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The current research deals with the dispersion of fine settling particles in a fluid flowing through an ice-covered channel under the laminar flow condition. An analytical solution of the two-dimensional convection–diffusion equation, based on the multi-scale homogenization technique, is obtained. To validate the current study, analytical results for the dispersion coefficient are compared with the available earlier research work. Moreover, the proposed analytical solutions for mean concentration distributions of the tracers are compared with the numerical results obtained from the finite difference technique. From the industrial and environmental points of view, the vertical concentration distribution provides a very significant information. The downstream evolution of the concentration distribution also is shown for typical time periods at different values of the settling velocity. The approach to the vertical uniformity shows that it is too slow a process in comparison to that of longitudinal normality. It was found that settling velocities of particles disturb the vertical uniformity and the centroid of the solute cloud rises due to the increase in settling velocity. Results illustrate that in the downstream direction, the vertical concentration distribution increases near the bed surface and it decreases in the proximity of the ice-covered surface of the channel with the increase of settling velocity, but the mean concentration of the solute increases. The current study may play an important role to understand the mechanism of the sedimentation process in a closed channel system. [ABSTRACT FROM AUTHOR]

Invasive species are a major threat to global diversity and can interact synergistically or antagonistically with various components of climate change. Using species distribution models (SDMs) at different spatial scales and resolutions, we determined the main variables affecting the distribution of six invasive macroalgae present on European coasts. We also studied occupation of the thermal realized niche and predicted areas potentially at risk of invasion. The climatic variables related to warming had a greater influence on distribution at large scales, while non-climatic variables related to river influence and maritime transport at regional scale. Invaders often seemed to occupy colder areas than in their native area. The combination of SDMs with thermal niche of species is a useful way of clarifying the invasion process. This approach will help in the development of preventive strategies whereby the responsible authorities can implement early detection systems and respond swiftly to the appearance of biopollutants. [Display omitted] • Invasive macroalgae occupy colder areas when invading. • Multi-scale and resolution SDMs could improve the management of invasive macroalgae. • Climatic variables related to temperature determined distribution at latitudinal scales. • Non-climatic variables related to human activities were determinant at regional scale. • Poleward range shifts are expected under different RCP climate change scenarios. [ABSTRACT FROM AUTHOR]

Understanding the formation and causes of cropland abandonment is crucial for developing effective strategies to mitigate this process. However, studies on cropland abandonment often look at one spatial scale, although the relationship between abandonment and evaluated factors may change depending on the specific scale, which limits our understanding of the process of cropland abandonment. Taking mountainous Southern Sichuan of China as an example, we utilized satellite-derived cropland abandonment maps to assess the evolving patterns of cropland abandonment from 2003 to 2018 across various scales. We then carried out a multi-scale (parcel, local and regional) assessment of the relationships between selected 17 variables representing natural, location and socioeconomic conditions and cropland abandonment. Results showed, the cropland abandonment rate increased from 2 % in 2003 to 15 % by 2018, and cropland abandonment always showed a higher concentration in the central part of the study area. At different scales, a combination of factors, which determined cropland abandonment, differed. We also found the distance to the nearest county center was scale-dependent factor and statistically significant factor of cropland abandonment only at the local scale. Among the factors with large contributions, topography mattered at all three scales; cropland per capita, aging and agricultural labor per unit of cropland mattered at the parcel and regional scales. Cropland fragmentation, air temperature and distance to the nearest settlement mattered at the local scale; the distance to the nearest water system, the distance to nearest county center and agricultural mechanization mattered at the regional scale. This multi-scale assessment framework embodied with multi-variable and multi-temporal could provide a new perspective to reveal the complex nonlinear relationship between the determinants and cropland abandonment, and further help to predict future cropland abandonment hotspots and identify relevant land-use policies. • The clustering of cropland abandonment was revealed across multiple scales. • Abandonment patterns at various scales were explained by various determinants. • The topography factor mattered at parcel, local and regional scales. • Observed a nonlinear relationship between the determinants and land abandonment. [ABSTRACT FROM AUTHOR]

• Remnant forest enhanced bee visits to forest plants at different spatial scales. • Native bee visits declined with increasing mass flowering soybean amount. • Honeybee visits was not related to increasing mass flowering soybean amount. Agricultural intensification promotes the loss and fragmentation of natural habitats, and negatively affects the provision of ecosystem services such as natural pollination of native plants and crops. Also, many crops produce large flower blooms for a short period of time, and some studies have found effects of this massive flowering pulse on the abundance and foraging behavior of pollinators. Particularly, soybean is one of the most extended crops globally, and its flowers are visited by native bees and honeybees. In this work, we evaluated the effects of mass flowering soybean at different spatial scales on visitation rates of co-flowering plants inhabiting in fragmented forests of central Argentina. We applied generalized linear mixed models and bootstrapping methods via a multi-scale approach, by defining circular landscapes of increasing radii, from 0.5 to 1.5 km, by 0.25 km intervals. Results show that the visitation rates on forest target plants by total flower visitors and honeybees increased with higher proportions of remnant forest, and a positive trend was found for native bees. Moreover, visitation rates by native bees decreased with increasing proportions of mass flowering soybean in the landscape, whereas visitation rate by honeybees showed a positive trend with increasing proportions of mass flowering soybean across all spatial scales. Our work highlights the importance of considering the crop matrix in landscape management for the conservation of functional biodiversity, including crops with apparently inconspicuous flowers, as these massive flowering pulses could affect pollinator foraging activity and therefore the pollination services delivered to native flora. [ABSTRACT FROM AUTHOR]

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification of MRI images into normal or low grade or high grade plays a vital role for the early diagnosis. The Non-Subsampled Shearlet Transform (NSST) that captures more visual information than conventional wavelet transforms is employed for feature extraction. As the feature space of NSST is very high, a statistical t-test is applied to select the dominant directional sub-bands at each level of NSST decomposition based on sub-band energies. A combination of features that includes Gray Level Co-occurrence Matrix (GLCM) based features, Histograms of Positive Shearlet Coefficients (HPSC), and Histograms of Negative Shearlet Coefficients (HNSC) are estimated. The combined feature set is utilized in the classification phase where a hybrid approach is designed with three classifiers; k-Nearest Neighbor (kNN), Naive Bayes (NB) and Support Vector Machine (SVM) classifiers. The output of individual trained classifiers for a testing input is hybridized to take a final decision. The quantitative results of ABIA system on Repository of Molecular Brain Neoplasia Data (REMBRANDT) database show the overall improved performance in comparison with a single classifier model with accuracy of 99% for normal/abnormal classification and 98% for low and high risk classification. [ABSTRACT FROM AUTHOR]

