Wisdom of the crowd: evidence for density-dependent species fitness in Hyptis suaveolens (L.) Poit.

The objective of this study was to estimate and compare the occurrence of AMR in wild red foxes in relation to human population densities. Samples from wild red foxes (n = 528) included in the Norwegian monitoring programme on antimicrobial resistance in bacteria from food, feed and animals were included. All samples were divided into three different groups based on population density in the municipality where the foxes were hunted. Of the 528 samples included, 108 (20.5%), 328 (62.1%) and 92 (17.4%) originated from areas with low, medium and high population density, respectively. A single faecal swab was collected from each fox. All samples were plated out on a selective medium for Enterobacteriaceae for culturing followed by inclusion and susceptibility testing of one randomly selected Escherichia coli to assess the overall occurrence of AMR in the Gram-negative bacterial population. Furthermore, the samples were subjected to selective screening for detection of E. coli displaying resistance towards extended-spectrum cephalosporins and fluoroquinolones. In addition, a subset of samples (n = 387) were subjected to selective culturing to detect E. coli resistant to carbapenems and colistin, and enterococci resistant to vancomycin. Of these, 98 (25.3%), 200 (51.7%) and 89 (23.0%) originated from areas with low, medium and high population density, respectively. Overall, the occurrence of AMR in indicator E. coli from wild red foxes originating from areas with different human population densities in Norway was low to moderate (8.8%). The total occurrence of AMR was significantly higher; χ2 (1,N = 336) = 6.53, p = 0.01 in areas with high population density compared to areas with medium population density. Similarly, the occurrence of fluoroquinolone resistant E. coli isolated using selective detection methods was low in areas with low population density and more common in areas with medium or high population density. In conclusion, we found indications that occurrence of AMR in wild red foxes in Norway is associated with human population density. Foxes living in urban areas are more likely to be exposed to AMR bacteria and resistance drivers from food waste, garbage, sewage, waste water and consumption of contaminated prey compared to foxes living in remote areas. The homerange of red fox has been shown to be limited thereby the red fox constitutes a good sentinel for monitoring antimicrobial resistance in the environment. Continuous monitoring on the occurrence of AMR in different wild species, ecological niches and geographical areas can facilitate an increased understanding of the environmental burden of AMR in the environment. Such information is needed to further assess the impact for humans, and enables implementation of possible control measures for AMR in humans, animals and the environment in a true “One Health” approach.

The association between invasive and native species varies across spatial scales and is affected by phylogenetic relatedness, but these issues have rarely been addressed in aquatic ecosystems. In this study, we used a non-native, highly invasive species of Poaceae (tropical signalgrass) to test the hypotheses that (i) tropical signalgrass success correlates negatively with success of most native species of macrophytes at fine spatial scales, but its success correlates positively or at random with natives at coarse spatial scales, and that (ii) tropical signalgrass is less associated with native species belonging to the family Poaceae than with species belonging to other families (Darwin’s naturalization hypothesis). We used a dataset obtained at fine (0.25 m2) and coarse (ca. 1,000 m2) scales. The presence/absence of all species was recorded at both scales, and their biomass was also measured at the fine scale. We tested the association between tropical signalgrass biomass and individual native species with logistic regressions at the fine scale, and using the T-score index between tropical signalgrass and each native species at both scales. The likelihood of the occurrence of six species (submersed and free-floating) was negatively affected by tropical signalgrass biomass at the fine scale. T-scores showed that three species were less associated with tropical signalgrass than expected by chance, but 22 species co-occurred more than expected by chance at the coarse scale. Associations between species of Poaceae and tropical signalgrass were null at the fine scale, but were positive or null at the coarse scale. In addition to showing that spatial scale affects the patterns of association among the non-native and individual native species, our results indicate that phylogeny did not explain associations between the invasive and native macrophytes, at both scales.

