Collective Interaction in a Linear Array of Supersonic Rectangular Jets: A Linear Spatial Instability Study

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

1999-01-01

A linear spatial instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. It is assumed that in the region of interest a coherent wave can propagate. For the case studied large spatial growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech and edge tone feedback locked subsonic jets. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a coherent wave can propagate. The large spatial growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of spacial growth rates will be presented for a set of relative Mach numbers and spacings for which experimental measurements have been made. Calculations of spatial growth rates are presented for relative Mach numbers from 1.25 to 1.75 with ratios of nozzle spacing to nozzle width ratios from s/w(sub N) = 4 to s/w(sub N) = 13.7. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Temporal, spatial, and body size effects on growth rates of loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic

USGS Publications Warehouse

Bjorndal, Karen A.; Schroeder, Barbara A.; Foley, Allen M.; Witherington, Blair E.; Bresette, Michael; Clark, David; Herren, Richard M.; Arendt, Michael D.; Schmid, Jeffrey R.; Meylan, Anne B.; Meylan, Peter A.; Provancha, Jane A.; Hart, Kristen M.; Lamont, Margaret M.; Carthy, Raymond R.; Bolten, Alan B.

2013-01-01

In response to a call from the US National Research Council for research programs to combine their data to improve sea turtle population assessments, we analyzed somatic growth data for Northwest Atlantic (NWA) loggerhead sea turtles (Caretta caretta) from 10 research programs. We assessed growth dynamics over wide ranges of geography (9–33°N latitude), time (1978–2012), and body size (35.4–103.3 cm carapace length). Generalized additive models revealed significant spatial and temporal variation in growth rates and a significant decline in growth rates with increasing body size. Growth was more rapid in waters south of the USA (<24°N) than in USA waters. Growth dynamics in southern waters in the NWA need more study because sample size was small. Within USA waters, the significant spatial effect in growth rates of immature loggerheads did not exhibit a consistent latitudinal trend. Growth rates declined significantly from 1997 through 2007 and then leveled off or increased. During this same interval, annual nest counts in Florida declined by 43 % (Witherington et al. in Ecol Appl 19:30–54, 2009) before rebounding. Whether these simultaneous declines reflect responses in productivity to a common environmental change should be explored to determine whether somatic growth rates can help interpret population trends based on annual counts of nests or nesting females. Because of the significant spatial and temporal variation in growth rates, population models of NWA loggerheads should avoid employing growth data from restricted spatial or temporal coverage to calculate demographic metrics such as age at sexual maturity.

Growth Scenarios for the City of Guangzhou, China: Transferability and Confirmability

NASA Astrophysics Data System (ADS)

Lehner, A.; Kraus, V.; Wei, C.; Steinnocher, K.

2016-09-01

This work deals with the development of urban growth scenarios and the prevision of the spatial distribution of built-up area and population for the urban area of the city of Guangzhou in China. Using freely-available data, including remotely sensed data as well as census data from the ground, expenditure of time and costs shall remain low. Guangzhou, one of the biggest cities within the Pearl River Delta, has faced an enormous economic and urban growth during the last three decades. Due to its economical and spatial characteristics it is a promising candidate for urban growth scenarios. The monitoring and prediction of urban growth comprises data of population and give them a spatial representation. The model, originally applied for the Indian city Ahmedabad, is used for urban growth scenarios. Therefore, transferability and confirmability of the model are evaluated. Challenges that may occur by transferring a model for urban growth from one region to another are discussed. With proposing the use of urban remote sensing and freely available data, urban planners shall be fitted with a comprehensible and simple tool to be able to contribute to the future challenge Smart Growth.

Predicting the Spatial Distribution of Aspen Growth Potential in the Upper Great Lakes Region

Treesearch

Eric J. Gustafson; Sue M. Lietz; John L. Wright

2003-01-01

One way to increase aspen yields is to produce aspen on sites where aspen growth potential is highest. Aspen growth rates are typically predicted using site index, but this is impractical for landscape-level assessments. We tested the hypothesis that aspen growth can be predicted from site and climate variables and generated a model to map the spatial variability of...

Coupled stochastic spatial and non-spatial simulations of ErbB1 signaling pathways demonstrate the importance of spatial organization in signal transduction.

PubMed

Costa, Michelle N; Radhakrishnan, Krishnan; Wilson, Bridget S; Vlachos, Dionisios G; Edwards, Jeremy S

2009-07-23

The ErbB family of receptors activates intracellular signaling pathways that control cellular proliferation, growth, differentiation and apoptosis. Given these central roles, it is not surprising that overexpression of the ErbB receptors is often associated with carcinogenesis. Therefore, extensive laboratory studies have been devoted to understanding the signaling events associated with ErbB activation. Systems biology has contributed significantly to our current understanding of ErbB signaling networks. However, although computational models have grown in complexity over the years, little work has been done to consider the spatial-temporal dynamics of receptor interactions and to evaluate how spatial organization of membrane receptors influences signaling transduction. Herein, we explore the impact of spatial organization of the epidermal growth factor receptor (ErbB1/EGFR) on the initiation of downstream signaling. We describe the development of an algorithm that couples a spatial stochastic model of membrane receptors with a nonspatial stochastic model of the reactions and interactions in the cytosol. This novel algorithm provides a computationally efficient method to evaluate the effects of spatial heterogeneity on the coupling of receptors to cytosolic signaling partners. Mathematical models of signal transduction rarely consider the contributions of spatial organization due to high computational costs. A hybrid stochastic approach simplifies analyses of the spatio-temporal aspects of cell signaling and, as an example, demonstrates that receptor clustering contributes significantly to the efficiency of signal propagation from ligand-engaged growth factor receptors.

Spatial Econometric Research on the Relationship between Highway Construction and Regional Economic Growth in China: Evidence from the Nationwide Panel Data

NASA Astrophysics Data System (ADS)

Ye, N. J.; Li, W. J.; Li, Y.; Bai, Y. F.

2017-12-01

Based on spatial panel data from 2010 to 2016 in China, this paper makes an empirical analysis on the relationship between highway construction and regional economic growth by means of spatial econometric model. The results show that there is positive spatial correlation on regional economic growth in China, and strong spatial dependences between some provinces and cities appear, specifically, Hebei, Beijing, Tianjin, Shanghai, Zhejiang and other eastern coastal areas show high-high agglomeration trend, the Pearl River Delta region presents high-low agglomeration trend; In terms of nationwide provinces and municipalities, a province’s highway construction investment for their own province and the neighboring provinces has pulling effect on economic growth to a certain extent, and the direct effect is more obvious.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Revisiting the Stability of Spatially Heterogeneous Predator-Prey Systems Under Eutrophication.

PubMed

Farkas, J Z; Morozov, A Yu; Arashkevich, E G; Nikishina, A

2015-10-01

We employ partial integro-differential equations to model trophic interaction in a spatially extended heterogeneous environment. Compared to classical reaction-diffusion models, this framework allows us to more realistically describe the situation where movement of individuals occurs on a faster time scale than on the demographic (population) time scale, and we cannot determine population growth based on local density. However, most of the results reported so far for such systems have only been verified numerically and for a particular choice of model functions, which obviously casts doubts about these findings. In this paper, we analyse a class of integro-differential predator-prey models with a highly mobile predator in a heterogeneous environment, and we reveal the main factors stabilizing such systems. In particular, we explore an ecologically relevant case of interactions in a highly eutrophic environment, where the prey carrying capacity can be formally set to 'infinity'. We investigate two main scenarios: (1) the spatial gradient of the growth rate is due to abiotic factors only, and (2) the local growth rate depends on the global density distribution across the environment (e.g. due to non-local self-shading). For an arbitrary spatial gradient of the prey growth rate, we analytically investigate the possibility of the predator-prey equilibrium in such systems and we explore the conditions of stability of this equilibrium. In particular, we demonstrate that for a Holling type I (linear) functional response, the predator can stabilize the system at low prey density even for an 'unlimited' carrying capacity. We conclude that the interplay between spatial heterogeneity in the prey growth and fast displacement of the predator across the habitat works as an efficient stabilizing mechanism. These results highlight the generality of the stabilization mechanisms we find in spatially structured predator-prey ecological systems in a heterogeneous environment.

Built environment and Property Crime in Seattle, 1998-2000: A Bayesian Analysis.

PubMed

Matthews, Stephen A; Yang, Tse-Chuan; Hayslett-McCall, Karen L; Ruback, R Barry

2010-06-01

The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems (GIS), spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998-2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary.

Built environment and Property Crime in Seattle, 1998–2000: A Bayesian Analysis

PubMed Central

Matthews, Stephen A.; Yang, Tse-chuan; Hayslett-McCall, Karen L.; Ruback, R. Barry

2014-01-01

The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems (GIS), spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998–2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary. PMID:24737924

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Gender, space, and the location changes of jobs and people: a spatial simultaneous equations analysis.

PubMed

Hoogstra, Gerke J

2012-01-01

This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes autoregressive and cross-regressive spatial lags to detect relations both within and among these groups. Spatial weights matrices reflecting different bands of travel times are used to calculate the spatial lags and to gauge the spatial nature of these relations. The empirical results show that although population–employment interaction is more localized for women's employment, no gender difference exists in the direction of interaction. Employment growth for both men and women is more influenced by population growth than vice versa. The interaction within employment groups is even more important than population growth. Women's, and especially men's, local employment growth mostly benefits from the same employment growth in neighboring locations. Finally, interaction between these groups is practically absent, although men's employment growth may have a negative impact on women's employment growth within small geographic areas. In summary, the results confirm the crucial roles of gender and space, and offer important insights into possible relations within and among subgroups of jobs and people.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

An adjoint-based method for a linear mechanically-coupled tumor model: application to estimate the spatial variation of murine glioma growth based on diffusion weighted magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Feng, Xinzeng; Hormuth, David A.; Yankeelov, Thomas E.

2018-06-01

We present an efficient numerical method to quantify the spatial variation of glioma growth based on subject-specific medical images using a mechanically-coupled tumor model. The method is illustrated in a murine model of glioma in which we consider the tumor as a growing elastic mass that continuously deforms the surrounding healthy-appearing brain tissue. As an inverse parameter identification problem, we quantify the volumetric growth of glioma and the growth component of deformation by fitting the model predicted cell density to the cell density estimated using the diffusion-weighted magnetic resonance imaging data. Numerically, we developed an adjoint-based approach to solve the optimization problem. Results on a set of experimentally measured, in vivo rat glioma data indicate good agreement between the fitted and measured tumor area and suggest a wide variation of in-plane glioma growth with the growth-induced Jacobian ranging from 1.0 to 6.0.

Modelling spatial patterns of urban growth in Africa

PubMed Central

Linard, Catherine; Tatem, Andrew J.; Gilbert, Marius

2013-01-01

The population of Africa is predicted to double over the next 40 years, driving exceptionally high urban expansion rates that will induce significant socio-economic, environmental and health changes. In order to prepare for these changes, it is important to better understand urban growth dynamics in Africa and better predict the spatial pattern of rural-urban conversions. Previous work on urban expansion has been carried out at the city level or at the global level with a relatively coarse 5–10 km resolution. The main objective of the present paper was to develop a modelling approach at an intermediate scale in order to identify factors that influence spatial patterns of urban expansion in Africa. Boosted Regression Tree models were developed to predict the spatial pattern of rural-urban conversions in every large African city. Urban change data between circa 1990 and circa 2000 available for 20 large cities across Africa were used as training data. Results showed that the urban land in a 1 km neighbourhood and the accessibility to the city centre were the most influential variables. Results obtained were generally more accurate than results obtained using a distance-based urban expansion model and showed that the spatial pattern of small, compact and fast growing cities were easier to simulate than cities with lower population densities and a lower growth rate. The simulation method developed here will allow the production of spatially detailed urban expansion forecasts for 2020 and 2025 for Africa, data that are increasingly required by global change modellers. PMID:25152552

Spatial optimization of prairie dog colonies for black-footed ferret recovery

Treesearch

Michael Bevers; John G. Hof; Daniel W. Uresk; Gregory L. Schenbeck

1997-01-01

A discrete-time reaction-diffusion model for black-footed ferret release, population growth, and dispersal is combined with ferret carrying capacity constraints based on prairie dog population management decisions to form a spatial optimization model. Spatial arrangement of active prairie dog colonies within a ferret reintroduction area is optimized over time for...

Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

PubMed Central

Luo, Xinchao; Zhu, Lixing; Kong, Linglong; Zhu, Hongtu

2015-01-01

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FN-MEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders. PMID:26213453

Does spatial variation in environmental conditions affect recruitment? A study using a 3-D model of Peruvian anchovy

NASA Astrophysics Data System (ADS)

Xu, Yi; Rose, Kenneth A.; Chai, Fei; Chavez, Francisco P.; Ayón, Patricia

2015-11-01

We used a 3-dimensional individual-based model (3-D IBM) of Peruvian anchovy to examine how spatial variation in environmental conditions affects larval and juvenile growth and survival, and recruitment. Temperature, velocity, and phytoplankton and zooplankton concentrations generated from a coupled hydrodynamic Nutrients-Phytoplankton-Zooplankton-Detritus (NPZD) model, mapped to a three dimensional rectangular grid, were used to simulate anchovy populations. The IBM simulated individuals as they progressed from eggs to recruitment at 10 cm. Eggs and yolk-sac larvae were followed hourly through the processes of development, mortality, and movement (advection), and larvae and juveniles were followed daily through the processes of growth, mortality, and movement (advection plus behavior). A bioenergetics model was used to grow larvae and juveniles. The NPZD model provided prey fields which influence both food consumption rate as well as behavior mediated movement with individuals going to grids cells having optimal growth conditions. We compared predicted recruitment for monthly cohorts for 1990 through 2004 between the full 3-D IBM and a point (0-D) model that used spatially-averaged environmental conditions. The 3-D and 0-D versions generated similar interannual patterns in monthly recruitment for 1991-2004, with the 3-D results yielding consistently higher survivorship. Both versions successfully captured the very poor recruitment during the 1997-1998 El Niño event. Higher recruitment in the 3-D simulations was due to higher survival during the larval stage resulting from individuals searching for more favorable temperatures that lead to faster growth rates. The strong effect of temperature was because both model versions provided saturating food conditions for larval and juvenile anchovies. We conclude with a discussion of how explicit treatment of spatial variation affected simulated recruitment, other examples of fisheries modeling analyses that have used a similar approach to assess the influence of spatial variation, and areas for further model development.

Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature

NASA Technical Reports Server (NTRS)

Sun, Guoqing; Liu, Dawei; Ranson, K. Jon; Koetz, Benjamin

2007-01-01

The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.

Life-History and Spatial Determinants of Somatic Growth Dynamics in Komodo Dragon Populations

PubMed Central

Laver, Rebecca J.; Purwandana, Deni; Ariefiandy, Achmad; Imansyah, Jeri; Forsyth, David; Ciofi, Claudio; Jessop, Tim S.

2012-01-01

Somatic growth patterns represent a major component of organismal fitness and may vary among sexes and populations due to genetic and environmental processes leading to profound differences in life-history and demography. This study considered the ontogenic, sex-specific and spatial dynamics of somatic growth patterns in ten populations of the world’s largest lizard the Komodo dragon (Varanus komodoensis). The growth of 400 individual Komodo dragons was measured in a capture-mark-recapture study at ten sites on four islands in eastern Indonesia, from 2002 to 2010. Generalized Additive Mixed Models (GAMMs) and information-theoretic methods were used to examine how growth rates varied with size, age and sex, and across and within islands in relation to site-specific prey availability, lizard population density and inbreeding coefficients. Growth trajectories differed significantly with size and between sexes, indicating different energy allocation tactics and overall costs associated with reproduction. This leads to disparities in maximum body sizes and longevity. Spatial variation in growth was strongly supported by a curvilinear density-dependent growth model with highest growth rates occurring at intermediate population densities. Sex-specific trade-offs in growth underpin key differences in Komodo dragon life-history including evidence for high costs of reproduction in females. Further, inverse density-dependent growth may have profound effects on individual and population level processes that influence the demography of this species. PMID:23028983

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs, with emphasis on Halimeda tuna

USGS Publications Warehouse

Yniguez, A.T.; McManus, J.W.; DeAngelis, D.L.

2008-01-01

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an 'individual' being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns. ?? 2008 Elsevier B.V.

AN INDIVIDUAL-BASED SIMULATION MODEL FOR MOTTLED SCULPIN (COTTUS BAIRDI) IN A SOUTHERN APPALACHIAN STREAM

EPA Science Inventory

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was bas...

Transition index maps for urban growth simulation: application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation.

PubMed

Shafizadeh-Moghadam, Hossein; Tayyebi, Amin; Helbich, Marco

2017-06-01

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.

Modeling Global Spatial-Temporal Evolution of Society: Hyperbolic Growth and Historical Cycles

NASA Astrophysics Data System (ADS)

Kurkina, E. S.

2011-09-01

The global historical processes are under consideration; and laws of global evolution of the world community are studied. The world community is considered as a united complex self-developing and self-organizing system. It supposed that the main driving force of social-economical evolution was the positive feedback between the population size and the level of technological development, which was a cause of growth in blow-up regime both of population and of global economic indexes. The study is supported by the results of mathematical modeling founded on a nonlinear heat equation with a source. Every social-economical epoch characterizes by own specific spatial distributed structures. So the global dynamics of world community during the whole history is investigated throughout the prism of the developing of spatial-temporal structures. The model parameters have been chosen so that 1) total population follows stable hyperbolic growth, consistently with the demographic data; 2) the evolution of the World-System goes through 11 stages corresponding to the main historical epochs.

Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Dutta, Subashisa

2016-12-01

Chlorophyll and nitrogen are the most essential parameters for paddy crop growth. Spectroradiometric measurements were collected at canopy level during critical growth period of rice. Chemical analysis was performed to quantify the total leaf content. By exploiting the ground based measurements, regression models were established for chlorophyll and nitrogen aimed indices with their corresponding crop growth variables. Vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the present Simple Ratio (SR) and Leaf Nitrogen Concentration (LNC) indices, which followed a linear and nonlinear relationship respectively, were completely different from published Tian et al. (2011). The nitrogen content varied widely from 1 to 4% and only 2 to 3% for paddy crop using present modified index models and Tian et al. (2011) respectively. The modified LNC index model performed better than the established Tian et al. (2011) model as far as estimated nitrogen content from Hyperion imagery was concerned. Furthermore, within the observed chlorophyll range obtained from the studied rice varieties grown in the rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) performed well in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content varied widely from 1.77 to 5.81 mg/g (LNC), 3.0 to 13 mg/g (OASVI), 0.5 to 10.43 mg/g (Gitelson), 2.18 to 10.61 mg/g (mSR) and 2.90 to 5.40 mg/g (MTCI). The spatial information of these parameters will help in proper nutrient management, yield forecasting, and will serve as inputs for crop growth and forecasting models for a precision rice agriculture system.

Monte Carlo grain growth modeling with local temperature gradients

NASA Astrophysics Data System (ADS)

Tan, Y.; Maniatty, A. M.; Zheng, C.; Wen, J. T.

2017-09-01

This work investigated the development of a Monte Carlo (MC) simulation approach to modeling grain growth in the presence of non-uniform temperature field that may vary with time. We first scale the MC model to physical growth processes by fitting experimental data. Based on the scaling relationship, we derive a grid site selection probability (SSP) function to consider the effect of a spatially varying temperature field. The SSP function is based on the differential MC step, which allows it to naturally consider time varying temperature fields too. We verify the model and compare the predictions to other existing formulations (Godfrey and Martin 1995 Phil. Mag. A 72 737-49 Radhakrishnan and Zacharia 1995 Metall. Mater. Trans. A 26 2123-30) in simple two-dimensional cases with only spatially varying temperature fields, where the predicted grain growth in regions of constant temperature are expected to be the same as for the isothermal case. We also test the model in a more realistic three-dimensional case with a temperature field varying in both space and time, modeling grain growth in the heat affected zone of a weld. We believe the newly proposed approach is promising for modeling grain growth in material manufacturing processes that involves time-dependent local temperature gradient.

A one-dimensional sectional model to simulate multicomponent aerosol dynamics in the marine boundary layer 3. Numerical methods and comparisons with exact solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gelbard, F.; Fitzgerald, J.W.; Hoppel, W.A.

1998-07-01

We present the theoretical framework and computational methods that were used by {ital Fitzgerald} {ital et al.} [this issue (a), (b)] describing a one-dimensional sectional model to simulate multicomponent aerosol dynamics in the marine boundary layer. The concepts and limitations of modeling spatially varying multicomponent aerosols are elucidated. New numerical sectional techniques are presented for simulating multicomponent aerosol growth, settling, and eddy transport, coupled to time-dependent and spatially varying condensing vapor concentrations. Comparisons are presented with new exact solutions for settling and particle growth by simultaneous dynamic condensation of one vapor and by instantaneous equilibration with a spatially varying secondmore » vapor. {copyright} 1998 American Geophysical Union« less

Spatial and temporal features of the growth of a bacterial species colonizing the zebrafish gut.

PubMed

Jemielita, Matthew; Taormina, Michael J; Burns, Adam R; Hampton, Jennifer S; Rolig, Annah S; Guillemin, Karen; Parthasarathy, Raghuveer

2014-12-16

The vertebrate intestine is home to microbial ecosystems that play key roles in host development and health. Little is known about the spatial and temporal dynamics of these microbial communities, limiting our understanding of fundamental properties, such as their mechanisms of growth, propagation, and persistence. To address this, we inoculated initially germ-free zebrafish larvae with fluorescently labeled strains of an Aeromonas species, representing an abundant genus in the zebrafish gut. Using light sheet fluorescence microscopy to obtain three-dimensional images spanning the gut, we quantified the entire bacterial load, as founding populations grew from tens to tens of thousands of cells over several hours. The data yield the first ever measurements of the growth kinetics of a microbial species inside a live vertebrate intestine and show dynamics that robustly fit a logistic growth model. Intriguingly, bacteria were nonuniformly distributed throughout the gut, and bacterial aggregates showed considerably higher growth rates than did discrete individuals. The form of aggregate growth indicates intrinsically higher division rates for clustered bacteria, rather than surface-mediated agglomeration onto clusters. Thus, the spatial organization of gut bacteria both relative to the host and to each other impacts overall growth kinetics, suggesting that spatial characterizations will be an important input to predictive models of host-associated microbial community assembly. Our intestines are home to vast numbers of microbes that influence many aspects of health and disease. Though we now know a great deal about the constituents of the gut microbiota, we understand very little about their spatial structure and temporal dynamics in humans or in any animal: how microbial populations establish themselves, grow, fluctuate, and persist. To address this, we made use of a model organism, the zebrafish, and a new optical imaging technique, light sheet fluorescence microscopy, to visualize for the first time the colonization of a live, vertebrate gut by specific bacteria with sufficient resolution to quantify the population over a range from a few individuals to tens of thousands of bacterial cells. Our results provide unprecedented measures of bacterial growth kinetics and also show the influence of spatial structure on bacterial populations, which can be revealed only by direct imaging. Copyright © 2014 Jemielita et al.

Modeling Alaska boreal forests with a controlled trend surface approach

Treesearch

Mo Zhou; Jingjing Liang

2012-01-01

An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

Class of self-limiting growth models in the presence of nonlinear diffusion

NASA Astrophysics Data System (ADS)

Kar, Sandip; Banik, Suman Kumar; Ray, Deb Shankar

2002-06-01

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand, are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.

How to use the Stand-Damage Model: Version 2.0. (Computer program)

Treesearch

J.J. Colbert; George Racin

2001-01-01

The Stand-Damage Model simulates the growth of a forest stand, a spatially homogeneous collection of trees growing on a site. The model simulates growth from an initial inventory, user-prescribed management practices, and the effects of gypsy moth defoliation. Here we provide installation and operating instructions for Version 2.0.

Void Growth and Coalescence Simulations

DTIC Science & Technology

2013-08-01

distortion and damage, minimum time step, and appropriate material model parameters. Further, a temporal and spatial convergence study was used to...estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we use a Gurson model with Johnson-Cook...spatial convergence study was used to estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we

Modeling a beaver population on the Prescott Peninsula, Massachusetts: Feasibility of LANDSAT as an input

NASA Technical Reports Server (NTRS)

Finn, J. T.; Howard, R.

1981-01-01

A preliminary dynamic model of beaver spatial distribution and population growth was developed. The feasibility of locating beaver ponds on LANDSAT digital tapes, and of using this information to provide initial conditions of beaver spatial distribution for the model, and to validate model predictions is discussed. The techniques used to identify beaver ponds on LANDSAT are described.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

NASA Astrophysics Data System (ADS)

Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

2011-11-01

In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

Mapping the Spread of Methamphetamine Abuse in California From 1995 to 2008

PubMed Central

Ponicki, William R.; Remer, Lillian G.; Waller, Lance A.; Zhu, Li; Gorman, Dennis M.

2013-01-01

Objectives. From 1983 to 2008, the incidence of methamphetamine abuse and dependence (MA) presenting at hospitals in California increased 13-fold. We assessed whether this growth could be characterized as a drug epidemic. Methods. We geocoded MA discharges to residential zip codes from 1995 through 2008. We related discharges to population and environmental characteristics using Bayesian Poisson conditional autoregressive models, correcting for small area effects and spatial misalignment and enabling an assessment of contagion between areas. Results. MA incidence increased exponentially in 3 phases interrupted by implementation of laws limiting access to methamphetamine precursors. MA growth from 1999 through 2008 was 17% per year. MA was greatest in areas with larger White or Hispanic low-income populations, small household sizes, and good connections to highway systems. Spatial misalignment was a source of bias in estimated effects. Spatial autocorrelation was substantial, accounting for approximately 80% of error variance in the model. Conclusions. From 1995 through 2008, MA exhibited signs of growth and spatial spread characteristic of drug epidemics, spreading most rapidly through low-income White and Hispanic populations living outside dense urban areas. PMID:23078474

Spatial match-mismatch between juvenile fish and prey provides a mechanism for recruitment variability across contrasting climate conditions in the eastern Bering Sea.

PubMed

Siddon, Elizabeth Calvert; Kristiansen, Trond; Mueter, Franz J; Holsman, Kirstin K; Heintz, Ron A; Farley, Edward V

2013-01-01

Understanding mechanisms behind variability in early life survival of marine fishes through modeling efforts can improve predictive capabilities for recruitment success under changing climate conditions. Walleye pollock (Theragra chalcogramma) support the largest single-species commercial fishery in the United States and represent an ecologically important component of the Bering Sea ecosystem. Variability in walleye pollock growth and survival is structured in part by climate-driven bottom-up control of zooplankton composition. We used two modeling approaches, informed by observations, to understand the roles of prey quality, prey composition, and water temperature on juvenile walleye pollock growth: (1) a bioenergetics model that included local predator and prey energy densities, and (2) an individual-based model that included a mechanistic feeding component dependent on larval development and behavior, local prey densities and size, and physical oceanographic conditions. Prey composition in late-summer shifted from predominantly smaller copepod species in the warmer 2005 season to larger species in the cooler 2010 season, reflecting differences in zooplankton composition between years. In 2010, the main prey of juvenile walleye pollock were more abundant, had greater biomass, and higher mean energy density, resulting in better growth conditions. Moreover, spatial patterns in prey composition and water temperature lead to areas of enhanced growth, or growth 'hot spots', for juvenile walleye pollock and survival may be enhanced when fish overlap with these areas. This study provides evidence that a spatial mismatch between juvenile walleye pollock and growth 'hot spots' in 2005 contributed to poor recruitment while a higher degree of overlap in 2010 resulted in improved recruitment. Our results indicate that climate-driven changes in prey quality and composition can impact growth of juvenile walleye pollock, potentially severely affecting recruitment variability.

An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

Treesearch

Brenda Rashleigh; Gary D. Grossman

2005-01-01

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...

Modeling urban growth by the use of a multiobjective optimization approach: environmental and economic issues for the Yangtze watershed, China.

PubMed

Zhang, Wenting; Wang, Haijun; Han, Fengxiang; Gao, Juan; Nguyen, Thuminh; Chen, Yarong; Huang, Bo; Zhan, F Benjamin; Zhou, Lequn; Hong, Song

2014-11-01

Urban growth is an unavoidable process caused by economic development and population growth. Traditional urban growth models represent the future urban growth pattern by repeating the historical urban growth regulations, which can lead to a lot of environmental problems. The Yangtze watershed is the largest and the most prosperous economic area in China, and it has been suffering from rapid urban growth from the 1970s. With the built-up area increasing from 23,238 to 31,054 km(2) during the period from 1980 to 2005, the watershed has suffered from serious nonpoint source (NPS) pollution problems, which have been mainly caused by the rapid urban growth. To protect the environment and at the same time maintain the economic development, a multiobjective optimization (MOP) is proposed to tradeoff the multiple objectives during the urban growth process of the Yangtze watershed. In particular, the four objectives of minimization of NPS pollution, maximization of GDP value, minimization of the spatial incompatibility between the land uses, and minimization of the cost of land-use change are considered by the MOP approach. Conventionally, a genetic algorithm (GA) is employed to search the Pareto solution set. In our MOP approach, a two-dimensional GA, rather than the traditional one-dimensional GA, is employed to assist with the search for the spatial optimization solution, where the land-use cells in the two-dimensional space act as genes in the GA. Furthermore, to confirm the superiority of the MOP approach over the traditional prediction approaches, a widely used urban growth prediction model, cellular automata (CA), is also carried out to allow a comparison with the Pareto solution of MOP. The results indicate that the MOP approach can make a tradeoff between the multiple objectives and can achieve an optimal urban growth pattern for Yangtze watershed, while the CA prediction model just represents the historical urban growth pattern as the future growth pattern. Moreover, according to the spatial clustering index, the urban growth pattern predicted through MOP is more reasonable. In summary, the proposed model provides a set of Pareto urban growth solutions, which compromise environmental and economic issues for the Yangtze watershed.

An exactly solvable, spatial model of mutation accumulation in cancer

NASA Astrophysics Data System (ADS)

Paterson, Chay; Nowak, Martin A.; Waclaw, Bartlomiej

2016-12-01

One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours, even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model.

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

DOE PAGES

Vekselman, V.; Khrabry, A.; Kaganovich, I.; ...

2018-02-06

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vekselman, V.; Khrabry, A.; Kaganovich, I.

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Examples of Level Products Possible from Existing Assets

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

2012-01-01

How do patterns of human environmental and infectious diseases respond to leading environmental changes, particularly to urban growth and change and the associated impacts of urbanization? We use HyspIRI high spatial resolution, multispectral, and multitemporal TIR data to track energy balance and energy flux characteristics for changing land covers/land uses through time to provide synoptic views of impacts on surface energy fluxes, emissivity and temperature and HyspIRI data in conjunction with spatial growth models to project land cover/land use changes in the future to assess impacts on natural and human ecosystems. We use multispectral thermal IR land cover maps at a high spatial resolution (60m) on a weekly basis for long-term validation of surface energy responses and changes in emissivity and integration of HyspIRI TIR data with spatial modeling to assess changes in land cover/land use through time and subsequent changes in thermal energy responses

Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost

NASA Astrophysics Data System (ADS)

Juchem Neto, J. P.; Claeyssen, J. C. R.; Pôrto Júnior, S. S.

2018-03-01

In this paper we introduce capital transport cost in a unidimensional spatial Solow-Swan model of economic growth with capital-induced labor migration, considered in an unbounded domain. Proceeding with a stability analysis, we show that there is a critical value for the capital transport cost where the dynamic behavior of the economy changes, provided that the intensity of capital-induced labor migration is strong enough. On the one hand, if the capital transport cost is higher than this critical value, the spatially homogeneous equilibrium of coexistence of the model is stable, and the economy converges to this spatially homogeneous state in the long run; on the other hand, if transport cost is lower than this critical value, the equilibrium is unstable, and the economy may develop different spatio-temporal dynamics, including the formation of stable economic agglomerations and spatio-temporal economic cycles, depending on the other parameters in the model. Finally, numerical simulations support the results of the stability analysis, and illustrate the spatio-temporal dynamics generated by the model, suggesting that the economy as a whole benefits from the formation of economic agglomerations and cycles, with a higher capital transport cost reducing this gain.

Single Plant Root System Modeling under Soil Moisture Variation

NASA Astrophysics Data System (ADS)

Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.

2016-12-01

A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.

The Geographic Concentration of Enterprise in Developing Countries

PubMed Central

Felkner, John S.; Townsend, Robert M.

2011-01-01

A nation’s economic geography can have an enormous impact on its development. In Thailand, we show that a high concentration of enterprise in an area predicts high subsequent growth in and around that area. We also find spatially contiguous convergence of enterprise with stagnant areas left behind. Exogenous physiographic conditions are correlated with enterprise location and growth. We fit a structural, micro-founded model of occupation transitions with fine-tuned geographic capabilities to village data and replicate these salient facts. Key elements of the model include costs, credit constraints on occupation choice, and spatially varying expansion of financial service providers. PMID:22844158

Verbal and visual-spatial working memory and mathematical ability in different domains throughout primary school.

PubMed

Van de Weijer-Bergsma, Eva; Kroesbergen, Evelyn H; Van Luit, Johannes E H

2015-04-01

The relative importance of visual-spatial and verbal working memory for mathematics performance and learning seems to vary with age, the novelty of the material, and the specific math domain that is investigated. In this study, the relations between verbal and visual-spatial working memory and performance in four math domains (i.e., addition, subtraction, multiplication, and division) at different ages during primary school are investigated. Children (N = 4337) from grades 2 through 6 participated. Visual-spatial and verbal working memory were assessed using online computerized tasks. Math performance was assessed at the start, middle, and end of the school year using a speeded arithmetic test. Multilevel Multigroup Latent Growth Modeling was used to model individual differences in level and growth in math performance, and examine the predictive value of working memory per grade, while controlling for effects of classroom membership. The results showed that as grade level progressed, the predictive value of visual-spatial working memory for individual differences in level of mathematics performance waned, while the predictive value of verbal working memory increased. Working memory did not predict individual differences between children in their rate of performance growth throughout the school year. These findings are discussed in relation to three, not mutually exclusive, explanations for such age-related findings.

Using a GIS-based spot growth model and visual simulator to evaluate the effects of silvicultural treatments on southern pine beetle-infested stands

Treesearch

Chiao-Ying Chou; Roy L. Hedden; Bo Song; Thomas M. Williams

2013-01-01

Many models are available for simulating the probability of southern pine beetle (Dendroctonus frontalis Zimmermann) (SPB) infestation and outbreak dynamics. However, only a few models focused on the potential spatial SPB growth. Although the integrated pest management systems are currently adopted, SPB management is still challenging because of...

Urban change analysis and future growth of Istanbul.

PubMed

Akın, Anıl; Sunar, Filiz; Berberoğlu, Süha

2015-08-01

This study is aimed at analyzing urban change within Istanbul and assessing the city's future growth potential using appropriate approach modeling for the year 2040. Urban growth is a major driving force of land-use change, and spatial and temporal components of urbanization can be identified through accurate spatial modeling. In this context, widely used urban modeling approaches, such as the Markov chain and logistic regression based on cellular automata (CA), were used to simulate urban growth within Istanbul. The distance from each pixel to the urban and road classes, elevation, and slope, together with municipality and land use maps (as an excluded layer), were identified as factors. Calibration data were obtained from remotely sensed data recorded in 1972, 1986, and 2013. Validation was performed by overlaying the simulated and actual 2013 urban maps, and a kappa index of agreement was derived. The results indicate that urban expansion will influence mainly forest areas during the time period of 2013-2040. The urban expansion was predicted as 429 and 327 km(2) with the Markov chain and logistic regression models, respectively.

Selective sweeps in growing microbial colonies

NASA Astrophysics Data System (ADS)

Korolev, Kirill S.; Müller, Melanie J. I.; Karahan, Nilay; Murray, Andrew W.; Hallatschek, Oskar; Nelson, David R.

2012-04-01

Evolutionary experiments with microbes are a powerful tool to study mutations and natural selection. These experiments, however, are often limited to the well-mixed environments of a test tube or a chemostat. Since spatial organization can significantly affect evolutionary dynamics, the need is growing for evolutionary experiments in spatially structured environments. The surface of a Petri dish provides such an environment, but a more detailed understanding of microbial growth on Petri dishes is necessary to interpret such experiments. We formulate a simple deterministic reaction-diffusion model, which successfully predicts the spatial patterns created by two competing species during colony expansion. We also derive the shape of these patterns analytically without relying on microscopic details of the model. In particular, we find that the relative fitness of two microbial strains can be estimated from the logarithmic spirals created by selective sweeps. The theory is tested with strains of the budding yeast Saccharomyces cerevisiae for spatial competitions with different initial conditions and for a range of relative fitnesses. The reaction-diffusion model also connects the microscopic parameters like growth rates and diffusion constants with macroscopic spatial patterns and predicts the relationship between fitness in liquid cultures and on Petri dishes, which we confirmed experimentally. Spatial sector patterns therefore provide an alternative fitness assay to the commonly used liquid culture fitness assays.