• Demand simulation of ecosystem services (ES) was refined using a system dynamics model. • Supply-demand bundles were established to identify mismatches in ES supply-demand (ESSD). • Imbalances and mismatches of the ESSD were analyzed at the grid, city, and sub-city cluster scales. • Eight, six, and three regulatory zones were identified via the supply-demand bundles at three scales. • Multi-tier regulatory strategies were proposed to improve ES management. Ensuring ecological sustainability in urbanizing mega-regions like the Yangtze River Middle Reaches (YRMR) city cluster is crucial. Distinct dynamics in ecosystem service supply and demand (ESSD) have emerged due to land use changes, climate shifts, and policy drivers. Addressing potential imbalances and mismatches necessitates strategic ESSD regulation. However, it remains unclear how the future ESSD relationship will evolve under the combined impact of climate change and rapid urbanization. To improve demand simulation, this study examined causal links between socio-economic factors, land use, and ES demands from 2000 to 2018 using a system dynamics model. Six ES supplies and demands were simulated under the SSP-RCP scenarios in 2018–2050. Imbalances and mismatches in ESSD were assessed at grid, city, and sub-city cluster scales. The results showed sizable deficits in crop production (CP) and nature access (NA) services at three scales. A synergistic relationship between CP supply and water yield (WY) demand suggested that increased agricultural production could strain water resources. Growing demand for carbon storage (CS) and WY would worsen ESSD imbalance. To maintain long-term ESSD balance, strict carbon policies, land-use restrictions, cross-scale collaboration are needed. A tiered zoning approach based on supply-demand bundles can enhance ecosystem management in a socio-ecological context. [ABSTRACT FROM AUTHOR]

Emerging diseases of wildlife origin are increasingly spilling over into humans and domestic animals. Surveillance and risk assessments for transmission between these populations are informed by a mechanistic understanding of the pathogens in wildlife reservoirs. For avian influenza viruses (AIV), much observational and experimental work in wildlife has been conducted at local scales, yet fully understanding their spread and distribution requires assessing the mechanisms acting at both local, (e.g., intrinsic epidemic dynamics), and continental scales, (e.g., long‐distance migration). Here, we combined a large, continental‐scale data set on low pathogenic, Type A AIV in the United States with a novel network‐based application of bird banding/recovery data to investigate the migration‐based drivers of AIV and their relative importance compared to well‐characterized local drivers (e.g., demography, environmental persistence). We compared among regression models reflecting hypothesized ecological processes and evaluated their ability to predict AIV in space and time using within and out‐of‐sample validation. We found that predictors of AIV were associated with multiple mechanisms at local and continental scales. Hypotheses characterizing local epidemic dynamics were strongly supported, with age, the age‐specific aggregation of migratory birds in an area and temperature being the best predictors of infection. Hypotheses defining larger, network‐based features of the migration processes, such as clustering or between‐cluster mixing explained less variation but were also supported. Therefore, our results support a role for local processes in driving the continental distribution of AIV. [ABSTRACT FROM AUTHOR]

In this paper, based on the basic theory and method of wavelet transform, we systematically analyze the conditions for the combined use of a single wavelet transform and multi-scale resolution analysis. Three models of multi-scale representation of geographic data were constructed using wavelet analysis. Then, wavelet detection methods and models are used to simplify DEM data for large-scale expression of DEM data. In our research, various eco-environment data expression models are taken as an integral part of the research. Through comprehensive research on spatial data, multi-dimensional data and cartographic data, and based on the semantic correlation and the characteristics of the ecological environment, we constructed a multi-faceted expression model based on ecological utilization data. The experimental results show that different models and methods have a very obvious influence on the multidimensional expression of DEM. The defect deduction method can get N = 94.95, which belongs to the superior level. Therefore, the model proposed in this study can be used to express multi-scale ecological environment data, and it is conducive to the construction of ecological environment system and sustainable development. [ABSTRACT FROM AUTHOR]

The Clapper Rail (Rallus crepitans) is an avian marsh specialist that depends exclusively on coastal wetlands for all aspects of its life cycle, and is valued for its role as an indicator of ecosystem health. This study used radio telemetry in the Ashepoo-Combahee-Edisto Basin in South Carolina, USA, to assess Clapper Rail habitat selection in response to local and landscape variables and to investigate possible demographic consequences of differences in habitat selection. Compared to simulated home ranges, observed Clapper Rail home ranges during the breeding season contained greater amounts of potential forage area and shorter distances to potential forage locations at both local and landscape scales. Mean (± SE) Clapper Rail home range size was 1.06 ha ± 0.19. There were no significant differences between males (1.05 ha ± 0.26) and females (1.08 ha ± 0.25) in home range size. Home range selection based on optimization of potential forage resources may have demographic consequences for Clapper Rails; however, this hypothesis was only weakly supported. Clapper Rails foraging near exposed edges may increase mortality risk through predation, but this behavior may be negligible to survival provided that sufficient nearby cover exists. Resource abundance near cover is likely a major driver of habitat selection and is influencing Clapper Rail habitat selection at multiple scales, which may have consequences for adult survival. [ABSTRACT FROM AUTHOR]

The aim of this study was to build an in silico computer-aided design and computer-aided manufacturing (CAD/CAM) resincomposite-block (RCB) model with different silane coupling ratios and to evaluate the physical and mechanical properties of the models, including the elastic modulus, Poisson's ratio, compressive strength, and maximum principal strain. Nanoscale CAD/CAM RCB models were designed by using CAD software that consisted of twelve spherical silica nanofiller particles and a resin matrix. Seven nanoscale models with different silane coupling ratios were prepared with the same filler volume contents. Homogenization analysis was conducted by using voxel-base finite-element analysis software to predict the elastic moduli and Poisson's ratio of the macro CAD/CAM RCB. Localization analysis was used to analyze the maximum principal strain distribution in the hydrolysis layer. In silico multi-scale analysis demonstrated that the compressive strength of the CAD/CAM RCB was reduced with a decrease in the silane coupling ratios of the fillers. [ABSTRACT FROM AUTHOR]