An efficient space-angle subgrid scale discretisation of the neutron transport equation

A population exhibiting Allee effect shows a positive correlation between population fitness and population size or density. Allee effect decides the extinction or conservation of a microbial population and thus appears to be an important criterion in population ecology. The underlying factor of Allee effect that decides the stabilization and extinction of a particular population density is the threshold or the critical density of their abundance. According to Allee, microbial populations exhibit a definite, critical or threshold density, beyond which the population fitness of a particular population increases with the rise in population density and below it, the population fitness goes down with the decrease in population density. In particular, microbial population displays advantageous traits such as biofilm formation, expression of virulence genes, spore formation and many more only at a high population density. It has also been observed that microorganisms exhibiting a lower population density undergo complete extinction from the residual microbial ecosystem. In reference to Allee effect, decrease in population density or size introduces deleterious mutations among the population density through genetic drift. Mutations are carried forward to successive generations resulting in its accumulation among the population density thus reducing its microbial fitness and thereby increasing the risk of extinction of a particular microbial population. However, when the microbial load is high, the chance of genetic drift is less, and through the process of biofilm formation, the cooperation existing among the microbial population increases that increases the microbial fitness. Thus, the high microbial population through the formation of microbial biofilm stabilizes the ecosystem by increasing fitness. Taken together, microbial fitness shows positive correlation with the ecosystem conservation and negative correlation with ecosystem extinction.

Juveniles of chum salmon (Oncorhynchus keta) held at high population density were apparently smaller than those held at medium and low population densities. The effects of high population density on pituitary growth hormone (GH) cells in juvenile chum salmon were examined using immunocytochemical and in situ hybridization techniques. The ratio of GH-immunoreactive (ir) area to the whole pituitary was almost constant in all of the high, medium and low population density groups, although the number and sizes of GH-ir cells were decreased in the high population density group. Image-analysis of GH-ir cells indicated the presence of a population of heterogenous cells, in which medium or rather strongly stained smaller cells and as extreme weakly stained larger cells. The medium or rather strongly stained smaller cells predominated in the high population density group, while weakly stained larger cells in the low population density group. In situ hybridization study showed somewhat different distributions and intensities of hybridization signals for mRNAs encoding GH I and II precursors. The area showing signals for GH II mRNA in the high population density group was significantly smaller than those in the medium and low population density groups. In contrast, the sizes of areas showing signals for GH I mRNA did not differ among the groups, although the intensity was slightly higher in the high population density group. These results indicate that high population density decreased the number of weakly immunoreactive larger GH cells, and also suppressed expression of the gene encoding GH II precursor, which may result in retarded somatic growth.

Integration of dynamic data typically requires the solution of an inverse problem that can be computationally intensive and practically infeasible for fine scale reservoir models. In this paper we present a new methodology to directly update fine scale geostatistically-based reservoir models by combining gradual deformation parameterization for the fine scale geostatistical model and an upscaling technique for the coarse scale flow simulation model. The proposed methodology includes: Perturbation of the fine scale geostatistical model using the gradual deformation parameterization. Gradual deformation ensures the preservation of the overall geostatistical properties of the fine model. Generation of the coarse scale flow simulation model by upscaling the fine scale geostatistical model. Sensitivity computation of the flow simulation results with respect to the fine scale parameterization. This sensitivity computation is analytical and takes into account the upscaling process. Direct updating of the fine scale geostatistical model using classical optimization process. Direct updating ensures consistency between the fine and coarse scale models. The accuracy of the proposed methodology was improved by calibrating the flow simulation model. The objective of this calibration is to reduce the error introduced by the upscaling step during the flow simulation. We applied successfully our methodology for fine scale reservoir description by integrating permanent down-hole gauge measurements directly into a three-dimensional geostatistical model containing about two million grid blocks. This test is designed to highlight several key issues of the proposed methodology: Efficiency of the upscaling step coupled with gradient-based optimization to speed up the history matching process. Usefulness of the calibration step for a correct integration of upscaling techniques in history matching. Capability of the methodology for maintaining consistency and coherency between fine scale and coarse scale models. Improvement of the reservoir characterization by integrating dynamic data at the fine geostatistical scale. We conclude that the proposed methodology can be used effectively and efficiently for reservoir characterization purposes.