Irruptive dynamics of introduced caribou on Adak Island, Alaska: an evaluation of Riney-Caughley model predictions

USGS Publications Warehouse

Ricca, Mark A.; Van Vuren, Dirk H.; Weckerly, Floyd W.; Williams, Jeffrey C.; Miles, A. Keith

2014-01-01

Large mammalian herbivores introduced to islands without predators are predicted to undergo irruptive population and spatial dynamics, but only a few well-documented case studies support this paradigm. We used the Riney-Caughley model as a framework to test predictions of irruptive population growth and spatial expansion of caribou (Rangifer tarandus granti) introduced to Adak Island in the Aleutian archipelago of Alaska in 1958 and 1959. We utilized a time series of spatially explicit counts conducted on this population intermittently over a 54-year period. Population size increased from 23 released animals to approximately 2900 animals in 2012. Population dynamics were characterized by two distinct periods of irruptive growth separated by a long time period of relative stability, and the catalyst for the initial irruption was more likely related to annual variation in hunting pressure than weather conditions. An unexpected pattern resembling logistic population growth occurred between the peak of the second irruption in 2005 and the next survey conducted seven years later in 2012. Model simulations indicated that an increase in reported harvest alone could not explain the deceleration in population growth, yet high levels of unreported harvest combined with increasing density-dependent feedbacks on fecundity and survival were the most plausible explanation for the observed population trend. No studies of introduced island Rangifer have measured a time series of spatial use to the extent described in this study. Spatial use patterns during the post-calving season strongly supported Riney-Caughley model predictions, whereby high-density core areas expanded outwardly as population size increased. During the calving season, caribou displayed marked site fidelity across the full range of population densities despite availability of other suitable habitats for calving. Finally, dispersal and reproduction on neighboring Kagalaska Island represented a new dispersal front for irruptive dynamics and a new challenge for resource managers. The future demography of caribou on both islands is far from certain, yet sustained and significant hunting pressure should be a vital management tool.

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

An immersed boundary-lattice Boltzmann model for biofilm growth and its impact on the NAPL dissolution in porous media

NASA Astrophysics Data System (ADS)

Benioug, M.; Yang, X.

2017-12-01

The evolution of microbial phase within porous medium is a complex process that involves growth, mortality, and detachment of the biofilm or attachment of moving cells. A better understanding of the interactions among biofilm growth, flow and solute transport and a rigorous modeling of such processes are essential for a more accurate prediction of the fate of pollutants (e.g. NAPLs) in soils. However, very few works are focused on the study of such processes in multiphase conditions (oil/water/biofilm systems). Our proposed numerical model takes into account the mechanisms that control bacterial growth and its impact on the dissolution of NAPL. An Immersed Boundary - Lattice Boltzmann Model (IB-LBM) is developed for flow simulations along with non-boundary conforming finite volume methods (volume of fluid and reconstruction methods) used for reactive solute transport. A sophisticated cellular automaton model is also developed to describe the spatial distribution of bacteria. A series of numerical simulations have been performed on complex porous media. A quantitative diagram representing the transitions between the different biofilm growth patterns is proposed. The bioenhanced dissolution of NAPL in the presence of biofilms is simulated at the pore scale. A uniform dissolution approach has been adopted to describe the temporal evolution of trapped blobs. Our simulations focus on the dissolution of NAPL in abiotic and biotic conditions. In abiotic conditions, we analyze the effect of the spatial distribution of NAPL blobs on the dissolution rate under different assumptions (blobs size, Péclet number). In biotic conditions, different conditions are also considered (spatial distribution, reaction kinetics, toxicity) and analyzed. The simulated results are consistent with those obtained from the literature.

Spatial and directional variation of growth rates in Arabidopsis root apex: a modelling study.

PubMed

Nakielski, Jerzy; Lipowczan, Marcin

2013-01-01

Growth and cellular organization of the Arabidopsis root apex are investigated in various aspects, but still little is known about spatial and directional variation of growth rates in very apical part of the apex, especially in 3D. The present paper aims to fill this gap with the aid of a computer modelling based on the growth tensor method. The root apex with a typical shape and cellular pattern is considered. Previously, on the basis of two types of empirical data: the published velocity profile along the root axis and dimensions of cell packets formed in the lateral part of the root cap, the displacement velocity field for the root apex was determined. Here this field is adopted to calculate the linear growth rate in different points and directions. The results are interpreted taking principal growth directions into account. The root apex manifests a significant anisotropy of the linear growth rate. The directional preferences depend on a position within the root apex. In the root proper the rate in the periclinal direction predominates everywhere, while in the root cap the predominating direction varies with distance from the quiescent centre. The rhizodermis is distinguished from the neighbouring tissues (cortex, root cap) by relatively high contribution of the growth rate in the anticlinal direction. The degree of growth anisotropy calculated for planes defined by principal growth directions and exemplary cell walls may be as high as 25. The changes in the growth rate variation are modelled.

Landscape scale measures of steelhead (Oncorhynchus mykiss) bioenergetic growth rate potential in Lake Michigan and comparison with angler catch rates

USGS Publications Warehouse

Hook, T.O.; Rutherford, E.S.; Brines, Shannon J.; Geddes, C.A.; Mason, D.M.; Schwab, D.J.; Fleischer, G.W.

2004-01-01

The relative quality of a habitat can influence fish consumption, growth, mortality, and production. In order to quantify habitat quality, several authors have combined bioenergetic and foraging models to generate spatially explicit estimates of fish growth rate potential (GRP). However, the capacity of GRP to reflect the spatial distributions of fishes over large areas has not been fully evaluated. We generated landscape scale estimates of steelhead (Oncorhynchus mykiss) GRP throughout Lake Michigan for 1994-1996, and used these estimates to test the hypotheses that GRP is a good predictor of spatial patterns of steelhead catch rates. We used surface temperatures (measured with AVHRR satellite imagery) and acoustically measured steelhead prey densities (alewife, Alosa pseudoharengus) as inputs for the GRP model. Our analyses demonstrate that potential steelhead growth rates in Lake Michigan are highly variable in both space and time. Steelhead GRP tended to increase with latitude, and mean GRP was much higher during September 1995, compared to 1994 and 1996. In addition, our study suggests that landscape scale measures of GRP are not good predictors of steelhead catch rates throughout Lake Michigan, but may provide an index of interannual variation in system-wide habitat quality.

Hierarchical stochastic modeling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.; Dey, Rima

2017-01-01

We present a hierarchical series of spatially decreasing and temporally increasing models to evaluate the uncertainty in the atmosphere – ocean global climate model (AOGCM) and the regional climate model (RCM) relative to the uncertainty in the somatic growth of the endangered pallid sturgeon (Scaphirhynchus albus). For effects on fish populations of riverine ecosystems, cli- mate output simulated by coarse-resolution AOGCMs and RCMs must be downscaled to basins to river hydrology to population response. One needs to transfer the information from these climate simulations down to the individual scale in a way that minimizes extrapolation and can account for spatio-temporal variability in the intervening stages. The goal is a framework to determine whether, given uncertainties in the climate models and the biological response, meaningful inference can still be made. The non-linear downscaling of climate information to the river scale requires that one realistically account for spatial and temporal variability across scale. Our down- scaling procedure includes the use of fixed/calibrated hydrological flow and temperature models coupled with a stochastically parameterized sturgeon bioenergetics model. We show that, although there is a large amount of uncertainty associated with both the climate model output and the fish growth process, one can establish significant differences in fish growth distributions between models, and between future and current climates for a given model.

Collective Interaction of a Compressible Periodic Parallel Jet Flow

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

1997-01-01

A linear instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. The disturbance environment is investigated using a two dimensional perturbation of a mean flow. For all cases large temporal growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a disturbance can propagate. The large temporal growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of growth rates are presented for a range of Mach numbers and nozzle spacings corresponding to experimental test conditions where screech synchronized phase locking was observed. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Dissecting a new connection between cytokinin and jasmonic acid in control of leaf growth

USDA-ARS?s Scientific Manuscript database

Plant growth is mediated by two cellular processes: division and elongation. The maize leaf is an excellent model to study plant growth since these processes are spatially separated into discreet zones - a division zone (DZ), transition zone (TZ), and elongation zone (EZ) - at the base of the leaf. ...

Cell motility and ECM proteolysis regulate tumor growth and tumor relapse by altering the fraction of cancer stem cells and their spatial scattering

NASA Astrophysics Data System (ADS)

Kumar, Sandeep; Kulkarni, Rahul; Sen, Shamik

2016-06-01

Tumors consist of multiple cell sub-populations including cancer stem cells (CSCs), transiently amplifying cells and terminally differentiated cells (TDCs), with the CSC fraction dictating the aggressiveness of the tumor and drug sensitivity. In epithelial cancers, tumor growth is influenced greatly by properties of the extracellular matrix (ECM), with cancer progression associated with an increase in ECM density. However, the extent to which increased ECM confinement induced by an increase in ECM density influences tumor growth and post treatment relapse dynamics remains incompletely understood. In this study, we use a cellular automata-based discrete modeling approach to study the collective influence of ECM density, cell motility and ECM proteolysis on tumor growth, tumor heterogeneity, and tumor relapse after drug treatment. We show that while increased confinement suppresses tumor growth and the spatial scattering of CSCs, this effect can be reversed when cells become more motile and proteolytically active. Our results further suggest that, in addition to the absolute number of CSCs, their spatial positioning also plays an important role in driving tumor growth. In a nutshell, our study suggests that, in confined environments, cell motility and ECM proteolysis are two key factors that regulate tumor growth and tumor relapse dynamics by altering the number and spatial distribution of CSCs.

Applying fire spread simulators in New Zealand and Australia: Results from an international seminar

Treesearch

Tonja Opperman; Jim Gould; Mark Finney; Cordy Tymstra

2006-01-01

There is currently no spatial wildfire spread and growth simulation model used commonly across New Zealand or Australia. Fire management decision-making would be enhanced through the use of spatial fire simulators. Various groups from around the world met in January 2006 to evaluate the applicability of different spatial fire spread applications for common use in both...

Cross-continent comparisons reveal differing environmental drivers of growth of the coral reef fish, Lutjanus bohar

NASA Astrophysics Data System (ADS)

Ong, Joyce J. L.; Rountrey, Adam N.; Marriott, Ross J.; Newman, Stephen J.; Meeuwig, Jessica J.; Meekan, Mark G.

2017-03-01

Biochronologies provide important insights into the growth responses of fishes to past variability in physical and biological environments and, in so doing, allow modelling of likely responses to climate change in the future. We examined spatial variability in the key drivers of inter-annual growth patterns of a widespread, tropical snapper, Lutjanus bohar, at similar tropical latitudes on the north-western and north-eastern coasts of the continent of Australia. For this study, we developed biochronologies from otoliths that provided proxies of somatic growth and these were analysed using mixed-effects models to examine the historical drivers of growth. Our analyses demonstrated that growth patterns of fish were driven by different climatic and biological factors in each region, including Pacific Ocean climate indices, regional sea level and the size structure of the fish community. Our results showed that the local oceanographic and biological context of reef systems strongly influenced the growth of L. bohar and that a single age-related growth trend cannot be assumed for separate populations of this species that are likely to experience different environmental conditions. Generalised predictions about the growth response of fishes to climate change will thus require adequate characterisation of the spatial variability in growth determinants likely to be found throughout the range of species that have cosmopolitan distributions.

Spatial distribution of nuclei in progressive nucleation: Modeling and application

NASA Astrophysics Data System (ADS)

Tomellini, Massimo

2018-04-01

Phase transformations ruled by non-simultaneous nucleation and growth do not lead to random distribution of nuclei. Since nucleation is only allowed in the untransformed portion of space, positions of nuclei are correlated. In this article an analytical approach is presented for computing pair-correlation function of nuclei in progressive nucleation. This quantity is further employed for characterizing the spatial distribution of nuclei through the nearest neighbor distribution function. The modeling is developed for nucleation in 2D space with power growth law and it is applied to describe electrochemical nucleation where correlation effects are significant. Comparison with both computer simulations and experimental data lends support to the model which gives insights into the transition from Poissonian to correlated nearest neighbor probability density.

Evaluating effects of Everglades restoration on American crocodile populations in south Florida using a spatially-explicit, stage-based population model

USGS Publications Warehouse

Green, Timothy W.; Slone, Daniel H.; Swain, Eric D.; Cherkiss, Michael S.; Lohmann, Melinda; Mazzotti, Frank J.; Rice, Kenneth G.

2014-01-01

The distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.

Influence of Scale Effect and Model Performance in Downscaling ASTER Land Surface Temperatures to a Very High Spatial Resolution in an Agricultural Area

NASA Astrophysics Data System (ADS)

Zhou, J.; Li, G.; Liu, S.; Zhan, W.; Zhang, X.

2015-12-01

At present land surface temperatures (LSTs) can be generated from thermal infrared remote sensing with spatial resolutions from ~100 m to tens of kilometers. However, LSTs with high spatial resolution, e.g. tens of meters, are still lack. The purpose of LST downscaling is to generate LSTs with finer spatial resolutions than their native spatial resolutions. The statistical linear or nonlinear regression models are most frequently used for LST downscaling. The basic assumption of these models is the scale-invariant relationships between LST and its descriptors, which is questioned but rare researches have been reported. In addition, few researches can be found for downscaling satellite LST or TIR data to a high spatial resolution, i.e. better than 100 m or even finer. The lack of LST with high spatial resolution cannot satisfy the requirements of applications such as evapotranspiration mapping at the field scale. By selecting a dynamically developing agricultural oasis as the study area, the aim of this study is to downscale the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSTs to 15 m, to satisfy the requirement of evapotranspiration mapping at the field scale. Twelve ASTER images from May to September in 2012, covering the entire growth stage of maize, were selected. Four statistical models were evaluated, including one global model, one piecewise model, and two local models. The influence from scale effect in downscaling LST was quantified. The downscaled LSTs are evaluated from accuracy and image quality. Results demonstrate that the influence from scale effect varies according to models and the maize growth stage. Significant influence about -4 K to 6 K existed at the early stage and weaker influence existed in the middle stage. When compared with the ground measured LSTs, the downscaled LSTs resulted from the global and local models yielded higher accuracies and better image qualities than the local models. In addition to the vegetation indices, the surface albedo is an important descriptor for downscaling LST through explaining its spatial variation induced by soil moisture.

A Decade of Growth

NASA Technical Reports Server (NTRS)

Johnson, Nicholas L.; Anzz-Meador, Phillip D.

2001-01-01

This paper examines the Space Surveillance Network catalog's growth in low Earth orbit (LEO) and the geosynchronous Earth orbit (GEO) over the decade 1990-2000. During this time, innovative space utilization concepts, e.g. the Iridium and Globalstar commercial communication satellite constellations, have increased the public's consciousness of space. At the same time, however, these constellations have increased spatial density per 10 km altitude bin by factors of two and three respectively. While not displaying as spectacular a growth in spatial density, other regions of space have grown steadily in terms of number, mass, size, and operational lifetime. In this work we categorize launch traffic by type (e.g. payload, rocket body, operational debris, fragmentation debris, or anomalous debris), mass, and size so as to present the observed growth numerically, in terms of mass, and in terms of cross-sectional area. GEO traffic is further categorized by operational longitude. Because growth itself defines only the instantaneous environment, we also examine the higher-order derivatives of growth. In addition, we compare the last decade's growth with modeling results to illustrate the subtle effects of inclination, eccentricity, and size, in addition to spatial densities, on estimating the collision probability. We identify those regions of space most subject to accidental collision.

Socioeconomic Status Accounts for Rapidly Increasing Geographic Variation in the Incidence of Poor Fetal Growth

PubMed Central

Ball, Stephen J.; Jacoby, Peter; Zubrick, Stephen R.

2013-01-01

Fetal growth is an important risk factor for infant morbidity and mortality. In turn, socioeconomic status is a key predictor of fetal growth; however, other sociodemographic factors and environmental effects may also be important. This study modelled geographic variation in poor fetal growth after accounting for socioeconomic status, with a fixed effect for socioeconomic status and a combination of spatially-correlated and spatially-uncorrelated random effects. The dataset comprised 88,246 liveborn singletons, aggregated within suburbs in Perth, Western Australia. Low socioeconomic status was strongly associated with an increased risk of poor fetal growth. An increase in geographic variation of poor fetal growth from 1999–2001 (interquartile odds ratio among suburbs = 1.20) to 2004–2006 (interquartile odds ratio = 1.40) indicated a widening risk disparity by socioeconomic status. Low levels of residual spatial patterns strengthen the case for targeting policies and practices in areas of low socioeconomic status for improved outcomes. This study indicates an alarming increase in geographic inequalities in poor fetal growth in Perth which warrants further research into the specific aspects of socioeconomic status that act as risk factors. PMID:23799513

AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

EPA Science Inventory

We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma)

USGS Publications Warehouse

Midway, Stephen R.; Wagner, Tyler; Arnott, Stephen A.; Biondo, Patrick; Martinez-Andrade, Fernando; Wadsworth, Thomas F.

2015-01-01

Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder (Paralichthys lethostigma) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evidence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters (L∞, K, andt0). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

USGS Publications Warehouse

Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

2015-01-01

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Spatio-temporal transitions in the dynamics of bacterial populations

NASA Astrophysics Data System (ADS)

Lin, Anna; Lincoln, Bryan; Mann, Bernward; Torres, Gelsy; Kas, Josef; Swinney, Harry

2001-03-01

We experimentally investigate the population dynamics of a strain of E. coli bacteria living under spatially inhomogeneous growth conditions. A localized perturbation that moves with a well-defined drift velocity is imposed on the system. A reaction-diffusion model of this situation^1 predicts that an abrupt transition between spatial localization and extinction of the colony occurs for a fixed average growth rate when the drift velocity exceeds a critical value. Also, a transition between localized and delocalized populations is predicted to occur at a fixed drift velocity when the spatially averaged growth rate is varied. We create a spatially localized perturbation with UV light and vary the strength and drift velocity of the perturbation to investigate the existence of the different bacterial population distributions and the transitions between them. Numerical simulations of a 250 mm by 20 mm system guide our experiments. ^1K. A. Dahmen, D. R. Nelson, N. M. Shnerb, Jour. Math. Bio., 41 1 (2000).

The Evolving Urban Community and Military Installations: A Dynamic Spatial Decision Support System for Sustainable Military Communities

DTIC Science & Technology

2007-01-01

focus on identifying growth by income and housing costs. These, and other models are focused on the city itself and deal with growth over the course...2. This model employs a set of econometric models to project future population, household, and employment. The landscape is gridded into one... model in LEAM (LEAMecon) forecasts changes in output, employment and income over time based on changes in the market, technology, productivity and

75 years of dryland science: Trends and gaps in arid ecology literature.

PubMed

Greenville, Aaron C; Dickman, Chris R; Wardle, Glenda M

2017-01-01

Growth in the publication of scientific articles is occurring at an exponential rate, prompting a growing need to synthesise information in a timely manner to combat urgent environmental problems and guide future research. Here, we undertake a topic analysis of dryland literature over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging. Four topics-wetlands, mammal ecology, litter decomposition and spatial modelling, were identified as 'hot topics' that showed higher than average growth in publications from 1940 to 2015. Five topics-remote sensing, climate, habitat and spatial, agriculture and soils-microbes, were identified as 'cold topics', with lower than average growth over the survey period, but higher than average numbers of publications. Topics in arid ecology clustered into seven broad groups on word-based similarity. These groups ranged from mammal ecology and population genetics, broad-scale management and ecosystem modelling, plant ecology, agriculture and ecophysiology, to populations and paleoclimate. These patterns may reflect trends in the field of ecology more broadly. We also identified two broad research gaps in arid ecology: population genetics, and habitat and spatial research. Collaborations between population genetics and ecologists and investigations of ecological processes across spatial scales would contribute profitably to the advancement of arid ecology and to ecology more broadly.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Assessing the Dynamic Effects of Climate on Individual Tree Growth Across Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; D'Amato, A. W.; Foster, J. R.; Bradford, J. B.

2015-12-01

The relationship between climate variability and an ecosystem process, such as forest growth, is frequently not fixed over time, but changes due to complex interactions between unobserved ecological factors and the process of interest. Climate data and forecasts are frequently spatially and temporally misaligned with ecological observations making inference regarding the effects of climate on ecosystem processes particularly challenging. Here we develop a Bayesian dynamic hierarchical model for annual tree growth increment that allows the effects of climate to evolve over time, applies climate data at a spatial-temporal scale consistent with observations, and controls for individual-level variability commonly encountered in ecological datasets. The model is applied to individual tree data from northern Minnesota using a modified Thornthwaite-type water balance model to transform PRISM temperature and precipitation estimates to physiologically relevant values of actual and potential evapotranspiration (AET, PET), and climatic water deficit. Model results indicate that mean tree growth is most sensitive to AET during the growing season and PET and minimum temperature in the spring prior to growth. The effects of these variables on tree growth, however, are not stationary with significant effects observed in only a subset of years during the 111-year study period. Importantly, significant effects of climate do not result from anomalous climate observations, but follow from large growth deviations unexplained by tree age and size, and time since forest disturbance. Results differ markedly from alternative models that assume the effects of climate are stationary over time or apply climate estimates at the individual scale. Forecasts of future tree growth as a function of climate follow directly from the dynamic hierarchical model allowing for assessment of forest change. Current work is focused on extending the model framework to include regional climate and ecosystem effects for application to a larger tree growth dataset spanning a latitudinal gradient within the US from Maine to Florida.

Theoretical and Experimental Study of Bacterial Colony Growth in 3D

NASA Astrophysics Data System (ADS)

Shao, Xinxian; Mugler, Andrew; Nemenman, Ilya

2014-03-01

Bacterial cells growing in liquid culture have been well studied and modeled. However, in nature, bacteria often grow as biofilms or colonies in physically structured habitats. A comprehensive model for population growth in such conditions has not yet been developed. Based on the well-established theory for bacterial growth in liquid culture, we develop a model for colony growth in 3D in which a homogeneous colony of cells locally consume a diffusing nutrient. We predict that colony growth is initially exponential, as in liquid culture, but quickly slows to sub-exponential after nutrient is locally depleted. This prediction is consistent with our experiments performed with E. coli in soft agar. Our model provides a baseline to which studies of complex growth process, such as such as spatially and phenotypically heterogeneous colonies, must be compared.

Demographic controls of aboveground forest biomass across North America.

PubMed

Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

2016-04-01

Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments.

PubMed

Lambert, Guillaume; Vyawahare, Saurabh; Austin, Robert H

2014-08-06

One of the predictions of game theory is that cooperative behaviours are vulnerable to exploitation by selfish individuals, but this result seemingly contradicts the survival of cooperation observed in nature. In this review, we will introduce game theoretical concepts that lead to this conclusion and show how the spatial competition dynamics between microorganisms can be used to model the survival and maintenance of cooperation. In particular, we focus on how Escherichia coli bacteria with a growth advantage in stationary phase (GASP) phenotype maintain a proliferative phenotype when faced with overcrowding to gain a fitness advantage over wild-type populations. We review recent experimental approaches studying the growth dynamics of competing GASP and wild-type strains of E. coli inside interconnected microfabricated habitats and use a game theoretical approach to analyse the observed inter-species interactions. We describe how the use of evolutionary game theory and the ideal free distribution accurately models the spatial distribution of cooperative and selfish individuals in spatially heterogeneous environments. Using bacteria as a model system of cooperative and selfish behaviours may lead to a better understanding of the competition dynamics of other organisms-including tumour-host interactions during cancer development and metastasis.

Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico

Treesearch

Robert E. Keane; Scott A. Mincemoyer; Kirsten M. Schmidt; Donald G. Long; Janice L. Garner

2000-01-01

(Please note: This PDF is part of a CD-ROM package only and was not printed on paper.) Fuels and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Gila National Forest in New Mexico. Satellite imagery, terrain modeling, and biophysical simulation were used to create the three...

Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

PubMed

Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

2018-03-01

This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

Homogenization analysis of invasion dynamics in heterogeneous landscapes with differential bias and motility.

PubMed

Yurk, Brian P

2018-07-01

Animal movement behaviors vary spatially in response to environmental heterogeneity. An important problem in spatial ecology is to determine how large-scale population growth and dispersal patterns emerge within highly variable landscapes. We apply the method of homogenization to study the large-scale behavior of a reaction-diffusion-advection model of population growth and dispersal. Our model includes small-scale variation in the directed and random components of movement and growth rates, as well as large-scale drift. Using the homogenized model we derive simple approximate formulas for persistence conditions and asymptotic invasion speeds, which are interpreted in terms of residence index. The homogenization results show good agreement with numerical solutions for environments with a high degree of fragmentation, both with and without periodicity at the fast scale. The simplicity of the formulas, and their connection to residence index make them appealing for studying the large-scale effects of a variety of small-scale movement behaviors.

Modeling the population-level effects of hypoxia on a coastal fish: implications of a spatially-explicit individual-based model

NASA Astrophysics Data System (ADS)

Rose, K.; Creekmore, S.; Thomas, P.; Craig, K.; Neilan, R.; Rahman, S.; Wang, L.; Justic, D.

2016-02-01

The northwestern Gulf of Mexico (USA) currently experiences a large hypoxic area ("dead zone") during the summer. The population-level effects of hypoxia on coastal fish are largely unknown. We developed a spatially-explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of individual Atlantic croaker could lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 x 800 spatial grid of 1 km2 cells for 140 years. Chlorophyll-a concentration and water temperature were specified daily for each grid cell. Dissolved oxygen (DO) was obtained from a 3-D water quality model for four years that differed in their severity of hypoxia. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and movement behavior was based on temperature preferences and avoidance of low DO. Hypoxia effects were imposed using exposure-effects sub-models that converted time-varying exposure to DO to reductions in growth and fecundity, and increases in mortality. Using sequences of mild, intermediate, and severe hypoxia years, the model predicted a 20% decrease in population abundance. Additional simulations were performed under the assumption that river-based nutrients loadings that lead to more hypoxia also lead to higher primary production and more food for croaker. Twenty-five percent and 50% nutrient reduction scenarios were simulated by adjusting the cholorphyll-a concentrations used as food proxy for the croaker. We then incrementally increased the DO concentrations to determine how much hypoxia would need to be reduced to offset the lower food production resulting from reduced nutrients. We discuss the generality of our results, the hidden effects of hypoxia on fish, and our overall strategy of combining laboratory and field studies with modeling to produce robust predictions of population responses to stressors under dynamic and multi-stressor conditions.

Measuring crown dynamics of longleaf pine in the sandhills of Eglin Air Force Base

Treesearch

Matt Anderson; Greg L. Somers; W. Rick Smith; Mickey Freeland; Donna Ruth

1998-01-01

The USDA Forest Service SRS, in cooperation with Auburn University, is developing an individual tree, spatially explicit, and btoiogicaily based growth model for natural iongieaf pine sands at Eglin Air Force Base in Florida. The goal of the growth model is to provide a tool for the land managers to compare silvicultural practices effects on the light and water...

Evaluation of hydrologic equilibrium in a mountainous watershed: incorporating forest canopy spatial adjustment to soil biogeochemical processes

NASA Astrophysics Data System (ADS)

Mackay, D. Scott

Hydrologic equilibrium theory has been used to describe both short-term regulation of gas exchange and long-term adjustment of forest canopy density. However, by focusing on water and atmospheric conditions alone a hydrologic equilibrium may impose an oversimplification of the growth of forests adjusted to hydrology. In this study nitrogen is incorporated as a third regulation of catchment level forest dynamics and gas exchange. This was examined with an integrated distributed hydrology and forest growth model in a central Sierra Nevada watershed covered primarily by old-growth coniferous forest. Water and atmospheric conditions reasonably reproduced daily latent heat flux, and predicted the expected catenary trend of leaf area index (LAI). However, it was not until the model was provided a spatially detailed description of initial soil carbon and nitrogen pools that spatial patterns of LAI were generated. This latter problem was attributed to a lack of soil history or memory in the initialization of the simulations. Finally, by reducing stomatal sensitivity to vapor pressure deficit (VPD) the canopy density increased when water and nitrogen limitations were not present. The results support a three-control hydrologic equilibrium in the Sierra Nevada watershed. This has implications for modeling catchment level soil-vegetation-atmospheric interactions over interannual, decade, and century time-scales.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Modeling growth and dissemination of lymphoma in a co-evolving lymph node: a diffuse-domain approach

NASA Astrophysics Data System (ADS)

Chuang, Yao-Li; Cristini, Vittorio; Chen, Ying; Li, Xiangrong; Frieboes, Hermann; Lowengrub, John

2013-03-01

While partial differential equation models of tumor growth have successfully described various spatiotemporal phenomena observed for in-vitro tumor spheroid experiments, one challenge towards taking these models to further study in-vivo tumors is that instead of relatively static tissue culture with regular boundary conditions, in-vivo tumors are often confined in organ tissues that co-evolve with the tumor growth. Here we adopt a recently developed diffuse-domain method to account for the co-evolving domain boundaries, adapting our previous in-vitro tumor model for the development of lymphoma encapsulated in a lymph node, which may swell or shrink due to proliferation and dissemination of lymphoma cells and treatment by chemotherapy. We use the model to study the induced spatial heterogeneity, which may arise as an emerging phenomenon in experimental observations and model analysis. Spatial heterogeneity is believed to lead to tumor infiltration patterns and reduce the efficacy of chemotherapy, leaving residuals that cause cancer relapse after the treatment. Understanding the spatiotemporal evolution of in-vivo tumors can be an essential step towards more effective strategies of curing cancer. Supported by NIH-PSOC grant 1U54CA143907-01.

Seasonal and spatial patterns of growth of rainbow trout in the Colorado River in Grand Canyon, AZ

USGS Publications Warehouse

Yard, Micheal D.; Korman, Josh; Walters, Carl J.; Kennedy, T.A.

2016-01-01

Rainbow trout (Oncorhynchus mykiss) have been purposely introduced in many regulated rivers, with inadvertent consequences on native fishes. We describe how trout growth rates and condition could be influencing trout population dynamics in a 130 km section of the Colorado River below Glen Canyon Dam based on a large-scale mark–recapture program where ∼8000 rainbow trout were recaptured over a 3-year period (2012–2014). There were strong temporal and spatial variations in growth in both length and weight as predicted from von Bertalanffy and bioenergetic models, respectively. There was more evidence for seasonal variation in the growth coefficient and annual variation in the asymptotic length. Bioenergetic models showed more variability for growth in weight across seasons and years than across reaches. These patterns were consistent with strong seasonal variation in invertebrate drift and effects of turbidity on foraging efficiency. Highest growth rates and relative condition occurred in downstream reaches with lower trout densities. Results indicate that reduction in rainbow trout abundance in Glen Canyon will likely increase trout size in the tailwater fishery and may reduce downstream dispersal into Grand Canyon.

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS

EPA Science Inventory

Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

PubMed

You, Li; Brown, Joel S; Thuijsman, Frank; Cunningham, Jessica J; Gatenby, Robert A; Zhang, Jingsong; Staňková, Kateřina

2017-12-21

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T + ), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T P ), and (3) those independent of testosterone (T - ). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T -  cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling the Impact of Spatial Structure on Growth Dynamics of Invasive Plant Species

NASA Astrophysics Data System (ADS)

Murphy, James T.; Johnson, Mark P.; Walshe, Ray

2013-07-01

Invasive nonindigenous plant species can have potentially serious detrimental effects on local ecosystems and, as a result, costly control efforts often have to be put in place to protect habitats. An example of an invasive problem on a global scale involves the salt marsh grass species from the genus Spartina. The spread of Spartina anglica in Europe and Asia has drawn much concern due to its ability to convert coastal habitats into cord-grass monocultures and to alter the native food webs. However, the patterns of invasion of Spartina species are amenable to spatially-explicit modeling strategies that take into account both temporal and spatio-temporal processes. In this study, an agent-based model of Spartina growth on a simulated mud flat environment was developed in order to study the effects of spatial pattern and initial seedling placement on the invasion dynamics of the population. The spatial pattern of an invasion plays a key role in the rate of spread of the species and understanding this can lead to significant cost savings when designing efficient control strategies. We present here a model framework that can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on invasion dynamics. This would be a useful tool for assessing eradication strategies and choosing optimal control solutions in order to be able to minimize future control costs.

Coupling urban growth scenarios with nearshore biophysical change models to inform coastal restoration planning in Puget Sound, Washington

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Kreitler, J.; Labiosa, W.

2010-12-01

A scenario represents an account of a plausible future given logical assumptions about how conditions change over discrete bounds of space and time. Development of multiple scenarios provides a means to identify alternative directions of urban growth that account for a range of uncertainty in human behavior. Interactions between human and natural processes may be studied by coupling urban growth scenario outputs with biophysical change models; if growth scenarios encompass a sufficient range of alternative futures, scenario assumptions serve to constrain the uncertainty of biophysical models. Spatially explicit urban growth models (map-based) produce output such as distributions and densities of residential or commercial development in a GIS format that can serve as input to other models. Successful fusion of growth model outputs with other model inputs requires that both models strategically address questions of interest, incorporate ecological feedbacks, and minimize error. The U.S. Geological Survey (USGS) Puget Sound Ecosystem Portfolio Model (PSEPM) is a decision-support tool that supports land use and restoration planning in Puget Sound, Washington, a 35,500 sq. km region. The PSEPM couples future scenarios of urban growth with statistical, process-based and rule-based models of nearshore biophysical changes and ecosystem services. By using a multi-criteria approach, the PSEPM identifies cross-system and cumulative threats to the nearshore environment plus opportunities for conservation and restoration. Sub-models that predict changes in nearshore biophysical condition were developed and existing models were integrated to evaluate three growth scenarios: 1) Status Quo, 2) Managed Growth, and 3) Unconstrained Growth. These decadal scenarios were developed and projected out to 2060 at Oregon State University using the GIS-based ENVISION model. Given land management decisions and policies under each growth scenario, the sub-models predicted changes in 1) fecal coliform in shellfish growing areas, 2) sediment supply to beaches, 3) State beach recreational visits, 4) eelgrass habitat suitability, 5) forage fish habitat suitability, and 6) nutrient loadings. In some cases thousands of shoreline units were evaluated with multiple predictive models, creating a need for streamlined and consistent database development and data processing. Model development over multiple disciplines demonstrated the challenge of merging data types from multiple sources that were inconsistent in spatial and temporal resolution, classification schemes, and topology. Misalignment of data in space and time created potential for error and misinterpretation of results. This effort revealed that the fusion of growth scenarios and biophysical models requires an up-front iterative adjustment of both scenarios and models so that growth model outputs provide the needed input data in the correct format. Successful design of data flow across models that includes feedbacks between human and ecological systems was found to enhance the use of the final data product for decision making.

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Landsat's role in ecological applications of remote sensing.

Treesearch

Warren B. Cohen; Samuel N. Goward

2004-01-01

Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

USGS Publications Warehouse

Wildhaber, Mark L.; Lamberson, Peter J.

2004-01-01

Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks

PubMed Central

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-01-01

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a ‘retention effect’. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. PMID:26311313

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks.

PubMed

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-09-06

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a 'retention effect'. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. © 2015 The Author(s).

A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

Treesearch

Stephen R. Shifley; Hong S. He; Heike Lischke; Wen J. Wang; Wenchi Jin; Eric J. Gustafson; Jonathan R. Thompson; Frank R. Thompson; William D. Dijak; Jian Yang

2017-01-01

Context. Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent. Objectives. We highlight milestones in the development of forest dynamics models and identify future research and application opportunities. Methods. We reviewed...

Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models

USDA-ARS?s Scientific Manuscript database

Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a variety of crop biophysical properties. However, the outcome of the model inversion procedure will be ...

Chaotic and stable perturbed maps: 2-cycles and spatial models

NASA Astrophysics Data System (ADS)

Braverman, E.; Haroutunian, J.

2010-06-01

As the growth rate parameter increases in the Ricker, logistic and some other maps, the models exhibit an irreversible period doubling route to chaos. If a constant positive perturbation is introduced, then the Ricker model (but not the classical logistic map) experiences period doubling reversals; the break of chaos finally gives birth to a stable two-cycle. We outline the maps which demonstrate a similar behavior and also study relevant discrete spatial models where the value in each cell at the next step is defined only by the values at the cell and its nearest neighbors. The stable 2-cycle in a scalar map does not necessarily imply 2-cyclic-type behavior in each cell for the spatial generalization of the map.

Progress on Discrete Fracture Network models with implications on the predictions of permeability and flow channeling structure

NASA Astrophysics Data System (ADS)

Darcel, C.; Davy, P.; Le Goc, R.; Maillot, J.; Selroos, J. O.

2017-12-01

We present progress on Discrete Fracture Network (DFN) flow modeling, including realistic advanced DFN spatial structures and local fracture transmissivity properties, through an application to the Forsmark site in Sweden. DFN models are a framework to combine fracture datasets from different sources and scales and to interpolate them in combining statistical distributions and stereological relations. The resulting DFN upscaling function - size density distribution - is a model component key to extrapolating fracture size densities between data gaps, from borehole core up to site scale. Another important feature of DFN models lays in the spatial correlations between fractures, with still unevaluated consequences on flow predictions. Indeed, although common Poisson (i.e. spatially random) models are widely used, they do not reflect these geological evidences for more complex structures. To model them, we define a DFN growth process from kinematic rules for nucleation, growth and stopping conditions. It mimics in a simplified way the geological fracturing processes and produces DFN characteristics -both upscaling function and spatial correlations- fully consistent with field observations. DFN structures are first compared for constant transmissivities. Flow simulations for the kinematic and equivalent Poisson DFN models show striking differences: with the kinematic DFN, connectivity and permeability are significantly smaller, down to a difference of one order of magnitude, and flow is much more channelized. Further flow analyses are performed with more realistic transmissivity distribution conditions (sealed parts, relations to fracture sizes, orientations and in-situ stress field). The relative importance of the overall DFN structure in the final flow predictions is discussed.

