Egg Laying on Patchy Resources and the Importance of Spatial Scale

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.

Summary1. The distribution of herbivores among plant patches may be an important factor determining plant population persistence. The resource concentration hypothesis proposes that herbivores are more abundant per unit plant at higher host plant densities and this has been found to occur in many systems. However, the opposite pattern, resource dilution, in which the herbivores are more abundant in low‐density patches and situations in which the number of insect herbivores per unit plant remains constant, also occurs.2. We developed a simulation model to explore how the distribution of insects per plant affects plant population decline and persistence. We varied the numbers of plants per patch and the distribution pattern, i.e. whether insects were found in a resource concentration distribution, a resource dilution distribution or a distribution in which insect abundance increased linearly with plant density.3. Resource concentration resulted in longer persistence of plant populations. Plant populations declined more rapidly with either weak resource dilution or directly proportional insect distribution patterns. As the intensity of resource concentration increased, the decline in plant population density was reduced, and plant persistence increased because of increasing variance in insect load. Under strong resource dilution, increasing variance in the insect load also led to a reduction in plant population decline and an increase in plant persistence.4. We complement our model with field data from the diffuse knapweed, Centaurea diffusa biocontrol system. We compared the relationship with plant density of a successful biocontrol agent, Larinus minutus, and an unsuccessful one, Urophora affinis. Larinus minutus density was directly proportional to plant density, while U. affinis showed a resource concentration pattern with higher rates of attack in high‐density patches.5. Synthesis: Patterns of insect distribution with host plant density will alter the extent to which patches of differing plant densities decline or persist. Resource concentration promotes persistence of the insect–plant system because increased herbivore pressure in high‐density patches leads to negative density‐dependent plant growth. Weak resource dilution and a distribution of insects that is directly proportionate to plant density can accelerate plant population decline. Strong resource dilution leads to positive density dependence with higher population growth in large patches. Our simulation model and field data demonstrate that the relationship between insect distribution and plant densities can influence plant population dynamics and has implications for choices of weed biological control agents.

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

Correlation between plant size and reproductive output may be modified by herbivory in accordance with host plant density and the presence of nonhost plants. To elucidate the effects of nonhost plant density and host plant density on the intensity of herbivory and reproductive output of the host plant in relation to plant size under natural conditions, we investigated the abundance of three lepidopteran insects, Plutella maculipennis, Anthocharis scolymus, and Pieris rapae the intensity of herbivory, and fruit set of their host plant, Turritis glabra (Cruciferae). To elucidate the effects of nonhost and host plant density, we selected four categories of plots under natural conditions: low density of nonhost and high density of host plants; low density of both nonhost and host plants; high density of both nonhost and host plants; and high density of nonhost and low density of host plants. The plant size indicated by stem diameter was a good predictor of the abundance of all herbivorous species. The effects of density of nonhost and host plants on the abundance of insects varied among species and stages of insects. As the abundance of insects affected the intensity of herbivory, herbivory was more apparent on larger host plants in plots with low density of both nonhost and host plants. Consequently, the correlation between plant size and the number of fruits disappeared in low plots with density of both nonhost and host plants. In this T. glabra– herbivorous insect system, the density of nonhost plants and host plants plays an important role in modifying the relationship between plants and herbivores under natural conditions.

ABSTRACTThe fact that plant spatial aggregation patterns shape insect-herbivore communities in a variety of ways has resulted in a large body of literature on the subject. The landmark resource concentration hypothesis predicts that density of insect herbivores per plant will increase as host plant density increases. I examined this prediction across temporal samplings using Jatropha nana and the associated specialist insect herbivores as a system. Through 12 field samplings, I modelled the effect of host plant density on insect-herbivore loads. The initial samplings (2–3) provided evidence for the resource concentration hypothesis, with insect loads increasing with increasing host plant density, whereas the later samplings (4–5, 7–11) showed the opposite; a resource dilution pattern with a decline of insect loads with increasing host plant density. These patterns also depend on the biology of the herbivores and have important implications on J. nana population dynamics.This article has an associated First Person interview with the first author of the paper.

