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opencc-zeroDec 2016View details →

Data from: Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Although heterogeneity in contact rate, physiology, and behavioral response to infection have all been empirically demonstrated in host–pathogen systems, little is known about how interactions between individual variation in behavior and physiology scale-up to affect pathogen transmission at a population level. The objective of this study is to evaluate how covariation between the behavioral and physiological components of transmission might affect epidemic outcomes in host populations. We tested the consequences of contact rate covarying with susceptibility, infectiousness, and infection status using an individual-based, dynamic network model where individuals initiate and terminate contacts with conspecifics based on their behavioral predispositions and their infection status. Our results suggest that both heterogeneity in physiology and subsequent covariation of physiology with contact rate could powerfully influence epidemic dynamics. Overall, we found that 1) individual variability in susceptibility and infectiousness can reduce the expected maximum prevalence and increase epidemic variability; 2) when contact rate and susceptibility or infectiousness negatively covary, it takes substantially longer for epidemics to spread throughout the population, and rates of epidemic spread remained suppressed even for highly transmissible pathogens; and 3) reductions in contact rate resulting from infection-induced behavioral changes can prevent the pathogen from reaching most of the population. These effects were strongest for theoretical pathogens with lower transmissibility and for populations where the observed variation in contact rate was higher, suggesting that such heterogeneity may be most important for less infectious, more chronic diseases in wildlife. Understanding when and how variability in pathogen transmission should be modelled is a crucial next step for disease ecology.

opencc-zeroDec 2015View details →

Data from: Consumer versus resource control and the importance of habitat heterogeneity for estuarine bivalves

The relative influence of consumers (top down) and resources (bottom up) on the distribution and abundance of organisms remains a key question in ecology. We examined the relationships between consumer and resource variables along a productivity gradient for a dominant predator–prey interaction in a marine soft-sediment system. We 1) quantified density and size of the clam Macoma balthica (prey species) in six replicate sites at each of four habitat types (shallow mud, deep mud, muddy sand and detrital mud) in the Rhode River, Chesapeake Bay. We selected one habitat type of high food availability and clam density (shallow mud) and another of low food availability and clam density (muddy sand) for manipulative experiments. Then, we 2) measured M. balthica survival and growth through transplants, 3) measured food availability as sedimentary organic carbon content, 4) quantified predator density, and 5) calculated predator foraging efficiency in the two habitat types. Clam density in the four habitat types differed and was related to sedimentary carbon availability and predator density. One of the habitats, detrital mud, appeared to be a population sink because it only held juvenile Macoma that never survived to reproductive age. Macoma size and growth, and predator (mainly blue crab Callinectes sapidus) densities were positively correlated with productivity and were higher in shallow mud than muddy sand. In contrast, Macoma mortality, local 'interaction strength', and predator foraging efficiency were lower in the productive habitat (shallow mud). Thus, predation intensity was inversely correlated with productivity (food availability); consumer and resource effects differed by habitat type; and, at a relatively small spatial scale, consumer and resource forces jointly determined population dynamics in this soft-sediment marine system.

opencc-zeroDec 2015View details →

Data from: Heterogeneity and concordance in locus-specific differentiation and introgression between species of towhees

The maintenance or breakdown of reproductive isolation are observable outcomes of secondary contact between species. In cases where hybrids beyond the F1 are formed, the representation of each species' ancestry can vary dramatically among genomic regions. This genomic heterogeneity in ancestry and introgression can offer insight into evolutionary processes, particularly if introgression is compared in multiple hybrid zones. Similarly, considerable heterogeneity exists across the genome in the extent to which populations and species have diverged, reflecting the combined effects of different evolutionary processes on genetic variation. We studied hybridization across two hybrid zones of two phenotypically well-differentiated bird species in Mexico (Pipilo maculatus and P. ocai), to investigate genomic heterogeneity in differentiation and introgression. Using genotyping by sequencing (GBS) and hierarchical Bayesian models, we genotyped 460 birds at over 41,000 single nucleotide polymorphism (SNP) loci. We identified loci exhibiting extreme introgression relative to the genome-wide expectation using a Bayesian genomic cline model. We also estimated locus-specific FST and identified loci with exceptionally high genetic divergence between the parental species. We found some concordance of locus-specific introgression in the two independent hybrid zones (6-20% of extreme loci shared across zones), reflecting areas of the genome that experience similar gene flow when the species interact. Additionally, heterogeneity in introgression and divergence across the genome revealed another subset of loci under the influence of locally specific factors. These results are consistent with a history in which reproductive isolation has been influenced by a common set of loci in both hybrid zones, but where local environmental and stochastic factors also lead to genomic differentiation.

opencc-zeroDec 2018View details →

Data from: Vegetation phenology and nest survival: diagnosing heterogeneous effects through time