Space versus Place in Complex Human-Natural Systems: Spatial and Multi-level Models of Tropical Land Use and Cover Change (LUCC) in Guatemala

PubMed Central

López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew

2013-01-01

The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908

Regional Growth and income convergence in the western black belt counties of Alabama: evidence from census block group data

Treesearch

Buddhi Gyawali; Rory Fraser; James Bukenya; John Schelhas

2010-01-01

This paper examines the effects of growth in African Ameriocan population, employment, and human capital on growth in per capita income at the census block group (CBG) level using ordinary least square and spatial reqression models. The results indicate the presence of conditional incaom conbergence between 1980 and 2000 with poorer CBGs growing faster than the...

75 years of dryland science: Trends and gaps in arid ecology literature

PubMed Central

Dickman, Chris R.; Wardle, Glenda M.

2017-01-01

Growth in the publication of scientific articles is occurring at an exponential rate, prompting a growing need to synthesise information in a timely manner to combat urgent environmental problems and guide future research. Here, we undertake a topic analysis of dryland literature over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging. Four topics—wetlands, mammal ecology, litter decomposition and spatial modelling, were identified as ‘hot topics’ that showed higher than average growth in publications from 1940 to 2015. Five topics—remote sensing, climate, habitat and spatial, agriculture and soils-microbes, were identified as ‘cold topics’, with lower than average growth over the survey period, but higher than average numbers of publications. Topics in arid ecology clustered into seven broad groups on word-based similarity. These groups ranged from mammal ecology and population genetics, broad-scale management and ecosystem modelling, plant ecology, agriculture and ecophysiology, to populations and paleoclimate. These patterns may reflect trends in the field of ecology more broadly. We also identified two broad research gaps in arid ecology: population genetics, and habitat and spatial research. Collaborations between population genetics and ecologists and investigations of ecological processes across spatial scales would contribute profitably to the advancement of arid ecology and to ecology more broadly. PMID:28384186

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds

USGS Publications Warehouse

Brown, Michelle L.; Donovan, Therese; Schwenk, W. Scott; Theobald, David M.

2014-01-01

Forest loss and fragmentation are among the largest threats to forest-dwelling wildlife species today, and projected increases in human population growth are expected to increase these threats in the next century. We combined spatially-explicit growth models with wildlife distribution models to predict the effects of human development on 5 forest-dependent bird species in Vermont, New Hampshire, and Massachusetts, USA. We used single-species occupancy models to derive the probability of occupancy for each species across the study area in the years 2000 and 2050. Over half a million new housing units were predicted to be added to the landscape. The maximum change in housing density was nearly 30 houses per hectare; however, 30% of the towns in the study area were projected to add less than 1 housing unit per hectare. In the face of predicted human growth, the overall occupancy of each species decreased by as much as 38% (ranging from 19% to 38% declines in the worst-case scenario) in the year 2050. These declines were greater outside of protected areas than within protected lands. Ninety-seven percent of towns experienced some decline in species occupancy within their borders, highlighting the value of spatially-explicit models. The mean decrease in occupancy probability within towns ranged from 3% for hairy woodpecker to 8% for ovenbird and hermit thrush. Reductions in occupancy probability occurred on the perimeters of cities and towns where exurban development is predicted to increase in the study area. This spatial approach to wildlife planning provides data to evaluate trade-offs between development scenarios and forest-dependent wildlife species.

Focal adhesion kinase regulates neuronal growth, synaptic plasticity and hippocampus-dependent spatial learning and memory.

PubMed

Monje, Francisco J; Kim, Eun-Jung; Pollak, Daniela D; Cabatic, Maureen; Li, Lin; Baston, Arthur; Lubec, Gert

2012-01-01

The focal adhesion kinase (FAK) is a non-receptor tyrosine kinase abundantly expressed in the mammalian brain and highly enriched in neuronal growth cones. Inhibitory and facilitatory activities of FAK on neuronal growth have been reported and its role in neuritic outgrowth remains controversial. Unlike other tyrosine kinases, such as the neurotrophin receptors regulating neuronal growth and plasticity, the relevance of FAK for learning and memory in vivo has not been clearly defined yet. A comprehensive study aimed at determining the role of FAK in neuronal growth, neurotransmitter release and synaptic plasticity in hippocampal neurons and in hippocampus-dependent learning and memory was therefore undertaken using the mouse model. Gain- and loss-of-function experiments indicated that FAK is a critical regulator of hippocampal cell morphology. FAK mediated neurotrophin-induced neuritic outgrowth and FAK inhibition affected both miniature excitatory postsynaptic potentials and activity-dependent hippocampal long-term potentiation prompting us to explore the possible role of FAK in spatial learning and memory in vivo. Our data indicate that FAK has a growth-promoting effect, is importantly involved in the regulation of the synaptic function and mediates in vivo hippocampus-dependent spatial learning and memory. Copyright © 2011 S. Karger AG, Basel.

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

USDA-ARS?s Scientific Manuscript database

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

The fission yeast cytokinetic contractile ring regulates septum shape and closure

PubMed Central

Thiyagarajan, Sathish; Munteanu, Emilia Laura; Arasada, Rajesh; Pollard, Thomas D.; O'Shaughnessy, Ben

2015-01-01

ABSTRACT During cytokinesis, fission yeast and other fungi and bacteria grow a septum that divides the cell in two. In fission yeast closure of the circular septum hole by the β-glucan synthases (Bgs) and other glucan synthases in the plasma membrane is tightly coupled to constriction of an actomyosin contractile ring attached to the membrane. It is unknown how septum growth is coordinated over scales of several microns to maintain septum circularity. Here, we documented the shapes of ingrowing septum edges by measuring the roughness of the edges, a measure of the deviation from circularity. The roughness was small, with spatial correlations indicative of spatially coordinated growth. We hypothesized that Bgs-mediated septum growth is mechanosensitive and coupled to contractile ring tension. A mathematical model showed that ring tension then generates almost circular septum edges by adjusting growth rates in a curvature-dependent fashion. The model reproduced experimental roughness statistics and showed that septum synthesis sets the mean closure rate. Our results suggest that the fission yeast cytokinetic ring tension does not set the constriction rate but regulates septum closure by suppressing roughness produced by inherently stochastic molecular growth processes. PMID:26240178

The fission yeast cytokinetic contractile ring regulates septum shape and closure.

PubMed

Thiyagarajan, Sathish; Munteanu, Emilia Laura; Arasada, Rajesh; Pollard, Thomas D; O'Shaughnessy, Ben

2015-10-01

During cytokinesis, fission yeast and other fungi and bacteria grow a septum that divides the cell in two. In fission yeast closure of the circular septum hole by the β-glucan synthases (Bgs) and other glucan synthases in the plasma membrane is tightly coupled to constriction of an actomyosin contractile ring attached to the membrane. It is unknown how septum growth is coordinated over scales of several microns to maintain septum circularity. Here, we documented the shapes of ingrowing septum edges by measuring the roughness of the edges, a measure of the deviation from circularity. The roughness was small, with spatial correlations indicative of spatially coordinated growth. We hypothesized that Bgs-mediated septum growth is mechanosensitive and coupled to contractile ring tension. A mathematical model showed that ring tension then generates almost circular septum edges by adjusting growth rates in a curvature-dependent fashion. The model reproduced experimental roughness statistics and showed that septum synthesis sets the mean closure rate. Our results suggest that the fission yeast cytokinetic ring tension does not set the constriction rate but regulates septum closure by suppressing roughness produced by inherently stochastic molecular growth processes. © 2015. Published by The Company of Biologists Ltd.

Spatial Frequency Responses of Anisotropic Refractive Index Gratings Formed in Holographic Polymer Dispersed Liquid Crystals

PubMed Central

Fukuda, Yoshiaki; Tomita, Yasuo

2016-01-01

We report on an experimental investigation of spatial frequency responses of anisotropic transmission refractive index gratings formed in holographic polymer dispersed liquid crystals (HPDLCs). We studied two different types of HPDLC materials employing two different monomer systems: one with acrylate monomer capable of radical mediated chain-growth polymerizations and the other with thiol-ene monomer capable of step-growth polymerizations. It was found that the photopolymerization kinetics of the two HPDLC materials could be well explained by the autocatalytic model. We also measured grating-spacing dependences of anisotropic refractive index gratings at a recording wavelength of 532 nm. It was found that the HPDLC material with the thiol-ene monomer gave higher spatial frequency responses than that with the acrylate monomer. Statistical thermodynamic simulation suggested that such a spatial frequency dependence was attributed primarily to a difference in the size of formed liquid crystal droplets due to different photopolymerization mechanisms. PMID:28773314

Spatial Frequency Responses of Anisotropic Refractive Index Gratings Formed in Holographic Polymer Dispersed Liquid Crystals.

PubMed

Fukuda, Yoshiaki; Tomita, Yasuo

2016-03-10

We report on an experimental investigation of spatial frequency responses of anisotropic transmission refractive index gratings formed in holographic polymer dispersed liquid crystals (HPDLCs). We studied two different types of HPDLC materials employing two different monomer systems: one with acrylate monomer capable of radical mediated chain-growth polymerizations and the other with thiol-ene monomer capable of step-growth polymerizations. It was found that the photopolymerization kinetics of the two HPDLC materials could be well explained by the autocatalytic model. We also measured grating-spacing dependences of anisotropic refractive index gratings at a recording wavelength of 532 nm. It was found that the HPDLC material with the thiol-ene monomer gave higher spatial frequency responses than that with the acrylate monomer. Statistical thermodynamic simulation suggested that such a spatial frequency dependence was attributed primarily to a difference in the size of formed liquid crystal droplets due to different photopolymerization mechanisms.

Propagation of ion acoustic wave energy in the plume of a high-current LaB6 hollow cathode

NASA Astrophysics Data System (ADS)

Jorns, Benjamin A.; Dodson, Christoper; Goebel, Dan M.; Wirz, Richard

2017-08-01

A frequency-averaged quasilinear model is derived and experimentally validated for the evolution of ion acoustic turbulence (IAT) along the centerline of a 100-A class, LaB6 hollow cathode. Probe-based diagnostics and a laser induced fluorescence system are employed to measure the properties of both the turbulence and the background plasma parameters as they vary spatially in the cathode plume. It is shown that for the three discharge currents investigated, 100 A, 130 A, and 160 A, the spatial growth of the total energy density of the IAT in the near field of the cathode plume is exponential and agrees quantitatively with the predicted growth rates from the quasilinear formulation. However, in the downstream region of the cathode plume, the growth of IAT energy saturates at a level that is commensurate with the Sagdeev limit. The experimental validation of the quasilinear model for IAT growth and its limitations are discussed in the context of numerical efforts to describe self-consistently the plasma processes in the hollow cathode plume.

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

Spatial Characteristics of Tree Diameter Distributions in a Temperate Old-Growth Forest

PubMed Central

Zhao, Xiuhai; von Gadow, Klaus

2013-01-01

This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice. PMID:23527066

Spatial characteristics of tree diameter distributions in a temperate old-growth forest.

PubMed

Zhang, Chunyu; Wei, Yanbo; Zhao, Xiuhai; von Gadow, Klaus

2013-01-01

This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice.

Disease Spread and Its Effect on Population Dynamics in Heterogeneous Environment

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Roy, Parimita

In this paper, an eco-epidemiological model in which both species diffuse along a spatial gradient has been shown to exhibit temporal chaos at a fixed point in space. The proposed model is a modification of the model recently presented by Upadhyay and Roy [2014]. The spatial interactions among the species have been represented in the form of reaction-diffusion equations. The model incorporates the intrinsic growth rate of fish population which varies linearly with the depth of water. Numerical results show that diffusion can drive otherwise stable system into aperiodic behavior with sensitivity to initial conditions. We show that spatially induced chaos plays an important role in spatial pattern formation in heterogeneous environment. Spatiotemporal distributions of species have been simulated using the diffusivity assumptions realistic for natural eco-epidemic systems. We found that in heterogeneous environment, the temporal dynamics of both the species are drastically different and show chaotic behavior. It was also found that the instability observed in the model is due to spatial heterogeneity and diffusion-driven. Cumulative death rate of predator has an appreciable effect on model dynamics as the spatial distribution of all constituent populations exhibit significant changes when this model parameter is changed and it acts as a regularizing factor.

Bayesian methods to estimate urban growth potential

USGS Publications Warehouse

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

2017-01-01

Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.

Modeling fuels and fire effects in 3D: Model description and applications

Treesearch

Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

2016-01-01

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

Critical Point in Self-Organized Tissue Growth

NASA Astrophysics Data System (ADS)

Aguilar-Hidalgo, Daniel; Werner, Steffen; Wartlick, Ortrud; González-Gaitán, Marcos; Friedrich, Benjamin M.; Jülicher, Frank

2018-05-01

We present a theory of pattern formation in growing domains inspired by biological examples of tissue development. Gradients of signaling molecules regulate growth, while growth changes these graded chemical patterns by dilution and advection. We identify a critical point of this feedback dynamics, which is characterized by spatially homogeneous growth and proportional scaling of patterns with tissue length. We apply this theory to the biological model system of the developing wing of the fruit fly Drosophila melanogaster and quantitatively identify signatures of the critical point.

Experimental simulation and morphological quantification of volcano growth

NASA Astrophysics Data System (ADS)

Grosse, Pablo; Kervyn, Matthieu; Gallland, Olivier; Delcamp, Audray; Poppe, Sam

2016-04-01

Volcanoes display very diverse morphologies as a result of a complex interplay of several constructive and destructive processes. Here the role played by the spatial distribution of eruption centre and by an underlying strike-slip fault in controlling the long term growth of volcanoes is investigated with analogue models. Volcano growth was simulated by depositing loads of granular material (sand-kaolin mixtures) from a point source. An individual load deposited at a fixed location produces a simple symmetrical cone with flank slopes at the angle of repose of the granular material (~33°) that can be considered as the building-block for the experiments. Two sets of experiments were undertaken: (1) the location of deposition of the granular material (i.e. the volcano growth location) was shifted with time following specific probability density functions simulating shifts or migrations in vent location; (2) the location of deposition was kept fixed, but the deposition rate (i.e. the volcano growth rate) was varied coupled with the movement of a basal plate attached to a step-motor simulating a strike-slip displacement under the growing cone (and hence deformation of the cone). During the progression of the experiments, the models were photographed at regular time intervals using four digital cameras positioned at slightly different angles over the models. The photographs were used to generate synthetic digital elevation models (DEMs) with 0.2 mm spatial resolution of each step of the models by applying the MICMAC digital stereo-photogrammetry software. Morphometric data were extracted from the DEMs by applying two IDL-language algorithms: NETVOLC, used to automatically calculate the volcano edifice basal outline, and MORVOLC, used to extract a set of morphometric parameters that characterize the volcano edifice in terms of size, plan shape, profile shape and slopes. Analysis of the DEM-derived morphometric parameters allows to quantitatively characterize the growth evolution of the volcano models in terms of vent distribution and growth rate-deformation rate ratios.

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Youngsoo; Carlberg, Kevin Thomas

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over allmore » space and time in a weighted ℓ 2-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.« less

Spatial localization of nanoparticle growth in photoinduced nanocomposites

NASA Astrophysics Data System (ADS)

Smirnov, Anton A.; Pikulin, Alexander; Bityurin, Nikita

2018-02-01

Photoinduced nanocomposites are the polymer materials where the nanoparticles can be generated by the light irradiation. The single atoms of metal are formed due to the photoreduction of the metal-containing precursor added to the polymer matrix. Then the atoms precipitate into the nanoparticles (NPs). Similarly, semiconductor NPs are assembled from the monomer species such as CdS, which can be released due to the photodestruction of the appropriate precursor. We analyze theoretically the possibility of spatial confinement of growing nanoparticles in a domain where the elementary species are generated by a three-dimensionally localized source. It is shown that the effective confinement can be achieved only if the size of the generation domain exceeds some critical spatial scale determined by the parameters of the system. The confinement is provided by the trapping of the diffusing elementary species by the growing nanoparticles. The proposed model considers the irreversible particle growth, typical for the noble metals. Both the nucleation and the particle growth processes are suggested to be diffusion controlled.

Simulation of Long-Term Landscape-Level Fuel Treatment Effects on Large Wildfires

Treesearch

Mark A. Finney; Rob C. Seli; Charles W. McHugh; Alan A. Ager; Berni Bahro; James K. Agee

2006-01-01

A simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of a forest/fuel dynamics simulation module (FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel...

Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.

PubMed

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations.

Tumor Evolution in Space: The Effects of Competition Colonization Tradeoffs on Tumor Invasion Dynamics

PubMed Central

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations. PMID:23508890

Hormone-Mediated Pattern Formation in Seedling of Plants: a Competitive Growth Dynamics Model

NASA Astrophysics Data System (ADS)

Kawaguchi, Satoshi; Mimura, Masayasu; Ohya, Tomoyuki; Oikawa, Noriko; Okabe, Hirotaka; Kai, Shoichi

2001-10-01

An ecologically relevant pattern formation process mediated by hormonal interactions among growing seedlings is modeled based on the experimental observations on the effects of indole acetic acid, which can act as an inhibitor and activator of root growth depending on its concentration. In the absence of any lateral root with constant hormone-sensitivity, the edge effect phenomenon is obtained depending on the secretion rate of hormone from the main root. Introduction of growth-stage-dependent hormone-sensitivity drastically amplifies the initial randomness, resulting in spatially irregular macroscopic patterns. When the lateral root growth is introduced, periodic patterns are obtained whose periodicity depends on the length of lateral roots. The growth-stage-dependent hormone-sensitivity and the lateral root growth are crucial for macroscopic periodic-pattern formation.

Monitoring growth condition of spring maize in Northeast China using a process-based model

NASA Astrophysics Data System (ADS)

Wang, Peijuan; Zhou, Yuyu; Huo, Zhiguo; Han, Lijuan; Qiu, Jianxiu; Tan, Yanjng; Liu, Dan

2018-04-01

Early and accurate assessment of the growth condition of spring maize, a major crop in China, is important for the national food security. This study used a process-based Remote-Sensing-Photosynthesis-Yield Estimation for Crops (RS-P-YEC) model, driven by satellite-derived leaf area index and ground-based meteorological observations, to simulate net primary productivity (NPP) of spring maize in Northeast China from the first ten-day (FTD) of May to the second ten-day (STD) of August during 2001-2014. The growth condition of spring maize in 2014 in Northeast China was monitored and evaluated spatially and temporally by comparison with 5- and 13-year averages, as well as 2009 and 2013. Results showed that NPP simulated by the RS-P-YEC model, with consideration of multi-scattered radiation inside the crop canopy, could reveal the growth condition of spring maize more reasonably than the Boreal Ecosystem Productivity Simulator. Moreover, NPP outperformed other commonly used vegetation indices (e.g., Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) for monitoring and evaluating the growth condition of spring maize. Compared with the 5- and 13-year averages, the growth condition of spring maize in 2014 was worse before the STD of June and after the FTD of August, and it was better from the third ten-day (TTD) of June to the TTD of July across Northeast China. Spatially, regions with slightly worse and worse growth conditions in the STD of August 2014 were concentrated mainly in central Northeast China, and they accounted for about half of the production area of spring maize in Northeast China. This study confirms that NPP is a good indicator for monitoring and evaluating growth condition because of its capacity to reflect the physiological characteristics of crops. Meanwhile, the RS-P-YEC model, driven by remote sensing and ground-based meteorological data, is effective for monitoring crop growth condition over large areas in a near real time.

Evolution of the potential distribution area of french mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-02-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Predictive spatial modeling of narcotic crop growth patterns

USGS Publications Warehouse

Waltz, Frederick A.; Moore, D.G.

1986-01-01

Spatial models for predicting the geographic distribution of marijuana crops have been developed and are being evaluated for use in law enforcement programs. The models are based on growing condition preferences and on psychological inferences regarding grower behavior. Experiences of local law officials were used to derive the initial model, which was updated and improved as data from crop finds were archived and statistically analyzed. The predictive models are changed as crop locations are moved in response to the pressures of law enforcement. The models use spatial data in a raster geographic information system. The spatial data are derived from the U.S. Geological Survey's US GeoData, standard 7.5-minute topographic quadrangle maps, interpretations of aerial photographs, and thematic maps. Updating of cultural patterns, canopy closure, and other dynamic features is conducted through interpretation of aerial photographs registered to the 7.5-minute quadrangle base. The model is used to numerically weight various data layers that have been processed using spread functions, edge definition, and categorization. The building of the spatial data base, model development, model application, product generation, and use are collectively referred to as the Area Reduction Program (ARP). The goal of ARP is to provide law enforcement officials with tactical maps that show the most likely locations for narcotic crops.

An individual-based growth and competition model for coastal redwood forest restoration

USGS Publications Warehouse

van Mantgem, Phillip J.; Das, Adrian J.

2014-01-01

Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

Mapping of Biophysical Parameters of Rice Agriculture System from Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Duta, Subashisa

2017-04-01

Chlorophyll, nitrogen and leaf water content are the most essential parameters for paddy crop growth. Ground hyperspectral observations were collected at canopy level during critical growth period of rice by using hand held Spectroradiometer. Chemical analysis was carried out to quantify the total chlorophyll, nitrogen and leaf water content. By exploiting the in-situ hyperspectral measurements, regression models were established between each of the crop growth parameters and the spectral indices specifically designed for chlorophyll, nitrogen and water stress. Narrow band vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the modified simple ratio (SR) and leaf nitrogen concentration (LNC) predictive index models, which followed a linear and nonlinear relationship respectively, produced satisfactory results in predicting rice nitrogen content from hyperspectral imagery. The presently developed model was compared with other models proposed by researchers. It was ascertained that, nitrogen content varied widely from 1-4 percentage and only 2-3 percentage for paddy crop using present modified index models and well-known predicted Tian et al. (2011) model respectively. The modified present LNC index model performed better than the established Tian et al. (2011) model as far as the estimated nitrogen content from Hyperion imagery was concerned. Moreover, within the observed chlorophyll range attained from the rice genotypes cultivated in the studied rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) accomplished satisfactory results in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content widely varied from 1.77-5.81 mg/g (LNC), 3.0-13 mg/g (OASVI) and 2.90-5.40 mg/g (MTCI). Following the similar guideline, it was found that normalized difference water index (NDWI) and normalized difference infrared index (NDII) predictive models demonstrated the spatial variability of leaf water content from 40 percentage to 90 percentage in the same rice agriculture system which has a good agreement with observed in-situ leaf water measurements. The spatial information of these parameters will be useful for crop nutrient management and yield forecasting, and will serve as inputs to various crop-forecasting models for developing a precision rice agriculture system. Key words: Rice agriculture system, nitrogen, chlorophyll, leaf water content, vegetation index

Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties

USDA-ARS?s Scientific Manuscript database

Tillage is an important procedure for modifying the soil environment in order to enhance crop growth and conserve soil and water resources. Process-based models of crop production are widely used in decision support, but few explicitly simulate tillage. The Cropping Systems Model (CSM) was modified ...

Spatial models reveal the microclimatic buffering capacity of old-growth forests

Treesearch

Sarah J. K. Frey; Adam S. Hadley; Sherri L. Johnson; Mark Schulze; Julia A. Jones; Matthew. G. Betts

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by...

Ecological invasion, roughened fronts, and a competitor's extreme advance: integrating stochastic spatial-growth models.

PubMed

O'Malley, Lauren; Korniss, G; Caraco, Thomas

2009-07-01

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibits universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.

Entanglement growth after a global quench in free scalar field theory

DOE PAGES

Cotler, Jordan S.; Hertzberg, Mark P.; Mezei, Márk; ...

2016-11-28

We compute the entanglement and Rényi entropy growth after a global quench in various dimensions in free scalar field theory. We study two types of quenches: a boundary state quench and a global mass quench. Both of these quenches are investigated for a strip geometry in 1, 2, and 3 spatial dimensions, and for a spherical geometry in 2 and 3 spatial dimensions. We compare the numerical results for massless free scalars in these geometries with the predictions of the analytical quasiparticle model based on EPR pairs, and find excellent agreement in the limit of large region sizes. As amore » result, at subleading order in the region size, we observe an anomalous logarithmic growth of entanglement coming from the zero mode of the scalar.« less

Entanglement growth after a global quench in free scalar field theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cotler, Jordan S.; Hertzberg, Mark P.; Mezei, Márk

We compute the entanglement and Rényi entropy growth after a global quench in various dimensions in free scalar field theory. We study two types of quenches: a boundary state quench and a global mass quench. Both of these quenches are investigated for a strip geometry in 1, 2, and 3 spatial dimensions, and for a spherical geometry in 2 and 3 spatial dimensions. We compare the numerical results for massless free scalars in these geometries with the predictions of the analytical quasiparticle model based on EPR pairs, and find excellent agreement in the limit of large region sizes. As amore » result, at subleading order in the region size, we observe an anomalous logarithmic growth of entanglement coming from the zero mode of the scalar.« less

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.

Evaluating land-use change scenarios for the Puget Sound Basin, Washington, within the ecosystem recovery target model-based framework

USGS Publications Warehouse

Villarreal, Miguel; Labiosa, Bill; Aiello, Danielle

2017-05-23

The Puget Sound Basin, Washington, has experienced rapid urban growth in recent decades, with varying impacts to local ecosystems and natural resources. To plan for future growth, land managers often use scenarios to assess how the pattern and volume of growth may affect natural resources. Using three different land-management scenarios for the years 2000–2060, we assessed various spatial patterns of urban growth relative to maps depicting a model-based characterization of the ecological integrity and recent development pressure of individual land parcels. The three scenarios depict future trajectories of land-use change under alternative management strategies—status quo, managed growth, and unconstrained growth. The resulting analysis offers a preliminary assessment of how future growth patterns in the Puget Sound Basin may impact land targeted for conservation and how short-term metrics of land-development pressure compare to longer term growth projections.

Model of Fission Yeast Cell Shape Driven by Membrane-Bound Growth Factors and the Cytoskeleton

PubMed Central

Drake, Tyler; Vavylonis, Dimitrios

2013-01-01

Fission yeast serves as a model for how cellular polarization machinery consisting of signaling molecules and the actin and microtubule cytoskeleton regulates cell shape. In this work, we develop mathematical models to investigate how these cells maintain a tubular shape of approximately constant diameter. Many studies identify active Cdc42, found in a cap at the inner membrane of growing cell tips, as an important regulator of local cell wall remodeling, likely through control of exocyst tethering and the targeting of other polarity-enhancing structures. First, we show that a computational model with Cdc42-dependent local cell wall remodeling under turgor pressure predicts a relationship between spatial extent of growth signal and cell diameter that is in agreement with prior experiments. Second, we model the consequences of feedback between cell shape and distribution of Cdc42 growth signal at cell tips. We show that stability of cell diameter over successive cell divisions places restrictions on their mutual dependence. We argue that simple models where the spatial extent of the tip growth signal relies solely on geometrical alignment of confined microtubules might lead to unstable width regulation. Third, we study a computational model that combines a growth signal distributed over a characteristic length scale (as, for example, by a reaction-diffusion mechanism) with an axis-sensing microtubules system that places landmarks at positions where microtubule tips touch the cortex. A two-dimensional implementation of this model leads to stable cell diameter for a wide range of parameters. Changes to the parameters of this model reproduce straight, bent, and bulged cell shapes, and we discuss how this model is consistent with other observed cell shapes in mutants. Our work provides an initial quantitative framework for understanding the regulation of cell shape in fission yeast, and a scaffold for understanding this process on a more molecular level in the future. PMID:24146607

Pair and triplet approximation of a spatial lattice population model with multiscale dispersal using Markov chains for estimating spatial autocorrelation.

PubMed

Hiebeler, David E; Millett, Nicholas E

2011-06-21

We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fractal dimension and universality in avascular tumor growth

NASA Astrophysics Data System (ADS)

Ribeiro, Fabiano L.; dos Santos, Renato Vieira; Mata, Angélica S.

2017-04-01

For years, the comprehension of the tumor growth process has been intriguing scientists. New research has been constantly required to better understand the complexity of this phenomenon. In this paper, we propose a mathematical model that describes the properties, already known empirically, of avascular tumor growth. We present, from an individual-level (microscopic) framework, an explanation of some phenomenological (macroscopic) aspects of tumors, such as their spatial form and the way they develop. Our approach is based on competitive interaction between the cells. This simple rule makes the model able to reproduce evidence observed in real tumors, such as exponential growth in their early stage followed by power-law growth. The model also reproduces (i) the fractal-space distribution of tumor cells and (ii) the universal growth behavior observed in both animals and tumors. Our analyses suggest that the universal similarity between tumor and animal growth comes from the fact that both can be described by the same dynamic equation—the Bertalanffy-Richards model—even if they do not necessarily share the same biological properties.

Spatially distributed model calibration of flood inundation guided by consequences such as loss of property

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Beven, K. J.; Frodsham, K.; Matgen, P.

2005-12-01

Flood inundation models play an increasingly important role in assessing flood risk. The growth of 2D inundation models that are intimately related to raster maps of floodplains is occurring at the same time as an increase in the availability of 2D remote data (e.g. SAR images and aerial photographs), against which model performancee can be evaluated. This requires new techniques to be explored in order to evaluate model performance in two dimensional space. In this paper we present a fuzzified pattern matching algorithm which compares favorably to a set of traditional measures. However, we further argue that model calibration has to go beyond the comparison of physical properties and should demonstrate how a weighting towards consequences, such as loss of property, can enhance model focus and prediction. Indeed, it will be necessary to abandon a fully spatial comparison in many scenarios to concentrate the model calibration exercise on specific points such as hospitals, police stations or emergency response centers. It can be shown that such point evaluations lead to significantly different flood hazard maps due to the averaging effect of a spatial performance measure. A strategy to balance the different needs (accuracy at certain spatial points and acceptable spatial performance) has to be based in a public and political decision making process.

Forest canopy growth dynamic modeling based on remote sensing prodcuts and meteorological data in Daxing'anling of Northeast China

NASA Astrophysics Data System (ADS)

Wu, Qiaoli; Song, Jinling; Wang, Jindi; Xiao, Zhiqiang

2014-11-01

Leaf Area Index (LAI) is an important biophysical variable for vegetation. Compared with vegetation indexes like NDVI and EVI, LAI is more capable of monitoring forest canopy growth quantitatively. GLASS LAI is a spatially complete and temporally continuous product derived from AVHRR and MODIS reflectance data. In this paper, we present the approach to build dynamic LAI growth models for young and mature Larix gmelinii forest in north Daxing'anling in Inner Mongolia of China using the Dynamic Harmonic Regression (DHR) model and Double Logistic (D-L) model respectively, based on the time series extracted from multi-temporal GLASS LAI data. Meanwhile we used the dynamic threshold method to attract the key phenological phases of Larix gmelinii forest from the simulated time series. Then, through the relationship analysis between phenological phases and the meteorological factors, we found that the annual peak LAI and the annual maximum temperature have a good correlation coefficient. The results indicate this forest canopy growth dynamic model to be very effective in predicting forest canopy LAI growth and extracting forest canopy LAI growth dynamic.

Abiotic and biotic controls of spatial pattern at alpine treeline

USGS Publications Warehouse

Malanson, George P.; Xiao, Ningchuan; Alftine, K.J.; Bekker, Mathew; Butler, David R.; Brown, Daniel G.; Cairns, David M.; Fagre, Daniel; Walsh, Stephen J.

2000-01-01

At alpine treeline, trees and krummholz forms affect the environment in ways that increase their growth and reproduction. We assess the way in which these positive feedbacks combine in spatial patterns to alter the environment in the neighborhood of existing plants. The research is significant because areas of alpine tundra are susceptible to encroachment by woody species as climate changes. Moreover, understanding the general processes of plant invasion is important. The importance of spatial pattern has been recognized, but the spatial pattern of positive feedbacks per se has not been explored in depth. We present a linked set of models of vegetation change at an alpine forest-tundra ecotone. Our aim is to create models that are as simple as possible in order to test specific hypotheses. We present results from a model of the resource averaging hypothesis and the positive feedback switch hypothesis of treelines. We compare the patterns generated by the models to patterns observed in fine scale remotely sensed data.

The biogeodynamics of microbial landscapes

NASA Astrophysics Data System (ADS)

Battin, T. J.; Hödl, I.; Bertuzzo, E.; Mari, L.; Suweis, S. S.; Rinaldo, A.

2011-12-01

Spatial configuration is fundamental in defining the structural and functional properties of biological systems. Biofilms, surface-attached and matrix-enclosed microorganisms, are a striking example of spatial organisation. Coupled biotic and abiotic processes shape the spatial organisation across scales of the landscapes formed by these benthic biofilms in streams and rivers. Experimenting with such biofilms in streams, we found that, depending on the streambed topography and the related hydrodynamic microenvironment, biofilm landscapes form increasingly diverging spatial patterns as they grow. Strikingly, however, cluster size distributions tend to converge even in contrasting hydrodynamic microenvironments. To reproduce the observed cluster size distributions we used a continuous, size-structured population model. The model accounts for the formation, growth, erosion and merging of biofilm clusters. Our results suggest not only that hydrodynamic forcing induce the diverging patterning of the microbial landscape, but also that microorganisms have developed strategies to equally exploit spatial resources independently of the physical structure of the microenvironment where they live.

A systematic intercomparison of regional flood frequency analysis models in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, Daniele; Laio, Francesco; Claps, Pierluigi

2015-04-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve (or other discharge-related variables), based on the fundamental concept of substituting temporal information at a site (no data or short time series) by exploiting observations at other sites (spatial information). Different RFA paradigms exist, depending on the way the information is transferred to the site of interest. Despite the wide use of such methodology, a systematic comparison between these paradigms has not been performed. The aim of this study is to provide a framework wherein carrying out the intercomparison: we thus synthetically generate data through Monte Carlo simulations for a number of (virtual) stations, following a GEV parent distribution; different scenarios can be created to represent different spatial heterogeneity patterns by manipulating the parameters of the parent distribution at each station (e.g. with a linear variation in space of the shape parameter of the GEV). A special case is the homogeneous scenario where each station record is sampled from the same parent distribution. For each scenario and each simulation, different regional models are applied to evaluate the 200-year growth factor at each station. Results are than compared to the exact growth factor of each station, which is known in our virtual world. Considered regional approaches include: (i) a single growth curve for the whole region; (ii) a multiple-region model based on cluster analysis which search for an adequate number of homogeneous subregions; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially-smooth estimation procedure based on linear regressions.. A further benchmark model is the at-site estimate based on the analysis of the local record. A comprehensive analysis of the results of the simulations shows that, if the scenario is homogeneous (no spatial variability), all the regional approaches have comparable performances. Moreover, as expected, regional estimates are much more reliable than the at-site estimates. If the scenario is heterogeneous, the performances of the regional models depend on the pattern of heterogeneity; in general, however, the spatially-smooth regional approach performs better than the others, and its performances improve for increasing record lengths. For heterogeneous scenarios, the at-site estimates appear to be comparably more efficient than in the homogeneous case, and in general less biased than the regional estimates.

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru

PubMed Central

Arima, E. Y.

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200–300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads. PMID:27010739

A Spatial Probit Econometric Model of Land Change: The Case of Infrastructure Development in Western Amazonia, Peru.

PubMed

Arima, E Y

2016-01-01

Tropical forests are now at the center stage of climate mitigation policies worldwide given their roles as sources of carbon emissions resulting from deforestation and forest degradation. Although the international community has created mechanisms such as REDD+ to reduce those emissions, developing tropical countries continue to invest in infrastructure development in an effort to spur economic growth. Construction of roads in particular is known to be an important driver of deforestation. This article simulates the impact of road construction on deforestation in Western Amazonia, Peru, and quantifies the amount of carbon emissions associated with projected deforestation. To accomplish this objective, the article adopts a Bayesian probit land change model in which spatial dependencies are defined between regions or groups of pixels instead of between individual pixels, thereby reducing computational requirements. It also compares and contrasts the patterns of deforestation predicted by both spatial and non-spatial probit models. The spatial model replicates complex patterns of deforestation whereas the non-spatial model fails to do so. In terms of policy, both models suggest that road construction will increase deforestation by a modest amount, between 200-300 km2. This translates into aboveground carbon emissions of 1.36 and 1.85 x 106 tons. However, recent introduction of palm oil in the region serves as a cautionary example that the models may be underestimating the impact of roads.

Locally adaptive, spatially explicit projection of US population for 2030 and 2050.

PubMed

McKee, Jacob J; Rose, Amy N; Bright, Edward A; Huynh, Timmy; Bhaduri, Budhendra L

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

Modeling tree crown dynamics with 3D partial differential equations.

PubMed

Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry

2014-01-01

We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.

Large scale pre-rain vegetation green up across Africa.