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.

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.

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 & Sons, Ltd.

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.

<p>This thesis presents a spatially explicit, agent based simulation, used to explore the ovipositing behaviour of the Small Cabbage White butterfly, Pieris rapae (Lepidoptera). The study concerns the effects of host-plant (Cabbage, Brassica oleracae) density upon P. rapae egg distribution patterns, at multiple scales. A general review of the literature is provided which covers the ecology of animal movement, methods of quantifying movement, models of movement, ecological theory of herbivore responses to plant density (Resource Concentration Hypothesis) and the biology of P.rapae.</p> <p><br></p> <p>The construction of the simulation is described in detail and the source code plus an executable version of the software are available as a companion CD. A number of simulation experiments are reported which demonstrate the basic behaviour of the simulation over a simplified resource layout. The framework is then used to explore more complex layouts which are compared to field experiments conducted as part of a separate PhD thesis (Hasenbank, in prep). A Correlated Random Walk simulated a negative relationship between forager egg distributions and resource densities, observed at all scales. Including a diffuse attraction to resources (e.g. olfaction), simulated a negative relationship between egg distributions and resource densities at smaller scales, and a positive relationship at larger scales.</p> <p><br></p> <p>This work builds on a large body of previous simulation studies and attempts to produce a useful framework for subsequent researchers to explore the effects of animal movement through the use of random walks. It demonstrates the use of the framework with a specific example concerning the egg distributions of P. rapae and the effect of scale. It provides some useful insights into both the analysis of results from a complex spatial experimental layout, and potential responses which may be observed. It demonstrates that a simple model can, in the case of P rapae be used to obtain relatively realistic egg distributions.</p>

<p>This thesis presents a spatially explicit, agent based simulation, used to explore the ovipositing behaviour of the Small Cabbage White butterfly, Pieris rapae (Lepidoptera). The study concerns the effects of host-plant (Cabbage, Brassica oleracae) density upon P. rapae egg distribution patterns, at multiple scales. A general review of the literature is provided which covers the ecology of animal movement, methods of quantifying movement, models of movement, ecological theory of herbivore responses to plant density (Resource Concentration Hypothesis) and the biology of P.rapae. The construction of the simulation is described in detail and the source code plus an executable version of the software are available as a companion CD. A number of simulation experiments are reported which demonstrate the basic behaviour of the simulation over a simplified resource layout. The framework is then used to explore more complex layouts which are compared to field experiments conducted as part of a separate PhD thesis (Hasenbank, in prep). A Correlated Random Walk simulated a negative relationship between forager egg distributions and resource densities, observed at all scales. Including a diffuse attraction to resources (e.g. olfaction), simulated a negative relationship between egg distributions and resource densities at smaller scales, and a positive relationship at larger scales. This work builds on a large body of previous simulation studies and attempts to produce a useful framework for subsequent researchers to explore the effects of animal movement through the use of random walks. It demonstrates the use of the framework with a specific example concerning the egg distributions of P. rapae and the effect of scale. It provides some useful insights into both the analysis of results from a complex spatial experimental layout, and potential responses which may be observed. It demonstrates that a simple model can, in the case of P rapae be used to obtain relatively realistic egg distributions.</p>