In order to manipulate large-scale coherent structures in the wall-bounded turbulence and reduce the skin-friction, an active-control experimental investigation was performed through synchronous and asynchronous vibrations of double piezoelectric vibrators embedded spanwisely on a smooth flat plate surface. A TSI-IFA300 hot-wire anemometer and TSI-1621A-T1.5 hot-wire probe were used to measure the time series of instantaneous velocity at different locations. Influence of the vibrations on wall-bounded turbulence are compared in a multi-scale point of view. A disturbance Reynolds Number Red = ρd2f/μ is introduced to represent the disturbance. A probability density functions (PDFs) of the multi-scale components of the turbulence velocity and multi-scale conditional phase-averaged waveform are studied in detail using the Wavelet transform. The results show that the maximum drag reduction rate 18.54% was obtained at 100V/160Hz and Red = 0.54 case with an asynchronous vibration mode. The disturbances generated by the vibrators have a significant influence on the sweep events of burst. The asynchronous vibration model is more effective than synchronous vibration one. A possible physical mechanism is recognized to explain why the disturbance frequency of 160Hz leads to an optimal parameter set for drag reduction. [ABSTRACT FROM AUTHOR]

• Achieved super-resolution images using multi-scale pyramid features. • Detailed texture and structure in images were extracted using the Bendlets transform. • Introduced structured dictionaries for effective high and low-resolution image reconstruction. • Our research improved the quality of high-resolution imaging in multiple scientific fields. High-resolution biological tissue slice images provide opportunities for more precise observation and analysis of histopathological features. These images typically consist of enclosed contours, and Bendlets transform is an effective means to approximate such structures. In this study, we leverage Bendlet transform to incorporate multi-level image data, thereby establishing a multi-scale pyramid feature set. This approach aids in achieving a sparser representation of image textures and structures. We apply Bendlets transform to extract multi-frequency wavelet subband features and formulate structured dictionaries for both high and low resolutions based on these features. After creating these dictionaries, we compute sparse representation coefficients using the low-resolution dictionary and subsequently integrate them with the high-resolution dictionary to generate high-resolution subbands. Ultimately, through the process of inverse wavelet transformation, we completed the reconstruction of high-resolution images. This method not only significantly enhances the restoration of image details and clarity but also effectively preserves the overall structural characteristics of the original images. [ABSTRACT FROM AUTHOR]

• Future pluvial flood exposure related to vulnerability at two spatial scales • Parcel scale revealed more spatial bias and correlations than census block group scale • Future flood exposure was negatively correlated with building age at parcel scale • City historical context affected relationships between flood exposure and redlining Flooding occurs at different scales and unevenly affects urban populations based on the broader social, ecological, and technological system (SETS) characteristics particular to cities. As hydrological models improve in spatial scale and account for more mechanisms of flooding, there is a continuous need to examine the relationships between flood exposure and SETS drivers of flood vulnerability. In this study, we related fine-scale measures of future flood exposure—the First Street Foundation's Flood Factor and estimated change in chance of extreme flood exposure—to SETS indicators like building age, poverty, and historical redlining, at the parcel and census block group (CBG) scales in Portland, OR, Phoenix, AZ, Baltimore, MD, and Atlanta, GA. We used standard regression models and accounted for spatial bias in relationships. The results show that flood exposure was more often correlated with SETS variables at the parcel scale than at the CBG scale, indicating scale dependence. However, these relationships were often inconsistent among cities, indicating place-dependence. We found that marginalized populations were significantly more exposed to future flooding at the CBG scale. Combining newly-available, high-resolution future flood risk estimates with SETS data available at multiple scales offers cities a new set of tools to assess the exposure and multi-dimensional vulnerability of populations. These tools will better equip city managers to proactively plan and implement equitable interventions to meet evolving hazard exposure. [ABSTRACT FROM AUTHOR]

The penetration of water into rubber-like protein networks such as cross-linked resilin, which is found in insects, can lead to changes in stiffness that range over several orders of magnitude. This softening effect cannot be explained by the volumetric changes associated with pure swelling/deswelling used to describe networks with covalent bonds. Rather, this property stems from the reversible swelling-induced breaking of hydrogen cross-linking bonds that connect the chains in the network. This work presents a model for the swelling and the mechanical response of hydrogen-bond dominated biopolymer networks. It is shown that the penetration of water molecules into the network leads to the breaking of non-covalent cross-linking sites. In turn, the network experiences a reduction in the effective chain-density, an increase in entropy, and a consequent decrease in free energy, thus explaining the dramatic softening. Additionally, the breaking of hydrogen bonds alters the micro-structure and changes the quantitative elastic behavior of the network. The proposed model is found to be in excellent agreement with several experimental findings. The merit of the work is twofold in that it (1) accounts for the number and the strength of non-covalent cross-linking bonds, thus explaining the drastic reduction in stiffness upon water uptake, and (2) provides a method to characterize the micro-structural evolution of hydrogen-bond dominated networks. Consequently, the model can be used as a micro-structural design-guide to program the response of synthetic polymers. Hydrogen-bond dominated biopolymer networks are found in insects and have a unique structure that allows a dramatic reduction of several orders of magnitude in stiffness upon hydration. Understanding the micro-structure of such networks is key in the fabrication of new biomimetic polymers with tunable mechanical properties. This work introduces a microscopically motivated model that explains the dramatic reduction in stiffness and quantifies the influence of key micro-structural quantities on the overall response. The model is validated through several experimental findings. The insights from this work motivate further attempts at the fabrication of new biomimetic polymers and serve as a micro-structural design guide that enables the programming of the elastic swelling-induced response. [ABSTRACT FROM AUTHOR]

This presentation predicts the elastic properties of three-dimensional (3D) orthogonal woven composite (3DOWC) by finite element analysis based on micro/meso repeated unit cell (RUC) models. First, the properties of fiber yarn are obtained by analysis on a micro-scale RUC model assuming fibers in a hexagonal distribution pattern in the polymer matrix. Then a full thickness meso-scale RUC model including weft yarns, warp yarns, Z-yarns and pure resin zones is established and full stiffness matrix of the 3DOWC including the in-plane and flexural constants are predicted. For thick 3DOWC with large number of weft, warp layers, an alternative analysis method is proposed in which an inner meso-RUC and a surface meso-RUC are established, respectively. Then the properties of 3DOWC are deduced based on laminate theory and properties of the inner and surface layers. The predicted results by the above two alternative methods are in good experimental agreement. [ABSTRACT FROM AUTHOR]

The Ecological footprint accounting is a resource accounting tool that is used to track the sustainability of human systems. In this paper, we present a new approach to calculate the Ecological Footprint metrics at different geographic scales using Net Primary Productivity data. Our study focuses on the town of Afourar, Morocco, as a case study examined at three different scales; national, regional, and provincial scale. In contrast with other studies, our footprint accounting results are expressed in what we have called territorial hectares. The accounting results show that geographic scale has a significant influence on the footprint model, where three cases of sustainability were found. This implies that the efforts to maintain the sustainability of territories are more important at some scales than others. We argue that the relationship between sustainability and geographic scale is both strong and complex and that sustainability is a spatially relative concept. Therefore, we conclude that multi-scale analysis is crucial for making sustainable decisions and management policies. [ABSTRACT FROM AUTHOR]