PubMed

Adole, Tracy; Dash, Jadunandan; Atkinson, Peter M

2018-05-16

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of pre-rain flush effects in some parts of Africa. The spatial extent of this pre-rain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa, and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of pre-rain green-up over Africa than previously reported, with pre-rain green-up being the norm rather than the exception. We also show the relative sparsity of post-rain green-up, confined largely to the Sudano-Sahel region. While the pre-rain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Spatial landscape model to characterize biological diversity using R statistical computing environment.

PubMed

Singh, Hariom; Garg, R D; Karnatak, Harish C; Roy, Arijit

2018-01-15

Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relating structural growth environment to white spruce sapling establishment at the Forest-Tundra Ecotone

NASA Astrophysics Data System (ADS)

Maguire, A.; Boelman, N.; Griffin, K. L.; Jensen, J.; Hiers, E.; Johnson, D. M.; Vierling, L. A.; Eitel, J.

2017-12-01

The effect of climate change on treeline position at the latitudinal Forest-Tundra ecotone (FTE) is poorly understood. While the FTE is expansive (stretching 13,000 km acros the panarctic), understanding relationships between climate and tree function may depend on very fine scale processes. High resolution tools are therefore needed to appropriately characterize the leading (northernmost) edge of the FTE. We hypothesized that microstructural metrics obtainable from lidar remote sensing may explain variation in the physical growth environment that governs sapling establishment. To test our hypothesis, we used terrestrial laser scanning (TLS) to collect highly spatially resolved 3-D structural information of white spruce (Picea glauca) saplings and their aboveground growth environment at the leading edge of a FTE in northern Alaska and Northwest Territories, Canada. Coordinates of sapling locations were extracted from the 3-D TLS data. Within each sampling plot, 20 sets of coordinates were randomly selected from regions where no saplings were present. Ground roughness, canopy roughness, average aspect, average slope, average curvature, wind shelter index, and wetness indexwere extracted from point clouds within a variable radius from all coordinates. Generalized linear models (GLM) were fit to determine which microstructural metrics were most strongly associated with sapling establishment. Preliminary analyses of three plots suggest that vegetation roughness, wetness index, ground roughness, and slope were the most important terrain metrics governing sapling presence (Figure 1). Comprehensive analyses will include eight plots and GLMs optimized for scale at which structural parameters affect sapling establishment. Spatial autocorrelation of sample locations will be accounted for in models. Because these analyses address how the physical growth environment affects sapling establishment, model outputs will provide information for improving understanding of the ecological processes that regulate treeline dynamics. Moreover, establishing relationships between the remotely sensed structural growth environment and tree establishment provides new ways of spatially scaling across larger areas to study ecological change at the FTE.

Mass and energy budgets of animals: Behavioral and ecological implications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porter, W.P.

1991-11-01

The two major aims of our lab are as follows: First, to develop and field-test general mechanistic models that predict animal life history characteristics as influenced by climate and the physical, physiological behavioral characteristics of species. This involves: understanding how animal time and energy budgets are affected by climate and animal properties; predicting growth and reproductive potential from time and energy budgets; predicting mortality based on climate and time and energy budgets; and linking these individual based models to population dynamics. Second to conduct empirical studies of animal physiological ecology, particularly the effects of temperature on time and energy budgets.more » The physiological ecology of individual animals is the key link between the physical environment and population-level phenomena. We address the macroclimate to microclimate linkage on a broad spatial scale; address the links between individuals and population dynamics for lizard species; test the endotherm energetics and behavior model using beaver; address the spatial variation in climate and its effects on individual energetics, growth and reproduction; and address patchiness in the environment and constraints they may impose on individual energetics, growth and reproduction. These projects are described individually in the following section. 24 refs., 9 figs.« less

Temporal slow-growth formulation for direct numerical simulation of compressible wall-bounded flows

NASA Astrophysics Data System (ADS)

Topalian, Victor; Oliver, Todd A.; Ulerich, Rhys; Moser, Robert D.

2017-08-01

A slow-growth formulation for DNS of wall-bounded turbulent flow is developed and demonstrated to enable extension of slow-growth modeling concepts to wall-bounded flows with complex physics. As in previous slow-growth approaches, the formulation assumes scale separation between the fast scales of turbulence and the slow evolution of statistics such as the mean flow. This separation enables the development of approaches where the fast scales of turbulence are directly simulated while the forcing provided by the slow evolution is modeled. The resulting model admits periodic boundary conditions in the streamwise direction, which avoids the need for extremely long domains and complex inflow conditions that typically accompany spatially developing simulations. Further, it enables the use of efficient Fourier numerics. Unlike previous approaches [Guarini, Moser, Shariff, and Wray, J. Fluid Mech. 414, 1 (2000), 10.1017/S0022112000008466; Maeder, Adams, and Kleiser, J. Fluid Mech. 429, 187 (2001), 10.1017/S0022112000002718; Spalart, J. Fluid Mech. 187, 61 (1988), 10.1017/S0022112088000345], the present approach is based on a temporally evolving boundary layer and is specifically tailored to give results for calibration and validation of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The use of a temporal homogenization simplifies the modeling, enabling straightforward extension to flows with complicating features, including cold and blowing walls. To generate data useful for calibration and validation of RANS models, special care is taken to ensure that the mean slow-growth forcing is closed in terms of the mean and other quantities that appear in standard RANS models, ensuring that there is no confounding between typical RANS closures and additional closures required for the slow-growth problem. The performance of the method is demonstrated on two problems: an essentially incompressible, zero-pressure-gradient boundary layer and a transonic boundary layer over a cooled, transpiring wall. The results show that the approach produces flows that are qualitatively similar to other slow-growth methods as well as spatially developing simulations and that the method can be a useful tool in investigating wall-bounded flows with complex physics.

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William L.; Khan, Maudood N.

2006-01-01

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Modelling dwarf mistletoe at three scales: life history, ballistics and contagion

Treesearch

Donald C. E. Robinson; Brian W. Geils

2006-01-01

The epidemiology of dwarf mistletoe (Arceuthobium) is simulated for the reproduction, dispersal, and spatial patterns of these plant pathogens on conifer trees. A conceptual model for mistletoe spread and intensification is coded as sets of related subprograms that link to either of two individual-tree growth models (FVS and TASS) used by managers to develop...

Plant growth and architectural modelling and its applications

PubMed Central

Guo, Yan; Fourcaud, Thierry; Jaeger, Marc; Zhang, Xiaopeng; Li, Baoguo

2011-01-01

Over the last decade, a growing number of scientists around the world have invested in research on plant growth and architectural modelling and applications (often abbreviated to plant modelling and applications, PMA). By combining physical and biological processes, spatially explicit models have shown their ability to help in understanding plant–environment interactions. This Special Issue on plant growth modelling presents new information within this topic, which are summarized in this preface. Research results for a variety of plant species growing in the field, in greenhouses and in natural environments are presented. Various models and simulation platforms are developed in this field of research, opening new features to a wider community of researchers and end users. New modelling technologies relating to the structure and function of plant shoots and root systems are explored from the cellular to the whole-plant and plant-community levels. PMID:21638797

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

A numerical study of biofilm growth in a microgravity environment

NASA Astrophysics Data System (ADS)

Aristotelous, A. C.; Papanicolaou, N. C.

2017-10-01

A mathematical model is proposed to investigate the effect of microgravity on biofilm growth. We examine the case of biofilm suspended in a quiescent aqueous nutrient solution contained in a rectangular tank. The bacterial colony is assumed to follow logistic growth whereas nutrient absorption is assumed to follow Monod kinetics. The problem is modeled by a coupled system of nonlinear partial differential equations in two spatial dimensions solved using the Discontinuous Galerkin Finite Element method. Nutrient and biofilm concentrations are computed in microgravity and normal gravity conditions. A preliminary quantitative relationship between the biofilm concentration and the gravity field intensity is derived.

Grain Growth and Precipitation Behavior of Iridium Alloy DOP-26 During Long Term Aging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, Dean T.; Muralidharan, Govindarajan; Fox, Ethan E.

The influence of long term aging on grain growth and precipitate sizes and spatial distribution in iridium alloy DOP-26 was studied. Samples of DOP-26 were fabricated using the new process, recrystallized for 1 hour (h) at 1375 C, then aged at either 1300, 1400, or 1500 C for times ranging from 50 to 10,000 h. Grain size measurements (vertical and horizontal mean linear intercept and horizontal and vertical projection) and analyses of iridium-thorium precipitates (size and spacing) were made on the longitudinal, transverse, and rolling surfaces of the as-recrystallized and aged specimens from which the two-dimensional spatial distribution and meanmore » sizes of the precipitates were obtained. The results obtained from this study are intended to provide input to grain growth models.« less

The Role of Mechanical Variance and Spatial Clustering on the Likelihood of Tumor Incidence and Growth

NASA Astrophysics Data System (ADS)

Mirzakhel, Zibah

When considering factors that contribute to cancer progression, modifications to both the biological and mechanical pathways play significant roles. However, less attention is placed on how the mechanical pathways can specifically contribute to cancerous behavior. Experimental studies have found that malignant cells are significantly softer than healthy, normal cells. In a tissue environment where healthy or malignant cells exist, a distribution of cell stiffness values is observed, with the mean values used to differentiate between these two populations. Rather than focus on the mean values, emphasis will be placed on the distribution, where instances of soft and stiff cells exist in the healthy tissue environment. Since cell deformability is a trait associated with cancer, the question arises as to whether the mechanical variation observed in healthy tissue cell stiffness distributions can influence any instances of tumor growth. To approach this, a 3D discrete model of cells is used, able to monitor and predict the behavior of individual cells while determining any instances of tumor growth in a healthy tissue. In addition to the mechanical variance, the spatial arrangement of cells will also be modeled, as cell interaction could further implicate any incidences of tumor-like malignant populations within the tissue. Results have shown that the likelihood of tumor incidence is driven by both by the increases in the mechanical variation in the distributions as well as larger clustering of cells that are mechanically similar, quantified primarily through higher proliferation rates of tumor-like soft cells. This can be observed though prominent negative shifts in the mean of the distribution, as it begins to transition and show instances of earlystage tumor growth. The model reveals the impact that both the mechanical variation and spatial arrangement of cells has on tumor progression, suggesting the use of these parameters as potential novel biomarkers. With a patient-specific approach in mind, the model may be applied for early-stage cancer detection, useful to establish a timeline on tumor progression.

ABOVE- AND BELOWGROUND CONTROLS ON FOREST TREE GROWTH, MORTALITY AND SPATIAL PATTERN

EPA Science Inventory

We investigated the relative importance of above- and belowground competition in controlling growth, mortality and spatial patterns of trees in a nitrogen-limited, old-growth forest in western Oregon. To assess the effects of competition for light, we applied a spatially-explici...

Hydraulic redistribution of soil water in two old-growth coniferous forests: quantifying patterns and controls.

Treesearch

J.M. Warren; F.C. Meinzer; J.R. Brooks; J.-C. Domec; R. Coulombe

2006-01-01

We incorporated soil/plant biophysical properties into a simple model to predict seasonal trajectories of hydraulic redistribution (HR). We measured soil water content, water potential root conductivity, and climate across multiple years in two old-growth coniferous forests. The HR variability within sites (0 to 0.5 mm/d) was linked to spatial patterns of roots, soil...

Finite-size effects on bacterial population expansion under controlled flow conditions

NASA Astrophysics Data System (ADS)

Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc; Toschi, Federico

2017-03-01

The expansion of biological species in natural environments is usually described as the combined effect of individual spatial dispersal and growth. In the case of aquatic ecosystems flow transport can also be extremely relevant as an extra, advection induced, dispersal factor. We designed and assembled a dedicated microfluidic device to control and quantify the expansion of populations of E. coli bacteria under both co-flowing and counter-flowing conditions, measuring the front speed at varying intensity of the imposed flow. At variance with respect to the case of classic advective-reactive-diffusive chemical fronts, we measure that almost irrespective of the counter-flow velocity, the front speed remains finite at a constant positive value. A simple model incorporating growth, dispersion and drift on finite-size hard beads allows to explain this finding as due to a finite volume effect of the bacteria. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) that ignore the finite size of organisms may be inaccurate to describe the physics of spatial growth dynamics of bacteria.

Spatial variability and macro‐scale drivers of growth for native and introduced Flathead Catfish populations

USGS Publications Warehouse

Massie, Danielle L.; Smith, Geoffrey; Bonvechio, Timothy F.; Bunch, Aaron J.; Lucchesi, David O.; Wagner, Tyler

2018-01-01

Quantifying spatial variability in fish growth and identifying large‐scale drivers of growth are fundamental to many conservation and management decisions. Although fish growth studies often focus on a single population, it is becoming increasingly clear that large‐scale studies are likely needed for addressing transboundary management needs. This is particularly true for species with high recreational value and for those with negative ecological consequences when introduced outside of their native range, such as the Flathead Catfish Pylodictis olivaris. This study quantified growth variability of the Flathead Catfish across a large portion of its contemporary range to determine whether growth differences existed between habitat types (i.e., reservoirs and rivers) and between native and introduced populations. Additionally, we investigated whether growth parameters varied as a function of latitude and time since introduction (for introduced populations). Length‐at‐age data from 26 populations across 11 states in the USA were modeled using a Bayesian hierarchical von Bertalanffy growth model. Population‐specific growth trajectories revealed large variation in Flathead Catfish growth and relatively high uncertainty in growth parameters for some populations. Relatively high uncertainty was also evident when comparing populations and when quantifying large‐scale patterns. Growth parameters (Brody growth coefficient [K] and theoretical maximum average length [L∞]) were not different (based on overlapping 90% credible intervals) between habitat types or between native and introduced populations. For populations within the introduced range of Flathead Catfish, latitude was negatively correlated with K. For native populations, we estimated an 85% probability that L∞ estimates were negatively correlated with latitude. Contrary to predictions, time since introduction was not correlated with growth parameters in introduced populations of Flathead Catfish. Results of this study suggest that Flathead Catfish growth patterns are likely shaped more strongly by finer‐scale processes (e.g., exploitation or prey abundances) as opposed to macro‐scale drivers.

A Validated Multiscale In-Silico Model for Mechano-sensitive Tumour Angiogenesis and Growth

PubMed Central

Loizidou, Marilena; Stylianopoulos, Triantafyllos; Hawkes, David J.

2017-01-01

Vascularisation is a key feature of cancer growth, invasion and metastasis. To better understand the governing biophysical processes and their relative importance, it is instructive to develop physiologically representative mathematical models with which to compare to experimental data. Previous studies have successfully applied this approach to test the effect of various biochemical factors on tumour growth and angiogenesis. However, these models do not account for the experimentally observed dependency of angiogenic network evolution on growth-induced solid stresses. This work introduces two novel features: the effects of hapto- and mechanotaxis on vessel sprouting, and mechano-sensitive dynamic vascular remodelling. The proposed three-dimensional, multiscale, in-silico model of dynamically coupled angiogenic tumour growth is specified to in-vivo and in-vitro data, chosen, where possible, to provide a physiologically consistent description. The model is then validated against in-vivo data from murine mammary carcinomas, with particular focus placed on identifying the influence of mechanical factors. Crucially, we find that it is necessary to include hapto- and mechanotaxis to recapitulate observed time-varying spatial distributions of angiogenic vasculature. PMID:28125582

Analytical approximation of a stochastic, spatial simulation model of fire and forest landscape dynamics

Treesearch

A.J. Tepley; E.A. Thomann

2012-01-01

Recent increases in computation power have prompted enormous growth in the use of simulation models in ecological research. These models are valued for their ability to account for much of the ecological complexity found in field studies, but this ability usually comes at the cost of losing transparency into how the models work. In order to foster greater understanding...

Combining Remote Sensing imagery of both fine and coarse spatial resolution to Estimate Crop Evapotranspiration and quantifying its Influence on Crop Growth Monitoring.

NASA Astrophysics Data System (ADS)

Sepulcre-Cantó, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio; Duveiller, Gregory; Piccard, Isabelle; de Wit, Allard; Tychon, Bernard; Bakary, Djaby; Defourny, Pierre

2010-05-01

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. Evapotranspiration (ET) is a valuable parameter in the crop monitoring context since it provides information on the plant water stress status, which strongly influences crop development and, by extension, crop yield. To assess crop evapotranspiration over the GLOBAM study areas (300x300 km sites in Northern Europe and Central Ethiopia), a Soil-Vegetation-Atmosphere Transfer (SVAT) model forced with remote sensing and numerical weather prediction data has been used. This model runs at pre-operational level in the framework of the EUMETSAT LSA-SAF (Land Surface Analysis Satellite Application Facility) using SEVIRI and ECMWF data, as well as the ECOCLIMAP database to characterize the vegetation. The model generates ET images at the Meteosat Second Generation (MSG) spatial resolution (3 km at subsatellite point),with a temporal resolution of 30 min and monitors the entire MSG disk which covers Europe, Africa and part of Sud America . The SVAT model was run for 2007 using two approaches. The first approach is at the standard pre-operational mode. The second incorporates remote sensing information at various spatial resolutions going from LANDSAT (30m) to SEVIRI (3-5 km) passing by AWIFS (56m) and MODIS (250m). Fine spatial resolution data consists of crop type classification which enable to identify areas where pure crop specific MODIS time series can be compiled and used to derive Leaf Area Index estimations for the most important crops (wheat and maize). The use of this information allowed to characterize the type of vegetation and its state of development in a more accurate way than using the ECOCLIMAP database. Finally, the CASA method was applied using the evapotranspiration images with FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) images from LSA-SAF to obtain Dry Matter Productivity (DMP) and crop yield. The potential of using evapotranspiration obtained from remote sensing in crop growth modeling is studied and discussed. Results of comparing the evapotranspiration obtained with ground truth data are shown as well as the influence of using high resolution information to characterize the vegetation in the evapotranspiration estimation. The values of DMP and yield obtained with the CASA method are compared with those obtained using crop growth modeling and field data, showing the potential of using this simplified remote sensing method for crop monitoring and yield forecasting. This methodology could be applied in an operative way to the entire MSG disk, allowing the continuous crop growth monitoring.

Assessment of the ripple effects and spatial heterogeneity of total losses in the capital of China after a great catastrophic shock

NASA Astrophysics Data System (ADS)

Zhang, Zhengtao; Li, Ning; Xie, Wei; Liu, Yu; Feng, Jieling; Chen, Xi; Liu, Li

2017-03-01

The total losses caused by natural disasters have spatial heterogeneity due to the different economic development levels inside the disaster-hit areas. This paper uses scenarios of direct economic loss to introduce the sectors' losses caused by the 2008 Wenchuan earthquake (2008 WCE) in Beijing, utilizing the Adaptive Regional Input-Output (ARIO) model and the Inter-regional ripple effect (IRRE) model. The purpose is to assess the ripple effects of indirect economic loss and spatial heterogeneity of both direct and indirect economic loss at the scale of the smallest administrative divisions of China (streets, villages, and towns). The results indicate that the district of Beijing with the most severe indirect economic loss is the Chaoyang District; the finance and insurance industry (15, see Table 1) of Chaowai Street suffers the most in the Chaoyang District, which is 1.46 times that of its direct economic loss. During 2008-2014, the average annual GDP (gross domestic product) growth rate of Beijing was decreased 3.63 % by the catastrophe. Compared with the 8 % of GDP growth rate target, the decreasing GDP growth rate is a significant and noticeable economic impact, and it can be efficiently mitigated by increasing rescue effort and by supporting the industries which are located in the seriously damaged regions.

Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

NASA Astrophysics Data System (ADS)

Gruber, A.; Crow, W. T.; Dorigo, W. A.

2018-02-01

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape.

PubMed

Chambers, Jeffrey Q; Negron-Juarez, Robinson I; Marra, Daniel Magnabosco; Di Vittorio, Alan; Tews, Joerg; Roberts, Dar; Ribeiro, Gabriel H P M; Trumbore, Susan E; Higuchi, Niro

2013-03-05

Old-growth forest ecosystems comprise a mosaic of patches in different successional stages, with the fraction of the landscape in any particular state relatively constant over large temporal and spatial scales. The size distribution and return frequency of disturbance events, and subsequent recovery processes, determine to a large extent the spatial scale over which this old-growth steady state develops. Here, we characterize this mosaic for a Central Amazon forest by integrating field plot data, remote sensing disturbance probability distribution functions, and individual-based simulation modeling. Results demonstrate that a steady state of patches of varying successional age occurs over a relatively large spatial scale, with important implications for detecting temporal trends on plots that sample a small fraction of the landscape. Long highly significant stochastic runs averaging 1.0 Mg biomass⋅ha(-1)⋅y(-1) were often punctuated by episodic disturbance events, resulting in a sawtooth time series of hectare-scale tree biomass. To maximize the detection of temporal trends for this Central Amazon site (e.g., driven by CO2 fertilization), plots larger than 10 ha would provide the greatest sensitivity. A model-based analysis of fractional mortality across all gap sizes demonstrated that 9.1-16.9% of tree mortality was missing from plot-based approaches, underscoring the need to combine plot and remote-sensing methods for estimating net landscape carbon balance. Old-growth tropical forests can exhibit complex large-scale structure driven by disturbance and recovery cycles, with ecosystem and community attributes of hectare-scale plots exhibiting continuous dynamic departures from a steady-state condition.

Spatial competition dynamics between reef corals under ocean acidification.

PubMed

Horwitz, Rael; Hoogenboom, Mia O; Fine, Maoz

2017-01-09

Climate change, including ocean acidification (OA), represents a major threat to coral-reef ecosystems. Although previous experiments have shown that OA can negatively affect the fitness of reef corals, these have not included the long-term effects of competition for space on coral growth rates. Our multispecies year-long study subjected reef-building corals from the Gulf of Aqaba (Red Sea) to competitive interactions under present-day ocean pH (pH 8.1) and predicted end-of-century ocean pH (pH 7.6). Results showed coral growth is significantly impeded by OA under intraspecific competition for five out of six study species. Reduced growth from OA, however, is negligible when growth is already suppressed in the presence of interspecific competition. Using a spatial competition model, our analysis indicates shifts in the competitive hierarchy and a decrease in overall coral cover under lowered pH. Collectively, our case study demonstrates how modified competitive performance under increasing OA will in all likelihood change the composition, structure and functionality of reef coral communities.

Spatial competition dynamics between reef corals under ocean acidification

NASA Astrophysics Data System (ADS)

Horwitz, Rael; Hoogenboom, Mia O.; Fine, Maoz

2017-01-01

Climate change, including ocean acidification (OA), represents a major threat to coral-reef ecosystems. Although previous experiments have shown that OA can negatively affect the fitness of reef corals, these have not included the long-term effects of competition for space on coral growth rates. Our multispecies year-long study subjected reef-building corals from the Gulf of Aqaba (Red Sea) to competitive interactions under present-day ocean pH (pH 8.1) and predicted end-of-century ocean pH (pH 7.6). Results showed coral growth is significantly impeded by OA under intraspecific competition for five out of six study species. Reduced growth from OA, however, is negligible when growth is already suppressed in the presence of interspecific competition. Using a spatial competition model, our analysis indicates shifts in the competitive hierarchy and a decrease in overall coral cover under lowered pH. Collectively, our case study demonstrates how modified competitive performance under increasing OA will in all likelihood change the composition, structure and functionality of reef coral communities.

Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

USDA-ARS?s Scientific Manuscript database

Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

Assimilation of spatially sparse in situ soil moisture networks into a continuous model domain

USDA-ARS?s Scientific Manuscript database

Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ...

Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data

Treesearch

Chad Babcock; Andrew O. Finley; Bruce D. Cook; Aaron Weiskittel; Christopher W. Woodall

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB...

Mathematical models to characterize early epidemic growth: A Review

PubMed Central

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-01-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-15 Ebola epidemic in West Africa. PMID:27451336

Mathematical models to characterize early epidemic growth: A review

NASA Astrophysics Data System (ADS)

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-09-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-2015 Ebola epidemic in West Africa.

Electrostatic and electromagnetic gyroharmonic emissions due to energetic electrons in magnetospheric plasma

NASA Technical Reports Server (NTRS)

Curtis, S. A.; Wu, C. S.

1979-01-01

The paper derives the growth rates and growth lengths of the electrostatic emission for spatially homogeneous and inhomogeneous energetic electrons, and numerically evaluates the growth rate and growth length spectra for several parameter sets representative of magnetospheric plasmas. In addition, the growth rates are derived for the case of electromagnetic emission modeled by the ordinary mode. The numerical results of the electromagnetic and electrostatic cases are compared with observations made by satellites in the earth's magnetosphere. It is concluded that the electrostatic gyroharmonic excitation is possible without the cold composition of plasma which is often postulated in the existing literature.

Application of evolutionary games to modeling carcinogenesis.

PubMed

Swierniak, Andrzej; Krzeslak, Michal

2013-06-01

We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.

Effects of urban growth controls on intercity commuting.

PubMed

Ogura, Laudo M

2010-01-01

This paper presents an empirical study of the effects of urban growth controls on the intercity commuting of workers. Growth controls (land use regulations that attempt to restrict population growth and urban sprawl) have increased housing prices and diverted population growth to uncontrolled cities. It has been suggested that resulting changes in local labour supply might stimulate intercity commuting from uncontrolled to controlled cities. To test this hypothesis, a gravity model of commuting flows between places in California is estimated using alternative econometric methods (OLS, Heckman selection and count-data). The possibility of spatial dependence in commuting flows is also taken into consideration. Results suggest larger commuting flows to destination places that restrict residential growth.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

PubMed

Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2018-04-01

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

The impact of natural transformation on adaptation in spatially structured bacterial populations.

PubMed

Moradigaravand, Danesh; Engelstädter, Jan

2014-06-20

Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations.

A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth

NASA Astrophysics Data System (ADS)

Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.

2017-12-01

The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.

Growth characteristics and Otolith analysis on Age-0 American Shad

USGS Publications Warehouse

Sauter, Sally T.; Wetzel, Lisa A.

2011-01-01

Otolith microstructure analysis provides useful information on the growth history of fish (Campana and Jones 1992, Bang and Gronkjaer 2005). Microstructure analysis can be used to construct the size-at-age growth trajectory of fish, determine daily growth rates, and estimate hatch date and other ecologically important life history events (Campana and Jones 1992, Tonkin et al. 2008). This kind of information can be incorporated into bioenergetics modeling, providing necessary data for estimating prey consumption, and guiding the development of empirically-based modeling scenarios for hypothesis testing. For example, age-0 American shad co-occur with emigrating juvenile fall Chinook salmon originating from Hanford Reach and the Snake River in the lower Columbia River reservoirs during the summer and early fall. The diet of age-0 American shad appears to overlap with that of juvenile fall Chinook salmon (Chapter 1, this report), but juvenile fall Chinook salmon are also known to feed on age-0 American shad in the reservoirs (USGS unpublished data). Abundant, energy-dense age-0 American shad may provide juvenile fall Chinook salmon opportunities for rapid growth during the time period when large numbers of age-0 American shad are available. Otolith analysis of hatch dates and the growth curve of age-0 American shad could be used to identify when eggs, larvae, and juveniles of specific size classes are temporally available as food for fall Chinook salmon in the lower Columbia River reservoirs. This kind of temporally and spatially explicit life history information is important to include in bioenergetics modeling scenarios. Quantitative estimates of prey consumption could be used with spatially-explicit estimates of prey abundance to construct a quantitative assessment of the age-0 American shad impact on a reservoir food web.

Simple spatial scaling rules behind complex cities.

PubMed

Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2017-11-28

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

Spatial and Temporal Changes of Aerosol Optical Depth and its Driving Factors Based on Modis in Jiangsu Province

NASA Astrophysics Data System (ADS)

Jiang, C.; Xu, Q.; Gu, Y. K.; Qian, X. Y.; He, J. N.

2018-04-01

Aerosol Optical Depth (AOD) is of great value for studying air mass and its changes. In this paper, we studied the spatial-temporal changes of AOD and its driving factors based on spatial autocorrelation model, gravity model and multiple regression analysis in Jiangsu Province from 2007 to 2016. The results showed that in terms of spatial distribution, the southern AOD value is higher, and the high-value aggregation areas are significant, while the northern AOD value is lower, but the low-value aggregation areas constantly change. The AOD gravity centers showed a clear point-like aggregation. In terms of temporal changes, the overall AOD in Jiangsu Province increased year by year in fluctuation. In terms of driving factors, the total amount of vehicles, precipitation and temperature are important factors for the growth of AOD.

Growth rates of the buoyancy-driven instability of an autocatalytic reaction front in a narrow cell

PubMed

Bockmann; Muller

2000-09-18

Experimental studies were performed on the buoyancy-driven instability of an autocatalytic reaction front in a quasi-2D cell. The unstable density stratification at an ascending front leads to convection that results in a fingerlike front deformation. The growth rates of the spatial modes of the instability are determined at the initial stage. A stabilization is found at higher wave numbers, while the system is unstable against low wave number perturbations. Whereas comparison with a reported model governed by Hele-Shaw flow fails, a two-dimensional Navier-Stokes model yields more satisfactory results. Still, present deviations suggest the presence of an additional mechanism that suppresses the growth.

Growth and nonlinear response of driven water bells

NASA Astrophysics Data System (ADS)

Kolinski, John M.; Aharoni, Hillel; Fineberg, Jay; Sharon, Eran

2017-04-01

A water bell forms when a fluid jet impacts upon a target and separates into a two-dimensional sheet. Depending on the angle of separation from the target, the sheet can curve into a variety of different geometries. We show analytically that harmonic perturbations of water bells have linear wave solutions with geometry-dependent growth. We test the predictions of this model experimentally with a custom target system, and observe growth in agreement with the model below a critical forcing amplitude. Once the critical forcing amplitude is exceeded, a nonlinear transcritical bifurcation occurs; the response amplitude increases linearly with increasing forcing amplitude, albeit with a fundamentally different spatial form, and distinct nodes appear in the amplitude envelope.

Ion and lipid signaling in apical growth-a dynamic machinery responding to extracellular cues.

PubMed

Malhó, Rui; Serrazina, Susana; Saavedra, Laura; Dias, Fernando V; Ul-Rehman, Reiaz

2015-01-01

Apical cell growth seems to have independently evolved throughout the major lineages of life. To a certain extent, so does our body of knowledge on the mechanisms regulating this morphogenetic process. Studies on pollen tubes, root hairs, rhizoids, fungal hyphae, even nerve cells, have highlighted tissue and cell specificities but also common regulatory characteristics (e.g., ions, proteins, phospholipids) that our focused research sometimes failed to grasp. The working hypothesis to test how apical cell growth is established and maintained have thus been shaped by the model organism under study and the type of methods used to study them. The current picture is one of a dynamic and adaptative process, based on a spatial segregation of components that network to achieve growth and respond to environmental (extracellular) cues. Here, we explore some examples of our live imaging research, namely on cyclic nucleotide gated ion channels, lipid kinases and syntaxins involved in exocytosis. We discuss how their spatial distribution, activity and concentration suggest that the players regulating apical cell growth may display more mobility than previously thought. Furthermore, we speculate on the implications of such perspective in our understanding of the mechanisms regulating apical cell growth and their responses to extracellular cues.

Changes of the potential distribution area of French Mediterranean forests under global warming

NASA Astrophysics Data System (ADS)

Gaucherel, C.; Guiot, J.; Misson, L.

2008-11-01

This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growth with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20th and 21st centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5 K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak respectively) at the end of the 21st century. While both species have different growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21st century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.

Monitoring urbanization and its implications in a mega city from space: spatiotemporal patterns and its indicators.

PubMed

Ramachandra, T V; Bharath, A H; Sowmyashree, M V

2015-01-15

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources .Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geoinformatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. Copyright © 2014 Elsevier Ltd. All rights reserved.

Density of founder cells affects spatial pattern formation and cooperation in Bacillus subtilis biofilms

PubMed Central

van Gestel, Jordi; Weissing, Franz J; Kuipers, Oscar P; Kovács, Ákos T

2014-01-01

In nature, most bacteria live in surface-attached sedentary communities known as biofilms. Biofilms are often studied with respect to bacterial interactions. Many cells inhabiting biofilms are assumed to express ‘cooperative traits', like the secretion of extracellular polysaccharides (EPS). These traits can enhance biofilm-related properties, such as stress resilience or colony expansion, while being costly to the cells that express them. In well-mixed populations cooperation is difficult to achieve, because non-cooperative individuals can reap the benefits of cooperation without having to pay the costs. The physical process of biofilm growth can, however, result in the spatial segregation of cooperative from non-cooperative individuals. This segregation can prevent non-cooperative cells from exploiting cooperative neighbors. Here we examine the interaction between spatial pattern formation and cooperation in Bacillus subtilis biofilms. We show, experimentally and by mathematical modeling, that the density of cells at the onset of biofilm growth affects pattern formation during biofilm growth. At low initial cell densities, co-cultured strains strongly segregate in space, whereas spatial segregation does not occur at high initial cell densities. As a consequence, EPS-producing cells have a competitive advantage over non-cooperative mutants when biofilms are initiated at a low density of founder cells, whereas EPS-deficient cells have an advantage at high cell densities. These results underline the importance of spatial pattern formation for competition among bacterial strains and the evolution of microbial cooperation. PMID:24694715

Density of founder cells affects spatial pattern formation and cooperation in Bacillus subtilis biofilms.

PubMed

van Gestel, Jordi; Weissing, Franz J; Kuipers, Oscar P; Kovács, Akos T

2014-10-01

In nature, most bacteria live in surface-attached sedentary communities known as biofilms. Biofilms are often studied with respect to bacterial interactions. Many cells inhabiting biofilms are assumed to express 'cooperative traits', like the secretion of extracellular polysaccharides (EPS). These traits can enhance biofilm-related properties, such as stress resilience or colony expansion, while being costly to the cells that express them. In well-mixed populations cooperation is difficult to achieve, because non-cooperative individuals can reap the benefits of cooperation without having to pay the costs. The physical process of biofilm growth can, however, result in the spatial segregation of cooperative from non-cooperative individuals. This segregation can prevent non-cooperative cells from exploiting cooperative neighbors. Here we examine the interaction between spatial pattern formation and cooperation in Bacillus subtilis biofilms. We show, experimentally and by mathematical modeling, that the density of cells at the onset of biofilm growth affects pattern formation during biofilm growth. At low initial cell densities, co-cultured strains strongly segregate in space, whereas spatial segregation does not occur at high initial cell densities. As a consequence, EPS-producing cells have a competitive advantage over non-cooperative mutants when biofilms are initiated at a low density of founder cells, whereas EPS-deficient cells have an advantage at high cell densities. These results underline the importance of spatial pattern formation for competition among bacterial strains and the evolution of microbial cooperation.

Extremely Low Frequency (ELF) Communications System Ecological Monitoring Program: Summary of 1986 Progress.

DTIC Science & Technology

1987-12-01

assessment of data collection techniques *quantification of temporal and spatial patterns of variables *assessment of end point variability...nutrient variables are also being examined as covarlates. Development of a model to test for differences in growth patterns is continuing. At each of...condition. These variables are recorded at the end of each growing season. For evaluation of height growth patterns , a subsample of 100 seedlings per

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions.

PubMed

Wilmoth, Jared L; Doak, Peter W; Timm, Andrea; Halsted, Michelle; Anderson, John D; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P . aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

PubMed Central

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; Halsted, Michelle; Anderson, John D.; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T.; Fuentes-Cabrera, Miguel

2018-01-01

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. PMID:29467721

Climate Change Simulations Predict Altered Biotic Response in a Thermally Heterogeneous Stream System

PubMed Central

Westhoff, Jacob T.; Paukert, Craig P.

2014-01-01

Climate change is predicted to increase water temperatures in many lotic systems, but little is known about how changes in air temperature affect lotic systems heavily influenced by groundwater. Our objectives were to document spatial variation in temperature for spring-fed Ozark streams in Southern Missouri USA, create a spatially explicit model of mean daily water temperature, and use downscaled climate models to predict the number of days meeting suitable stream temperature for three aquatic species of concern to conservation and management. Longitudinal temperature transects and stationary temperature loggers were used in the Current and Jacks Fork Rivers during 2012 to determine spatial and temporal variability of water temperature. Groundwater spring influence affected river water temperatures in both winter and summer, but springs that contributed less than 5% of the main stem discharge did not affect river temperatures beyond a few hundred meters downstream. A multiple regression model using variables related to season, mean daily air temperature, and a spatial influence factor (metric to account for groundwater influence) was a strong predictor of mean daily water temperature (r2 = 0.98; RMSE = 0.82). Data from two downscaled climate simulations under the A2 emissions scenario were used to predict daily water temperatures for time steps of 1995, 2040, 2060, and 2080. By 2080, peak numbers of optimal growth temperature days for smallmouth bass are expected to shift to areas with more spring influence, largemouth bass are expected to experience more optimal growth days (21 – 317% increase) regardless of spring influence, and Ozark hellbenders may experience a reduction in the number of optimal growth days in areas with the highest spring influence. Our results provide a framework for assessing fine-scale (10 s m) thermal heterogeneity and predict shifts in thermal conditions at the watershed and reach scale. PMID:25356982

Fine-resolution Modeling of Urban-Energy Systems' Water Footprint in River Networks

NASA Astrophysics Data System (ADS)

McManamay, R.; Surendran Nair, S.; Morton, A.; DeRolph, C.; Stewart, R.