Birds should select nest sites that minimize predation risk, but understanding the influence of vegetation on nest survival has proven problematic. Specifically, the common practice of measuring vegetation on nest fate date can overestimate its effect on survival, simply because vegetation at hatched nests grows for a longer period of time than vegetation at nests that were depredated. Here, we sampled the literature to determine the prevalence of this bias in studies of duck breeding ecology. We then used survival data collected from ~2,800 duck nests to empirically evaluate evidence of bias in four different vegetation metrics: vegetation density measured when the nest was found, density when the nest was fated, and date-corrected regression residuals of these two. We also diagnosed the magnitude of vegetation effects on nest survival by restricting analysis to only nests which were fated contemporaneously (thereby removing potential bias in the timing of measurement). Finally, we examined whether systematic phenological differences exist between vegetation at hatched and depredated nests that have the potential to further obfuscate the relationship between vegetation and nest survival. We found evidence for a true positive effect of vegetation density on nest survival that appeared to be inflated when using raw vegetation measurements collected at fate date. However, taken in combination with the literature review, our results suggest that the majority of duck nesting studies have evaluated the role of vegetation on nest survival using a relatively less biased metric—vegetation density when the nest was found. Finally, we found that over the course of a nesting attempt, vegetation increased in density at successful nests, but decreased in density at depredated nests. This seasonal change potentially points to an important new metric for understanding predation risk, but further experimental research is required to fully eliminate potential biases in the timing of vegetation measurements.

opencc-zeroJun 2021View details →

Data and code for Heterogeneous selection on exploration behavior within and among West European populations of a passerine bird

Heterogeneous selection is often proposed as a key mechanism maintaining repeatable behavioral variation ("animal personality") in wild populations. Previous studies largely focused on temporal variation in selection within single populations. The relative importance of spatial versus temporal variation remains unexplored, despite these processes having distinct effects on local adaptation. Using data from >3500 great tits (Parus major) and 35 nest box plots situated within five West-European populations monitored over 4-18 years, we show that selection on exploration behavior varies primarily spatially, across populations, and study plots within populations. Exploration was, simultaneously, selectively neutral in the average population and year. These findings imply that spatial variation in selection may represent a primary mechanism maintaining animal personalities, likely promoting the evolution of local adaptation, phenotype-dependent dispersal, and nonrandom settlement. Selection also varied within populations among years, which may counteract local adaptation. Our study underlines the importance of combining multiple spatiotemporal scales in the study of behavioral adaptation.

opencc-by-4.0Jun 2021View details →

Strain partitioning and localization due to heterogeneities in the fold - and - thrust belt 2 detachment: Analogue models of progressive arcs

Although most arcuate orogens are deformed as progressive arcs–curvature is acquired during12shortening-, they have been scarcely simulated by analogue modelling. Our team work designed13a backstop that deformed in map view building up fold-and-thrust belts (FTBs) that acquire14progressively its curved shape (Jiménez-Bonilla et al., 2020); silicone and sand layers15reproduced the brittle-ductile conditions expected to be common in external tectonic wedges.16However, natural cases usually includeheterogeneities in the detachment such as diapirs,17thickness variations of the viscous layer or pinch outs. Based on the same progressive arc model18setup, we present here seven new experiments including these three types of heterogeneities.19Our results show that strain was partitioned between shortening structures whose transport20directions draw a radial pattern and normal faults and oblique strike-slip faults that21accommodate arc-lengthening. Moreover, any heterogeneity conditions the wedge evolution and22the nucleation of structures. Both diapirs and the presence of a silicone pinch-out perpendicular23to the apex movement favour that frontal deformation slows down and the wedge thickens up to24reach the supercritical angle. Interestingly, the presence of diapirs or silicone thickness25variations favour the arc-parallel stretching localization close to these heterogeneities. In26addition, silicone bands parallel to the apex movement generate different structural styles along27the FTB. More frictional detachments favour thicker wedges and less frontal propagation.28Transfer zones accommodate the differential displacement between FTB segments. These29results may be useful to investigate geometric and kinematic changes along natural progressive30arcs such as the Gibraltar, Sulaiman and Zagros cases

FIGURE 2 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 2. Principal component analysis showing distribution of samples with 95% confidence ellipses around the group means and correlation of characters with the first two axes. Symbols refer to Table 1.

FIGURE 5 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 5. Percentages of pollinator species by insect order for subgenera Masculae and Orchis (from various sources collected by Claessens & Kleynen, 2011).

FIGURE 1 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 1. Maximum clade credibility tree of ITS sequences of 26 Orchis species with Traunsteinera globosa as outgroup, inferred with Bayesian relaxed clock analysis. Original data were from Bateman et al. (2003). The uncorrelated lognormal clock model was used, and the root height was fixed at 1.0. Posterior distributions of parameters were approximated using two independent Markov chain Monte Carlo analyses of 2.0 × 107 generations followed by a discarded burn-in of 2.0 × 106 generations (10%).

FIGURE 4 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 4. Discriminant analysis showing distribution of individuals and correlation of characters, according to the first two canonical axes (78.2% and 21.8% of total variation, respectively). Ellipses incorporate 50% of individuals. Symbols refer to Table 1.

FIGURE 6 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 6. Comparison of total numbers of fungal OTUs (operational taxonomic units) and average number of OTUs per species between representatives of subgenera Orchis and Masculae (data from Jacquemyn et al. 2011).