Abstract Global environmental changes are expected to alter the functional characteristics of understorey herb-layer communities, potentially affecting forest ecosystem functioning. However, little is known about what drives the variability of functional traits in forest understories. Here, we assessed the role of different environmental drivers in shaping the functional trait distribution of understorey herbs in fragmented forests across three spatial scales. We focused on 708 small, deciduous forest patches located in 16 agricultural landscape windows, spanning a 2500-km macroclimatic gradient across the temperate forest biome in Europe. We estimated the relative effect of patch-scale, landscape-scale and macroclimatic variables on the community mean and variation of plant height, specific leaf area and seed mass. Macroclimatic variables (monthly temperature and precipitation extremes) explained the largest proportion of variation in community trait means (on average 77% of the explained variation). In contrast, patch-scale factors dominated in explaining community trait variation (on average 68% of the explained variation). Notably, patch age, size and internal heterogeneity had a positive effect on the community-level variability. Landscape-scale variables explained only a minor part of the variation in both trait distribution properties. The variation explained by shared combinations of the variable groups was generally negligible. These findings highlight the importance of considering multiple spatial scales in predictions of environmental-change effects on the functionality of forest understories. We propose that forest management sustainability could benefit from conserving larger, historically continuous and internally heterogeneous forest patches to maximise ecosystem service diversity in rural landscapes. [ABSTRACT FROM AUTHOR]

Allee effect, as one of the research hotspots in ecology and conservation biology, extremely easily affects the distribution of population in space, especially for the low-density population. In the ecosystem, the spatial distribution of predator is more vulnerable to Allee effect since the density of predator is always smaller than that of prey, but the relevant attention paid to it is few. In this paper, we establish and analyze a spatial predator–prey system incorporating Allee effect on predator population. Theoretically, we use multi-scale analysis to derive the amplitude equation and obtain the different Turing patterns under different intensities of Allee effect. Numerically, we verify the theoretical results. We also find that the growth rate of predator is significantly inhibited and the time of reaching equilibrium tends to be slower with the increase of Allee effect intensity within certain limits. More interestingly, it is discovered that the predator under Allee effect in a certain extent is more stable although Allee effect on predator may lead to more complex dynamic behaviors. Our results help better understand species invasion and nature conservation in ecology. • We establish a spatial predator-prey model with Allee effect on predator. • Different patterns can be obtained under different Allee effect. • The growth of predator is inhibited as raises of Allee effect to certain limits. • The predator with Allee effect is easier to survive. • Allee effect may lead to more complex dynamic behaviors. [ABSTRACT FROM AUTHOR]

The conservation and restoration of old stained manuscripts is an activity devoted to the preservation and protection of things of historical and personal significance made mainly from paper, parchment, and skin. We present in this paper a hybrid implementation for de-noising and restoration of old degraded and stained manuscripts. This implementation is based on the statistical dependence of the wavelet coefficients of type Ortho-normal Wavelet Thresholding Algorithm based on the principle of Stein’s Unbiased Risk-Estimate Linear Expansion of Thresholds (OWT SURE-LET) and the synergy with bilateral filtering. First, the non-biased quadratic risk Stein estimator is applied to de-noise images corrupted by white Gaussian noise. In a second step, an improved bilateral filter is introduced to smooth and eliminate unnecessary details with the advantage of preserving edges between image regions. Obtained results show the effectiveness of the proposed synergy compared to separated approaches both on gray scale images and stained old manuscript. [ABSTRACT FROM AUTHOR]

To measure the efficiency of clean energy markets, a multi-scale complexity analysis approach is proposed. Due to the coexisting characteristics of clean energy markets, the “divide and conquer” strategy is introduced to provide a more comprehensive complexity analysis framework for both overall dynamics and hidden features (in different time scales), and to identify the leading factors contributing to the complexity. In the proposed approach, ensemble empirical mode decomposition (EEMD), a competitive multi-scale analysis tool, is first implemented to capture meaningful features hidden in the original market system. Second, fuzzy entropy, an effective complexity measurement, is employed to analyze both the whole system and inner features. In empirical analysis, the nuclear energy and hydropower markets in China and US are investigated, and some interesting results are obtained. For overall dynamics, the US clean energy markets appear a significantly higher complexity level than China’s markets, implying market maturity and efficiency of US clean energy relative to China. For inner features, similar features (in terms of similar time scales) in different markets present similar complexity levels. For different inner features, there are some distinct differences in clean energy markets between US and China. China’s markets are mainly driven by upward long-term trends with a low-level complexity, while short-term fluctuations with high-level complexity are the leading features for the US markets. All these results demonstrate that the proposed EEMD-based multi-scale fuzzy entropy approach can provide a new analysis tool to understand the complexity of clean energy markets. [ABSTRACT FROM AUTHOR]

Urban parks have been widely recognized for the critical functions they provide in enhancing health and wellbeing. However, parks are known to be inadequately provided and non-uniformly distributed in cities, leading to an increasing interest to examine spatial equity of park distribution. Such studies have mostly focused on the distributional attributes of park supply in determining spatial equity, while the role of residents' demand is usually ignored or not adequately assessed. In addition, people's preferences for park use were normally ignored and nearest parks were assumed as supplier of park services. Moreover, even though equity assessment is scale-dependent, few studies adopt a multi-scale assessment. We report on a study to address these gaps. A multi-scale Supply-Demand Equity Index (SDEI) was developed to assess spatial equity of park distribution from the perspective of supply and demand interactions, and data were collected at a fine scale of neighborhood level. Residents' accessibility to their most often used parks and nearest parks were used to assess and compare supply level; while residents' perceptions obtained from surveys and population density were used to assess and compare demand level. Results showed that supply measured by accessibility to most often used park more accurately reflects supply, and demand assessment on the basis of perception could reflect variations among different social groups and reveal otherwise hidden patterns of spatial inequity. It was also shown that SDEI could identify areas where mismatch between supply and demand occurs. We demonstrated in a single study that different definitions and approaches of quantifying spatial equity can lead to distinct conclusions, therein highlighting that the complex nature of equity requires nuanced approaches and providing a broader view of equity assessment. In addition, the implications of this study for urban park planning and management were highlighted. [ABSTRACT FROM AUTHOR]