2015-12-01

Characterizing the interplay between urbanization, energy production, and water resources is essential for ensuring sustainable population growth. In order to balance limited water supplies, competing users must account for their realized and virtual water footprint, i.e. the total direct and indirect amount of water used, respectively. Unfortunately, publicly reported US water use estimates are spatially coarse, temporally static, and completely ignore returns of water to rivers after use. These estimates are insufficient to account for the high spatial and temporal heterogeneity of water budgets in urbanizing systems. Likewise, urbanizing areas are supported by competing sources of energy production, which also have heterogeneous water footprints. Hence, a fundamental challenge of planning for sustainable urban growth and decision-making across disparate policy sectors lies in characterizing inter-dependencies among urban systems, energy producers, and water resources. A modeling framework is presented that provides a novel approach to integrate urban-energy infrastructure into a spatial accounting network that accurately measures water footprints as changes in the quantity and quality of river flows. River networks (RNs), i.e. networks of branching tributaries nested within larger rivers, provide a spatial structure to measure water budgets by modeling hydrology and accounting for use and returns from urbanizing areas and energy producers. We quantify urban-energy water footprints for Atlanta, GA and Knoxville, TN (USA) based on changes in hydrology in RNs. Although water intakes providing supply to metropolitan areas were proximate to metropolitan areas, power plants contributing to energy demand in Knoxville and Atlanta, occurred 30 and 90km outside the metropolitan boundary, respectively. Direct water footprints from urban landcover primarily comprised smaller streams whereas indirect footprints from water supply reservoirs and energy producers included larger river systems. By using projections in urban populations for 2030 and 2050, we estimated scenarios of expansion in water footprints depending on urban growth policies and energy production technology. We provide examples of how this framework can be used to minimize water footprints and impacts to aquatic biodiversity.

Dendritic growth model of multilevel marketing

NASA Astrophysics Data System (ADS)

Pang, James Christopher S.; Monterola, Christopher P.

2017-02-01

Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species.

PubMed

Gravel, Dominique; Beaudet, Marilou; Messier, Christian

2008-10-01

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.

Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

NASA Astrophysics Data System (ADS)

Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

2014-12-01

The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Computational Modeling of 3D Tumor Growth and Angiogenesis for Chemotherapy Evaluation

PubMed Central

Tang, Lei; van de Ven, Anne L.; Guo, Dongmin; Andasari, Vivi; Cristini, Vittorio; Li, King C.; Zhou, Xiaobo

2014-01-01

Solid tumors develop abnormally at spatial and temporal scales, giving rise to biophysical barriers that impact anti-tumor chemotherapy. This may increase the expenditure and time for conventional drug pharmacokinetic and pharmacodynamic studies. In order to facilitate drug discovery, we propose a mathematical model that couples three-dimensional tumor growth and angiogenesis to simulate tumor progression for chemotherapy evaluation. This application-oriented model incorporates complex dynamical processes including cell- and vascular-mediated interstitial pressure, mass transport, angiogenesis, cell proliferation, and vessel maturation to model tumor progression through multiple stages including tumor initiation, avascular growth, and transition from avascular to vascular growth. Compared to pure mechanistic models, the proposed empirical methods are not only easy to conduct but can provide realistic predictions and calculations. A series of computational simulations were conducted to demonstrate the advantages of the proposed comprehensive model. The computational simulation results suggest that solid tumor geometry is related to the interstitial pressure, such that tumors with high interstitial pressure are more likely to develop dendritic structures than those with low interstitial pressure. PMID:24404145

The spatial and metabolic basis of colony size variation.

PubMed

Chacón, Jeremy M; Möbius, Wolfram; Harcombe, William R

2018-03-01

Spatial structure impacts microbial growth and interactions, with ecological and evolutionary consequences. It is therefore important to quantitatively understand how spatial proximity affects interactions in different environments. We tested how proximity influences colony size when either Escherichia coli or Salmonella enterica are grown on various carbon sources. The importance of colony location changed with species and carbon source. Spatially explicit, genome-scale metabolic modeling recapitulated observed colony size variation. Competitors that determine territory size, according to Voronoi diagrams, were the most important drivers of variation in colony size. However, the relative importance of different competitors changed through time. Further, the effect of location increased when colonies took up resources quickly relative to the diffusion of limiting resources. These analyses made it apparent that the importance of location was smaller than expected for experiments with S. enterica growing on glucose. The accumulation of toxic byproducts appeared to limit the growth of large colonies and reduced variation in colony size. Our work provides an experimentally and theoretically grounded understanding of how location interacts with metabolism and diffusion to influence microbial interactions.

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots.

PubMed

Ozgul, Arpat; Oli, Madan K; Olson, Lucretia E; Blumstein, Daniel T; Armitage, Kenneth B

2007-11-01

Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962-2004) of data from 17 locations and a capture-mark-recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (lambda). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in lambda. Our analysis indicated that lambda was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in lambda.

Recent growth of conifer species of western North America: Assessing spatial patterns of radial growth trends

USGS Publications Warehouse

McKenzie, D.; Hessl, Amy E.; Peterson, D.L.

2001-01-01

We explored spatial patterns of low-frequency variability in radial tree growth among western North American conifer species and identified predictors of the variability in these patterns. Using 185 sites from the International Tree-Ring Data Bank, each of which contained 10a??60 raw ring-width series, we rebuilt two chronologies for each site, using two conservative methods designed to retain any low-frequency variability associated with recent environmental change. We used factor analysis to identify regional low-frequency patterns in site chronologies and estimated the slope of the growth trend since 1850 at each site from a combination of linear regression and time-series techniques. This slope was the response variable in a regression-tree model to predict the effects of environmental gradients and species-level differences on growth trends. Growth patterns at 27 sites from the American Southwest were consistent with quasi-periodic patterns of drought. Either 12 or 32 of the 185 sites demonstrated patterns of increasing growth between 1850 and 1980 A.D., depending on the standardization technique used. Pronounced growth increases were associated with high-elevation sites (above 3000 m) and high-latitude sites in maritime climates. Future research focused on these high-elevation and high-latitude sites should address the precise mechanisms responsible for increased 20th century growth.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

NASA Astrophysics Data System (ADS)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Producing a satellite-derived map and modelling Spartina alterniflora expansion for Willapa Bay in Washington State

NASA Astrophysics Data System (ADS)

Berlin, Cynthia Jane

1998-12-01

This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential habitat is filled.

Large-scale changes in bloater growth and condition in Lake Huron

USGS Publications Warehouse

Prichard, Carson G.; Roseman, Edward F.; Keeler, Kevin M.; O'Brien, Timothy P.; Riley, Stephen C.

2016-01-01

Native Bloaters Coregonus hoyi have exhibited multiple strong year-classes since 2005 and now are the most abundant benthopelagic offshore prey fish in Lake Huron, following the crash of nonnative AlewivesAlosa pseudoharengus and substantial declines in nonnative Rainbow Smelt Osmerus mordax. Despite recent recoveries in Bloater abundance, marketable-size (>229 mm) Bloaters remain scarce. We used annual survey data to assess temporal and spatial dynamics of Bloater body condition and lengths at age in the main basin of Lake Huron from 1973 to 2014. Basinwide lengths at age were modeled by cohort for the 1973–2003 year-classes using a von Bertalanffy growth model with time-varying Brody growth coefficient (k) and asymptotic length () parameters. Median Bloater weights at selected lengths were estimated to assess changes in condition by modeling weight–length relations with an allometric growth model that allowed growth parameters to vary spatially and temporally. Estimated Bloater lengths at age declined 14–24% among ages 4–8 for all year-classes between 1973 and 2004. Estimates of  declined from a peak of 394 mm (1973 year-class) to a minimum of 238 mm (1998 year-class). Observed mean lengths at age in 2014 were at all-time lows, suggesting that year-classes comprising the current Bloater population would have to follow growth trajectories unlike those characterizing the 1973–2003 year-classes to attain marketable size. Furthermore, estimated weights of 250-mm Bloaters (i.e., a large, commercially valuable size-class) declined 17% among all regions from 1976 to 2007. Decreases in body condition of large Bloaters are associated with lower lipid content and may be linked to marked declines in abundance of the amphipodsDiporeia spp. in Lake Huron. We hypothesize that since at least 1976, large Bloaters have become more negatively buoyant and may have incurred an increasingly greater metabolic cost performing diel vertical migrations to prey upon the opossum shrimp Mysis diluviana and zooplankton.

Mound-Interface Kinetics in Dictyostelium Aggregation

NASA Astrophysics Data System (ADS)

Tutu, Hiroki

2002-09-01

The mound development of the cellular slime mold amoebae Dictyostelium discoideum is studied with an interface kinetic model for the height of cell layers. As a competitive role for the chemotaxis, we compare two types of curvature relaxations; the surface relaxation induced by cell-substrate affinity (model A), and that comes from a cell-cell adhesive effect (model B). It is found that both models are characterized by the growth law for the maximum mound height. Based on a self-similarity scaling hypothesis for the spatial structure of streaming pattern, we suggest a scaling law for the growth of mound-height hmax ˜ t1-1/α+β/α with α = 2 (4) for the model A (B) and a number 0 ≤ β < 1.

Comparing approaches to spatially explicit ecosystem service modeling: a case study from the San Pedro River, Arizona

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius J.; Winthrop, Robert

2013-01-01

Although the number of ecosystem service modeling tools has grown in recent years, quantitative comparative studies of these tools have been lacking. In this study, we applied two leading open-source, spatially explicit ecosystem services modeling tools – Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) – to the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. We modeled locally important services that both modeling systems could address – carbon, water, and scenic viewsheds. We then applied managerially relevant scenarios for urban growth and mesquite management to quantify ecosystem service changes. InVEST and ARIES use different modeling approaches and ecosystem services metrics; for carbon, metrics were more similar and results were more easily comparable than for viewsheds or water. However, findings demonstrate similar gains and losses of ecosystem services and conclusions when comparing effects across our scenarios. Results were more closely aligned for landscape-scale urban-growth scenarios and more divergent for a site-scale mesquite-management scenario. Follow-up studies, including testing in different geographic contexts, can improve our understanding of the strengths and weaknesses of these and other ecosystem services modeling tools as they move closer to readiness for supporting day-to-day resource management.

Modelling the growth of Populus species using Ecosystem Demography (ED) model

NASA Astrophysics Data System (ADS)

Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.

2010-12-01

Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE PAGES

Shi, Yuning; Eissenstat, David M.; He, Yuting; ...

2018-05-12

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Yuning; Eissenstat, David M.; He, Yuting

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solarmore » radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.« less

A physically based analytical spatial air temperature and humidity model

NASA Astrophysics Data System (ADS)

Yang, Yang; Endreny, Theodore A.; Nowak, David J.

2013-09-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: sensitivity to climatic variability.

Treesearch

Melisa L. Holman; David L. Peterson

2006-01-01

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

DOE PAGES

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

The linkages between photosynthesis, productivity, growth and biomass in lowland Amazonian forests.

PubMed

Malhi, Yadvinder; Doughty, Christopher E; Goldsmith, Gregory R; Metcalfe, Daniel B; Girardin, Cécile A J; Marthews, Toby R; Del Aguila-Pasquel, Jhon; Aragão, Luiz E O C; Araujo-Murakami, Alejandro; Brando, Paulo; da Costa, Antonio C L; Silva-Espejo, Javier E; Farfán Amézquita, Filio; Galbraith, David R; Quesada, Carlos A; Rocha, Wanderley; Salinas-Revilla, Norma; Silvério, Divino; Meir, Patrick; Phillips, Oliver L

2015-06-01

Understanding the relationship between photosynthesis, net primary productivity and growth in forest ecosystems is key to understanding how these ecosystems will respond to global anthropogenic change, yet the linkages among these components are rarely explored in detail. We provide the first comprehensive description of the productivity, respiration and carbon allocation of contrasting lowland Amazonian forests spanning gradients in seasonal water deficit and soil fertility. Using the largest data set assembled to date, ten sites in three countries all studied with a standardized methodology, we find that (i) gross primary productivity (GPP) has a simple relationship with seasonal water deficit, but that (ii) site-to-site variations in GPP have little power in explaining site-to-site spatial variations in net primary productivity (NPP) or growth because of concomitant changes in carbon use efficiency (CUE), and conversely, the woody growth rate of a tropical forest is a very poor proxy for its productivity. Moreover, (iii) spatial patterns of biomass are much more driven by patterns of residence times (i.e. tree mortality rates) than by spatial variation in productivity or tree growth. Current theory and models of tropical forest carbon cycling under projected scenarios of global atmospheric change can benefit from advancing beyond a focus on GPP. By improving our understanding of poorly understood processes such as CUE, NPP allocation and biomass turnover times, we can provide more complete and mechanistic approaches to linking climate and tropical forest carbon cycling. © 2015 John Wiley & Sons Ltd.

Modeling urbanization patterns at a global scale with generative adversarial networks

NASA Astrophysics Data System (ADS)

Albert, A. T.; Strano, E.; Gonzalez, M.

2017-12-01

Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a scale-free behavior), and the traditional statistical learning approaches (whereby values of individual pixels are modeled as functions of locally-defined, hand-engineered features). This is a first-of-its-kind analysis of urban forms using data at a planetary scale.

Spatial aspects of tree mortality strongly differ between young and old-growth forests.

PubMed

Larson, Andrew J; Lutz, James A; Donato, Daniel C; Freund, James A; Swanson, Mark E; HilleRisLambers, Janneke; Sprugel, Douglas G; Franklin, Jerry F

2015-11-01

Rates and spatial patterns of tree mortality are predicted to change during forest structural development. In young forests, mortality should be primarily density dependent due to competition for light, leading to an increasingly spatially uniform pattern of surviving trees. In contrast, mortality in old-growth forests should be primarily caused by contagious and spatially autocorrelated agents (e.g., insects, wind), causing spatial aggregation of surviving trees to increase through time. We tested these predictions by contrasting a three-decade record of tree mortality from replicated mapped permanent plots located in young (< 60-year-old) and old-growth (> 300-year-old) Abies amabilis forests. Trees in young forests died at a rate of 4.42% per year, whereas trees in old-growth forests died at 0.60% per year. Tree mortality in young forests was significantly aggregated, strongly density dependent, and caused live tree patterns to become more uniform through time. Mortality in old-growth forests was spatially aggregated, but was density independent and did not change the spatial pattern of surviving trees. These results extend current theory by demonstrating that density-dependent competitive mortality leading to increasingly uniform tree spacing in young forests ultimately transitions late in succession to a more diverse tree mortality regime that maintains spatial heterogeneity through time.

Mistletoe effects on Scots pine decline following drought events: insights from within-tree spatial patterns, growth and carbohydrates.

PubMed

Sangüesa-Barreda, Gabriel; Linares, Juan Carlos; Camarero, J Julio

2012-05-01

Forest decline has been attributed to the interaction of several stressors including biotic factors such as mistletoes and climate-induced drought stress. However, few data exist on how mistletoes are spatially arranged within trees and how this spatial pattern is related to changes in radial growth, responses to drought stress and carbon use. We used dendrochronology to quantify how mistletoe (Viscum album L.) infestation and drought stress affected long-term growth patterns in Pinus sylvestris L. at different heights. Basal area increment (BAI) trends and comparisons between trees of three different infestation degrees (without mistletoe, ID1; moderately infested trees, ID2; and severely infested trees, ID3) were performed using linear mixed-effects models. To identify the main climatic drivers of tree growth tree-ring widths were converted into indexed chronologies and related to climate data using correlation functions. We performed spatial analyses of the 3D distribution of mistletoe individuals and their ages within the crowns of three severely infested pines to describe their patterns. Lastly, we quantified carbohydrate and nitrogen concentrations in needles and sapwood of branches from severely infested trees and from trees without mistletoe. Mistletoe individuals formed strongly clustered groups of similar age within tree crowns and their age increased towards the crown apex. Mistletoe infestation negatively impacted growth but this effect was stronger near the tree apex than in the rest of sampled heights, causing an average loss of 64% in BAI (loss of BAI was ∼51% at 1.3 m or near the tree base). We found that BAI of severely infested trees and moderately or non-infested trees diverged since 2001 and such divergence was magnified by drought. Infested trees had lower concentrations of soluble sugars in their needles than non-infested ones. We conclude that mistletoe infestation causes growth decline and increases the sensitivity of trees to drought stress.

Simulation of wheat growth and development based on organ-level photosynthesis and assimilate allocation.

PubMed

Evers, J B; Vos, J; Yin, X; Romero, P; van der Putten, P E L; Struik, P C

2010-05-01

Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.

Landscapes of facilitation: how self-organized patchiness of aquatic macrophytes promotes diversity in streams.

PubMed

Cornacchia, Loreta; van de Koppel, Johan; van der Wal, Daphne; Wharton, Geraldene; Puijalon, Sara; Bouma, Tjeerd J

2018-04-01

Spatial heterogeneity plays a crucial role in the coexistence of species. Despite recognition of the importance of self-organization in creating environmental heterogeneity in otherwise uniform landscapes, the effects of such self-organized pattern formation in promoting coexistence through facilitation are still unknown. In this study, we investigated the effects of pattern formation on species interactions and community spatial structure in ecosystems with limited underlying environmental heterogeneity, using self-organized patchiness of the aquatic macrophyte Callitriche platycarpa in streams as a model system. Our theoretical model predicted that pattern formation in aquatic vegetation - due to feedback interactions between plant growth, water flow and sedimentation processes - could promote species coexistence, by creating heterogeneous flow conditions inside and around the plant patches. The spatial plant patterns predicted by our model agreed with field observations at the reach scale in naturally vegetated rivers, where we found a significant spatial aggregation of two macrophyte species around C. platycarpa. Field transplantation experiments showed that C. platycarpa had a positive effect on the growth of both beneficiary species, and the intensity of this facilitative effect was correlated with the heterogeneous hydrodynamic conditions created within and around C. platycarpa patches. Our results emphasize the importance of self-organized patchiness in promoting species coexistence by creating a landscape of facilitation, where new niches and facilitative effects arise in different locations. Understanding the interplay between competition and facilitation is therefore essential for successful management of biodiversity in many ecosystems. © 2018 The Authors Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration

NASA Astrophysics Data System (ADS)

Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

2014-07-01

The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA

USGS Publications Warehouse

Perkl, Ryan; Norman, Laura M.; Mitchell, David; Feller, Mark R.; Smith, Garrett; Wilson, Natalie R.

2018-01-01

Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.

Physical basis of large microtubule aster growth

PubMed Central

Ishihara, Keisuke; Korolev, Kirill S; Mitchison, Timothy J

2016-01-01

Microtubule asters - radial arrays of microtubules organized by centrosomes - play a fundamental role in the spatial coordination of animal cells. The standard model of aster growth assumes a fixed number of microtubules originating from the centrosomes. However, aster morphology in this model does not scale with cell size, and we recently found evidence for non-centrosomal microtubule nucleation. Here, we combine autocatalytic nucleation and polymerization dynamics to develop a biophysical model of aster growth. Our model predicts that asters expand as traveling waves and recapitulates all major aspects of aster growth. With increasing nucleation rate, the model predicts an explosive transition from stationary to growing asters with a discontinuous jump of the aster velocity to a nonzero value. Experiments in frog egg extract confirm the main theoretical predictions. Our results suggest that asters observed in large fish and amphibian eggs are a meshwork of short, unstable microtubules maintained by autocatalytic nucleation and provide a paradigm for the assembly of robust and evolvable polymer networks. DOI: http://dx.doi.org/10.7554/eLife.19145.001 PMID:27892852

A necessary condition for dispersal driven growth of populations with discrete patch dynamics.

PubMed

Guiver, Chris; Packman, David; Townley, Stuart

2017-07-07

We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Numerical modeling of the traction process in the treatment for Pierre-Robin Sequence.

PubMed

Słowiński, Jakub J; Czarnecka, Aleksandra

2016-10-01

The goal of this numerical study was to identify the results of modulated growth simulation of the mandibular bone during traction in Pierre-Robin Sequence (PRS) treatment. Numerical simulation was conducted in the Ansys 16.2 environment. Two FEM (finite elements method) models of a newborn's mandible (a spatial and a flat model) were developed. The procedure simulated a 20-week traction period. The adopted growth measure was mandibular length increase, defined as the distance between the Co-Pog anatomic points used in cephalometric analysis. The simulation calculations conducted on the developed models showed that modulation had a significant influence on the pace of bone growth. In each of the analyzed cases, growth modulation resulted in an increase in pace. The largest value of increase was 6.91 mm. The modulated growth with the most beneficial load variant increased the basic value of the growth by as much as 24.6%, and growth with the least beneficial variant increased by 7.4%. Traction is a simple, minimally invasive and inexpensive procedure. The proposed algorithm may enable the development of a helpful forecasting tool, which could be of real use to doctors working on Pierre-Robin Sequence and other mandibular deformations in children. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modeling triple-negative breast cancer heterogeneity: effects of stromal macrophages, fibroblasts and tumor vasculature.

PubMed

Norton, Kerri-Ann; Jin, Kideok; Popel, Aleksander S

2018-05-08

A hallmark of breast tumors is its spatial heterogeneity that includes its distribution of cancer stem cells and progenitor cells, but also heterogeneity in the tumor microenvironment. In this study we focus on the contributions of stromal cells, specifically macrophages, fibroblasts, and endothelial cells on tumor progression. We develop a computational model of triple-negative breast cancer based on our previous work and expand it to include macrophage infiltration, fibroblasts, and angiogenesis. In vitro studies have shown that the secretomes of tumor-educated macrophages and fibroblasts increase both the migration and proliferation rates of triple-negative breast cancer cells. In vivo studies also demonstrated that blocking signaling of selected secreted factors inhibits tumor growth and metastasis in mouse xenograft models. We investigate the influences of increased migration and proliferation rates on tumor growth, the effect of the presence on fibroblasts or macrophages on growth and morphology, and the contributions of macrophage infiltration on tumor growth. We find that while the presence of macrophages increases overall tumor growth, the increase in macrophage infiltration does not substantially increase tumor growth and can even stifle tumor growth at excessive rates. Copyright © 2018. Published by Elsevier Ltd.

Large-Scale Partial-Duplicate Image Retrieval and Its Applications

DTIC Science & Technology

2016-04-23

SECURITY CLASSIFICATION OF: The explosive growth of Internet Media (partial-duplicate/similar images, 3D objects, 3D models, etc.) sheds bright...light on many promising applications in forensics, surveillance, 3D animation, mobile visual search, and 3D model/object search. Compared with the...and stable spatial configuration. Compared with the general 2D objects, 3D models/objects consist of 3D data information (typically a list of

Validation databases for simulation models: aboveground biomass and net primary productive, (NPP) estimation using eastwide FIA data

Treesearch

Jennifer C. Jenkins; Richard A. Birdsey

2000-01-01

As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Micron-Resolution X-ray Structural Microscopy Studies of 3-D Grain Growth in Polycrystalline Aluminum

NASA Astrophysics Data System (ADS)

Budai, J. D.; Yang, W.; Tischler, J. Z.; Liu, W.; Larson, B. C.; Ice, G. E.

2004-03-01

We describe a new polychromatic x-ray microdiffraction technique providing 3D measurements of lattice structure, orientation and strain with submicron point-to-point spatial resolution. The instrument is located on the UNI-CAT II undulator beamline at the Advanced Photon Source and uses Kirkpatrick-Baez focusing mirrors, differential aperture CCD measurements and automated analysis of spatially-resolved Laue patterns. 3D x-ray structural microscopy is applicable to a wide range of materials investigations and here we describe 3D thermal grain growth studies in polycrystalline aluminum ( ˜1% Fe,Si) from Alcoa. The morphology and orientations of the grains in a hot-rolled aluminum sample were initially mapped. The sample was then annealed to induce grain growth, cooled to room temperature, and the same volume region was re-mapped to determine the thermal migration of all grain boundaries. Significant grain growth was observed after annealing above ˜350^oC where both low-angle and high-angle boundaries were mobile. These measurements will provide the detailed 3D experimental input needed for testing theories and computer models of 3D grain growth in bulk materials.

Landscape Builder: software for the creation of initial landscapes for LANDIS from FIA data

Treesearch

William Dijak

2013-01-01

I developed Landscape Builder to create spatially explicit landscapes as starting conditions for LANDIS Pro 7.0 and LANDIS II landscape forest simulation models from classified satellite imagery and Forest Inventory and Analysis (FIA) data collected over multiple years. LANDIS Pro and LANDIS II models project future landscapes by simulating tree growth, tree species...

Impacts of crop growth dynamics on soil quality at the regional scale

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Agricultural land use and in particular crop growth dynamics can greatly affect soil quality. Both the amount of soil lost from erosion by water and soil organic matter are key indicators for soil quality. The aim was to develop a modelling framework for quantifying the impacts of crop growth dynamics on soil quality at the regional scale with test case Flanders. A framework for modelling the impacts of crop growth on soil erosion and soil organic matter was developed by coupling the dynamic crop cover model REGCROP (Gobin, 2010) to the PESERA soil erosion model (Kirkby et al., 2009) and to the RothC carbon model (Coleman and Jenkinson, 1999). All three models are process-based, spatially distributed and intended as a regional diagnostic tool. A geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System). Crop allometric models were developed from variety trials to calculate crop residues for common crops in Flanders and subsequently derive stable organic matter fluxes to the soil. Results indicate that crop growth dynamics and crop rotations influence soil quality for a very large percentage. soil erosion mainly occurs in the southern part of Flanders, where silty to loamy soils and a hilly topography are responsible for soil loss rates of up to 40 t/ha. Parcels under maize, sugar beet and potatoes are most vulnerable to soil erosion. Crop residues of grain maize and winter wheat followed by catch crops contribute most to the total carbon sequestered in agricultural soils. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. This implies that agricultural policies that impact on agricultural land management influence soil quality for a large percentage. The coupled REGCROP-PESERA-ROTHC model allows for quantifying the impact of seasonal and year-to-year crop growth dynamics on soil quality. When coupled to a multi-annual crop rotation database both spatial and temporal analysis becomes possible and allows for decision support at both farm and regional level. The framework is therefore suited for further scenario analysis and impact assessment. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE PAGES

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; ...

2018-02-06

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma

NASA Astrophysics Data System (ADS)

Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel

2017-03-01

Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.

A Microfluidics and Agent-Based Modeling Framework for Investigating Spatial Organization in Bacterial Colonies: The Case of Pseudomonas Aeruginosa and H1-Type VI Secretion Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less

Spatial competition dynamics between reef corals under ocean acidification

PubMed Central

Horwitz, Rael; Hoogenboom, Mia O.; Fine, Maoz

2017-01-01

Climate change, including ocean acidification (OA), represents a major threat to coral-reef ecosystems. Although previous experiments have shown that OA can negatively affect the fitness of reef corals, these have not included the long-term effects of competition for space on coral growth rates. Our multispecies year-long study subjected reef-building corals from the Gulf of Aqaba (Red Sea) to competitive interactions under present-day ocean pH (pH 8.1) and predicted end-of-century ocean pH (pH 7.6). Results showed coral growth is significantly impeded by OA under intraspecific competition for five out of six study species. Reduced growth from OA, however, is negligible when growth is already suppressed in the presence of interspecific competition. Using a spatial competition model, our analysis indicates shifts in the competitive hierarchy and a decrease in overall coral cover under lowered pH. Collectively, our case study demonstrates how modified competitive performance under increasing OA will in all likelihood change the composition, structure and functionality of reef coral communities. PMID:28067281

Kif18A and chromokinesins confine centromere movements via microtubule growth suppression and spatial control of kinetochore tension

PubMed Central

Stumpff, Jason; Wagenbach, Michael; Franck, Andrew; Asbury, Charles L.; Wordeman, Linda

2012-01-01

Summary Alignment of chromosomes at the metaphase plate is a signature of cell division in metazoan cells, yet the mechanisms controlling this process remain ambiguous. Here we use a combination of quantitative live cell imaging and reconstituted dynamic microtubule assays to investigate the molecular control of mitotic centromere movements. We establish that Kif18A (kinesin-8) attenuates centromere movement by directly promoting microtubule pausing in a concentration-dependent manner. This activity provides the dominant mechanism for restricting centromere movement to the spindle midzone. Furthermore, polar ejection forces spatially confine chromosomes via position-dependent regulation of kinetochore tension and centromere switch rates. We demonstrate that polar ejection forces are antagonistically modulated by chromokinesins. These pushing forces depend on Kid (kinesin-10) activity and are antagonized by Kif4A (kinesin-4), which functions to directly suppress microtubule growth. These data support a model in which Kif18A and polar ejection forces synergistically promote centromere alignment via spatial control of kinetochore-microtubule dynamics. PMID:22595673

Growth studies of Mytilus californianus using satellite surface temperatures and chlorophyll data for coastal Oregon

NASA Astrophysics Data System (ADS)

Price, J.; Lakshmi, V.

2013-12-01

The advancement of remote sensing technology has led to better understanding of the spatial and temporal variation in many physical and biological parameters, such as, temperature, salinity, soil moisture, vegetation cover, and community composition. This research takes a novel approach in understanding the temporal and spatial variability of mussel body growth using remotely sensed surface temperatures and chlorophyll-a concentration. Within marine rocky intertidal ecosystems, temperature and food availability influence species abundance, physiological performance, and distribution of mussel species. Current methods to determine the temperature mussel species experience range from in-situ field observations, temperature loggers, temperature models, and using other temperature variables. However, since the temperature that mussel species experience is different from the air temperature due to physical and biological characteristics (size, color, gaping, etc.), it is difficult to accurately predict the thermal stresses they experience. Methods to determine food availability (chlorophyll-a concentration used as a proxy) for mussel species are mostly done at specific study sites using water sampling. This implies that analysis of temperature and food availability across large spatial scales and long temporal scales is not a trivial task given spatial heterogeneity. However, this is an essential step in determination of the impact of changing climate on vulnerable ecosystems such as the marine rocky intertidal system. The purpose of this study was to investigate the potential of using remotely sensed surface temperatures and chlorophyll-a concentration to better understand the temporal and spatial variability of the body growth of the ecologically and economically important rocky intertidal mussel species, Mytilus californianus. Remotely sensed sea surface temperature (SST), land surface temperature (LST), intertidal surface temperature (IST), chlorophyll-a concentration, and mussel body growth were collected for eight study sites along the coast of Oregon, USA for a 12 year period from 2000 through 2011. Differences in surface temperatures, chlorophyll-a concentration, and mussel body growth were seen across study sites. The northernmost study site, Cape Meares, had the highest average SST and the lowest average chlorophyll-a concentration. Interestingly, it also had high average mussel growth. Whereas, Cape Arago and Cape Blanco, the two southernmost study sites, had the lowest average SST and lowest average mussel growth, but had higher average chlorophyll-a concentrations. Furthermore, some study sites showed that mussel growth was related to temperature and at other study sites chlorophyll-a concentration was related to mussel growth. The strongest relationship between either temperature or chlorophyll-a concentration, was found at Boiler Bay, Oregon. Approximately 81% of the variations in mean size-specific mussel growth was explained by mean annual LST anomalies. This means that at Boiler Bay, cooler LST years resulted in less mussel growth and warmer years resulted in higher mussel growth. Results suggest that SST may influence mussel body growth more than chlorophyll-a concentration.

Development of an Ex Vivo Porcine Lung Model for Studying Growth, Virulence, and Signaling of Pseudomonas aeruginosa

PubMed Central

Muruli, Aneesha; Higgins, Steven; Diggle, Stephen P.

2014-01-01

Research into chronic infection by bacterial pathogens, such as Pseudomonas aeruginosa, uses various in vitro and live host models. While these have increased our understanding of pathogen growth, virulence, and evolution, each model has certain limitations. In vitro models cannot recapitulate the complex spatial structure of host organs, while experiments on live hosts are limited in terms of sample size and infection duration for ethical reasons; live mammal models also require specialized facilities which are costly to run. To address this, we have developed an ex vivo pig lung (EVPL) model for quantifying Pseudomonas aeruginosa growth, quorum sensing (QS), virulence factor production, and tissue damage in an environment that mimics a chronically infected cystic fibrosis (CF) lung. In a first test of our model, we show that lasR mutants, which do not respond to 3-oxo-C12-homoserine lactone (HSL)-mediated QS, exhibit reduced virulence factor production in EVPL. We also show that lasR mutants grow as well as or better than a corresponding wild-type strain in EVPL. lasR mutants frequently and repeatedly arise during chronic CF lung infection, but the evolutionary forces governing their appearance and spread are not clear. Our data are not consistent with the hypothesis that lasR mutants act as social “cheats” in the lung; rather, our results support the hypothesis that lasR mutants are more adapted to the lung environment. More generally, this model will facilitate improved studies of microbial disease, especially studies of how cells of the same and different species interact in polymicrobial infections in a spatially structured environment. PMID:24866798

The geostatistical approach for structural and stratigraphic framework analysis of offshore NW Bonaparte Basin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahid, Ali, E-mail: ali.wahid@live.com; Salim, Ahmed Mohamed Ahmed, E-mail: mohamed.salim@petronas.com.my; Yusoff, Wan Ismail Wan, E-mail: wanismail-wanyusoff@petronas.com.my

2016-02-01

Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rockmore » properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin.« less

Experimental and mathematical modeling of the consumer’s influence on productivity of algae in a model aquatic ecosystem

NASA Astrophysics Data System (ADS)

Pisman, T. I.; Galayda, Ya. V.; Shirobokova, I. M.

A "producer-consumer" ( Chlorella vulgaris- Paramecium caudatum) closed aquatic system has been investigated experimentally and theoretically. It has been found that there is a direct relationship between the growth of the paramecia population and their release of ammonia nitrogen, which is the best form of nitrogen for Chlorella growth. The theoretical study of a model of a "producer-consumer" aquatic biotic cycle with spatially separated compartments has confirmed the contribution of paramecia to nitrogen cycling. It has been shown that an increase in the concentration of nitrogen released as metabolites of paramecia is accompanied by an increase in the productivity of microalgae.

Mechanistic principles of colloidal crystal growth by evaporation-induced convective steering.

PubMed

Brewer, Damien D; Allen, Joshua; Miller, Michael R; de Santos, Juan M; Kumar, Satish; Norris, David J; Tsapatsis, Michael; Scriven, L E

2008-12-02

We simulate evaporation-driven self-assembly of colloidal crystals using an equivalent network model. Relationships between a regular hexagonally close-packed array of hard, monodisperse spheres, the associated pore space, and selectivity mechanisms for face-centered cubic microstructure propagation are described. By accounting for contact line rearrangement and evaporation at a series of exposed menisci, the equivalent network model describes creeping flow of solvent into and through a rigid colloidal crystal. Observations concerning colloidal crystal growth are interpreted in terms of the convective steering hypothesis, which posits that solvent flow into and through the pore space of the crystal may play a major role in colloidal self-assembly. Aspects of the convective steering and deposition of high-Peclet-number rigid spherical particles at a crystal boundary are inferred from spatially resolved solvent flow into the crystal. Gradients in local flow through boundary channels were predicted due to the channels' spatial distribution relative to a pinned free surface contact line. On the basis of a uniform solvent and particle flux as the criterion for stability of a particular growth plane, these network simulations suggest the stability of a declining {311} crystal interface, a symmetry plane which exclusively propagates fcc microstructure. Network simulations of alternate crystal planes suggest preferential growth front evolution to the declining {311} interface, in consistent agreement with the proposed stability mechanism for preferential fcc microstructure propagation in convective assembly.

Modeling Growth of Nanostructures in Plasmas

NASA Technical Reports Server (NTRS)

Hwang, Helen H.; Bose, Deepak; Govindan, T. R.; Meyyappan, M.

2004-01-01

As semiconductor circuits shrink to CDs below 0.1 nm, it is becoming increasingly critical to replace and/or enhance existing technology with nanoscale structures, such as nanowires for interconnects. Nanowires grown in plasmas are strongly dependent on processing conditions, such as gas composition and substrate temperature. Growth occurs at specific sites, or step-edges, with the bulk growth rate of the nanowires determined from the equation of motion of the nucleating crystalline steps. Traditional front-tracking algorithms, such as string-based or level set methods, suffer either from numerical complications in higher spatial dimensions, or from difficulties in incorporating surface-intense physical and chemical phenomena. Phase field models have the robustness of the level set method, combined with the ability to implement surface-specific chemistry that is required to model crystal growth, although they do not necessarily directly solve for the advancing front location. We have adopted a phase field approach and will present results of the adatom density and step-growth location in time as a function of processing conditions, such as temperature and plasma gas composition.

Mapping the environmental limitations to growth of coastal Douglas-fir stands on Vancouver Island, British Columbia.

PubMed

Coops, Nicholas C; Coggins, Sam B; Kurz, Werner A

2007-06-01

Coastal Douglas-fir (Pseudotsuga menziesii spp. menziesii (Mirb.) Franco) occurs over a wide range of environmental conditions on Vancouver Island, British Columbia. Although ecological zones have been drawn, no formal spatial analysis of environmental limitations on tree growth has been carried out. Such an exercise is desirable to identify areas that may warrant intensive management and to evaluate the impacts of predicted climate change this century. We applied a physiologically based forest growth model, 3-PG (Physiological Principles Predicting Growth), to interpret and map current limitations to Douglas-fir growth across Vancouver Island at 100-m cell resolution. We first calibrated the model to reproduce the regional productivity estimates reported in yield table growth curves. Further analyses indicated that slope exposure is important; southwest slopes of 30 degrees receive 40% more incident radiation than similarly inclined northeast slopes. When combined with other environmental differences associated with aspect, the model predicted 60% more growth on southwest exposures than on northeast exposures. The model simulations support field observations that drought is rare in the wetter zones, but common on the eastern side of Vancouver Island at lower elevations and on more exposed slopes. We illustrate the current limitations on growth caused by suboptimal temperature, high vapor pressure deficits and other factors. The modeling approach complements ecological classifications and offers the potential to identify the most favorable sites for management of other native tree species under current and future climatic conditions.