It has been argued in sociology, economics, and evolutionary anthropology that family size limitation enhances the intergenerational upward mobility chances in modernized societies. If parents have a large flock, family resources get diluted and intergenerational mobility is bound to head downwards. Yet, the empirical record supporting this resource dilution hypothesis is limited. This article investigates the empirical association between family size limitation and intergenerational mobility in an urban, late nineteenth century population in Western Europe. It uses life course data from the Belgian city of Antwerp between 1846 and 1920. Findings are consistent with the resource dilution hypothesis: after controlling for confounding factors, people with many children were more likely to end up in the lower classes. Yet, family size limitation was effective as a defensive rather than an offensive strategy: it prevented the next generation from going down rather than helping them to climb up the social ladder. Also, family size appears to have been particularly relevant for the middle classes. Implications for demographic transition theory are discussed. 1. Resource dilution and decline In his 1890 classic Depopulation et civilisation, the French social scientist Arsene Dumont argued that adults with ambition tend to limit their family size because numerous offspring are an obstacle to success and achievement. For people who want to rise socially, he wrote, many children make inconvenient luggage (Dumont 1890(1990):77). The same holds for those who project their ambitions onto their children: numerous offspring dilute parental resources and therefore complicates or aggravates the social situation in the next generation (Dumont 1890(1990):73-91). Philippe Aries (1980), referring to Dumont, argued in an article amply cited by demographers (Dalla Zuanna 2007) that the decline of in the West is the consequence of the emergence of a child-oriented society. In such a society, parents' main investment consists of helping their children to get ahead. In the English-speaking world, Joseph A. Banks' Prosperity and Parenthood (1954) was instrumental in spreading the same ideas. Banks, who explicitly referred to Dumont's work, argued that social ambition was one of the motivating forces for family size limitation in the English middle classes. In economics, the negative effect of family size on the future social status of children, due to resource dilution, is known under the heading of the quality-quantity trade-off (Black, Devereux, and Salvanes 2005; Maralani 2008). Becker (1991) calls proper consideration of the interaction between child quantity and quality probably the major contribution of the economic analysis of fertility (Becker 1991:135). Becker's economic theory implies that a reduction in the number of children raises investments in child quality, where quality is measured by the current as well as the future well-being of children, including their income when they become adults. In a nutshell, the resource dilution hypothesis states that parental resources are finite and that additional children dilute the amount of time, money, and patience that each child receives from its parents. As a consequence of reduced parental investment per child, the opportunities to move up the social ladder, for example, through higher education are reduced (Downey 1995; Desai 1995; Maralani 2008). Historically, resource dilution is argued to have motivated limitation as inheritance systems became more egalitarian and as education became more important in securing a good social position in terms of wealth and prestige (Van Bavel 2006; Dalla Zuanna 2007). Despite its longstanding record in social and demographic theory, there is little direct empirical evidence backing the relevance of the resource dilution hypothesis for the historical decline in Europe (Downey 1995; Haaga 2001; Black, Devereux, and Salvanes 2005; Dalla Zuanna 2007). …

This study addresses four hypotheses that may account for differences in the number of insect herbivore species among plant species. These hypotheses are based on the assumption that insect diversity is a function of the number, quantity, and distribution of plant resources used by herbivores. The study investigated predictions that herbivore species richness will increase as a function of increasing the following: (1) host plant distribution over the landscape (host plant geographical distribution hypothesis), (2) host plant density within a habitat (resource concentration hypothesis), (3) size of individual plants (plant size hypothesis), or (4) abundance of resources (resource abundance hypothesis). We tested predictions from these hypotheses by examining the species richness of insect herbivores on five sympatric species of fabaceous plants that varied in their local dispersion of individual plants and plant architecture. Among these five species, plant geographical distribution varied threefold, density varied 38-fold, plant size and food resources available to insect herbivores varied ≈100-fold. Plant geographical distribution, plant size, and the resource concentration hypotheses were not corroborated in this study. Resource abundance, measured as plant dry weight, accounted for the differences in number and abundance of insect species between host plant species. Leaf biomass accounted for 44.15% of the variation in number of insect herbivore species and 51.76% of the variation in abundance of insect herbivores using leaves as resources. Flower biomass accounted for 32.86% of the variation in the number of insect herbivore species using flowers. Therefore, plants that offered a greater quantity of resources, especially leaves and flowers, had greater species richness and abundance in insect herbivores.

A variational multiscale approach to strain localization – formulation for multidimensional problems