FIGURE 3 in On the morphological, biological and genetic heterogeneity of the genus Orchis (Orchidaceae, Orchidinae)

FIGURE 3. Phenogram obtained with the Ward clustering procedure using Mahalanobis distances between samples of populations. Length of horizontal segments corresponds to distances.

opencc-zeroJul 2021View details →

Data from: Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture-recapture data

Population dynamics models combine density-dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density-dependence. This is typically addressed using state-space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true abundance, which is common in capture-recapture settings. However, many of the models proposed to estimate abundance in the presence of capture heterogeneity lead to incomplete likelihood functions and cannot be straightforwardly included in state-space models. We assessed the importance of estimating sampling error explicitly by taking an intermediate approach between ignoring uncertainty in abundance estimates and fully specified state-space models for density-dependence estimation based on autoregressive processes. First, we estimated individual capture probabilities based on a heterogeneity model, using a conditional multinomial likelihood, followed by a Horvitz-Thompson estimate for abundance. Second, we estimated coefficients of autoregressive models for the log abundance. Inference was performed using the methodology of integrated nested Laplace approximation (INLA). We performed an extensive simulation study to compare our approach with estimates disregarding capture history information, and using R-package VGAM, for different parameter specifications. The methods were then applied to a real dataset of gray-sided voles Myodes rufocanusfrom Northern Norway. We found that density-dependence estimation was improved when explicitly modelling sampling error in scenarios with low process variances, in which differences in coverage reached up to 8% in estimating the coefficients of the autoregressive processes. In this case, the bias also increased assuming a Poisson distribution in the observational model. For high process variances, the differences between methods were small and it appeared less important to model heterogeneity.

opencc-by-4.0Jul 2021View details →

Data for: A test of Sensory Drive in plant-pollinator interactions: habitat heterogeneity shapes pollinator preference for a floral visual signal

DATA: FinnKoski_PollData_Final: Pollinator visitation data to floral arrays analyzed Spectra used for vismodels.zip: reflectance spectra of flowers and floral backgrounds, irradiance spectra ColorContrastData: visual contrast data analyzed CODE:  vismod_code.R : code used for visual system modeling and calculation of contrast SAS_modelcode.R: SAS code used to analyze pollinator visitation data and color contrast data

opencc-zeroJul 2021View details →

Structural heterogeneity of cellular K5/K14 filaments as revealed by cryo-electron microscopy

Keratin intermediate filaments are an essential and major component of the cytoskeleton in epithelial cells. They form a stable yet dynamic filamentous network extending from the nucleus to the cell periphery, which provides resistance to mechanical stresses. Mutations in keratin genes are related to a variety of epithelial tissue diseases. Despite their importance, the molecular structure of keratin filaments remains largely unknown. In this study, we analyzed the structure of keratin 5/keratin 14 filaments within ghost keratinocytes by cryo-electron microscopy and cryo-electron tomography. By averaging a large number of keratin segments, we have gained insights into the helical architecture of the filaments. Two-dimensional classification revealed profound variations in the diameter of keratin filaments and their subunit organization. Reconstitution of filaments of substantial length uncovered a high degree of internal heterogeneity along single filaments, which can contain regions of helical symmetry, regions with less symmetry and regions with significant diameter fluctuations. Cross section views of filaments revealed that keratins form hollow cylinders consisting of multiple protofilaments, with an electron dense core located in the center of the filament. These findings shed light on the complex and remarkable heterogenic architecture of keratin filaments, suggesting that they are highly flexible, dynamic cytoskeletal structures.

Figure 4 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage

Figure 4. Distribution of total zooplankton biomass (mg/m3) in the layer 0–200 m. (A) Distribution of total biomass; circle area proportional to biomass value. Background and scale below: temperature (◦C) at a depth of 10 m; dotted line: boundary of the Polar Front. (B) Average zooplankton biomass. (C) Distribution of the total zooplankton biomass along frontal transect; dotted line: boundary of the Polar Front.

Figure 7 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage

Figure 7. Biomass (mg/m3) of dominant copepods in the layer 0–200 m. Dotted line: boundary of the Polar Front.

Figure 1 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage

Figure 1. Distribution of dominant copepod species in the Subantarctic Zone (SAZ), Polar Frontal Zone (PFZ) and Antarctic Zone (AZ). PF, Polar Front. Wide solid line indicates maximal abundance (75–100% of maximal recorded values), thin solid line indicates intermediate abundance (50–75% of maximal recorded values), and thin dotted line indicates minimal abundance (<50% of maximal recorded values).

Figure 3 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage

Figure 3. (A) Examples of the T-S diagrams for Polar Frontal Zone (St. 2060), Polar Front (St. 2088) and Antarctic Zone (St. 2105). (B) Current vectors at a depth of 100 m (Koshlyakov et al., 2010). Circles mark hydrological stations, depths <2500 m are shaded.

Figure 6 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage

Figure 6. Contribution of dominant copepods to the total biomass of each zone. 1. Calanus simillimus; 2. Calanoides acutus; 3. Rhincalanus gigas; 4. remaining species. PFZ, Polar Frontal Zone; PF, Polar Front; AZ, Antarctic Zone.