Exploring the importance of within-canopy spatial temperature variation on transpiration predictions

PubMed Central

Bauerle, William L.; Bowden, Joseph D.; Wang, G. Geoff; Shahba, Mohamed A.

2009-01-01

Models seldom consider the effect of leaf-level biochemical acclimation to temperature when scaling forest water use. Therefore, the dependence of transpiration on temperature acclimation was investigated at the within-crown scale in climatically contrasting genotypes of Acer rubrum L., cv. October Glory (OG) and Summer Red (SR). The effects of temperature acclimation on intracanopy gradients in transpiration over a range of realistic forest growth temperatures were also assessed by simulation. Physiological parameters were applied, with or without adjustment for temperature acclimation, to account for transpiration responses to growth temperature. Both types of parameterization were scaled up to stand transpiration (expressed per unit leaf area) with an individual tree model (MAESTRA) to assess how transpiration might be affected by spatial and temporal distributions of foliage properties. The MAESTRA model performed well, but its reproducibility was dependent on physiological parameters acclimated to daytime temperature. Concordance correlation coefficients between measured and predicted transpiration were higher (0.95 and 0.98 versus 0.87 and 0.96) when model parameters reflected acclimated growth temperature. In response to temperature increases, the southern genotype (SR) transpiration responded more than the northern (OG). Conditions of elevated long-term temperature acclimation further separate their transpiration differences. Results demonstrate the importance of accounting for leaf-level physiological adjustments that are sensitive to microclimate changes and the use of provenance-, ecotype-, and/or genotype-specific parameter sets, two components likely to improve the accuracy of site-level and ecosystem-level estimates of transpiration flux. PMID:19561047

Effective equations governing an active poroelastic medium

PubMed Central

2017-01-01

In this work, we consider the spatial homogenization of a coupled transport and fluid–structure interaction model, to the end of deriving a system of effective equations describing the flow, elastic deformation and transport in an active poroelastic medium. The ‘active’ nature of the material results from a morphoelastic response to a chemical stimulant, in which the growth time scale is strongly separated from other elastic time scales. The resulting effective model is broadly relevant to the study of biological tissue growth, geophysical flows (e.g. swelling in coals and clays) and a wide range of industrial applications (e.g. absorbant hygiene products). The key contribution of this work is the derivation of a system of homogenized partial differential equations describing macroscale growth, coupled to transport of solute, that explicitly incorporates details of the structure and dynamics of the microscopic system, and, moreover, admits finite growth and deformation at the pore scale. The resulting macroscale model comprises a Biot-type system, augmented with additional terms pertaining to growth, coupled to an advection–reaction–diffusion equation. The resultant system of effective equations is then compared with other recent models under a selection of appropriate simplifying asymptotic limits. PMID:28293138

A spatially and temporally explicit, individual-based, life-history and productivity modeling approach for aquatic species

EPA Science Inventory

Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stag...

Potentiostatic controlled nucleation and growth modes of electrodeposited cobalt thin films on n-Si(1 1 1)

NASA Astrophysics Data System (ADS)

Mechehoud, Fayçal; Khelil, Abdelbacet; Eddine Hakiki, Nour; Bubendorff, Jean-Luc

2016-08-01

The nucleation and growth of Co electrodeposits on n-Si(1 1 1) substrate have been investigated as a function of the applied potential in a large potential range using electrochemical techniques (voltammetry and chrono-amperometry) and surface imaging by atomic force microscopy (AFM). The surface preparation of the sample is crucial and we achieve a controlled n-Si(1 1 1) surface with mono-atomic steps and flat terraces. Using Scharifker-Hills models for fitting the current-time transients, we show that a transition from an instantaneous nucleation process to a progressive one occurs when the overpotential increases. A good agreement between the nucleation and growth parameters extracted from the models and the AFM data's is observed. The growth is of the Volmer-Weber type with a roughness and a spatial extension in the substrate plane of the deposited islands that increase with thickness.

Impact of future urban growth on regional climate changes in the Seoul Metropolitan Area, Korea.

PubMed

Kim, Hyunsu; Kim, Yoo-Keun; Song, Sang-Keun; Lee, Hwa Woon

2016-11-15

The influence of changes in future urban growth (e.g., land use changes) on the future climate variability in the Seoul metropolitan area (SMA), Korea was evaluated using the WRF model and an urban growth model (SLEUTH). The land use changes in the study area were simulated using the SLEUTH model under three different urban growth scenarios: (1) current development trends scenario (SC 1), (2) managed development scenario (SC 2) and (3) ecological development scenario (SC 3). The maximum difference in the ratio of urban growth between SC 1 and SC 3 (SC 1 - SC 3) for 50years (2000-2050) was approximately 6.72%, leading to the largest differences (0.01°C and 0.03ms(-1), respectively) in the mean air temperature at 2m (T2) and wind speed at 10m (WS10). From WRF-SLEUTH modeling, the effects of future urban growth (or future land use changes) in the SMA are expected to result in increases in the spatial mean T2 and WS10 of up to 1.15°C and 0.03ms(-1), respectively, possibly due to thermal circulation caused by the thermal differences between urban and rural regions. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling spatial invasion of Ebola in West Africa.

PubMed

D'Silva, Jeremy P; Eisenberg, Marisa C

2017-09-07

The 2014-2016 Ebola Virus Disease (EVD) epidemic in West Africa was the largest ever recorded, representing a fundamental shift in Ebola epidemiology with unprecedented spatiotemporal complexity. To understand the spatiotemporal dynamics of EVD in West Africa, we developed spatial transmission models using a gravity-model framework at both the national and district-level scales, which we used to compare effectiveness of local interventions (e.g. local quarantine) and long-range interventions (e.g. border-closures). The country-level gravity model captures the epidemic data, including multiple waves of initial epidemic growth observed in Guinea. We found that local-transmission reductions were most effective in Liberia, while long-range transmission was dominant in Sierra Leone. Both models illustrated that interventions in one region result in an amplified protective effect on other regions by preventing spatial transmission. In the district-level model, interventions in the strongest of these amplifying regions reduced total cases in all three countries by over 20%, in spite of the region itself generating only ∼0.1% of total cases. This model structure and associated intervention analysis provide information that can be used by public health policymakers to assist planning and response efforts for future epidemics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2015-09-30

spatial and temporal distribution of key marine organisms over multiple trophic levels, and (2) natural and anthropogenic variability in ecosystem...areas of climate modeling in upwelling regions (E. Curchitser), physical-biological modeling in the CCLME (J. Fiechter and C. Edwards), data...optimal growth conditions). By comparing interannual changes in fat depot against EOF modes for environmental variability (i.e., SST) and prey

Simulating historical variability in the amount of old forests in the Oregon Coast Range.

Treesearch

M.C. Wimberly; T.M. Spies; C.J. Long; C. Whitlock

2000-01-01

We developed the landscape age-class demographics simulator (LADS) to model historical variability in the amount of old-growth and late-successional forest in the Oregon Coast Range over the past 3,000 years. The model simulated temporal and spatial patterns of forest fires along with the resulting fluctuations in the distribution of forest age classes across the...

Simulation of crop yield variability by improved root-soil-interaction modelling

NASA Astrophysics Data System (ADS)

Duan, X.; Gayler, S.; Priesack, E.

2009-04-01

Understanding the processes and factors that govern the within-field variability in crop yield has attached great importance due to applications in precision agriculture. Crop response to environment at field scale is a complex dynamic process involving the interactions of soil characteristics, weather conditions and crop management. The numerous static factors combined with temporal variations make it very difficult to identify and manage the variability pattern. Therefore, crop simulation models are considered to be useful tools in analyzing separately the effects of change in soil or weather conditions on the spatial variability, in order to identify the cause of yield variability and to quantify the spatial and temporal variation. However, tests showed that usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability, while their performance on crop growth simulation under more homogeneous and mainly non-limiting conditions was sufficent to simulate average yields at the field-scale. On a study site in South Germany, within-field variability in crop growth has been documented since years. After detailed analysis and classification of the soil patterns, two site specific factors, the plant-available-water and the O2 deficiency, were considered as the main causes of the crop growth variability in this field. Based on our measurement of root distribution in the soil profile, we hypothesize that in our case the insufficiency of the applied crop models to simulate the yield variability can be due to the oversimplification of the involved root models which fail to be sensitive to different soil conditions. In this study, the root growth model described by Jones et al. (1991) was adapted by using data of root distributions in the field and linking the adapted root model to the CERES crop model. The ability of the new root model to increase the sensitivity of the CERES crop models to different enviromental conditions was then evaluated by means of comparison of the simualtion results with measured data and by scenario calculations.

The Role of Spatially Controlled Cell Proliferation in Limb Bud Morphogenesis

PubMed Central

Boehm, Bernd; Westerberg, Henrik; Lesnicar-Pucko, Gaja; Raja, Sahdia; Rautschka, Michael; Cotterell, James; Swoger, Jim; Sharpe, James

2010-01-01

Although the vertebrate limb bud has been studied for decades as a model system for spatial pattern formation and cell specification, the cellular basis of its distally oriented elongation has been a relatively neglected topic by comparison. The conventional view is that a gradient of isotropic proliferation exists along the limb, with high proliferation rates at the distal tip and lower rates towards the body, and that this gradient is the driving force behind outgrowth. Here we test this hypothesis by combining quantitative empirical data sets with computer modelling to assess the potential role of spatially controlled proliferation rates in the process of directional limb bud outgrowth. In particular, we generate two new empirical data sets for the mouse hind limb—a numerical description of shape change and a quantitative 3D map of cell cycle times—and combine these with a new 3D finite element model of tissue growth. By developing a parameter optimization approach (which explores spatial patterns of tissue growth) our computer simulations reveal that the observed distribution of proliferation rates plays no significant role in controlling the distally extending limb shape, and suggests that directional cell activities are likely to be the driving force behind limb bud outgrowth. This theoretical prediction prompted us to search for evidence of directional cell orientations in the limb bud mesenchyme, and we thus discovered a striking highly branched and extended cell shape composed of dynamically extending and retracting filopodia, a distally oriented bias in Golgi position, and also a bias in the orientation of cell division. We therefore provide both theoretical and empirical evidence that limb bud elongation is achieved by directional cell activities, rather than a PD gradient of proliferation rates. PMID:20644711

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.

PubMed

Marquez-Lago, Tatiana T; Burrage, Kevin

2007-09-14

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

Pelagic larval duration and settlement size of a reef fish are spatially consistent, but post-settlement growth varies at the reef scale

NASA Astrophysics Data System (ADS)

Leahy, Susannah M.; Russ, Garry R.; Abesamis, Rene A.

2015-12-01

Recent research has demonstrated that, despite a pelagic larval stage, many coral reef fishes disperse over relatively small distances, leading to well-connected populations on scales of 0-30 km. Although variation in key biological characteristics has been explored on the scale of 100-1000 s of km, it has rarely been explored at the scale relevant to actual larval dispersal and population connectivity on ecological timescales. In this study, we surveyed the habitat and collected specimens ( n = 447) of juvenile butterflyfish, Chaetodon vagabundus, at nine sites along an 80-km stretch of coastline in the central Philippines to identify variation in key life history parameters at a spatial scale relevant to population connectivity. Mean pelagic larval duration (PLD) was 24.03 d (SE = 0.16 d), and settlement size was estimated to be 20.54 mm total length (TL; SE = 0.61 mm). Both traits were spatially consistent, although this PLD is considerably shorter than that reported elsewhere. In contrast, post-settlement daily growth rates, calculated from otolith increment widths from 1 to 50 d post-settlement, varied strongly across the study region. Elevated growth rates were associated with rocky habitats that this species is known to recruit to, but were strongly negatively correlated with macroalgal cover and exhibited negative density dependence with conspecific juveniles. Larger animals had lower early (first 50 d post-settlement) growth rates than smaller animals, even after accounting for seasonal variation in growth rates. Both VBGF and Gompertz models provided good fits to post-settlement size-at-age data ( n = 447 fish), but the VBGF's estimate of asymptotic length ( L ∞ = 168 mm) was more consistent with field observations of maximum fish length. Our findings indicate that larval characteristics are consistent at the spatial scale at which populations are likely well connected, but that site-level biological differences develop post-settlement, most likely as a result of key differences in quality of recruitment habitat.

Polarity, cell division, and out-of-equilibrium dynamics control the growth of epithelial structures

PubMed Central

Cerruti, Benedetta; Puliafito, Alberto; Shewan, Annette M.; Yu, Wei; Combes, Alexander N.; Little, Melissa H.; Chianale, Federica; Primo, Luca; Serini, Guido; Mostov, Keith E.; Celani, Antonio

2013-01-01

The growth of a well-formed epithelial structure is governed by mechanical constraints, cellular apico-basal polarity, and spatially controlled cell division. Here we compared the predictions of a mathematical model of epithelial growth with the morphological analysis of 3D epithelial structures. In both in vitro cyst models and in developing epithelial structures in vivo, epithelial growth could take place close to or far from mechanical equilibrium, and was determined by the hierarchy of time-scales of cell division, cell–cell rearrangements, and lumen dynamics. Equilibrium properties could be inferred by the analysis of cell–cell contact topologies, and the nonequilibrium phenotype was altered by inhibiting ROCK activity. The occurrence of an aberrant multilumen phenotype was linked to fast nonequilibrium growth, even when geometric control of cell division was correctly enforced. We predicted and verified experimentally that slowing down cell division partially rescued a multilumen phenotype induced by altered polarity. These results improve our understanding of the development of epithelial organs and, ultimately, of carcinogenesis. PMID:24145168

Classical and Non-Classical Regimes of the Limited-Fetch Wave Growth and Localized Structures on the Surface of Water

DTIC Science & Technology

2013-09-30

specifying the wave-maker driving signal . The short intense envelope solitons possess vertical asymmetry similar to regular Stokes waves with the same...presented in [P1], [P2]. 2. Physical model of sea wave period from altimeter data We use the asymptotic theory of wind wave growth proposed in [R6...relationship can be used for processing altimeter data assuming the wave field to be stationary and spatially inhomogeneous. It is consistent with

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions (proceedings)

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales.

EPA Science Inventory

The water quality of the Nation’s estuaries is attracting scrutiny in light of population growth and enhanced nutrient delivery. The USEPA has evaluated water quality in the National Coastal Assessment (NCA) and National Aquatic Resource Surveys (NARS) programs. Here we rep...

HYDRAULIC REDISTRIBUTION OF SOIL WATER IN TWO OLD-GROWTH CONIFEROUS FORESTS: QUANTIFYING PATTERNS AND CONTROLS

EPA Science Inventory

Although hydraulic redistribution of soil water (HR) by roots is a widespread phenomenon, the processes governing spatial and temporal patterns of HR are not well understood. We incorporated soil/plant biophysical properties into a simple model based on Darcy's law to predict sea...

Urban Sustainability and Public Health: Throwing the Bath Water Out and Not the Baby

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

2009-01-01

This slide presentation reviews the affect of urbanization on community health. It exams urbanization trends in the Atlanta metro area and includes information on impervious surfaces, air quality, mitigation strategies, spatial growth modeling, land use, public health surveillance and different data collection methods.

Spatially-explicit and spectral soil carbon modeling in Florida

USDA-ARS?s Scientific Manuscript database

Profound shifts have occurred over the last three centuries in which human actions have become the main driver to global environmental change. In this new epoch, the Anthropocene, human-driven changes such as population growth, climate and land use change, are pushing the Earth system well outside i...

Elements of Engagement: A Model of Teacher Interactions via Professional Learning Networks

ERIC Educational Resources Information Center

Krutka, Daniel G.; Carpenter, Jeffrey P.; Trust, Torrey

2016-01-01

In recent years, many educators have turned to participatory online affinity spaces for professional growth with peers who are more accessible because of reduced temporal and spatial constraints. Specifically, professional learning networks (PLNs) are "uniquely personalized, complex systems of interactions consisting of people, resources, and…

Potential economic consequences of local nonconformity to regional land use and transportation plans using a spatial economic model.

DOT National Transportation Integrated Search

2011-06-01

To achieve the greenhouse gas (GHG) reduction targets that are required by Californias global warming legislation (AB32), the state of California has determined that recent growth trends in vehicle miles traveled (VMT) must be curtailed. In recogn...

Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales

EPA Science Inventory

Background/Question/MethodThe water quality of the Nation’s estuaries is attracting increasing scrutiny in light of burgeoning coastal population growth and enhanced delivery of nutrients via riverine flux. The USEPA has evaluated water quality in US estuaries in the Nation...

Analysis of Plasma-Sprayed Thermal Barrier Coatings With Homogeneous and Heterogeneous Bond Coats Under Spatially Uniform Cyclic Thermal Loading

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Pindera, Marek-Jerzy; Aboudi, Jacob

2003-01-01

This report summarizes the results of a numerical investigation into the spallation mechanism in plasma-sprayed thermal barrier coatings observed under spatially-uniform cyclic thermal loading. The analysis focuses on the evolution of local stress and inelastic strain fields in the vicinity of the rough top/bond coat interface during thermal cycling, and how these fields are influenced by the presence of an oxide film and spatially uniform and graded distributions of alumina particles in the metallic bond coat aimed at reducing the top/bond coat thermal expansion mismatch. The impact of these factors on the potential growth of a local horizontal delamination at the rough interface's crest is included. The analysis is conducted using the Higher-Order Theory for Functionally Graded Materials with creep/relaxation constituent modeling capabilities. For two-phase bond coat microstructures, both the actual and homogenized properties are employed in the analysis. The results reveal the important contributions of both the normal and shear stress components to the delamination growth potential in the presence of an oxide film, and suggest mixed-mode crack propagation. The use of bond coats with uniform or graded microstructures is shown to increase the potential for delamination growth by increasing the magnitude of the crack-tip shear stress component.

Spatially random mortality in old-growth red pine forests of northern Minnesota

Treesearch

Tuomas ​Aakala; Shawn Fraver; Brian J. Palik; Anthony W. D' Amato

2012-01-01

Characterizing the spatial distribution of tree mortality is critical to understanding forest dynamics, but empirical studies on these patterns under old-growth conditions are rare. This rarity is due in part to low mortality rates in old-growth forests, the study of which necessitates long observation periods, and the confounding influence of tree in-growth during...

A Multi-Level Approach to Modeling Rapidly Growing Mega-Regions as a Coupled Human-Natural System

NASA Astrophysics Data System (ADS)

Koch, J. A.; Tang, W.; Meentemeyer, R. K.

2013-12-01

The FUTure Urban-Regional Environment Simulation (FUTURES) integrates information on nonstationary drivers of land change (per capita land area demand, site suitability, and spatial structure of conversion events) into spatial-temporal projections of changes in landscape patterns (Meentemeyer et al., 2013). One striking feature of FUTURES is its patch-growth algorithm that includes feedback effects of former development events across several temporal and spatial scales: cell-level transition events are aggregated into patches of land change and their further growth is based on empirically derived parameters controlling its size, shape, and dispersion. Here, we augment the FUTURES modeling framework by expanding its multilevel structure and its representation of human decision making. The new modeling framework is hierarchically organized as nested subsystems including the latest theory on telecouplings in coupled human-natural systems (Liu et al., 2013). Each subsystem represents a specific level of spatial scale and embraces agents that have decision making authority at a particular level. The subsystems are characterized with regard to their spatial representation and are connected via flows of information (e.g. regulations and policies) or material (e.g. population migration). To provide a modeling framework that is applicable to a wide range of settings and geographical regions and to keep it computationally manageable, we implement a 'zooming factor' that allows to enable or disable subsystems (and hence the represented processes), based on the extent of the study region. The implementation of the FUTURES modeling framework for a specific case study follows the observational modeling approach described in Grimm et al. (2005), starting from the analysis of empirical data in order to capture the processes relevant for specific scales and to allow a rigorous calibration and validation of the model application. In this paper, we give an introduction to the basic concept of our modeling approach and describe its strengths and weaknesses. We furthermore use empirical data for the states of North and South Carolina to demonstrate how the modeling framework can be applied to a large, heterogeneous study system with diverse decision-making agents. Grimm et al. (2005) Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology. Science 310, 987-991. Liu et al. (2013) Framing Sustainability in a Telecoupled World. Ecology and Society 18(2), 26. Meentemeyer et al. (2013) FUTURES: Multilevel Simulations of Merging Urban-Rural Landscape Structure Using a Stochastic Patch-Growing Algorithm. Annals of the Association of American Geographers 103(4), 785-807.

A Comparative Study of Spatial Aggregation Methodologies under the BioEarth Framework

NASA Astrophysics Data System (ADS)

Chandrasekharan, B.; Rajagopalan, K.; Malek, K.; Stockle, C. O.; Adam, J. C.; Brady, M.

2014-12-01

The increasing probability of water resource scarcity due to climate change has highlighted the need for adopting an economic focus in modelling water resource uses. Hydro-economic models, developed by integrating economic optimization with biophysical crop models, are driven by the economic value of water, revealing it's most efficient uses and helping policymakers evaluate different water management strategies. One of the challenges in integrating biophysical models with economic models is the difference in the spatial scales in which they operate. Biophysical models that provide crop production functions typically run at smaller scale than economic models, and substantial spatial aggregation is required. However, any aggregation introduces a bias, i.e., a discrepancy between the functional value at the higher spatial scale and the value at the spatial scale of the aggregated units. The objective of this work is to study the sensitivity of net economic benefits in the Yakima River basin (YRB) to different spatial aggregation methods for crop production functions. The spatial aggregation methodologies that we compare involve agro-ecological zones (AEZs) and aggregation levels that reflect water management regimes (e.g. irrigation districts). Aggregation bias can distort the underlying data and result in extreme solutions. In order to avoid this we use an economic optimization model that incorporates the synthetic and historical crop mixes approach (Onal & Chen, 2012). This restricts the solutions between the weighted averages of historical and simulated feasible planting decisions, with the weights associated with crop mixes being treated as endogenous variables. This study is focused on 5 major irrigation districts of the YRB in the Pacific Northwest US. The biophysical modeling framework we use, BioEarth, includes the coupled hydrology and crop growth model, VIC-Cropsyst and an economic optimization model. Preliminary findings indicate that the standard approach of developing AEZs does not perform well when overlaid with irrigation districts. Moreover, net economic benefits were significantly different between the two aggregation methodologies. Therefore, while developing hydro-economic models, significant consideration should be placed on the aggregation methodology.

On the genetic control of planar growth during tissue morphogenesis in plants.

PubMed

Enugutti, Balaji; Kirchhelle, Charlotte; Schneitz, Kay

2013-06-01

Tissue morphogenesis requires extensive intercellular communication. Plant organs are composites of distinct radial cell layers. A typical layer, such as the epidermis, is propagated by stereotypic anticlinal cell divisions. It is presently unclear what mechanisms coordinate cell divisions relative to the plane of a layer, resulting in planar growth and maintenance of the layer structure. Failure in the regulation of coordinated growth across a tissue may result in spatially restricted abnormal growth and the formation of a tumor-like protrusion. Therefore, one way to approach planar growth control is to look for genetic mutants that exhibit localized tumor-like outgrowths. Interestingly, plants appear to have evolved quite robust genetic mechanisms that govern these aspects of tissue morphogenesis. Here we provide a short summary of the current knowledge about the genetics of tumor formation in plants and relate it to the known control of coordinated cell behavior within a tissue layer. We further portray the integuments of Arabidopsis thaliana as an excellent model system to study the regulation of planar growth. The value of examining this process in integuments was established by the recent identification of the Arabidopsis AGC VIII kinase UNICORN as a novel growth suppressor involved in the regulation of planar growth and the inhibition of localized ectopic growth in integuments and other floral organs. An emerging insight is that misregulation of central determinants of adaxial-abaxial tissue polarity can lead to the formation of spatially restricted multicellular outgrowths in several tissues. Thus, there may exist a link between the mechanisms regulating adaxial-abaxial tissue polarity and planar growth in plants.

Combining Individual-Based Modeling and Food Microenvironment Descriptions To Predict the Growth of Listeria monocytogenes on Smear Soft Cheese

PubMed Central

Ferrier, Rachel; Hezard, Bernard; Lintz, Adrienne; Stahl, Valérie

2013-01-01

An individual-based modeling (IBM) approach was developed to describe the behavior of a few Listeria monocytogenes cells contaminating smear soft cheese surface. The IBM approach consisted of assessing the stochastic individual behaviors of cells on cheese surfaces and knowing the characteristics of their surrounding microenvironments. We used a microelectrode for pH measurements and micro-osmolality to assess the water activity of cheese microsamples. These measurements revealed a high variability of microscale pH compared to that of macroscale pH. A model describing the increase in pH from approximately 5.0 to more than 7.0 during ripening was developed. The spatial variability of the cheese surface characterized by an increasing pH with radius and higher pH on crests compared to that of hollows on cheese rind was also modeled. The microscale water activity ranged from approximately 0.96 to 0.98 and was stable during ripening. The spatial variability on cheese surfaces was low compared to between-cheese variability. Models describing the microscale variability of cheese characteristics were combined with the IBM approach to simulate the stochastic growth of L. monocytogenes on cheese, and these simulations were compared to bacterial counts obtained from irradiated cheeses artificially contaminated at different ripening stages. The simulated variability of L. monocytogenes counts with the IBM/microenvironmental approach was consistent with the observed one. Contrasting situations corresponding to no growth or highly contaminated foods could be deduced from these models. Moreover, the IBM approach was more effective than the traditional population/macroenvironmental approach to describe the actual bacterial behavior variability. PMID:23872572

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

Simulation and modeling of whistler mode wave growth through cyclotron resonance with energetic electrons in the magnetosphere

NASA Astrophysics Data System (ADS)

Carlson, Curtis Ray

New models and simulations of wave growth experienced by electromagnetic waves propagating through the magnetosphere in the whistler mode are presented. The main emphasis is to simulate single frequency wave pulses, in the 2 to 6 kHz range, that have been injected into the magnetosphere, near L approximately 4. Simulations using a new transient model reproduce exponential wave growth and saturation coincident with a linearly increasing frequency versus time (up to 60 Hz/s). Unique methods for calculating the phased bunched currents, stimulated radiation, and radiation propagation are based upon test particle trajectories calculated by integrating nonlinear equations of motion generalized to allow the evolution of the frequency and wave number at each point in space. Results show the importance of the transient aspects in the wave growth process. The wave growth established as the wave propagates toward the equator is given a spatially advancing wave phase structure by the geomagnetic inhomogeneity. Through the feedback of this radiation upon other electrons, the conditions are set up which result in the linearly increasing output frequency with time. The transient simulations also show that features like growth rate and total growth are simply related to the various parameters, such as applied wave intensity, energetic electron flux, and energetic electron distribution.

Nucleation and Spread of an Invasive Allele

NASA Astrophysics Data System (ADS)

Korniss, Gyorgy; Caraco, Thomas

2005-03-01

We analyze a prototypical discrete spatial model for the spread of an invasive allele when individuals compete preemptively for common limiting resources. Initially, the population is genetically monomorphic with the resident allele at high density. The invasive allele is introduced through rare, but recurrent, mutation. The mutant allele is the better competitor (has an individual-level advantage) but its spread is limited by the local availability of resources. We find that each successful introduction of the mutant leads to strong spatial clustering. Spatial patterns in simulation resemble nucleation and subsequent growth, articulately described by Avrami's law in sufficiently large systemsootnotetextG. Korniss and T. Caraco, J. Theor. Biol. (in press, 2004); http://www.rpi.edu/ korniss/Research/JTB04.pdf.

Topology of an intracellular transduction chain (phototropism of Phycomyces): 1. Joint review of functional, temporal, and spatial aspects.

PubMed

Wenzler, D; Reinhardt, M; Fukshansky, L

2001-08-21

Two light-induced growth reactions in a unicellular cylindrical sporangiophore of Phycomyces blakesleeanus-vertical growth acceleration under symmetrical irradiation (photomecism) and directional growth under unilateral irradiation (phototropism)-share common input light perception as well as common output growth mechanism but have strongly divergent dynamics and other distinctive features. This divergence culminates in the phototropic paradoxes the main of which states that photomecism shows total adaptation, while phototropism does not adapt. The basis for this contradiction is that the phototropic transduction chain, unlike that of photomecism, faces a spatially non-uniform stimulus and processes a series of spatial patterns (light and absorption profiles, adaptation profile, etc.). The only way to resolve the paradoxes and correlate features of both responses within a single transduction chain is to assume non-local signal transduction, e.g. a cross-talk between different azimuthal locations within the cylindrical cell. On the other hand, to establish the presence of an appropriate cross-talk is equivalent of gaining insight into the topology of the transduction chain. This series of two papers contains a review reconsidering the entire field from this viewpoint (Paper 1) and a mathematical model of pattern transduction which unifies features of phototropism and resolves the paradoxes (Paper 2). At the same time, this is the first "proof of concept" for the "activity/pooling (a/p) networks"-a specific mathematical apparatus designed to analyse systemic properties and control in metabolic pathways. Copyright 2001 Academic Press.

Phase-field crystal modeling of heteroepitaxy and exotic modes of crystal nucleation

NASA Astrophysics Data System (ADS)

Podmaniczky, Frigyes; Tóth, Gyula I.; Tegze, György; Pusztai, Tamás; Gránásy, László

2017-01-01

We review recent advances made in modeling heteroepitaxy, two-step nucleation, and nucleation at the growth front within the framework of a simple dynamical density functional theory, the Phase-Field Crystal (PFC) model. The crystalline substrate is represented by spatially confined periodic potentials. We investigate the misfit dependence of the critical thickness in the StranskiKrastanov growth mode in isothermal studies. Apparently, the simulation results for stress release via the misfit dislocations fit better to the PeopleBean model than to the one by Matthews and Blakeslee. Next, we investigate structural aspects of two-step crystal nucleation at high undercoolings, where an amorphous precursor forms in the first stage. Finally, we present results for the formation of new grains at the solid-liquid interface at high supersaturations/supercoolings, a phenomenon termed Growth Front Nucleation (GFN). Results obtained with diffusive dynamics (applicable to colloids) and with a hydrodynamic extension of the PFC theory (HPFC, developed for simple liquids) will be compared. The HPFC simulations indicate two possible mechanisms for GFN.

Parametric studies of metabolic cooperativity in Escherichia coli colonies: Strain and geometric confinement effects

PubMed Central

Cole, John A.; Luthey-Schulten, Zaida

2017-01-01

Characterizing the complex spatial and temporal interactions among cells in a biological system (i.e. bacterial colony, microbiome, tissue, etc.) remains a challenge. Metabolic cooperativity in these systems can arise due to the subtle interplay between microenvironmental conditions and the cells’ regulatory machinery, often involving cascades of intra- and extracellular signalling molecules. In the simplest of cases, as demonstrated in a recent study of the model organism Escherichia coli, metabolic cross-feeding can arise in monoclonal colonies of bacteria driven merely by spatial heterogeneity in the availability of growth substrates; namely, acetate, glucose and oxygen. Another recent study demonstrated that even closely related E. coli strains evolved different glucose utilization and acetate production capabilities, hinting at the possibility of subtle differences in metabolic cooperativity and the resulting growth behavior of these organisms. Taking a first step towards understanding the complex spatio-temporal interactions within microbial populations, we performed a parametric study of E. coli growth on an agar substrate and probed the dependence of colony behavior on: 1) strain-specific metabolic characteristics, and 2) the geometry of the underlying substrate. To do so, we employed a recently developed multiscale technique named 3D dynamic flux balance analysis which couples reaction-diffusion simulations with iterative steady-state metabolic modeling. Key measures examined include colony growth rate and shape (height vs. width), metabolite production/consumption and concentration profiles, and the emergence of metabolic cooperativity and the fractions of cell phenotypes. Five closely related strains of E. coli, which exhibit large variation in glucose consumption and organic acid production potential, were studied. The onset of metabolic cooperativity was found to vary substantially between these five strains by up to 10 hours and the relative fraction of acetate utilizing cells within the colonies varied by a factor of two. Additionally, growth with six different geometries designed to mimic those that might be found in a laboratory, a microfluidic device, and inside a living organism were considered. Geometries were found to have complex, often nonlinear effects on colony growth and cross-feeding with “hard” features resulting in larger effect than “soft” features. These results demonstrate that strain-specific features and spatial constraints imposed by the growth substrate can have significant effects even for microbial populations as simple as isogenic E. coli colonies. PMID:28820904

Parametric studies of metabolic cooperativity in Escherichia coli colonies: Strain and geometric confinement effects.

PubMed

Peterson, Joseph R; Cole, John A; Luthey-Schulten, Zaida

2017-01-01

Characterizing the complex spatial and temporal interactions among cells in a biological system (i.e. bacterial colony, microbiome, tissue, etc.) remains a challenge. Metabolic cooperativity in these systems can arise due to the subtle interplay between microenvironmental conditions and the cells' regulatory machinery, often involving cascades of intra- and extracellular signalling molecules. In the simplest of cases, as demonstrated in a recent study of the model organism Escherichia coli, metabolic cross-feeding can arise in monoclonal colonies of bacteria driven merely by spatial heterogeneity in the availability of growth substrates; namely, acetate, glucose and oxygen. Another recent study demonstrated that even closely related E. coli strains evolved different glucose utilization and acetate production capabilities, hinting at the possibility of subtle differences in metabolic cooperativity and the resulting growth behavior of these organisms. Taking a first step towards understanding the complex spatio-temporal interactions within microbial populations, we performed a parametric study of E. coli growth on an agar substrate and probed the dependence of colony behavior on: 1) strain-specific metabolic characteristics, and 2) the geometry of the underlying substrate. To do so, we employed a recently developed multiscale technique named 3D dynamic flux balance analysis which couples reaction-diffusion simulations with iterative steady-state metabolic modeling. Key measures examined include colony growth rate and shape (height vs. width), metabolite production/consumption and concentration profiles, and the emergence of metabolic cooperativity and the fractions of cell phenotypes. Five closely related strains of E. coli, which exhibit large variation in glucose consumption and organic acid production potential, were studied. The onset of metabolic cooperativity was found to vary substantially between these five strains by up to 10 hours and the relative fraction of acetate utilizing cells within the colonies varied by a factor of two. Additionally, growth with six different geometries designed to mimic those that might be found in a laboratory, a microfluidic device, and inside a living organism were considered. Geometries were found to have complex, often nonlinear effects on colony growth and cross-feeding with "hard" features resulting in larger effect than "soft" features. These results demonstrate that strain-specific features and spatial constraints imposed by the growth substrate can have significant effects even for microbial populations as simple as isogenic E. coli colonies.

Epitaxial Growth of Hetero-Ln-MOF Hierarchical Single Crystals for Domain- and Orientation-Controlled Multicolor Luminescence 3D Coding Capability.

PubMed

Pan, Mei; Zhu, Yi-Xuan; Wu, Kai; Chen, Ling; Hou, Ya-Jun; Yin, Shao-Yun; Wang, Hai-Ping; Fan, Ya-Nan; Su, Cheng-Yong

2017-11-13

Core-shell or striped heteroatomic lanthanide metal-organic framework hierarchical single crystals were obtained by liquid-phase anisotropic epitaxial growth, maintaining identical periodic organization while simultaneously exhibiting spatially segregated structure. Different types of domain and orientation-controlled multicolor photophysical models are presented, which show either visually distinguishable or visible/near infrared (NIR) emissive colors. This provides a new bottom-up strategy toward the design of hierarchical molecular systems, offering high-throughput and multiplexed luminescence color tunability and readability. The unique capability of combining spectroscopic coding with 3D (three-dimensional) microscale spatial coding is established, providing potential applications in anti-counterfeiting, color barcoding, and other types of integrated and miniaturized optoelectronic materials and devices. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inviscid spatial stability of a compressible mixing layer. II - The flame sheet model

NASA Technical Reports Server (NTRS)

Jackson, T. L.; Grosch, C. E.

1990-01-01

The results of an inviscid spatial calculation for a compressible reacting mixing layer are reported. The limit of infinitive activation energy is taken and the diffusion flame is approximated by a flame sheet. Results are reported for the phase speeds of the neutral waves and maximum growth rates of the unstable waves as a function of the parameters of the problem: the ratio of the temperature of the stationary stream to that of the moving stream, the Mach number of the moving streams, the heat release per unit mass fraction of the reactant, the equivalence ratio of the reaction, and the frequency of the disturbance. These results are compared to the phase speeds and growth rates of the corresponding nonreacting mixing layer. We show that the addition of combustion has important and complex effects on the flow stability.

Modelling of groundwater-vegetation interactions in a tidal marsh

NASA Astrophysics Data System (ADS)

Xin, Pei; Kong, Jun; Li, Ling; Barry, D. A.

