The spatial pattern of natural selection when selection depends upon experience

Apostatic (frequency‐ or density‐dependent) selection, aposematic signals, and mate choice behavior generally require that the mean prey or potential mate density m value be high enough (above a threshold T) to result in sufficient encounter rates for the searcher to learn or retain the association between conspicuous signals and prey unprofitability, to forage apostatically, or to choose among mates. This assumes that all searchers experience , which implicitly assumes an even dispersion of targets among searcher territories. Uneven dispersion generates new phenomena. If , then only territories with local density x values that are greater than T favor experience‐based behavior, leading to spatially variable frequency‐ or density‐dependent selection intensity. As aggregation increases, the increase in percentage of targets in favorable territories ( ) is greater than the increase in the percentage of territories that are favorable. The relationship is reversed when . In both cases, because as few as 10% of the territories can contain 80% of the targets, only a few territory holders may account for most of the selection on most of the target population; accidents of experience in only a few searchers can have unexpectedly large effects on the target population. This also provides an explanation for high searcher behavior variation (personalities) : individuals from favorable territories will behave differently in behavioral experiments than those from unfavorable territories, at least with respect to similar kinds of targets. These effects will generate spatial heterogeneity in natural and sexual selection in what are otherwise uniform environments.

Ripple effects of house prices : considering spatial correlations in geography and demography

Purpose: Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial-temporal interconnections between house price movements across the Australian capital cities. Design/methodology/approach: Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects. Findings: The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information. Originality/value: This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

Do spatial effects drive house prices away from the long-run equilibrium?

Long-run equilibrium of house prices has been investigated by researchers in multiple countries. The identification of this equilibrium not only provides references against contemporary house price levels, but also contributes to creation of stable-development policies and healthy investment strategies. However, there is little research investigating the factors that drive house prices away from the long-run equilibrium.
Based on a framework of the conventional stationarity test process, this research develops a panel regression model and a spatial regression model to investigate the roles of spatial heterogeneity and correlations on house prices preceding the long-run equilibrium, respectively. Housing data generated from the capital cities in Australia are used to illustrate the models. Spatial effects can have a strong influence in the long-run performance of house prices, while the short-run performance of house prices is not influenced by the spatial effects.

Impact of grain microstructure on the heterogeneity of precipitation strengthening in an Al-Li-Cu alloy

The effect of grain microstructure on the age-hardening behavior is investigated on recrystallized and un-recrystallized Al-Cu-Li alloys by combining electron-backscatter-diffraction and micro-hardness mapping. The spatial heterogeneity of micro-hardness is found to be strongly dependent on the grain microstructure. Controlled experiments are carried out to change the pre-strain before artificial ageing. These experiments lead to an evaluation of the range of local strain induced by pre-stretching as a function of the grain microstructure and results in heterogeneous formation of the hardening T1 precipitates.

Fire severity and fire-induced landscape heterogeneity affect arboreal mammals in fire-prone forests

In fire-prone regions, wildfire influences spatial and temporal patterns of landscape heterogeneity. The likely impacts of climate change on the frequency and intensity of wildfire highlights the importance of understanding how fire-induced heterogeneity may affect different components of the biota. Here, we examine the influence of wildfire, as an agent of landscape heterogeneity, on the distribution of arboreal mammals in fire-prone forests in south-eastern Australia. First, we used a stratified design to examine the role of topography, and the relative influence of fire severity and fire history, on the occurrence of arboreal mammals 2-3 years after wildfire. Second, we investigated the influence of landscape context on the occurrence of arboreal mammals at severely burnt sites. Forested gullies supported a higher abundance of arboreal mammals than slopes. Fire severity was the strongest influence, with abundance lower at severely burnt than unburnt sites. The occurrence of mammals at severely burned sites was influenced by landscape context: abundance increased with increasing amount of unburnt and understorey-only burnt forest within a 1 km radius. These results support the hypothesis that unburnt forest and moist gullies can serve as refuges for fauna in the post-fire environment and assist recolonization of severely burned forest. They highlight the importance of spatial heterogeneity created by wildfire and the need to incorporate spatial aspects of fire regimes (e.g., creation and protection of refuges) for fire management in fire-prone landscapes.

Fine-scale adaptation in a clonal sea anemone

Local adaptation in response to fine-scale spatial heterogeneity is well documented in terrestrial ecosystems. In contrast, in marine environments local adaptation has rarely been documented or rigorously explored. This may reflect real or anticipated effects of genetic homogenization, resulting from widespread dispersal in the sea. However, evolutionary theory predicts that for the many benthic species with complex life histories that include both sexual and asexual phases, each parental habitat patch should become dominated by the fittest and most competitive clones. In this study we used genotypic mapping to show that within headlands, clones of the sea anemone Actinia tenebrosa show restricted distributions to specific habitats despite the potential for more widespread dispersal. On these same shores we used reciprocal transplant experiments that revealed strikingly better performance of clones within their natal rather than foreign habitats as judged by survivorship, asexual fecundity, and growth. These findings highlight the importance of selection for fine-scale environmental adaptation in marine taxa and imply that the genotypic structure of populations reflects extensive periods of interclonal competition and site-specific selection.