In order to run reservoir simulation efficiently, a coarse scale (CS) dynamic model is created by upscaling of a fine scale (FS) static model. All history match (HM) changes usually done in the CS dynamic model need to be downscaled to FS for geological justifications and consistency maintenance between the FS static and CS dynamic models. This paper proposes a robust downscaling method for integration of FS static and CS dynamic models. The proposed method downscales a HMDM (dynamic model) to HMSM (static) in multiple steps. Scale-up the ISM (initial) to CS to create an IDM. Identify the cell changes between HMDM and IDM, and transfer the changes to FS to create a MSM (modified). Scale-up the MSM to CS to create to a MDM and calculate the ratios between HMDM and MDM for all cell properties. Transfer the ratios to FS to create a HMSM. Scale-up the HMSM to CS to confirm its identity to the HMDM. Selection of sampling and zone mapping methods is critical in all steps. The proposed method has been successfully applied in a giant carbonate oil field in the Caspian Sea that consists of a matrix dominated platform and a fracture/karst dominated rim. Due to the field's complex geology and high H2S content (15%), a dual porosity, dual permeability compositional model has been created to model compositional sour crude flow within/between matrix and fracture/karst. The FS static model contains a 236m × 236m horizontal grid with 593 layers while the CS dynamic model has the horizontal cell sizes in a range of 236m to 944m with 73 layers. Rock regions, permeability, and reservoir connectivity in the CS dynamic model were calibrated using the field historical production data (e.g., static pressure, PLT, interference test, and GOR/water-cut data) to create a HMDM. Since the HM process was performed only in the CS dynamic model, the FS static model and HMDM became inconsistent. Appling the proposed downscaling method has helped the HM team to resolve this issue and resulted in a seamless link between the FS static and CS dynamic models for current and future HM and model updates.

Revealing how plant architecture affects the responses of canopy temperature depression (CTD), water use (WU), and grain yield to population density (PD) in wheat (Triticum aestivum L.) would help explore a water‐saving pathway related to managing population. This study was conducted over three consecutive years under rainfed and supplemental irrigation conditions. The flat‐leafed Jinmai 47 and upright‐leafed Jing 411 genotypes were grown at high population density (HD), medium population density (MD), and low population density (LD); seeding rates were 450, 675, and 900 seeds m−2, respectively). CTD peaked at MD in Jinmai 47 but reached the highest at HD in Jing 411. WU generally increased with increasing PD but remained unchanged from LD to MD in Jinmai 47 under the two water conditions, while it remained unchanged from MD to HD under supplemental irrigation condition in Jing 411. Yield increased with increasing density in both genotypes under the two water conditions. It is thus clear that Jinmai 47 gained higher yield but did not consume more water at MD than at LD under the two water conditions; Jing 411 obtained higher yield at the expense of similar amount of water at HD than at MD under supplemental irrigation condition. The grain yield and WU responses of wheat crops to PD implied that through appropriately adjusting PD in combination with plant architecture and water condition, the dual goals of optimizing yield and effectively saving irrigation water could be realized synchronously.

Where land surface air temperature data are not available, satellite land surface temperature are used. However, the coarse spatial resolution of satellite‐derived products may yield errors at the local scale. This work shows the differences between the MODIS Land Surface Temperature and Emissivity (MOD11A1) product and ground measurements at two different scales. We used data from 21 SNOTEL stations across the northern Front Range of Colorado to represent the coarse scale and 17 iButton temperature sensors across the Colorado State University Mountain Campus to represent the fine scale. We found significant differences in the temperature and its changes with elevation for the two spatial scales. At the fine scale, cold air drainage can induce an inversion of the temperature gradient with elevation. A higher correlation was found during the nighttime at the fine scale, while, at the coarse scale, higher correlations were observed during the daytime. On windy nights, temperatures do not cool as much as on calmer nights, and the coarse scale near‐surface temperature gradient with elevation persists, though the fine scale inversions do not develop. The near‐surface temperature gradients with elevation based on the MODIS pixels are similar to the ground‐based data at the coarse scale but not at the fine scale. Thus, one must be cautious in selecting the near‐surface temperature gradients with elevation for mountainous terrain when different scales are considered, and a proper validation of satellite products is necessary prior to their use to avoid the propagation of uncertainties.