Connecting the signals of the vegetative and reproductive cycles of plants using large-scale phenological techniques is not always an easy task, and this complexity increases considerably when analysing the plant life cycle in grasses, due to the ubiquity and diversity of this taxonomic family. This work integrates remote sensing techniques (NDVI from satellite remote sensing data and greenness from near-surface imagery) and biological-based techniques (airborne pollen monitoring and field observations and sampling) to analyse phenological patterns and productivity in grass-dominated vegetation types. We aim to answer two main applied and unanswered questions; i) how are the specific phases of vegetative and reproductive cycles in grasses linked at the species and plant community level? and ii) which grass-dominant habitats are the major contributors of grass pollen emission to the atmosphere at the plant community level? The multi-scale integration and validation of large-scale methods such as satellite remote sensing data and aerobiological monitoring using high-resolution or field phenological techniques is recommended. The results clearly support the hypothesis that the highest rates of grass pollen emission are successively produced when the major grass-dominated vegetation types go through the final phases of vegetative development during their biological senescence or equivalent phases. At the plant community level, natural and semi-natural grass-dominated vegetation types, rather than grass cropland habitats, constitute the major sources of pollen emission. The major contributors to the grass pollen emission at the species level are also identified. Finally, a positive relationship between year-to-year primary productivity (measured as annual sum or maximum NDVI) and pollen production (measured as airborne pollen intensity) was observed at the community level. This is a very timely study, as the availability of remote sensing data is increasing interest in generating enhanced forecasting model of allergenic airborne pollen. [Display omitted] • A multi-scale study of the grass life cycle was carried out using different methods. • Remote sensing techniques were combined with field observations and pollen monitoring. • The results allowed to study the link between vegetative and reproductive stages. • The major contributors to airborne pollen were identified at the habitat level. • A relationship between primary productivity and pollen production was revealed. [ABSTRACT FROM AUTHOR]

We propose to date and analyze the financial cycle using the Maximum Overlap Discrete Wavelet Transform (MODWT). Our presentation points out limitations of the methods derived from the classical business cycle literature, while stressing their connection with wavelet analysis. The fundamental time-frequency uncertainty principle imposes replacing point estimates of turning points by interval estimates, which are themselves function of the scale of the analysis. We use financial time series from 19 OECD countries to illustrate the applicability of the tool. [ABSTRACT FROM AUTHOR]

The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in particular with respect to the cross-disciplinary role of data. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in modelling strategies. Visualization and data analysis techniques are successfully used in a wide variety of applications, both in theoretical and applied domains, but questions remains about their robustness, efficiency and applicability to the problems introduced before. The paper aims to analyze critically these topics by means of case studies, showing a possible path to create a multi-scale methodology able to synthesize all the relevant aspects. [ABSTRACT FROM AUTHOR]

The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle such as design phase, construction phase, commissioning phase, operation phase and eventually refurbishment phase, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Numerical simulation tools and optimization methods are needed to properly evaluate all the key performance indicators simultaneously, unveiling the existing gaps and identifying possible synergies and strategies in the performance estimation and decision-making processes for the building life cycle. Further, several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in the overall optimization process. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, subject to economic and comfort constraints, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in every modelling strategy. Data analysis and optimization techniques are successfully used in a wide variety of applications. Although these techniques have proven to be successful in both theoretical and applied domains, questions remains about their applicability for the problems introduced before. These questions involve primarily the robustness and efficiency of solutions procedures and the ability to identify relevant properties and to deal with large quantities of data. The paper aims to analyse critically these topics by means of case studies, showing a possible path to create an integrated methodology able to synthesize all the relevant aspects previously mentioned. [ABSTRACT FROM AUTHOR]

In this paper we derive rigorously the amplitude equation, using the natural separation of time-scales near a change of stability, for the stochastic generalized Swift–Hohenberg equation with quadratic and cubic nonlinearity in this form du = - ( 1 + ∂ x 2 ) 2 u + ν ε u + γ u 2 - u 3 dt + σ ε dW , where W ( t ) is a Wiener process. For deterministic PDE it is known that the quadratic term generates an additional cubic term, which is unstable. We consider two cases depending on γ 2 . If γ 2 < 27 38 , then we have amplitude equation with cubic nonlinearities. In the other case γ 2 = 27 38 the cubic term in the amplitude equation vanishes. Therefore we consider larger solutions to obtain an amplitude equation with quintic nonlinearities. [ABSTRACT FROM AUTHOR]

The near-fault ground motion with long period is one special kind of destructive ground motions and has significant damage to long period structures particularly. For further research on the effects of near-fault ground motion to structures, 53 typical near-fault ground motions that selected from 12 recent major earthquakes were decomposed based on multi-scale analysis method in wavelet theory, and a total of 266 ground motion components were obtained. A method to estimate seismic response of buildings that constructed in near-fault region was proposed by research on the characteristics of ground motion components, including amplitude, period and bi-normalized response spectra. This method is able to give the maximum absolute acceleration response of single degree freedom elastic system under the effect of ground motion components with period range from 0. 3 s to 20 s. The impact of site and rupture distance was considered, and a simple function was given. This method can provide detailed reference for the design of near-fault region structures, especially for long period structures. [ABSTRACT FROM AUTHOR]

This paper illustrates the analogy between Sudoku and the multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM). MuSIASEM is a transdisciplinary approach aimed at checking the viability, desirability and feasibility of actual and projected metabolic patterns of society. Building on Georgescu-Roegen's flow-fund model, it defines what the system is in terms of fund elements (human activity, managed land, power capacity), and what it does in terms of flow elements (energy, food, water, monetary flows). The accounting method of MuSIASEM generates a multi-scale, multi-dimensional representation of flow and fund elements that shares essential features with Sudoku, including mutual information and impredicativity between bottom–up and top–down causality. Data organization employed in MuSIASEM reveals the internal and external constraints that operate on the societal metabolic pattern and that determine its viability and feasibility domain. The dynamic equilibrium between the hypercyclic and dissipative macro-compartments of society expresses itself as a regional constraint on the viability of the metabolic pattern. The MuSIASEM approach is illustrated with case studies including the energy metabolism of Spain and the metabolic pattern of Mauritius. [ABSTRACT FROM AUTHOR]

The impinging jet concept has been proposed as a new ventilation strategy for use in office and industrial buildings. To improve the performance of impinging jet ventilation system to create a better thermal comfort environment, quantifying the detailed information of the flow behavior of impinging jet should be an essential prerequisite. This study reports an experimental study of an isothermal turbulent jet impinging normally on a flat surface in a closed cabin. The air jet issued from a round pipe with an inner diameter D . The distance between the pipe exit and the flat impingement plate was 9D. The Reynolds number, based on the jet centerline velocity at pipe exit and the pipe inner diameter, was 10,338. Measurements were performed in the free- and wall-jets using cross hot-wire anemometry, mean velocity, turbulence intensity, and power spectrum results being presented. In addition, a multi-scale analysis technique based on empirical mode decomposition was used to analyze and gain deeper insight into the multi-scale characteristics of coherent structures of the jet impingement on flat surface. [ABSTRACT FROM AUTHOR]