2013-07-01

Wetting and drying due to tidal fluctuations affect soil conditions and hence plant growth in tidal marshes. Here, a coupled one-dimensional model was developed to simulate interacting groundwater flow and plant growth in these wetlands. The simulation results revealed three characteristic zones of soil conditions for plant growth along a cross-creek section subjected to the combined influences of spring-neap tides and evapotranspiration: (1) a near-creek zone affected by semi-diurnal tides over the whole spring-neap cycle, where the soil is well aerated although the plant growth could be slightly limited by the local water content dropping periodically below the wilting point on the ebb tide; (2) a less well-drained zone where drainage occurs only during neap tides (for which the daily inundation is absent) and plant growth is aeration-limited; and (3) an interior zone where evapotranspiration determines the soil-water saturation. Plant growth dynamics, which depend on these soil conditions, lead to spatial biomass distributions that are consistent with the characteristic zonation. The simulations shed light on the feedback mechanism for groundwater-vegetation interactions in the marsh system. It was demonstrated that the growth of pioneer plants can improve the soil aeration condition as a result of transpiration. The strength of this feedback varies spatially in accordance with the three characteristic zones of soil-water saturation. However, the development of another species in the marsh system is likely to be more complicated than suggested by the "positive feedback" mechanism proposed previously, due to the influence of inter-species competition. The feedback effects are generally more complex, involving both plant growth enhancement and inhibition depending on the combined influence of the intra- and inter-species competition, the ecosystem's carrying capacity and plant transpiration. These findings demonstrate the interplay of ecological and hydrological processes in tidal marshes, and provide guidance for future research, including field investigations that aim to establish the principle relationship between marsh morphology and plant zonation.

Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control

PubMed Central

Kiskowski, Maria; Chowell, Gerardo

2016-01-01

The mechanisms behind the sub-exponential growth dynamics of the West Africa Ebola virus disease epidemic could be related to improved control of the epidemic and the result of reduced disease transmission in spatially constrained contact structures. An individual-based, stochastic network model is used to model immediate and delayed epidemic control in the context of social contact networks and investigate the extent to which the relative role of these factors may be determined during an outbreak. We find that in general, epidemics quickly establish a dynamic equilibrium of infections in the form of a wave of fixed size and speed traveling through the contact network. Both greater epidemic control and limited community mixing decrease the size of an infectious wave. However, for a fixed wave size, epidemic control (in contrast with limited community mixing) results in lower community saturation and a wave that moves more quickly through the contact network. We also found that the level of epidemic control has a disproportionately greater reductive effect on larger waves, so that a small wave requires nearly as much epidemic control as a larger wave to end an epidemic. PMID:26399855

Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control.

PubMed

Kiskowski, Maria; Chowell, Gerardo

2016-01-01

The mechanisms behind the sub-exponential growth dynamics of the West Africa Ebola virus disease epidemic could be related to improved control of the epidemic and the result of reduced disease transmission in spatially constrained contact structures. An individual-based, stochastic network model is used to model immediate and delayed epidemic control in the context of social contact networks and investigate the extent to which the relative role of these factors may be determined during an outbreak. We find that in general, epidemics quickly establish a dynamic equilibrium of infections in the form of a wave of fixed size and speed traveling through the contact network. Both greater epidemic control and limited community mixing decrease the size of an infectious wave. However, for a fixed wave size, epidemic control (in contrast with limited community mixing) results in lower community saturation and a wave that moves more quickly through the contact network. We also found that the level of epidemic control has a disproportionately greater reductive effect on larger waves, so that a small wave requires nearly as much epidemic control as a larger wave to end an epidemic.

Regulation of the demographic structure in isomorphic biphasic life cycles at the spatial fine scale.

PubMed

Vieira, Vasco Manuel Nobre de Carvalho da Silva; Mateus, Marcos Duarte

2014-01-01

Isomorphic biphasic algal life cycles often occur in the environment at ploidy abundance ratios (Haploid:Diploid) different from 1. Its spatial variability occurs within populations related to intertidal height and hydrodynamic stress, possibly reflecting the niche partitioning driven by their diverging adaptation to the environment argued necessary for their prevalence (evolutionary stability). Demographic models based in matrix algebra were developed to investigate which vital rates may efficiently generate an H:D variability at a fine spatial resolution. It was also taken into account time variation and type of life strategy. Ploidy dissimilarities in fecundity rates set an H:D spatial structure miss-fitting the ploidy fitness ratio. The same happened with ploidy dissimilarities in ramet growth whenever reproductive output dominated the population demography. Only through ploidy dissimilarities in looping rates (stasis, breakage and clonal growth) did the life cycle respond to a spatially heterogeneous environment efficiently creating a niche partition. Marginal locations were more sensitive than central locations. Related results have been obtained experimentally and numerically for widely different life cycles from the plant and animal kingdoms. Spore dispersal smoothed the effects of ploidy dissimilarities in fertility and enhanced the effects of ploidy dissimilarities looping rates. Ploidy dissimilarities in spore dispersal could also create the necessary niche partition, both over the space and time dimensions, even in spatial homogeneous environments and without the need for conditional differentiation of the ramets. Fine scale spatial variability may be the key for the prevalence of isomorphic biphasic life cycles, which has been neglected so far.

Regulation of the Demographic Structure in Isomorphic Biphasic Life Cycles at the Spatial Fine Scale

PubMed Central

Vieira, Vasco Manuel Nobre de Carvalho da Silva; Mateus, Marcos Duarte

2014-01-01

Isomorphic biphasic algal life cycles often occur in the environment at ploidy abundance ratios (Haploid:Diploid) different from 1. Its spatial variability occurs within populations related to intertidal height and hydrodynamic stress, possibly reflecting the niche partitioning driven by their diverging adaptation to the environment argued necessary for their prevalence (evolutionary stability). Demographic models based in matrix algebra were developed to investigate which vital rates may efficiently generate an H:D variability at a fine spatial resolution. It was also taken into account time variation and type of life strategy. Ploidy dissimilarities in fecundity rates set an H:D spatial structure miss-fitting the ploidy fitness ratio. The same happened with ploidy dissimilarities in ramet growth whenever reproductive output dominated the population demography. Only through ploidy dissimilarities in looping rates (stasis, breakage and clonal growth) did the life cycle respond to a spatially heterogeneous environment efficiently creating a niche partition. Marginal locations were more sensitive than central locations. Related results have been obtained experimentally and numerically for widely different life cycles from the plant and animal kingdoms. Spore dispersal smoothed the effects of ploidy dissimilarities in fertility and enhanced the effects of ploidy dissimilarities looping rates. Ploidy dissimilarities in spore dispersal could also create the necessary niche partition, both over the space and time dimensions, even in spatial homogeneous environments and without the need for conditional differentiation of the ramets. Fine scale spatial variability may be the key for the prevalence of isomorphic biphasic life cycles, which has been neglected so far. PMID:24658603

Force loading explains spatial sensing of ligands by cells

NASA Astrophysics Data System (ADS)

Oria, Roger; Wiegand, Tina; Escribano, Jorge; Elosegui-Artola, Alberto; Uriarte, Juan Jose; Moreno-Pulido, Cristian; Platzman, Ilia; Delcanale, Pietro; Albertazzi, Lorenzo; Navajas, Daniel; Trepat, Xavier; García-Aznar, José Manuel; Cavalcanti-Adam, Elisabetta Ada; Roca-Cusachs, Pere

2017-12-01

Cells can sense the density and distribution of extracellular matrix (ECM) molecules by means of individual integrin proteins and larger, integrin-containing adhesion complexes within the cell membrane. This spatial sensing drives cellular activity in a variety of normal and pathological contexts. Previous studies of cells on rigid glass surfaces have shown that spatial sensing of ECM ligands takes place at the nanometre scale, with integrin clustering and subsequent formation of focal adhesions impaired when single integrin-ligand bonds are separated by more than a few tens of nanometres. It has thus been suggested that a crosslinking ‘adaptor’ protein of this size might connect integrins to the actin cytoskeleton, acting as a molecular ruler that senses ligand spacing directly. Here, we develop gels whose rigidity and nanometre-scale distribution of ECM ligands can be controlled and altered. We find that increasing the spacing between ligands promotes the growth of focal adhesions on low-rigidity substrates, but leads to adhesion collapse on more-rigid substrates. Furthermore, disordering the ligand distribution drastically increases adhesion growth, but reduces the rigidity threshold for adhesion collapse. The growth and collapse of focal adhesions are mirrored by, respectively, the nuclear or cytosolic localization of the transcriptional regulator protein YAP. We explain these findings not through direct sensing of ligand spacing, but by using an expanded computational molecular-clutch model, in which individual integrin-ECM bonds—the molecular clutches—respond to force loading by recruiting extra integrins, up to a maximum value. This generates more clutches, redistributing the overall force among them, and reducing the force loading per clutch. At high rigidity and high ligand spacing, maximum recruitment is reached, preventing further force redistribution and leading to adhesion collapse. Measurements of cellular traction forces and actin flow speeds support our model. Our results provide a general framework for how cells sense spatial and physical information at the nanoscale, precisely tuning the range of conditions at which they form adhesions and activate transcriptional regulation.

Characterizing the reproduction number of epidemics with early subexponential growth dynamics

PubMed Central

Viboud, Cécile; Simonsen, Lone; Moghadas, Seyed M.

2016-01-01

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible–infectious–removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The generalized-growth concept also provides us a compelling argument for the unexpected extinction of certain emerging disease outbreaks during the early ascending phase. Overall, our approach promotes a more reliable and data-driven characterization of the early epidemic phase, which is important for accurate estimation of the reproduction number and prediction of disease impact. PMID:27707909

Cooperation in Harsh Environments and the Emergence of Spatial Patterns.

PubMed

Smaldino, Paul E

2013-11-01

This paper concerns the confluence of two important areas of research in mathematical biology: spatial pattern formation and cooperative dilemmas. Mechanisms through which social organisms form spatial patterns are not fully understood. Prior work connecting cooperation and pattern formation has often included unrealistic assumptions that shed doubt on the applicability of those models toward understanding real biological patterns. I investigated a more biologically realistic model of cooperation among social actors. The environment is harsh, so that interactions with cooperators are strictly needed to survive. Harshness is implemented via a constant energy deduction. I show that this model can generate spatial patterns similar to those seen in many naturally-occuring systems. Moreover, for each payoff matrix there is an associated critical value of the energy deduction that separates two distinct dynamical processes. In low-harshness environments, the growth of cooperator clusters is impeded by defectors, but these clusters gradually expand to form dense dendritic patterns. In very harsh environments, cooperators expand rapidly but defectors can subsequently make inroads to form reticulated patterns. The resulting web-like patterns are reminiscent of transportation networks observed in slime mold colonies and other biological systems.

Increased water deficit decreases Douglas fir growth throughout western US forests.

PubMed

Restaino, Christina M; Peterson, David L; Littell, Jeremy

2016-08-23

Changes in tree growth rates can affect tree mortality and forest feedbacks to the global carbon cycle. As air temperature increases, evaporative demand also increases, increasing effective drought in forest ecosystems. Using a spatially comprehensive network of Douglas fir (Pseudotsuga menziesii) chronologies from 122 locations that represent distinct climate environments in the western United States, we show that increased temperature decreases growth via vapor pressure deficit (VPD) across all latitudes. Using an ensemble of global circulation models, we project an increase in both the mean VPD associated with the lowest growth extremes and the probability of exceeding these VPD values. As temperature continues to increase in future decades, we can expect deficit-related stress to increase and consequently Douglas fir growth to decrease throughout its US range.

Increased water deficit decreases Douglas fir growth throughout western US forests

USGS Publications Warehouse

Restaino, Christina M; Peterson, David L.; Littell, Jeremy

2016-01-01

Changes in tree growth rates can affect tree mortality and forest feedbacks to the global carbon cycle. As air temperature increases, evaporative demand also increases, increasing effective drought in forest ecosystems. Using a spatially comprehensive network of Douglas-fir (Pseudotsuga menziesii) chronologies from 122 locations that experience distinctly different climate in the western United States, we show that increased temperature decreases growth via vapor pressure deficit (VPD) across all latitudes. Under an ensemble of global circulation models, we project an increase in both the mean VPD associated with the lowest growth extremes and the probability of exceeding these VPD values. As temperature continues to increase in future decades, we can expect deficit-related stress to increase and consequently Douglas-fir growth to decrease throughout its US range.

Increased water deficit decreases Douglas fir growth throughout western US forests

PubMed Central

Restaino, Christina M.; Peterson, David L.; Littell, Jeremy

2016-01-01

Changes in tree growth rates can affect tree mortality and forest feedbacks to the global carbon cycle. As air temperature increases, evaporative demand also increases, increasing effective drought in forest ecosystems. Using a spatially comprehensive network of Douglas fir (Pseudotsuga menziesii) chronologies from 122 locations that represent distinct climate environments in the western United States, we show that increased temperature decreases growth via vapor pressure deficit (VPD) across all latitudes. Using an ensemble of global circulation models, we project an increase in both the mean VPD associated with the lowest growth extremes and the probability of exceeding these VPD values. As temperature continues to increase in future decades, we can expect deficit-related stress to increase and consequently Douglas fir growth to decrease throughout its US range. PMID:27503880

Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

NASA Astrophysics Data System (ADS)

König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

2015-04-01

Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we show that spatial aspects play a main role for recovering after a severe stress event in a highly heterogeneous environment such as soil, and thus the relevance of the exact distribution of the stressed area. In consequence a spatial-mechanistic view is necessary for examining the functional resilience as the aggregated temporal view alone could not have led to these conclusions. Further research should explore the importance of a spatial view for quantifying the recovery of the ecosystem service also after more complex stress regimes.

Dynamical patterns and regime shifts in the nonlinear model of soil microorganisms growth

NASA Astrophysics Data System (ADS)

Zaitseva, Maria; Vladimirov, Artem; Winter, Anna-Marie; Vasilyeva, Nadezda

2017-04-01

Dynamical model of soil microorganisms growth and turnover is formulated as a system of nonlinear partial differential equations of reaction-diffusion type. We consider spatial distributions of concentrations of several substrates and microorganisms. Biochemical reactions are modelled by chemical kinetic equations. Transport is modelled by simple linear diffusion for all chemical substances, while for microorganisms we use different transport functions, e.g. some of them can actively move along gradient of substrate concentration, while others cannot move. We solve our model in two dimensions, starting from uniform state with small initial perturbations for various parameters and find parameter range, where small initial perturbations grow and evolve. We search for bifurcation points and critical regime shifts in our model and analyze time-space profile and phase portraits of these solutions approaching critical regime shifts in the system, exploring possibility to detect such shifts in advance. This work is supported by NordForsk, project #81513.

Mediterranean maquis fuel model development and mapping to support fire modeling

NASA Astrophysics Data System (ADS)

Bacciu, V.; Arca, B.; Pellizzaro, G.; Salis, M.; Ventura, A.; Spano, D.; Duce, P.

2009-04-01

Fuel load data and fuel model maps represent a critical issue for fire spread and behaviour modeling. The availability of accurate input data at different spatial and temporal scales can allow detailed analysis and predictions of fire hazard and fire effects across a landscape. Fuel model data are used in spatially explicit fire growth models to attain fire behaviour information for fuel management in prescribed fires, fire management applications, firefighters training, smoke emissions, etc. However, fuel type characteristics are difficult to be parameterized due to their complexity and variability: live and dead materials with different size contribute in different ways to the fire spread and behaviour. In the last decades, a strong help was provided by the use of remote sensing imagery at high spatial and spectral resolution. Such techniques are able to capture fine scale fuel distributions for accurate fire growth projections. Several attempts carried out in Europe were devoted to fuel classification and map characterization. In Italy, fuel load estimation and fuel model definition are still critical issues to be addressed due to the lack of detailed information. In this perspective, the aim of the present work was to propose an integrated approach based on field data collection, fuel model development and fuel model mapping to provide fuel models for the Mediterranean maquis associations. Field data needed for the development of fuel models were collected using destructive and non destructive measurements in experimental plots located in Northern Sardinia (Italy). Statistical tests were used to identify the main fuel types that were classified into four custom fuel models. Subsequently, a supervised classification by the Maximum Likelihood algorithm was applied on IKONOS images to identify and map the different types of maquis vegetation. The correspondent fuel model was then associated to each vegetation type to obtain the fuel model map. The results show the potential of this approach in achieving a reasonable accuracy in fuel model development and mapping; fine scale fuel model maps can be potentially helpful to obtain realistic predictions of fire behaviour and fire effects.

Molecular Physiology of Root System Architecture in Model Grasses

NASA Astrophysics Data System (ADS)

Hixson, K.; Ahkami, A. H.; Anderton, C.; Veličković, D.; Myers, G. L.; Chrisler, W.; Lindenmaier, R.; Fang, Y.; Yabusaki, S.; Rosnow, J. J.; Farris, Y.; Khan, N. E.; Bernstein, H. C.; Jansson, C.

2017-12-01

Unraveling the molecular and physiological mechanisms involved in responses of Root System Architecture (RSA) to abiotic stresses and shifts in microbiome structure is critical to understand and engineer plant-microbe-soil interactions in the rhizosphere. In this study, accessions of Brachypodium distachyon Bd21 (C3 model grass) and Setaria viridis A10.1 (C4 model grass) were grown in phytotron chambers under current and elevated CO2 levels. Detailed growth stage-based phenotypic analysis revealed different above- and below-ground morphological and physiological responses in C3 and C4 grasses to enhanced CO2 levels. Based on our preliminary results and by screening values of total biomass, water use efficiency, root to shoot ratio, RSA parameters and net assimilation rates, we postulated a three-phase physiological mechanism, i.e. RootPlus, BiomassPlus and YieldPlus phases, for grass growth under elevated CO2 conditions. Moreover, this comprehensive set of morphological and process-based observations are currently in use to develop, test, and calibrate biophysical whole-plant models and in particular to simulate leaf-level photosynthesis at various developmental stages of C3 and C4 using the model BioCro. To further link the observed phenotypic traits at the organismal level to tissue and molecular levels, and to spatially resolve the origin and fate of key metabolites involved in primary carbohydrate metabolism in different root sections, we complement root phenotypic observations with spatial metabolomics data using mass spectrometry imaging (MSI) methods. Focusing on plant-microbe interactions in the rhizosphere, six bacterial strains with plant growth promoting features are currently in use in both gel-based and soil systems to screen root growth and development in Brachypodium. Using confocal microscopy, GFP-tagged bacterial systems are utilized to study the initiation of different root types of RSA, including primary root (PR), coleoptile node axile root (CNR) and leaf node axile root (LNR) during developmental stages of root formation. The root exudates also will be quantified and preliminary data will be used to engineer our microbial consortium to improve plant growth.

A Framework Predicting Water Availability in a Rapidly Growing, Semi-Arid Region under Future Climate Change

NASA Astrophysics Data System (ADS)

Han, B.; Benner, S. G.; Glenn, N. F.; Lindquist, E.; Dahal, K. R.; Bolte, J.; Vache, K. B.; Flores, A. N.

2014-12-01

Climate change can lead to dramatic variations in hydrologic regime, affecting both surface water and groundwater supply. This effect is most significant in populated semi-arid regions where water availability are highly sensitive to climate-induced outcomes. However, predicting water availability at regional scales, while resolving some of the key internal variability and structure in semi-arid regions is difficult due to the highly non-linearity relationship between rainfall and runoff. In this study, we describe the development of a modeling framework to evaluate future water availability that captures elements of the coupled response of the biophysical system to climate change and human systems. The framework is built under the Envision multi-agent simulation tool, characterizing the spatial patterns of water demand in the semi-arid Treasure Valley area of Southwest Idaho - a rapidly developing socio-ecological system where urban growth is displacing agricultural production. The semi-conceptual HBV model, a population growth and allocation model (Target), a vegetation state and transition model (SSTM), and a statistically based fire disturbance model (SpatialAllocator) are integrated to simulate hydrology, population and land use. Six alternative scenarios are composed by combining two climate change scenarios (RCP4.5 and RCP8.5) with three population growth and allocation scenarios (Status Quo, Managed Growth, and Unconstrained Growth). Five-year calibration and validation performances are assessed with Nash-Sutcliffe efficiency. Irrigation activities are simulated using local water rights. Results show that in all scenarios, annual mean stream flow decreases as the projected rainfall increases because the projected warmer climate also enhances water losses to evapotranspiration. Seasonal maximum stream flow tends to occur earlier than in current conditions due to the earlier peak of snow melting. The aridity index and water deficit generally increase in the irrigated area. The most sensitive area is along the Boise Foothill which is the transitioning zone from water deficit to water abundant. However, these trends vary significantly between scenarios in space and time. The outcome of the study will serve as a reference for local stakeholders to make decisions on future land use.

Spatially explicit measures of production of young alewives in Lake Michigan: Linkage between essential fish habitat and recruitment

USGS Publications Warehouse

Hook, Tomas O.; Rutherford, Edward S.; Brines, Shannon J.; Mason, Doran M.; Schwab, David J.; McCormick, Michael; Desorcie, Timothy J.

2003-01-01

The identification and protection of essential habitats for early life stages of fishes are necessary to sustain fish stocks. Essential fish habitat for early life stages may be defined as areas where fish densities, growth, survival, or production rates are relatively high. To identify critical habitats for young-of-year (YOY) alewives (Alosa pseud oharengus) in Lake Michigan, we integrated bioenergetics models with GIS (Geographic Information Systems) to generate spatially explicit estimates of potential population production (an index of habitat quality). These estimates were based upon YOY alewife bioenergetic growth rate potential and their salmonine predators’ consumptive demand. We compared estimates of potential population production to YOY alewife yield (an index of habitat importance). Our analysis suggested that during 1994–1995, YOY alewife habitat quality and yield varied widely throughout Lake Michigan. Spatial patterns of alewife yield were not significantly correlated to habitat quality. Various mechanisms (e.g., predator migrations, lake circulation patterns, alternative strategies) may preclude YOY alewives from concentrating in areas of high habitat quality in Lake Michigan.

Modeling Temporal and Spatial Flows of Ecosystem Services in Chittenden County, VT

NASA Astrophysics Data System (ADS)

Voigt, B. G.; Bagstad, K.; Johnson, G.; Villa, F.

2010-12-01

This paper documents the integration of ARIES (ARtificial Intelligence for Ecosystem Services) with the land use change model UrbanSim to explore the impacts of current and future land use patterns on flood protection and water provision services in Chittenden County, VT. ARIES, an open source modeling platform, is particularly well-suited for measuring, mapping, and modeling the temporal and spatial flows of ecosystem services across the landscape, linking the areas of provision (sources) with human beneficiaries (users) through a spatially explicit agent-based modeling approach. UrbanSim is an open source agent-based land use model designed to facilitate a wide-range of scenarios based on user-specified behavioral assumptions, zoning regulations, and demographic, economic, and infrastructure (e.g. transportation, water, sewer, etc.) parameters. Ecosystem services travel through time and space and are susceptible to disruption and destruction from both natural and anthropogenic perturbations. The conversion of forested or agricultural land to urbanizing uses is replete with a long history of hydrologic impairment, habitat fragmentation, and the degradation of sensitive landscapes. Development decisions are predicated on the presence of landscape characteristics that meet the needs of developers and satisfy the desires of consumers, with minimal consideration of access to or effect on the provision of ecosystem services. The County houses nearly 25% of the state’s population and several employment centers that draw labor from throughout the region. Additionally, the County is expected to maintain modest residential and employment growth over the next 30 years, and will continue to serve as the state’s population and employment center. Expected future growth is likely to adversely affect the remaining farm and forest land in the County in the absence of policies to support sustainable development. We demonstrate how ARIES can be used to quantify changes in ecosystem service provision based on the outcomes of alternative land use change model scenarios. Stakeholder workshops were hosted to develop scenarios relevant to planning for future growth in the County, including alternative zoning regulations, road network improvements, and a range of future population projections. The results of the land use change simulations were passed to ARIES to model flood protection and water provision services for each of the alternative scenarios. We present Bayesian models of the ecosystem services as individual source, sink, and use components coupled with models of temporal and spatial flows of services across the landscape. Specific beneficiaries include homeowners, farmers, and other business property owners. The location choice decisions of residential and non-residential agents under the alternative scenarios resulted in varying access to ecosystem services depending on development density, habitat fragmentation, and the degree of hydrological impairment, among other factors. Modeled outputs include maps depicting flow paths (linking sources to beneficiaries), changes in land use, hotspot locations that are critical to sustain the flow of services across the landscape, and the demand for and supply of the modeled services.

Spatial Patterning of Newly-Inserted Material during Bacterial Cell Growth

NASA Astrophysics Data System (ADS)

Ursell, Tristan

2012-02-01

In the life cycle of a bacterium, rudimentary microscopy demonstrates that cell growth and elongation are essential characteristics of cellular reproduction. The peptidoglycan cell wall is the main load-bearing structure that determines both cell shape and overall size. However, simple imaging of cellular growth gives no indication of the spatial patterning nor mechanism by which material is being incorporated into the pre-existing cell wall. We employ a combination of high-resolution pulse-chase fluorescence microscopy, 3D computational microscopy, and detailed mechanistic simulations to explore how spatial patterning results in uniform growth and maintenance of cell shape. We show that growth is happening in discrete bursts randomly distributed over the cell surface, with a well-defined mean size and average rate. We further use these techniques to explore the effects of division and cell wall disrupting antibiotics, like cephalexin and A22, respectively, on the patterning of cell wall growth in E. coli. Finally, we explore the spatial correlation between presence of the bacterial actin-like cytoskeletal protein, MreB, and local cell wall growth. Together these techniques form a powerful method for exploring the detailed dynamics and involvement of antibiotics and cell wall-associated proteins in bacterial cell growth.[4pt] In collaboration with Kerwyn Huang, Stanford University.

An integrated approach for high spatial resolution mapping of water and carbon fluxes using multi-sensor data

USDA-ARS?s Scientific Manuscript database

In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a cor...

Use of artificial landscapes to isolate controls on burn probability

Treesearch

Marc-Andre Parisien; Carol Miller; Alan A. Ager; Mark A. Finney

2010-01-01

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of...

A computational method for optimizing fuel treatment locations

Treesearch

Mark A. Finney

2006-01-01

Modeling and experiments have suggested that spatial fuel treatment patterns can influence the movement of large fires. On simple theoretical landscapes consisting of two fuel types (treated and untreated) optimal patterns can be analytically derived that disrupt fire growth efficiently (i.e. with less area treated than random patterns). Although conceptually simple,...

Dynamics of Reactive Microbial Hotspots in Concentration Gradient.

NASA Astrophysics Data System (ADS)

Hubert, A.; Farasin, J.; Tabuteau, H.; Dufresne, A.; Meheust, Y.; Le Borgne, T.

2017-12-01

In subsurface environments, bacteria play a major role in controlling the kinetics of a broad range of biogeochemical reactions. In such environments, nutrients fluxes and solute concentrations needed for bacteria metabolism may be highly variable in space and intermittent in time. This can lead to the formation of reactive hotspots where and when conditions are favorable to particular microorganisms, hence inducing biogeochemical reaction kinetics that differ significantly from those measured in homogeneous model environments. To investigate the impact of chemical gradients on the spatial structure and temporal dynamics of subsurface microorganism populations, we develop microfluidic cells allowing for a precise control of flow and chemical gradient conditions, as well as quantitative monitoring of the bacteria's spatial distribution and biofilm development. Using the non-motile Escherichia coli JW1908-1 strain and Gallionella capsiferriformans ES-2 as model organisms, we investigate the behavior and development of bacteria over a range of single and double concentration gradients in the concentrations of nutrients, electron donors and electron acceptors. We measure bacterial activity and population growth locally in precisely known hydrodynamic and chemical environments. This approach allows time-resolved monitoring of the location and intensity of reactive hotspots in micromodels as a function of the flow and chemical gradient conditions. We compare reactive microbial hotspot dynamics in our micromodels to classic growth laws and well-known growth parameters for the laboratory model bacteria Escherichia coli.We also discuss consequences for the formation and temporal dynamics of biofilms in the subsurface.

Cells competition in tumor growth poroelasticity

NASA Astrophysics Data System (ADS)

Fraldi, Massimiliano; Carotenuto, Angelo R.

2018-03-01

Growth of biological tissues has been recently treated within the framework of Continuum Mechanics, by adopting heterogeneous poroelastic models where the interaction between soft matrix and interstitial fluid flow is coupled with inelastic effects ad hoc introduced to simulate the macroscopic volumetric growth determined by cells division, cells growth and extracellular matrix changes occurring at the micro-scale level. These continuum models seem to overcome some limitations intrinsically associated to other alternative approaches based on mass balances in multiphase systems, because the crucial role played by residual stresses accompanying growth and nutrients walkway is preserved. Nevertheless, when these strategies are applied to analyze solid tumors, mass growth is usually assigned in a prescribed form that essentially copies the in vitro measured intrinsic growth rates of the cell species. As a consequence, some important cell-cell dynamics governing mass evolution and invasion rates of cancer cells, as well as their coupling with feedback mechanisms associated to in situ stresses, are inevitably lost and thus the spatial distribution and the evolution with time of the growth inside the tumor -which would be results rather than inputs- are forced to enter in the model simply as data. In order to solve this paradox, it is here proposed an enhanced multi-scale poroelastic model undergoing large deformations and embodying inelastic growth, where the net growth terms directly result from the "interspecific" predator-prey (Volterra/Lotka-like) competition occurring at the micro-scale level between healthy and abnormal cell species. In this way, a system of fully-coupled non-linear PDEs is derived to describe how the fight among cell species to grab the available common resources, stress field, pressure gradients, interstitial fluid flows driving nutrients and inhomogeneous growth all simultaneously interact to decide the tumor fate.

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

2017-10-01

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air quality): A Study of how the Urban Landscape Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G.; Lo, C. P.; Kidder, Stanley Q.; Hafner, Jan; Taha, Haider; Bornstein, Robert D.; Gillies, Robert R.; Gallo, Kevin P.

1998-01-01

It is our intent through this investigation to help facilitate measures that can be Project ATLANTA (ATlanta Land-use ANalysis: applied to mitigate climatological or air quality Temperature and Air-quality) is a NASA Earth degradation, or to design alternate measures to sustain Observing System (EOS) Interdisciplinary Science or improve the overall urban environment in the future. investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta. The primary objectives for this research effort are: 1) To In the last half of the 20th century, Atlanta, investigate and model the relationship between Atlanta Georgia has risen as the premier commercial, urban growth, land cover change, and the development industrial, and transportation urban area of the of the urban heat island phenomenon through time at southeastern United States. The rapid growth of the nested spatial scales from local to regional; 2) To Atlanta area, particularly within the last 25 years, has investigate and model the relationship between Atlanta made Atlanta one of the fastest growing metropolitan urban growth and land cover change on air quality areas in the United States. The population of the through time at nested spatial scales from local to Atlanta metropolitan area increased 27% between 1970 regional; and 3) To model the overall effects of urban and 1980, and 33% between 1980-1990 (Research development on surface energy budget characteristics Atlanta, Inc., 1993). Concomitant with this high rate of across the Atlanta urban landscape through time at population growth, has been an explosive growth in nested spatial scales from local to regional. Our key retail, industrial, commercial, and transportation goal is to derive a better scientific understanding of how services within the Atlanta region. This has resulted in land cover changes associated with urbanization in the tremendous land cover change dynamics within the Atlanta area, principally in transforming forest lands to metropolitan region, wherein urbanization has urban land covers through time, has, and will, effect consumed vast acreas of land adjacent to the city local and regional climate, surface energy flux, and air proper and has pushed the rural/urban fringe farther quality characteristics. Allied with this goal is the and farther away from the original Atlanta urban core. prospect that the results from this research can be An enormous transition of land from forest and applied by urban planners, environmental managers agriculture to urban land uses has occurred in the and other decision-makers, for determining how Atlanta area in the last 25 years, along with subsequent urbanization has impacted the climate and overall

Boundedness and global stability of the two-predator and one-prey models with nonlinear prey-taxis

NASA Astrophysics Data System (ADS)

Wang, Jianping; Wang, Mingxin

2018-06-01

This paper concerns the reaction-diffusion systems modeling the population dynamics of two predators and one prey with nonlinear prey-taxis. We first investigate the global existence and boundedness of the unique classical solution for the general model. Then, we study the global stabilities of nonnegative spatially homogeneous equilibria for an explicit system with type I functional responses and density-dependent death rates for the predators and logistic growth for the prey. Moreover, the convergence rates are also established.

A time-space model for the growth of microalgae biofilms for biofuel production.

PubMed

Polizzi, B; Bernard, O; Ribot, M

2017-11-07

We present in this paper a spatial model describing the growth of a photosynthetic microalgae biofilm. In this model we consider photosynthesis, extracellular matrix excretion, and mortality. These mechanisms are described precisely using kinetic laws that take into account some saturation effects which limit the reaction rates and involve different components that we treat individually. In particular, to obtain a more detailed description of the microalgae growth, we consider separately the lipids they contain and the functional part of microalgae (proteins, RNA, etc ...), the latter playing a leading role in photosynthesis. We also consider the components dissolved in liquid phase as CO 2 . The model is based on mixture theory and the behaviour of each component is described on the one hand by mass conservation, which takes into account biological features of the system, and on the other hand by conservation of momentum, which describes the physical properties of the components. Some numerical simulations are displayed in the one-dimensional case and show that the model is able to estimate accurately the biofilm productivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Importance of growth rate on mercury and polychlorinated biphenyl bioaccumulation in fish

USGS Publications Warehouse

Li, Jiajia; Haffner, G. Douglas; Patterson, Gordon; Walters, David M.; Burtnyk, Michael D.; Drouillard, Ken G.

2018-01-01

To evaluate the effect of fish growth on mercury (Hg) and polychlorinated biphenyl (PCB) bioaccumulation, a non–steady‐state toxicokinetic model, combined with a Wisconsin bioenergetics model, was developed to simulate Hg and PCB bioaccumulation in bluegill (Lepomis macrochirus). The model was validated by comparing observed with predicted Hg and PCB 180 concentrations across 5 age classes from 5 different waterbodies across North America. The non–steady‐state model generated accurate predictions for Hg and PCB bioaccumulation in 3 of 5 waterbodies: Apsey Lake (ON, Canada), Sharbot Lake (ON, Canada), and Stonelick Lake (OH, USA). The poor performance of the model for the Detroit River (MI, USA/ON, Canada) and Lake Hartwell (GA/SC, USA), which are 2 well‐known contaminated sites with possibly high heterogeneity in spatial contamination, was attributed to changes in feeding behavior and/or prey contamination. Model simulations indicate that growth dilution is a major component of contaminant bioaccumulation patterns in fish, especially during early life stages, and was predicted to be more important for hydrophobic PCBs than for Hg. Simulations that considered tissue‐specific growth provided some improvement in model performance particularly for PCBs in fish populations that exhibited changes in their whole‐body lipid content with age. Higher variation in lipid growth compared with that of lean dry protein was also observed between different bluegill populations, which partially explains the greater variation in PCB bioaccumulation slopes compared with Hg across sampling sites.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Spatial and Temporal Relationships of Old-Growth and Secondary Forests in Indiana, USA

Treesearch

Martin A. Spetich; George R. Parker; Eric J. Gustafson

1997-01-01

We examined the spatial pattern of forests in Indiana to: (1) determine the extent, connectivity and percent edge of all forests, (2) examine the change in connectivity among these forests if all riparian zones were replanted to forest or other native vegetation, (3) determine the location, spatial dispersion and percent edge of current old-growth forest remnants, (4)...

Spatial optimal disturbances in swept-wing boundary layers

NASA Astrophysics Data System (ADS)

Chen, Cheng

2018-04-01

With the use of the adjoint-based optimization method proposed by Tempelmann et al. (J. Fluid Mech., vol. 704, 2012, pp. 251-279), in which the parabolized stability equation (PSE) and so-called adjoint parabolized stability equation (APSE) are solved iteratively, we obtain the spatial optimal disturbance shape and investigate its dependence on the parameters of disturbance wave and wall condition, such as radial frequency ω and wall temperature Twall, in a swept-wing boundary layer flow. Further, the non-modal growth mechanism of this optimal disturbance has been also discussed, regarding its spatial evolution way in the streamwise direction. The results imply that the spanwise wavenumber, disturbance frequency and wall cooling do not change the physical mechanism of perturbation growth, just with a substantial effect on the magnitude of perturbation growth. Further, wall cooling may have enhancing or suppressing effect on spatial optimal disturbance growth, depending on the streamwise location.