<p><b>Recent ecological studies have started integrate to spatial variation of ecological patterns into the study design rather than treating it as a statistical nuisance. In particular, the influence of the spatial scale at which ecological patterns are measured has gained much attention over the last two decades. Since, for example, sensory abilities as well as the ability to disperse vary among species, different species-specific responses to heterogeneous environments may be expected.</b></p> <p>Plant-insect interactions in heterogeneous landscapes, in particular, have gained much attention as experiments can be conducted on a more accessible scale and may yield new applications for crop and horticulture. Two hypotheses that describe insect herbivore aggregations in the landscape are: a) the resource concentration hypothesis which predicts higher numbers of specialist insect herbivores per unit biomass in dense and pure stands of their host plant, and b) the resource dilution hypothesis which predicts that insect herbivore numbers will decline with increasing plant density. I investigated resource dilution and resource concentration patterns in egg distributions of Pieris rapae and Tyria jacobaeae in relation to host plant density, which I defined differently by applying varying spatial scales of measurement. I also tested for effects of host plant density and the scale of measurement on flight patterns of P. rapae females.</p> <p>In a natural population of Lepidium oleraceum I investigated effects of scale of measurement of plant density, as well as white rust and hymenopteran parasitoids on P. rapae egg and larvae distributions. In a separate experiment I tested for any potential effects of arthropod predators on P. rapae egg distributions at different spatial scales. The number of P. rapae eggs per plant conformed to predictions made by the resource dilution hypothesis. However, such a pattern was only found for fine scale plant density but not for medium or coarse scale plant density. In contrast, the number of T. jacobaeae egg clutches per plant showed a resource concentration pattern for medium scale plant density but not for fine or coarse scale plant density. However, this result occurred only in one of two experiments with T. jacobaeae. A resource dilution pattern was also found for the number of visits per plant by P. rapae females at both coarse and fine scale measurement. Female flight paths were less directional when plants were present in the study area during fine scale observations and butterflies were attracted to areas containing host plants. Flight observations at coarse scale did not show any change in turning behaviour and butterflies moved at random across the study area. No effect of parasitism, or predation through arthropods was found on the distribution of P. rapae eggs. However, infection by white rust lead to a decreased number of eggs per plant in the natural L. oleraceum population. The results of my thesis underline the importance of spatial scale in ecological studies. Careful thought should be given to the scale of measurement and method of abstraction when describing real world patterns.</p>

In the coarse scale simulation of heterogeneous reservoirs, effective or upscaled flow functions, e.g., oil and water relative permeability and capillary pressure, can be used to represent heterogeneities at subgrid scales. The effective relative permeability is typically upscaled along with absolute permeability from a geostatistical model. However, the potentially important effects of smaller scale heterogeneities (on the centimeter to meter scale) in both capillarity and absolute permeability will not be captured by this approach. In this paper, we present a new two-stage upscaling procedure for two-phase flow. In the first stage, we upscale from the core (fine) scale to the geostatistical (intermediate) scale, while in the second stage we upscale from the geostatistical scale to the simulation (coarse) scale. The computational procedure includes numerical solution of the finite difference equations describing steady state flow over the local region to be upscaled, using either constant pressure or periodic boundary conditions. The two-stage method is applied to synthetic two-dimensional reservoir models with strong variation in capillarity on the fine scale. Results are presented in terms of both oil production rates and saturation fields. Accurate reproduction of the fine grid solutions (simulated on 500 × 500 grids) is achieved on coarse grids of 10 × 10 for different flow scenarios. It is shown that, although capillary forces are important on the fine scale, the assumption of capillary dominance in the first stage of upscaling is not always appropriate, and that the computation of rate dependent effective properties in the upscaling can significantly improve the accuracy of the coarse scale model. The assumption of viscous dominance in the second upscaling stage is found to be appropriate in all of the cases considered.

Experiments were performed to investigate if population density and social facilitation may influence fecundity (number of ova produced per female) and fertility (number of intrafollicular embryos produced by a female) in the presence of excess food in the guppy, Poecilia reticulate (Teleostei: Poeciliidae). No significant differences in total body length, standard length and total body weight were found between females exposed to different population densities in the presence of excess food. The frequencies of females with only intrafollicular embryos or with only ova or with both embryos and ova in the ovary were not significantly different between groups at different population levels. This was also true for the frequency of females with only previtellogenic oocytes. There were no significant differences concerning ovarian length, width, height and volume between females from different population densities. This clear-cut result persisted also when gonad weight was examined. The average gonadosomatic index was highest in the highest population density. Highly significant correlations occurred between ovarian volume and total body weight as well as between ovarian volume and gonad weight at each population level (P<0.001, P<0.01). This was also the case for gonad weight vs total body weight (P<0.001, P<0.01). A significant and inverse correlation between fecundity and ovum diameter appeared only at the highest population level (P<0.01). No significant differences of fecundity and ovum diameter in addition to fertility and embryo size were revealed between different population densities when feeding ad libitum. This result differed from an earlier study in which increased population density caused a decrease in fecundity and fertility under conditions of food scarcity.