This paper proposed a discrete wavelet transform based method for time-varying physical parameter identification of shear type structures. The time-varying physical parameters are dispersed and expanded at multi-scale as profile and detail signal using discrete wavelet basis. To reduce the number of unknown quantity, the wavelet coefficients that reflect the detail signal are ignored by setting as zero value. Consequently, the time-varying parameter can be approximately estimated only using the scale coefficients that reflect the profile signal, and the identification task is transformed to an equivalent time-invariant scale coefficient estimation. The time-invariant scale coefficients can be simply estimated using regular least-squares methods, and then the original time-varying physical parameters can be reconstructed by using the identified time-invariant scale coefficients. To reduce the influence of the ill-posed problem of equation resolving caused by noise, the Tikhonov regularization method instead of regular least-squares method is used in the paper to estimate the scale coefficients. A two-story shear type frame structure with time-varying stiffness and damping are simulated to validate the effectiveness and accuracy of the proposed method. It is demonstrated that the identified time-varying stiffness is with a good accuracy, while the identified damping is sensitive to noise. [ABSTRACT FROM AUTHOR]

Many disciplines are faced with the problem of handling time-series data. This study introduces an innovative visual representation for time series, namely the continuous triangular model. In the continuous triangular model, all subintervals of a time series can be represented in a two-dimensional continuous field, where every point represents a subinterval of the time series, and the value at the point is derived through a certain function (e.g. average or summation) of the time series within the subinterval. The continuous triangular model thus provides an explicit overview of time series at all different scales. In addition to time series, the continuous triangular model can be applied to a broader sense of linear data, such as traffic along a road. This study shows how the continuous triangular model can facilitate the visual analysis of different types of linear data. We also show how the coordinate interval space in the continuous triangular model can support the analysis of multiple time series through spatial analysis methods, including map algebra and cartographic modelling. Real-world datasets and scenarios are employed to demonstrate the usefulness of this approach. [ABSTRACT FROM PUBLISHER]

To give full play to the mechanical potentiality of the pin-loaded composite laminate, the macro-mesoscopic multi-scale numerical method is developed to predict accurately the failure load of the structure, to simulate partial damage initiation, expansion and to guide the structure design. The improved unit cell model (GMC) is implanted to the numerical model by the user subroutines (USDFLD) provided by ABAQUS. The macro-micro multi-scale numerical model considering the damage/failure of micro-constituent materials is created for the pin-loaded composite laminate based on the general finite element software ABAQUS. The failure modes and the extruding strength of the pin-loaded laminate structure under the double-shear loading are simulated and predicted. By comparing the simulated failure modes with the test results in the literature, and compare the limited load with the experimental results, the feasibility of model is verified. The effect of specimen geometry dimension on the failure mode and the limited extruding strength of pin-loaded laminate structure are analyzed. The change of the width-diameter ratio will affect the failure mode, the extruding strength of the pin-loaded composite laminate and especially for the extruding strength. [ABSTRACT FROM AUTHOR]

Multi-scale properties of Reynolds stress in decaying turbulence in a wind tunnel with high Reynolds number are investigated. Two filtering techniques i.e., the zeroth-order and first-order detrending methods are applied to the two velocity components, where the local mean value (resp. local linear trend) is removed in the former (latter) technique. Some basic statistics for thirty measurements show that the variation is very large at first two locations and relatively small at last two locations. Moderately good power law is found for the mean value of local Reynolds stress at last three measurement locations with scaling exponents approximately being 1.0 and a dual power law exists for the mean value of standard deviation of local Reynolds stress at all four measurement locations with scaling exponents being 0.53 and 0.58 for zerothand first-order filtering respectively. Present results about local Reynolds stress are useful to build and evaluate the model of sub-grid Reynolds stress in large eddy simulations. [ABSTRACT FROM AUTHOR]

Highlights: [•] Application of MuSIASEM approach to the analysis of rural land uses. [•] We establish quantitative links across various indicators of performance for Laos. [•] We utilize land use to go at different scales and different dimensions of performance. [•] We offer a robust tool to link the different levels, scales and typologies in Laos. [Copyright &y& Elsevier]

Abstract: Automatic detection of retinal blood vessels and measurement of vessel diameter are important steps in the computer aided diagnosis in ophthalmology. Here, we present a new multi-scale vessel enhancement method based on complex continuous wavelet transform (CCWT). The parameters of CCWT are optimized to represent line structures in all directions and separate them from simple edges. The final vessel network is obtained by applying an adaptive histogram-based thresholding process along with a proper length filtering method. An efficient circular structure operator is employed on the centerline of vessels to estimate their diameters. The performance of the proposed method is measured on the publicly available DRIVE and STARE databases and compared with several state-of-the-art methods as well as second observer. The proposed method shows much higher accuracy (95%) and sensitivity (79%) in the same range of specificity (97%). The predictive value of it is higher than 72.9%. The vessel diameter estimation process also shows lower root mean square error compared to the existing methods and second observer. [Copyright &y& Elsevier]

Abstract: In order to improve the speed of two-dimensional empirical mode decomposition(2-D EMD)’ procedure and improve the quality of edges extract from intrinsic mode function(IMF) image,an algorithm based on triangulation interpolation two-dimensional empirical mode decomposition to detect image edges at multiple scales is proposed.This algorithm is realized using the faster interpolation method of Delaunay triangulation and cubic spline functions for surface interpolation,then extract edges from the first IMF image that was processed by multi-scale wavelet decomposition.Through the simulation experiment,results demonstrate that this method can not only detect image edge precisely,but also effectively restrain noise. Finally, the proposed algorithm is confirmed feasible and valid. [Copyright &y& Elsevier]

