodicity in location (repeated space use). In the wet season, dogs mostly exhibited 24-hour cycles in activity and location, with peaks at midday. In the dry season, dogs exhibited both 12 and 24-hour cycles, with either a single peak at midday, or one peak between 6am and 12 noon and a second between 6 and 10pm. Strategies to control canine-mediated zoonoses can be improved by tailoring operations to the local spatial ecology of free-ranging dogs. Interventions using a door-to-door strategy in rural Chad would best conduct operations during the dry season, when access to dogs around their household more reliably exceeds 70% throughout the day. Given the importance of use in hunting for explaining variation in dog space-use, targeting approaches to disease control at the household level on the basis of owner activities offers potential to improve access to dogs.