Population density can influence all three phases of natal dispersal: departure from the place of birth, searching the landscape, and selecting a new site in which to settle. The direction of the effect of density on dispersal should be affected by the relative costs and benefits of living in an area with high population density. Animals may benefit from high population density due to mate availability and predator risk dilution, but may also face increased competition in high density areas. These conflicting mechanisms should influence the pattern of change in population density between pre‐ and post‐dispersal locations: do dispersing individuals choose to move to areas of higher or lower population density than that at their natal site? We examined the influence of density on dispersal in brush mice (Peromyscus boylii). We documented pre‐ and post‐dispersal locations of individuals using both radio telemetry and live‐trapping, and used a spatially explicit capture–recapture model to estimate density across the landscape. We also tested for a relationship between dispersal distance and local population density at the natal site. Animals tended to settle in areas with higher population densities than where they were born. This pattern held when landscape‐level changes in population density were incorporated: the magnitude of change in local population density between the pre‐ and post‐dispersal locations of a given individual tended to be greater than would be explained by increasing population density across the landscape alone. Further, dispersal distances were shorter when local natal population density was higher.

Sexually reproducing organisms require males and females to find each other. Increased difficulty of females finding mates as male density declines is the most frequently reported mechanism of Allee effects in animals. Evolving more effective mate search may alleviate Allee effects, but may depend on density regimes a population experiences. In particular, high-density populations may evolve mechanisms that induce Allee effects which become detrimental when populations are reduced and maintained at a low density. We develop an individual-based, eco-genetic model to study how mating systems and fitness trade-offs interact with changes in population density to drive evolution of the rate at which males or females search for mates. Finite mate search rate triggers Allee effects in our model and we explore how these Allee effects respond to such evolution. We allow a population to adapt to several population density regimes and examine whether high-density populations are likely to reverse adaptations attained at low densities. We find density-dependent selection in most of scenarios, leading to search rates that result in lower Allee thresholds in populations kept at lower densities. This mainly occurs when fecundity costs are imposed on mate search, and provides an explanation for why Allee effects are often observed in anthropogenically rare species. Optimizing selection, where the attained trait value minimizes the Allee threshold independent of population density, depended on the trade-off between search and survival, combined with monogamy when females were searching. Other scenarios led to runaway selection on the mate search rate, including evolutionary suicide. Trade-offs involved in mate search may thus be crucial to determining how density influences the evolution of Allee effects. Previous studies did not examine evolution of a trait related to the strength of Allee effects under density variation. We emphasize the crucial role that mating systems, fitness trade-offs and the evolving sex have in determining the density threshold for population persistence, in particular since evolution need not always take the Allee threshold to its minimum value.

SUMMARYThis paper presents residual‐based turbulence models for problems with moving boundaries and interfaces. The method is developed via a hierarchical application of variational multiscale ideas and the models are cast in an arbitrary Lagrangian–Eulerian (ALE) frame to accommodate the deformation of domain boundaries. An overlapping additive decomposition of velocity and pressure fields into coarse and fine scale components leads to coarse and fine scale mixed‐field problems. The problem governing fine scales is subjected to a further decomposition of the fine scale velocity into overlapping components termed as fine scales level I and level II. In turn, in the bottom‐up integration of scales, the model for level II fine scales serves to stabilize the problem governing level I fine scales, and model for level I fields yields the turbulence models. From the computational perspective, the coarse scales are represented in terms of the standard Lagrange shape functions, whereas level I and level II scales are represented via quadratic and fourth order polynomial bubbles, respectively. Because of the bubble functions approach employed in the consistently derived fine scale models, the resulting method is free of any embedded or tunable parameters. The proposed turbulence models share a common feature with the LES models in that the largest scales in the flow are numerically resolved, whereas the subgrid scales are modeled. The method is applied to flow around a plunging airfoil at Re = 40,000, and results are compared with experimental and numerical data published in the literature. Also presented are the results for the plunging airfoil at Re = 60,000 to show the robustness and range of applicability of the method. Copyright © 2013 John Wiley &amp; Sons, Ltd.