To improve the reliability and accuracy of the leak localization with traditional correlator, and to make the result be verified timely, a new method of leak localization with three sensors based on multi-scale analysis is proposed. The third sensor was added to form a three sensors model in this method, and then the correlation value for time delay was calculated in every sub-band through multi-scale decomposition for signals from three sensors. According to the matching relation among these three sensors, the optimal results could be obtained which showed that this method could not only calculate speed by itself but also make the leak localization more precise. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of the current work was to study vegetation patchiness of field boundaries within Mediterranean agricultural systems by analysing the effect of the management of field boundaries and their adjacent fields (organic vs. conventional fields), as well as the surrounding landscape evaluated at multiple spatial scales. Different habitat types were identified along 30 field boundaries next to organic fields and 30 boundaries next to conventional fields following the List of Catalonia CORINE Habitats. Vegetation patchiness of field boundaries was estimated by means of habitat richness, the Shannon habitat diversity index, and the percentage cover of ruderal vegetation, Mediterranean grasslands, and woody vegetation. In order to evaluate the surrounding landscape at multiple scales, circular sectors of different extent sizes (150, 300, 1000m radius) were centred on each field, and two grain size maps (100m2 and 22,500m2 minimum patch size) were used. Fourteen landscape metrics for each scale were computed, and they were summarized using a Principal Component Analysis (PCA). Although landscape metrics changed when altering the scale (grain size or extent), the first component of the PCA for all scales described a gradient in ‘agricultural intensification’, and the second component for all scales described a gradient in ‘anthropogenic intensification’. Boundary and field management had no influence on vegetation patchiness of field boundaries. Moreover, field boundaries were patchier in landscapes with a high proportion of natural habitats. [Copyright &y& Elsevier]

Abstract: Surface roughness is an important variable of geomorphologic research and hydrological modeling, and widely used in the Earth and planetary science. It plays an important role in determining how a ground object will interact with its environment. Quantification of surface-roughness variability using Digital elevation model (DEM) were applied to study area of Beichuan County, one of the most destructed areas during the Wenchuan earthquake (7.9 Mw at 14:28:01.42 CST on May 12, 2008). In this paper, four types of DEM were chosen for multi-scale assessment of the surface roughness. Three algorithms were employed, which were Root mean square of elevation, standard deviation of elevation, standard deviation of curvature profile. An overall trend of inclined to be flat from pre-earthquake to post-earthquake could be examined through the three measure methods, which indicate that Wenchuan earthquake indeed had effects on changing the surface roughness. The method of Root mean square of elevation shows the most obvious results in depicting the change before and after the earthquake. [Copyright &y& Elsevier]

Abstract: This paper presents some recent achievements of earthquake simulation, which is divided into the seismic wave propagation simulation and the seismic structure response simulation. These achievements are based on rigorous mathematical treatment of continuum mechanics problems, and numerical algorithms of solving the problems are developed. A multi-scale analysis method is developed for the seismic wave propagation simulation; numerical dispersion is reduced by introducing a new discretization scheme. A smart treatment of crack initiation and propagation is developed for the seismic structure response simulation, so that a numerical experiment is made for failure processes by using numerous samples of one structure. [Copyright &y& Elsevier]

Abstract: Automotive aluminum alloy sheet metal needs to improve the formability and the strength. In this study, the asymmetric rolling process was applied to the aluminum alloy sheet metal generation, because the {111}//ND texture, which corresponds to a part of the shear deformation texture, acts the high-formability. There are many processes of thermo-mechanical processes such as asymmetric and symmetric rollings and heat treatments in the sheet metal generation. We analyzed and optimized the microscopic texture evolution during plastic deformation in the macroscopic multi-stage warm rolling processes of the aluminum alloy sheet A6022 by using a crystallographic homogenized elasto/viscoplastic multi-scale finite element (FE) code and a discrete optimization method. In our multi-scale FE code, two scales ware considered. One is a microscopic polycrystal structure and the other is a macroscopic elastic plastic continuum. A three-dimensional representative volume element, which has initial crystal orientation distribution of the sheet metal is constructed by the electron back scattered diffraction measured pixel data. In order to evaluate the effect of temperature of warm rolling, a thermo-effect was introduced into the elastic/crystalline viscoplastic constitutive equation. Rolling parameters such as ratio of rolling speeds, rolling friction and the rolling temperature were optimized. We confirmed that Lankford value of the optimized sheet improved by 2-stage asymmetric rolling processes compared with commercial A6022-T43 sheet metal. [Copyright &y& Elsevier]

Abstract: The mechanical modelling of semi-crystalline polymers is highly complex due to their different micro-structural scales and to some lacks regarding the understanding of the respective contributions of crystalline and amorphous phases on the macroscopic behaviour. In particular, the important role of the confined amorphous phase has to be investigated. To this aim, this work proposes to combine full-field simulations with kinematics field measurements at the same scale. The material is the linear low density polyethylene (LLDPE), chosen for its “simple” microstructure. Displacement fields at the micro-scale are measured by using the digital image correlation technique in the SEM. It is scheduled to apply the experimental strain as periodic boundary conditions to a unit cell whose morphological content will be built from the observed real microstructure and to analyse both the resulting macroscopic average response and local fields. To this aim, specific numerical tools are developed notably for statistical field analysis. The results on a simple stack model under various loading cases/paths are presented as a preliminary stage before the complete analysis for the LLDPE under tensile tests. The long term aim is to better understand the strain mechanisms in the confined amorphous phase, to determine its mechanical behaviour and conclude on its influence on the macroscopic behaviour. [Copyright &y& Elsevier]

Abstract: Assessing threats to protected areas is a critical step to ensure effective resource conservation and to leverage future conservation actions. It is equally important to assess external and internal threats because human activities both in and around a protected area can impair the area''s ecological goals or impart important ecological benefits to adjacent lands. We applied a threat framework that accounts for both local and surrounding threats to identify areas in the conterminous United States that provide or offer opportunities for ecological conservation. We find that, of the lands that are least threatened locally, 49% have some existing formal protection, but that more than 35% of the existing protected portfolio is at risk from external threats. However, over 20% of currently unprotected lands provide potential opportunities for conservation. Of the area identified with highest potential conservation opportunities, over 50% is on private lands, highlighting the need to engage owners of private land in conservation. There is greater potential for large, buffered, core conservation areas in the West, but other areas require networks of stepping-stone conservation islands. We summarize our results by ecoregions and within 40 national parks, identifying areas that are notably unthreatened (Colorado Plateau and Northwestern Glaciated Plains ecoregions and Great Basin and Canyonlands parks) versus those that may require more intense management actions (Eastern Great Lakes and Hudson Lowlands and Southeastern Wisconsin Till Plains ecoregions and Cuyahoga Valley and Great Smoky Mountains parks). Finally, we discuss how the approach could be applied and improved for finer-grained, local assessments. [Copyright &y& Elsevier]