Spatio-temporal analysis of house price convergence based on a demographical distance

Convergences of house prices have been studied for over three decades, but yet have been confirmed because of spatial heterogeneity and autocorrelations in house prices. A spatio-temporal approach was recently proposed to address the spatial and temporal issues related to house prices. However, most previous studies placed the focus on the spatial heterogeneity and autocorrelations from geographical locations, which neglected other spatial factors. In order to overcome this shortfall, this research argued a demographical distance, constructed by demographical structure and housing market scales, to investigate the house price convergences in Australian capital cities. The results confirmed the house price levels in Canberra, Brisbane and Perth converged to the house price level in Sydney.

Variability of sedimentary organic carbon in patchy seagrass landscapes

Seagrass ecosystems, considered among the most efficient carbon sinks worldwide, encompass a wide variety of spatial configurations in the coastal landscape. Here we evaluated the influence of the spatial configuration of seagrass meadows at small scales (metres) on carbon storage in seagrass sediments. We intensively sampled carbon stocks and other geochemical properties (δ(13)C, particle size, depositional fluxes) across seagrass-sand edges in a Zostera muelleri patchy seagrass landscape. Carbon stocks were significantly higher (ca. 20%) inside seagrass patches than at seagrass-sand edges and bare sediments. Deposition was similar among all positions and most of the carbon was from allochthonous sources. Patch level attributes (e.g. edge distance) represent important determinants of the spatial heterogeneity of carbon stocks within seagrass ecosystems. Our findings indicate that carbon stocks of seagrass areas have likely been overestimated by not considering the influence of meadow landscapes, and have important relevance for the design of seagrass carbon stock assessments.

Is there long-run equilibrium in the house prices of Australian capital cities?

In order to explore the long-run equilibrium in the house prices of different cities, studies on house price convergence have been conducted by a number of researchers. However, the majority of previous studies have neglected the effects of spatial heterogeneity and autocorrelation on house prices. This research improves on the investigation of house price convergence by developing a spatio-temporal autoregressive model based on a framework of panel regression methods. Both spatial heterogeneity and autocorrelation of house prices in different cities are taken into account. Geographical distance and the scale of development of the urban housing market are used to construct temporal varying spatial measurements. The spatio-temporal model is then applied to investigate the long-run equilibrium in the house prices of Australian capital cities. The results confirm that house prices in Sydney approach a steady state in the long run, whereas house prices in Brisbane, Canberra, Melbourne and Perth are able to do with lower confidence. However, little evidence supports the existence of long-run equilibrium in the house prices of Adelaide, Darwin and Hobart.

Dispersal responses override density effects on genetic diversity during post-disturbance succession.

Dispersal fundamentally influences spatial population dynamics but little is known about dispersal variation in landscapes where spatial heterogeneity is generated predominantly by disturbance and succession. We tested the hypothesis that habitat succession following fire inhibits dispersal, leading to declines over time in genetic diversity in the early successional geckoNephrurus stellatus We combined a landscape genetics field study with a spatially explicit simulation experiment to determine whether successional patterns in genetic diversity were driven by habitat-mediated dispersal or demographic effects (declines in population density leading to genetic drift). Initial increases in genetic structure following fire were likely driven by direct mortality and rapid population expansion. Subsequent habitat succession increased resistance to gene flow and decreased dispersal and genetic diversity inN. stellatus Simulated changes in population density alone did not reproduce these results. Habitat-mediated reductions in dispersal, combined with changes in population density, were essential to drive the field-observed patterns. Our study provides a framework for combining demographic, movement and genetic data with simulations to discover the relative influence of demography and dispersal on patterns of landscape genetic structure. Our results suggest that succession can inhibit connectivity among individuals, opening new avenues for understanding how disturbance regimes influence spatial population dynamics.