Abstract: The mechanical modelling of semi-crystalline polymers is highly complex due to their different micro-structural scales and to some lacks regarding the understanding of the respective contributions of crystalline and amorphous phases on the macroscopic behaviour. In particular, the important role of the confined amorphous phase has to be investigated. To this aim, this work proposes to combine full-field simulations with kinematics field measurements at the same scale. The material is the linear low density polyethylene (LLDPE), chosen for its “simple” microstructure. Displacement fields at the micro-scale are measured by using the digital image correlation technique in the SEM. It is scheduled to apply the experimental strain as periodic boundary conditions to a unit cell whose morphological content will be built from the observed real microstructure and to analyse both the resulting macroscopic average response and local fields. To this aim, specific numerical tools are developed notably for statistical field analysis. The results on a simple stack model under various loading cases/paths are presented as a preliminary stage before the complete analysis for the LLDPE under tensile tests. The long term aim is to better understand the strain mechanisms in the confined amorphous phase, to determine its mechanical behaviour and conclude on its influence on the macroscopic behaviour. [Copyright &y& Elsevier]

Abstract: Automotive aluminum alloy sheet metal needs to improve the formability and the strength. In this study, the asymmetric rolling process was applied to the aluminum alloy sheet metal generation, because the {111}//ND texture, which corresponds to a part of the shear deformation texture, acts the high-formability. There are many processes of thermo-mechanical processes such as asymmetric and symmetric rollings and heat treatments in the sheet metal generation. We analyzed and optimized the microscopic texture evolution during plastic deformation in the macroscopic multi-stage warm rolling processes of the aluminum alloy sheet A6022 by using a crystallographic homogenized elasto/viscoplastic multi-scale finite element (FE) code and a discrete optimization method. In our multi-scale FE code, two scales ware considered. One is a microscopic polycrystal structure and the other is a macroscopic elastic plastic continuum. A three-dimensional representative volume element, which has initial crystal orientation distribution of the sheet metal is constructed by the electron back scattered diffraction measured pixel data. In order to evaluate the effect of temperature of warm rolling, a thermo-effect was introduced into the elastic/crystalline viscoplastic constitutive equation. Rolling parameters such as ratio of rolling speeds, rolling friction and the rolling temperature were optimized. We confirmed that Lankford value of the optimized sheet improved by 2-stage asymmetric rolling processes compared with commercial A6022-T43 sheet metal. [Copyright &y& Elsevier]

Three-scale homogenization procedure is proposed in this paper to provide estimates of the effective thermal conductivities of porous carbon-carbon textile composites. On each scale - the level of fiber tow (micro-scale), the level of yarns (meso-scale) and the level of laminate (macro-scale) - a two step homogenization procedure based on the Mori-Tanaka averaging scheme is adopted. This involves evaluation of the effective properties first in the absence of pores. In the next step, an ellipsoidal pore is introduced into a new, generally orthotropic, matrix to make provision for the presence of crimp voids and transverse and delamination cracks resulting from the thermal transformation of a polymeric precursor into the carbon matrix. Other sources of imperfections also attributed to the manufacturing processes, including non-uniform texture of the reinforcements, are taken into consideration through the histograms of inclination angles measured along the fiber tow path together with a particular shape of the equivalent ellipsoidal inclusion proposed already in Skoček (1998). The analysis shows that a reasonable agreement of the numerical predictions with experimental measurements can be achieved. [ABSTRACT FROM AUTHOR]

Abstract: Fire histories contribute important information to contemporary fire planning, however, our knowledge is not comprehensive geographically. We evaluated the influence of topography on fire history patterns in two contrasting landscapes within the Santa Catalina Mountains of southeastern Arizona. Multiple fire-scarred trees from randomly selected 2-ha plots were used to develop plot composite mean fire intervals (PCMFIs) within the Butterfly Peak (BP) and Rose Canyon (RC) landscapes. BP is dominated by steep, northerly aspects and presence of potential fire spread barriers (exposed rock bluffs and scree slopes). RC is dominated by more gentle and southerly aspects with relatively few fire barriers. Within each landscape, PCMFIs did not differ significantly between aspect classes from A.D. 1748 to 1910 (BP: p = 0.73 and RC: p = 0.57). Pooled PCMFIs in the gentler RC landscape were, however, significantly shorter (p <0.001) than in the steeper BP landscape. The frequency of relatively widespread fires (i.e., number of fire years when ≥2 plots scarred) was similar between landscapes, but fires in the gentler RC landscape were significantly larger (p = 0.033). The higher frequency of large fires (i.e., fires that burned >75% of the landscape) in RC resulted in more area burned over time and shorter fire intervals at individual plots. Conversely, smaller fires in the dissected BP landscape resulted in less area burned and longer periods between fires at individual plots. The different topographies in the two landscapes likely result in different wind intensities, fuel moistures, and fuel/vegetation types—and consequently, different historical fire spread patterns. Our conclusion is that fire history patterns are not influenced primarily by stand-scale topography, but rather by the topographic characteristics of the broader, surrounding landscape. [Copyright &y& Elsevier]

Mineral sites are scarce resources of high ion concentration used heavily by the Pacific Coast subpopulation of band-tailed pigeons. Over 20% of all known mineral sites used by band-tailed pigeons in western Oregon, including all hot springs, have been abandoned. Prior investigations have not analyzed stand or landscape level habitat composition in relation to band-tailed pigeon use of mineral sites. We used logistic regression models to evaluate the influence of habitat types, identified from Gap Analysis Program (GAP) products at two spatial scales, on the odds of mineral site use in Oregon (n = 69 currently used and 20 historically used). Our results indicated that the odds of current use were negatively associated with non-forested terrestrial and private land area around mineral sites. Similarly, the odds of current mineral site use were positively associated with forested and special status (GAP stewardship codes 1 and 2) land area. The most important variable associated with the odds of mineral site use was the amount of non-forested land cover at either spatial scale. Our results demonstrate the utility of meso-scale geographic information designed for regional, coarse-filter approaches to conservation in fine-filter investigation of wildlife-habitat relationships. Adjacent landcover and ownership status explain the pattern of use for known mineral sites in western Oregon. In order for conservation and management activities for band-tailed pigeons to be successful, mineral sites need to be addressed as important and vulnerable resources. Management of band-tailed pigeons should incorporate the potential for forest management activities and land ownership patterns to influence the risk of mineral site abandonment. [ABSTRACT FROM AUTHOR]

In the Thau lagoon, despite there being no phosphate limitation policy, the annual mean phosphate concentrations decreased by 90% between 1971 and 1994. The present study indicates a relationship between the decrease of phosphate concentrations and changes in urban, industrial and agricultural activities within the catchment generating phosphorus (P) inputs; and shellfish farming leading to phosphorus storage and export. The relationship (tonnes of P) is: P–PO43− in the lagoon waters=1.0124 anthropogenic phosphorus balance––47.62 (r2=0.824, p<0.000). As population growth is expected in coastal zones, sustainable development requires the need for addressing the role played by human activities and the multi-scale regulation of them. As an element of integrated coastal zone management, the present study provides a regional scale analysis of these aspects. [Copyright &y& Elsevier]