Spatial and temporal distribution of solute leaching in heterogeneous soils: analysis and application to multisampler lysimeter data

Accurate assessment of the fate of salts, nutrients, and pollutants in natural, heterogeneous soils requires a proper quantification of both spatial and temporal solute spreading during solute movement. The number of experiments with multisampler devices that measure solute leaching as a function of space and time is increasing. The breakthrough curve (BTC) can characterize the temporal aspect of solute leaching, and recently the spatial solute distribution curve (SSDC) was introduced to describe the spatial solute distribution. We combined and extended both concepts to develop a tool for the comprehensive analysis of the full spatio-temporal behavior of solute leaching. The sampling locations are ranked in order of descending amount of total leaching (defined as the cumulative leaching from an individual compartment at the end of the experiment), thus collapsing both spatial axes of the sampling plane into one. The leaching process can then be described by a curved surface that is a function of the single spatial coordinate and time. This leaching surface is scaled to integrate to unity, and termed S can efficiently represent data from multisampler solute transport experiments or simulation results from multidimensional solute transport models. The mathematical relationships between the scaled leaching surface S, the BTC, and the SSDC are established. Any desired characteristic of the leaching process can be derived from S. The analysis was applied to a chloride leaching experiment on a lysimeter with 300 drainage compartments of 25 cm2 each. The sandy soil monolith in the lysimeter exhibited fingered flow in the water-repellent top layer. The observed S demonstrated the absence of a sharp separation between fingers and dry areas, owing to diverging flow in the wettable soil below the fingers. Times-to-peak, maximum solute fluxes, and total leaching varied more in high-leaching than in low-leaching compartments. This suggests a stochastic–convective transport process in the high-flow streamtubes, while convection–dispersion is predominant in the low-flow areas. S can be viewed as a bivariate probability density function. Its marginal distributions are the BTC of all sampling locations combined, and the SSDC of cumulative solute leaching at the end of the experiment. The observed S cannot be represented by assuming complete independence between its marginal distributions, indicating that S contains information about the leaching process that cannot be derived from the combination of the BTC and the SSDC.

Quantifying effects of soil heterogeneity on groundwater pollution at four sites in the USA

Four sites located in the north-eastern region of the United States of America have been chosen to investigate the impacts of soil heterogeneity in the transport of solutes (bromide and chloride) through the vadose zone (the zone in the soil that lies below the root zone and above the permanent saturated groundwater). A recently proposed mathematical model based on the cumulative beta distribution has been deployed to compare and contrast the regions' heterogeneity from multiple sample percolation experiments. Significant differences in patterns of solute leaching were observed even over a small spatial scale, indicating that traditional sampling methods for solute transport, for example the gravity pan or suction Iysimeters, or more recent inventions such as the multiple sample percolation systems may not be effective in estimating solute fluxes in soils when a significant degree of soil heterogeneity is present. Consequently, ignoring soil heterogeneity in solute transport studies will likely result in under- or overprediction of leached fluxes and potentially lead to serious pollution of soils and/or groundwater. The cumulative beta distribution technique is found to be a versatile and simple technique of gaining valuable information regarding soil heterogeneity effects on solute transport. It is also an excellent tool for guiding future decisions of experimental designs particularly in regard to the number of samples within one site and the number of sampling locations between sites required to obtain a representative estimate of field solute or drainage flux.

Birds in agricultural mosaics : the influence of landscape pattern and countryside heterogeneity

Agricultural environments are critical to the conservation of biota throughout the world. Efforts to identify key influences on the conservation status of fauna in such environments have taken complementary approaches. Many studies have focused on the role of remnant or seminatural vegetation and emphasized the influence on biota of spatial patterns in the landscape. Others have recognized that many species use diverse ‘‘countryside’’ elements within farmland, and emphasize the benefits of landscape heterogeneity for conservation. Here, we investigated the effect of independent measures of both the spatial pattern (extent and configuration) and heterogeneity of elements (i.e., land uses/vegetation types) on bird occurrence in farm-scale agricultural mosaics in southeastern Australia. Birds were sampled in all types of elements in 27 mosaics (each 1 3 1 km) selected to incorporate variation in cover of native vegetation and the number of different element types in the mosaic. We used an information-theoretic approach to identify the mosaic properties that most strongly influenced bird species richness. Subgroups of birds based on habitat requirements responded most strongly to the extent of preferred elements in mosaics. Woodland birds were richer in mosaics with higher cover of native vegetation while open-tolerant species responded to the extent of scattered trees. In contrast, for total species richness, mosaic heterogeneity (richness of element types) and landscape context (cover of native vegetation in surrounding area) had the greatest influence. These results showed that up to 76% of landscape-level variation in richness of bird groups is attributable to mosaic properties directly amenable to management by landowners. Key implications include (1) conservation goals for farm landscapes must be carefully defined because the richness of different faunal components is influenced by different mosaic properties; (2) the extent of native vegetation is a critical influence in agricultural environments because it drives the farmscale richness of woodland birds and has a broader context effect on total bird richness in mosaics; (3) land-use practices that enhance the heterogeneity of farmland mosaics are beneficial for native birds; and (4) the cumulative effect of even small elements in farm mosaics contribute to the structural properties of entire landscapes.

Resource heterogeneity for stream detritivores

Invertebrate animals in headwater streams depend upon leaves, wood and bark for both food and living space. This project demonstrated the strength of that dependence where the patchiness in habitat is influenced at the smallest spatial scales by the movement of sediments, and at the largest by agricultural clearing.