Integration of an Individual-Based Fish Bioenergetics Model into a Spatially Explicit Water Quality Model (CE-QUAL-ICM)

DTIC Science & Technology

2010-04-01

energy a fish can devote to growth being the difference between consumption in the form of food and the sum of life process expenditures , including...can incur an elemental deficit, and subsequently retain higher fractions of that element when it is in abun- dance to regain the target composition...Organic nitrogen and caloric content of detritus. Estuarine, Coastal, and Shelf Science 12: 39-47

Collaborative Research: failure of RockMasses from Nucleation and Growth of Microscopic Defects and Disorder

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klein, William

Over the 21 years of funding we have pursued several projects related to earthquakes, damage and nucleation. We developed simple models of earthquake faults which we studied to understand Gutenburg-Richter scaling, foreshocks and aftershocks, the effect of spatial structure of the faults and its interaction with underlying self organization and phase transitions. In addition we studied the formation of amorphous solids via the glass transition. We have also studied nucleation with a particular concentration on transitions in systems with a spatial symmetry change. In addition we investigated the nucleation process in models that mimic rock masses. We obtained the structuremore » of the droplet in both homogeneous and heterogeneous nucleation. We also investigated the effect of defects or asperities on the nucleation of failure in simple models of earthquake faults.« less

Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China

NASA Astrophysics Data System (ADS)

Zeng, Chen; Liu, Yaolin; Stein, Alfred; Jiao, Limin

2015-02-01

Urban sprawl has led to environmental problems and large losses of arable land in China. In this study, we monitor and model urban sprawl by means of a combination of remote sensing, geographical information system and spatial statistics. We use time-series data to explore the potential socio-economic driving forces behind urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions. The methodology is applied to the city of Wuhan, China, for the period from 1990 to 2013. The results reveal that the built-up land has expanded and has dispersed in urban clusters. Population growth, and economic and transportation development are still the main causes of urban sprawl; however, when they have developed to certain levels, the area affected by construction in urban areas (Jian Cheng Qu (JCQ)) and the area of cultivated land (ACL) tend to be stable. Spatial regression models are shown to be superior to the traditional models. The interaction among districts with the same administrative status is stronger than if one of those neighbors is in the city center and the other in the suburban area. The expansion of urban built-up land is driven by the socio-economic development at the same period, and greatly influenced by its spatio-temporal neighbors. We conclude that the integration of remote sensing, a geographical information system, and spatial statistics offers an excellent opportunity to explore the spatio-temporal variation and interactions among the districts in the sprawling metropolitan areas. Relevant regulations to control the urban sprawl process are suggested accordingly.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

PubMed

Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

2016-07-15

We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

Use of spatially refined satellite remote sensing fire detection data to initialize and evaluate coupled weather-wildfire growth model simulations

NASA Astrophysics Data System (ADS)

Schroeder, W.; Coen, J.; Oliva, P.

2013-12-01

Availability of spatially refined satellite active fire detection data is gradually increasing. For example, the new 375 m Visible Infrared Imaging Radiometer Suite (VIIRS) data show improved active fire detection performance for both small and large size fires. The VIIRS data have proved superior to MODIS for mapping of wildfires events spanning several days to weeks of either continued or intermittent activity, delivering 12-h active fire data of improved spatial fidelity. The VIIRS active fire data are complemented by other satellite active fire data sets of similar or higher spatial resolution, including the new 30 m Landsat-8. Additional assets should include the upcoming 20 m Sentinel-2 Landsat-class satellite program by the European Space Agency to be launched in 2014-15. These improved active fire data sets are fostering new applications that rely on higher resolution input fire data. In this study, we describe the characteristics of the new VIIRS and Landsat-8 data and demonstrate one such new application of satellite active fire data in support of fire behavior modeling. We present results for a wildfire observed in June 2012 in New Mexico using an innovative approach to improving the simulation of large, long-duration wildfires, either for retrospective studies or forecasting in a number of geophysical applications. The approach uses (1) the Coupled Atmosphere-Wildland Fire Environment (CAWFE) Model, a numerical weather prediction model two-way coupled with a module representing the rate of spread of a wildfire's flaming front, its rate of consumption of different wildland fuels, and the feedback of this heat release upon the atmosphere - i.e. 'how a fire creates its own weather', combined with (2) spatially refined 375 m VIIRS active fire data, which is used for initialization of a wildfire already in progress in the model and evaluation of its simulated progression at the time of the next pass. Results show that initializing a fire that is 'in progress' with VIIRS data and a weather simulation based on more recent atmospheric analyses can overcome several issues and improve the simulation of late-developing fires and of later periods (particularly those with growth periods separated by lulls) in a long-lived fire.

Land Surface Process and Air Quality Research and Applications at MSFC

NASA Technical Reports Server (NTRS)

Quattrochi, Dale; Khan, Maudood

2007-01-01

This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.

The Epstein-Barr Virus Regulome in Lymphoblastoid Cells.

PubMed

Jiang, Sizun; Zhou, Hufeng; Liang, Jun; Gerdt, Catherine; Wang, Chong; Ke, Liangru; Schmidt, Stefanie C S; Narita, Yohei; Ma, Yijie; Wang, Shuangqi; Colson, Tyler; Gewurz, Benjamin; Li, Guoliang; Kieff, Elliott; Zhao, Bo

2017-10-11

Epstein-Barr virus (EBV) transforms B cells to continuously proliferating lymphoblastoid cell lines (LCLs), which represent an experimental model for EBV-associated cancers. EBV nuclear antigens (EBNAs) and LMP1 are EBV transcriptional regulators that are essential for LCL establishment, proliferation, and survival. Starting with the 3D genome organization map of LCL, we constructed a comprehensive EBV regulome encompassing 1,992 viral/cellular genes and enhancers. Approximately 30% of genes essential for LCL growth were linked to EBV enhancers. Deleting EBNA2 sites significantly reduced their target gene expression. Additional EBV super-enhancer (ESE) targets included MCL1, IRF4, and EBF. MYC ESE looping to the transcriptional stat site of MYC was dependent on EBNAs. Deleting MYC ESEs greatly reduced MYC expression and LCL growth. EBNA3A/3C altered CDKN2A/B spatial organization to suppress senescence. EZH2 inhibition decreased the looping at the CDKN2A/B loci and reduced LCL growth. This study provides a comprehensive view of the spatial organization of chromatin during EBV-driven cellular transformation. Copyright © 2017 Elsevier Inc. All rights reserved.

Making Spatial Statistics Service Accessible On Cloud Platform

NASA Astrophysics Data System (ADS)

Mu, X.; Wu, J.; Li, T.; Zhong, Y.; Gao, X.

2014-04-01

Web service can bring together applications running on diverse platforms, users can access and share various data, information and models more effectively and conveniently from certain web service platform. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With the rampant growth of massive data and restriction of net, traditional web services platforms have some prominent problems existing in development such as calculation efficiency, maintenance cost and data security. In this paper, we offer a spatial statistics service based on Microsoft cloud. An experiment was carried out to evaluate the availability and efficiency of this service. The results show that this spatial statistics service is accessible for the public conveniently with high processing efficiency.

A tumor growth model with deformable ECM

NASA Astrophysics Data System (ADS)

Sciumè, G.; Santagiuliana, R.; Ferrari, M.; Decuzzi, P.; Schrefler, B. A.

2014-12-01

Existing tumor growth models based on fluid analogy for the cells do not generally include the extracellular matrix (ECM), or if present, take it as rigid. The three-fluid model originally proposed by the authors and comprising tumor cells (TC), host cells (HC), interstitial fluid (IF) and an ECM, considered up to now only a rigid ECM in the applications. This limitation is here relaxed and the deformability of the ECM is investigated in detail. The ECM is modeled as a porous solid matrix with Green-elastic and elasto-visco-plastic material behavior within a large strain approach. Jauman and Truesdell objective stress measures are adopted together with the deformation rate tensor. Numerical results are first compared with those of a reference experiment of a multicellular tumor spheroid (MTS) growing in vitro, then three different tumor cases are studied: growth of an MTS in a decellularized ECM, growth of a spheroid in the presence of host cells and growth of a melanoma. The influence of the stiffness of the ECM is evidenced and comparison with the case of a rigid ECM is made. The processes in a deformable ECM are more rapid than in a rigid ECM and the obtained growth pattern differs. The reasons for this are due to the changes in porosity induced by the tumor growth. These changes are inhibited in a rigid ECM. This enhanced computational model emphasizes the importance of properly characterizing the biomechanical behavior of the malignant mass in all its components to correctly predict its temporal and spatial pattern evolution.

A novel adaptive algorithm for 3D finite element analysis to model extracortical bone growth.

PubMed

Cheong, Vee San; Blunn, Gordon W; Coathup, Melanie J; Fromme, Paul

2018-02-01

Extracortical bone growth with osseointegration of bone onto the shaft of massive bone tumour implants is an important clinical outcome for long-term implant survival. A new computational algorithm combining geometrical shape changes and bone adaptation in 3D Finite Element simulations has been developed, using a soft tissue envelope mesh, a novel concept of osteoconnectivity, and bone remodelling theory. The effects of varying the initial tissue density, spatial influence function and time step were investigated. The methodology demonstrated good correspondence to radiological results for a segmental prosthesis.

Inviscid spatial stability of a compressible mixing layer. Part 2: The flame sheet model

NASA Technical Reports Server (NTRS)

Jackson, T. L.; Grosch, C. E.

1989-01-01

The results of an inviscid spatial calculation for a compressible reacting mixing layer are reported. The limit of infinitive activation energy is taken and the diffusion flame is approximated by a flame sheet. Results are reported for the phase speeds of the neutral waves and maximum growth rates of the unstable waves as a function of the parameters of the problem: the ratio of the temperature of the stationary stream to that of the moving stream, the Mach number of the moving streams, the heat release per unit mass fraction of the reactant, the equivalence ratio of the reaction, and the frequency of the disturbance. These results are compared to the phase speeds and growth rates of the corresponding nonreacting mixing layer. We show that the addition of combustion has important, and complex effects on the flow stability.

Remote Sensing-Based Detection and Spatial Pattern Analysis for Geo-Ecological Niche Modeling of Tillandsia SPP. In the Atacama, Chile

NASA Astrophysics Data System (ADS)

Wolf, N.; Siegmund, A.; del Río, C.; Osses, P.; García, J. L.

2016-06-01

In the coastal Atacama Desert in Northern Chile plant growth is constrained to so-called `fog oases' dominated by monospecific stands of the genus Tillandsia. Adapted to the hyperarid environmental conditions, these plants specialize on the foliar uptake of fog as main water and nutrient source. It is this characteristic that leads to distinctive macro- and micro-scale distribution patterns, reflecting complex geo-ecological gradients, mainly affected by the spatiotemporal occurrence of coastal fog respectively the South Pacific Stratocumulus clouds reaching inlands. The current work employs remote sensing, machine learning and spatial pattern/GIS analysis techniques to acquire detailed information on the presence and state of Tillandsia spp. in the Tarapacá region as a base to better understand the bioclimatic and topographic constraints determining the distribution patterns of Tillandsia spp. Spatial and spectral predictors extracted from WorldView-3 satellite data are used to map present Tillandsia vegetation in the Tarapaca region. Regression models on Vegetation Cover Fraction (VCF) are generated combining satellite-based as well as topographic variables and using aggregated high spatial resolution information on vegetation cover derived from UAV flight campaigns as a reference. The results are a first step towards mapping and modelling the topographic as well as bioclimatic factors explaining the spatial distribution patterns of Tillandsia fog oases in the Atacama, Chile.

A spatial dynamic model to assess piospheric land degradation processes of SW Iberian rangelands

NASA Astrophysics Data System (ADS)

Herguido Sevillano, Estela; Ibáñez, Javier; Francisco Lavado Contador, Joaquín; Pulido-Fernández, Manuel; Schnabel, Susanne

2015-04-01

Iberian open wooded rangelands (known as dehesas or montados) constitute valuable agro-silvo-pastoral systems traditionally considered as highly sustainable. Nevertheless, in the recent decades, those systems are undergoing changes of land use and management practices that compromise its sustainability. Some of those changes, as the rising construction of watering points and the high spatial fragmentation and livestock movement restriction associated to fencing, show an aggregated effect with livestock, producing an impact gradient over soil and vegetation. Soil compaction related to livestock pressure is higher around watering points, with bare soil halos and patches of scarce vegetation or nude soil developing with higher frequency in areas close to them. Using the freeware Dinamica EGO as environmental modeling platform, we have developed a theoretic spatial dynamic model that represents some of the processes of land degradation associated to livestock grazing in dehesa fenced enclosures. Spatial resolution is high since every cell in the model is a square unit area of 1 m2. We paid particular attention to the relationships between soil degradation by compaction (porosity), livestock pressure, rainfall, pasture growth and shrub cover and bare soil generation. The model considers pasture growth as related to soil compaction, measured by the pore space in the top 10 cm soil layer. Annual precipitation is randomly generated following a normal distribution. When annual precipitation and pore space increase, also does pasture growth. Besides, there is a feedback between pasture growth and pore space, given that pasture roots increases soil porosity. The cell utility for livestock function has been defined as an exponential function of the distance of a cell to watering points and the amount of pasture present in it. The closer the cell to a pond and the higher the amount of pasture, the higher is cell utility. The latter is modulated by a normal random variable to capture accidental effects. This variable has zero mean and a standard deviation linearly related to the distance to the pond. Livestock utilization of a cell is a function of its relative utility, the stocking rate and the time that animals spend at the enclosure. Since livestock trampling promotes soil compaction, livestock utilization has a negative effect on pore space. The probability of transition from herbaceous to shrubs is also modulated by pore space, and thus livestock utilization, as shrub development needs a minimum porosity value for seeds to successfully germinate. In addition, it is influenced by the proportion of cells occupied by shrubs in a radius where seed dispersal or exclusion by competition may occur. The model contemplates the probability of transition from shrubs to herbaceous through shrub mortality, and the age of the shrubs, which influences seed production and shrub cover. Pasture consumption by livestock and pasture remaining at the end of summer were also modeled, so that it is possible to obtain maps of bare soil at that time. Likewise, the model generates maps of vegetation state (shrubs or herbaceous) and pasture growth. The values of the set of 31 parameters were obtained from field measurements and from publications. Those parameters lacking quantitative information were calibrated by comparing model performance with the dynamics of true enclosures analyzed between 1984 and 2009 in ortophotographs. Stocking rates were inferred from farmers' interviews performed in 2009 about present and past land use and management practices. The model developed is intended to analyze strategies of livestock management in dehesas. Particularly, soil conservation practices as related to livestock pressure can be simulated looking for optimized schemes. Moreover, the model provides the possibility of generating simulations for future climate scenarios, studying the effects of climate change on livestock carrying capacity on these systems. Thanks to the Spanish Ministerio de Economía y Competitividad for financially supporting this study through AMID (CGL2011-23361) project.

A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone.

PubMed

Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A

2006-11-01

A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.

Geographic Video 3d Data Model And Retrieval

NASA Astrophysics Data System (ADS)

Han, Z.; Cui, C.; Kong, Y.; Wu, H.

2014-04-01

Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

Spatially explicit control of invasive species using a reaction-diffusion model

USGS Publications Warehouse

Bonneau, Mathieu; Johnson, Fred A.; Romagosa, Christina M.

2016-01-01

Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction–diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction–diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction–diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.

Thermal analysis of the vertical bridgman semiconductor crystal growth technique. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Jasinski, T. J.

1982-01-01

The quality of semiconductor crystals grown by the vertical Bridgman technique is strongly influenced by the axial and radial variations of temperature within the charge. The relationship between the thermal parameters of the vertical Bridgman system and the thermal behavior of the charge are examined. Thermal models are developed which are capable of producing results expressable in analytical form and which can be used without recourse to extensive computer work for the preliminary thermal design of vertical Bridgman crystal growth systems. These models include the effects of thermal coupling between the furnace and the charge, charge translation rate, charge diameter, thickness and thermal conductivity of the confining crucible, thermal conductivity change and liberation of latent heat at the growth interface, and infinite charge length. The hot and cold zone regions, considered to be at spatially uniform temperatures, are separated by a gradient control region which provides added thermal design flexibility for controlling the temperature variations near the growth interface.

Functional trait differences influence neighbourhood interactions in a hyperdiverse Amazonian forest.

PubMed

Fortunel, Claire; Valencia, Renato; Wright, S Joseph; Garwood, Nancy C; Kraft, Nathan J B

2016-09-01

As distinct community assembly processes can produce similar community patterns, assessing the ecological mechanisms promoting coexistence in hyperdiverse rainforests remains a considerable challenge. We use spatially explicit neighbourhood models of tree growth to quantify how functional trait and phylogenetic similarities predict variation in growth and crowding effects for the 315 most abundant tree species in a 25-ha lowland rainforest plot in Ecuador. We find that functional trait differences reflect variation in (1) species maximum potential growth, (2) the intensity of interspecific interactions for some species, and (3) species sensitivity to neighbours. We find that neighbours influenced tree growth in 28% of the 315 focal tree species. Neighbourhood effects are not detected in the remaining 72%, which may reflect the low statistical power to model rare taxa and/or species insensitivity to neighbours. Our results highlight the spectrum of ways in which functional trait differences can shape community dynamics in highly diverse rainforests. © 2016 John Wiley & Sons Ltd/CNRS.

Effects of Spatial N nutrient mobility relevant to plants, soils and microtopograhy on plant growth and soil organic matter accumulation by using coupled CLM-PFLOTRAN biogeochemical model in an Area in NGEE-Arctic Intensive Study Sites, Barrow, AK.

NASA Astrophysics Data System (ADS)

Yuan, F.; Thornton, P. E.; Tang, G.; Xu, X.; Kumar, J.; Iversen, C. M.; Bisht, G.; Hammond, G. E.; Mills, R. T.; Wullschleger, S. D.

2015-12-01

At fine-scale spatially-explicit reactive-transport (RT) and hydrological coupled modeling for likely soil nutrient N transport mechanisms driven by gradients, soil properties and micro-topography is critical to spatial distribution of plants and thus soil organic matter stocks accumulation or changes. In this study we successfully carried out a fully coupled fine-scale CLM-PFLOTRAN soil biogeochemical (BGC) RT model simulation on Titan at 2.5mx2.5m resolution for the Area C of 100mx100m in the NGEE-Arctic Intensive Study Sites, Barrow, AK. The Area spatially varies in terms of plant function types (PFT) and soil thermal-hydraulic properties associated with locally polygonal landscape features. The spatially explicit CLM-PFLOTRAN coupled RT model allows soil N nutrient mobility driven either by diffusion or by advection or both. The modeling experiments are conducted with three soil nutrient N (NH4+ and NO3-) mobility mechanisms within the CLM-PFLOTAN: no transport, diffusion only, and diffusion and advection in 3-D soils. It shows that CLM-PFLOTRAN model simulated higher SOM C density in both lower troughs and neighbored areas when transport mechanism allowed, compared to no-transport, although with similar ranges (about 0.1~20 kgC m-3). It also simulates slightly higher LAI (0.16~0.84 vs. 0.11~0.85) in growing season, especially in lower troughs and neighbored regions. It's likely because CLM-PFLOTRAN can explicitly simulate transport of nutrients and others both vertically and laterally. So it can more mechanically mimic plant root N extract caused relatively low concentration in root zone and thus allow transport from surrounding high N concentration regions. The lateral mobility also implies that N nutrient can transport from initially high-production columns to the neighbored low-production area where then production could be improved. The results suggest that taking account of locally mobility of soil N nutrients may be critical to plant growth and thus long-term soil organic carbon stocks in this polygonal coastal tundra ecosystem at fine scale. It also implies that regional or global scale modelings should consider vertical transport (2D) due to shallow soil root zones, for which a feature in CLM-PFLOTRAN is available as well.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-03-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-07-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.

Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

PubMed

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-11-01

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA

USGS Publications Warehouse

Curry, Magdalena A. E.; Barnes, Jason B.; Colgan, Joseph P.

2016-01-01

Common fault growth models diverge in predicting how faults accumulate displacement and lengthen through time. A paucity of field-based data documenting the lateral component of fault growth hinders our ability to test these models and fully understand how natural fault systems evolve. Here we outline a framework for using apatite (U-Th)/He thermochronology (AHe) to quantify the along-strike growth of faults. To test our framework, we first use a transect in the normal fault-bounded Jackson Mountains in the Nevada Basin and Range Province, then apply the new framework to the adjacent Pine Forest Range. We combine new and existing cross sections with 18 new and 16 existing AHe cooling ages to determine the spatiotemporal variability in footwall exhumation and evaluate models for fault growth. Three age-elevation transects in the Pine Forest Range show that rapid exhumation began along the range-front fault between approximately 15 and 11 Ma at rates of 0.2–0.4 km/Myr, ultimately exhuming approximately 1.5–5 km. The ages of rapid exhumation identified at each transect lie within data uncertainty, indicating concomitant onset of faulting along strike. We show that even in the case of growth by fault-segment linkage, the fault would achieve its modern length within 3–4 Myr of onset. Comparison with the Jackson Mountains highlights the inadequacies of spatially limited sampling. A constant fault-length growth model is the best explanation for our thermochronology results. We advocate that low-temperature thermochronology can be further utilized to better understand and quantify fault growth with broader implications for seismic hazard assessments and the coevolution of faulting and topography.

Modeling Conformal Growth in Photonic Crystals and Comparing to Experiment

NASA Astrophysics Data System (ADS)

Brzezinski, Andrew; Chen, Ying-Chieh; Wiltzius, Pierre; Braun, Paul

2008-03-01

Conformal growth, e.g. atomic layer deposition (ALD), of materials such as silicon and TiO2 on three dimensional (3D) templates is important for making photonic crystals. However, reliable calculations of optical properties as a function of the conformal growth, such as the optical band structure, are hampered by difficultly in accurately assessing a deposited material's spatial distribution. A widely used approximation ignores ``pinch off'' of precursor gas and assumes complete template infilling. Another approximation results in non-uniform growth velocity by employing iso-intensity surfaces of the 3D interference pattern used to create the template. We have developed an accurate model of conformal growth in arbitrary 3D periodic structures, allowing for arbitrary surface orientation. Results are compared with the above approximations and with experimentally fabricated photonic crystals. We use an SU8 polymer template created by 4-beam interference lithography, onto which various amounts of TiO2 are grown by ALD. Characterization is performed by analysis of cross-sectional scanning electron micrographs and by solid angle resolved optical spectroscopy.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

Treesearch

Jill M. Nakawatase; David L. Peterson

2006-01-01

For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

A general modeling framework for describing spatially structured population dynamics

USGS Publications Warehouse

Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

2017-01-01

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

A Coarse-Grained Biophysical Model of E. coli and Its Application to Perturbation of the rRNA Operon Copy Number

PubMed Central

Tadmor, Arbel D.; Tlusty, Tsvi

2008-01-01

We propose a biophysical model of Escherichia coli that predicts growth rate and an effective cellular composition from an effective, coarse-grained representation of its genome. We assume that E. coli is in a state of balanced exponential steady-state growth, growing in a temporally and spatially constant environment, rich in resources. We apply this model to a series of past measurements, where the growth rate and rRNA-to-protein ratio have been measured for seven E. coli strains with an rRNA operon copy number ranging from one to seven (the wild-type copy number). These experiments show that growth rate markedly decreases for strains with fewer than six copies. Using the model, we were able to reproduce these measurements. We show that the model that best fits these data suggests that the volume fraction of macromolecules inside E. coli is not fixed when the rRNA operon copy number is varied. Moreover, the model predicts that increasing the copy number beyond seven results in a cytoplasm densely packed with ribosomes and proteins. Assuming that under such overcrowded conditions prolonged diffusion times tend to weaken binding affinities, the model predicts that growth rate will not increase substantially beyond the wild-type growth rate, as indicated by other experiments. Our model therefore suggests that changing the rRNA operon copy number of wild-type E. coli cells growing in a constant rich environment does not substantially increase their growth rate. Other observations regarding strains with an altered rRNA operon copy number, such as nucleoid compaction and the rRNA operon feedback response, appear to be qualitatively consistent with this model. In addition, we discuss possible design principles suggested by the model and propose further experiments to test its validity. PMID:18437222

Long-term Evaluation of Landuse Changes On Landscape Water Balance - A Case Study From North-east Germany

NASA Astrophysics Data System (ADS)

Wegehenkel, M.

In this paper, long-term effects of different afforestation scenarios on landscape wa- ter balance will be analyzed taking into account the results of a regional case study. This analysis is based on using a GIS-coupled simulation model for the the spatially distributed calculation of water balance.For this purpose, the modelling system THE- SEUS with a simple GIS-interface will be used. To take into account the special case of change in forest cover proportion, THESEUS was enhanced with a simple for- est growth model. In the regional case study, model runs will be performed using a detailed spatial data set from North-East Germany. This data set covers a mesoscale catchment located at the moraine landscape of North-East Germany. Based on this data set, the influence of the actual landuse and of different landuse change scenarios on water balance dynamics will be investigated taking into account the spatial distributed modelling results from THESEUS. The model was tested using different experimen- tal data sets from field plots as well as obsverded catchment discharge. Additionally to such convential validation techniques, remote sensing data were used to check the simulated regional distribution of water balance components like evapotranspiration in the catchment.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

The Spatial Distribution of the Exocyst and Actin Cortical Patches Is Sufficient To Organize Hyphal Tip Growth

PubMed Central

Caballero-Lima, David; Kaneva, Iliyana N.; Watton, Simon P.

2013-01-01

In the hyphal tip of Candida albicans we have made detailed quantitative measurements of (i) exocyst components, (ii) Rho1, the regulatory subunit of (1,3)-β-glucan synthase, (iii) Rom2, the specialized guanine-nucleotide exchange factor (GEF) of Rho1, and (iv) actin cortical patches, the sites of endocytosis. We use the resulting data to construct and test a quantitative 3-dimensional model of fungal hyphal growth based on the proposition that vesicles fuse with the hyphal tip at a rate determined by the local density of exocyst components. Enzymes such as (1,3)-β-glucan synthase thus embedded in the plasma membrane continue to synthesize the cell wall until they are removed by endocytosis. The model successfully predicts the shape and dimensions of the hyphae, provided that endocytosis acts to remove cell wall-synthesizing enzymes at the subapical bands of actin patches. Moreover, a key prediction of the model is that the distribution of the synthase is substantially broader than the area occupied by the exocyst. This prediction is borne out by our quantitative measurements. Thus, although the model highlights detailed issues that require further investigation, in general terms the pattern of tip growth of fungal hyphae can be satisfactorily explained by a simple but quantitative model rooted within the known molecular processes of polarized growth. Moreover, the methodology can be readily adapted to model other forms of polarized growth, such as that which occurs in plant pollen tubes. PMID:23666623

Correlates of Individual, and Age-Related, Differences in Short-Term Learning

ERIC Educational Resources Information Center

Zhang, Zhiyong; Davis, Hasker P.; Salthouse, Timothy A.; Tucker-Drob, Elliot M.

2007-01-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task…

Creep-fatigue modelling in structural steels using empirical and constitutive creep methods implemented in a strip-yield model

NASA Astrophysics Data System (ADS)

Andrews, Benjamin J.

The phenomena of creep and fatigue have each been thoroughly studied. More recently, attempts have been made to predict the damage evolution in engineering materials due to combined creep and fatigue loading, but these formulations have been strictly empirical and have not been used successfully outside of a narrow set of conditions. This work proposes a new creep-fatigue crack growth model based on constitutive creep equations (adjusted to experimental data) and Paris law fatigue crack growth. Predictions from this model are compared to experimental data in two steels: modified 9Cr-1Mo steel and AISI 316L stainless steel. Modified 9Cr-1Mo steel is a high-strength steel used in the construction of pressure vessels and piping for nuclear and conventional power plants, especially for high temperature applications. Creep-fatigue and pure creep experimental data from the literature are compared to model predictions, and they show good agreement. Material constants for the constitutive creep model are obtained for AISI 316L stainless steel, an alloy steel widely used for temperature and corrosion resistance for such components as exhaust manifolds, furnace parts, heat exchangers and jet engine parts. Model predictions are compared to pure creep experimental data, with satisfactory results. Assumptions and constraints inherent in the implementation of the present model are examined. They include: spatial discretization, similitude, plane stress constraint and linear elasticity. It is shown that the implementation of the present model had a non-trivial impact on the model solutions in 316L stainless steel, especially the spatial discretization. Based on these studies, the following conclusions are drawn: 1. The constitutive creep model consistently performs better than the Nikbin, Smith and Webster (NSW) model for predicting creep and creep-fatigue crack extension. 2. Given a database of uniaxial creep test data, a constitutive material model such as the one developed for modified 9Cr-1Mo can be developed for other materials. 3. Due to the assumptions used to develop the strip-yield model, model predictions are expected to show some scatter, especially in some situations. Several areas of future research are proposed from these conclusions: 1. Alternative methods for predicting fatigue crack growth, especially a constitutive fatigue crack growth model, 2. Continued development of new material models and refinement the existing ones, and 3. Implementation of the present creep-fatigue model as a user-defined subroutine in a finite element solver.

Grain-dependent responses of mammalian diversity to land use and the implications for conservation set-aside.

PubMed

Wearn, Oliver R; Carbone, Chris; Rowcliffe, J Marcus; Bernard, Henry; Ewers, Robert M

2016-07-01

Diversity responses to land-use change are poorly understood at local scales, hindering our ability to make forecasts and management recommendations at scales which are of practical relevance. A key barrier in this has been the underappreciation of grain-dependent diversity responses and the role that β-diversity (variation in community composition across space) plays in this. Decisions about the most effective spatial arrangement of conservation set-aside, for example high conservation value areas, have also neglected β-diversity, despite its role in determining the complementarity of sites. We examined local-scale mammalian species richness and β-diversity across old-growth forest, logged forest, and oil palm plantations in Borneo, using intensive camera- and live-trapping. For the first time, we were able to investigate diversity responses, as well as β-diversity, at multiple spatial grains, and across the whole terrestrial mammal community (large and small mammals); β-diversity was quantified by comparing observed β-diversity with that obtained under a null model, in order to control for sampling effects, and we refer to this as the β-diversity signal. Community responses to land use were grain dependent, with large mammals showing reduced richness in logged forest compared to old-growth forest at the grain of individual sampling points, but no change at the overall land-use level. Responses varied with species group, however, with small mammals increasing in richness at all grains in logged forest compared to old-growth forest. Both species groups were significantly depauperate in oil palm. Large mammal communities in old-growth forest became more heterogeneous at coarser spatial grains and small mammal communities became more homogeneous, while this pattern was reversed in logged forest. Both groups, however, showed a significant β-diversity signal at the finest grain in logged forest, likely due to logging-induced environmental heterogeneity. The β-diversity signal in oil palm was weak, but heterogeneity at the coarsest spatial grain was still evident, likely due to variation in landscape forest cover. Our findings suggest that the most effective spatial arrangement of set-aside will involve trade-offs between conserving large and small mammals. Greater consideration in the conservation and management of tropical landscapes needs to be given to β-diversity at a range of spatial grains. © 2016 by the Ecological Society of America.

Age and growth of round gobies in Lake Huron: Implications for food web dynamics

USGS Publications Warehouse

Duan, You J.; Madenjian, Charles P.; Xie, Cong X.; Diana, James S.; O'Brien, Timothy P.; Zhao, Ying M.; He, Ji X.; Farha, Steve A.; Huo, Bin

2016-01-01

Although the round goby (Neogobius melanostomus) has become established throughout the Laurentian Great Lakes, information is scarce on spatial variation in round goby growth between and within lakes. Based on a sample of 754 specimens captured in 2014, age, growth, and mortality of round gobies at four locations in Lake Huron were assessed via otolith analysis. Total length (TL) of round gobies ranged from 44 to 111 mm for Saginaw Bay, from 45 to 115 mm for Rockport, from 50 to 123 mm for Hammond Bay, and from 51 to 118 mm for Thunder Bay. Estimated ages of round gobies ranged from 2 to 5 years for Saginaw Bay, from 2 to 6 years for Rockport, and from 2 to 7 years for Hammond Bay and Thunder Bay. Sex-specific, body–otolith relationships were used to back-calculate total lengths at age, which were then fitted to von Bertalanffy growth models. For each sex, round goby growth showed significant spatial variation among the four locations within Lake Huron. At all four locations in Lake Huron, males grew significantly faster than females and attained a larger asymptotic length than females. Annual mortality rate estimates were high (62 to 85%), based on catch-curve analysis, suggesting that round gobies may be under predatory control in Lake Huron.

Simulating Thin Sheets: Buckling, Wrinkling, Folding and Growth

NASA Astrophysics Data System (ADS)

Vetter, Roman; Stoop, Norbert; Wittel, Falk K.; Herrmann, Hans J.

2014-03-01

Numerical simulations of thin sheets undergoing large deformations are computationally challenging. Depending on the scenario, they may spontaneously buckle, wrinkle, fold, or crumple. Nature's thin tissues often experience significant anisotropic growth, which can act as the driving force for such instabilities. We use a recently developed finite element model to simulate the rich variety of nonlinear responses of Kirchhoff-Love sheets. The model uses subdivision surface shape functions in order to guarantee convergence of the method, and to allow a finite element description of anisotropically growing sheets in the classical Rayleigh-Ritz formalism. We illustrate the great potential in this approach by simulating the inflation of airbags, the buckling of a stretched cylinder, as well as the formation and scaling of wrinkles at free boundaries of growing sheets. Finally, we compare the folding of spatially confined sheets subject to growth and shrinking confinement to find that the two processes are equivalent.

The Influence of Microgravity on Invasive Growth in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Van Mulders, Sebastiaan E.; Stassen, Catherine; Daenen, Luk; Devreese, Bart; Siewers, Verena; van Eijsden, Rudy G. E.; Nielsen, Jens; Delvaux, Freddy R.; Willaert, Ronnie

2011-01-01

This study investigates the effects of microgravity on colony growth and the morphological transition from single cells to short invasive filaments in the model eukaryotic organism Saccharomyces cerevisiae. Two-dimensional spreading of the yeast colonies grown on semi-solid agar medium was reduced under microgravity in the Σ1278b laboratory strain but not in the CMBSESA1 industrial strain. This was supported by the Σ1278b proteome map under microgravity conditions, which revealed upregulation of proteins linked to anaerobic conditions. The Σ1278b strain showed a reduced invasive growth in the center of the yeast colony. Bud scar distribution was slightly affected, with a switch toward more random budding. Together, microgravity conditions disturb spatially programmed budding patterns and generate strain-dependent growth differences in yeast colonies on semi-solid medium.

Shanghai: a study on the spatial growth of population and economy in a Chinese metropolitan area.

PubMed

Zhu, J

1995-01-01

In this study of the growth in population and industry in Shanghai, China, between the 1982 and 1990 censuses, data on administrative divisions was normalized through digitization and spatial analysis. Analysis focused on spatial units, intensity of growth, time period, distance, rate of growth, and direction of spatial growth. The trisection method divided the city into city proper, outskirts, and suburbs. The distance function method considered the distance from center city as a function: exponential, power, trigonometric, logarithmic, and polynomial. Population growth and employment in all sectors increased in the outskirts and suburbs and decreased in the city proper except tertiary sectors. Primary sector employment decreased in all three sections. Employment in the secondary increased faster in the outskirts and suburbs than the total rate of growth of population and employment. In the city secondary sector employment rates decreased faster than total population and employment rates. The tertiary sector had the highest rate of growth in all sections, and employment grew faster than secondary sector rates. Tertiary growth was highest in real estate, finance, and insurance. Industrial growth in the secondary sector was 160.2% in the suburbs, 156.6% in the outskirts, and 80.9% in the city. In the distance function analysis, industry expanded further out than the entire secondary sector. Commerce grew the fastest in areas 15.4 km from center city. Economic growth was faster after economic reforms in 1978. Growth was led by industry and followed by the secondary sector, the tertiary sector, and population. Industrial expansion resulted from inner pressure, political factors controlling size, the social and economic system, and the housing construction and distribution system. Initially sociopsychological factors affected urban concentration.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought.

PubMed

Carnwath, Gunnar; Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought

PubMed Central

Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales. PMID:28973008

Key variables influencing patterns of lava dome growth and collapse

NASA Astrophysics Data System (ADS)

Husain, T.; Elsworth, D.; Voight, B.; Mattioli, G. S.; Jansma, P. E.

2013-12-01

Lava domes are conical structures that grow by the infusion of viscous silicic or intermediate composition magma from a central volcanic conduit. Dome growth can be characterized by repeated cycles of growth punctuated by collapse, as the structure becomes oversized for its composite strength. Within these cycles, deformation ranges from slow long term deformation to sudden deep-seated collapses. Collapses may range from small raveling failures to voluminous and fast-moving pyroclastic flows with rapid and long-downslope-reach from the edifice. Infusion rate and magma rheology together with crystallization temperature and volatile content govern the spatial distribution of strength in the structure. Solidification, driven by degassing-induced crystallization of magma leads to the formation of a continuously evolving frictional talus as a hard outer shell. This shell encapsulates the cohesion-dominated soft ductile core. Here we explore the mechanics of lava dome growth and failure using a two-dimensional particle-dynamics model. This meshless model follows the natural evolution of a brittle carapace formed by loss of volatiles and rheological stiffening and avoids difficulties of hour-glassing and mesh-entangelment typical in meshed models. We test the fidelity of the model against existing experimental and observational models of lava dome growth. The particle-dynamics model follows the natural development of dome growth and collapse which is infeasible using simple analytical models. The model provides insight into the triggers that lead to the transition in collapse mechasnism from shallow flank collapse to deep seated sector collapse. Increase in material stiffness due to decrease in infusion rate results in the transition of growth pattern from endogenous to exogenous. The material stiffness and strength are strongly controlled by the magma infusion rate. Increase in infusion rate decreases the time available for degassing induced crystallization leading to a transition in the growth pattern, while a decrease in infusion rate results in larger crystals causing the material to stiffen leading to formation of spines. Material stiffness controls the growth direction of the viscous plug in the lava dome interior. Material strength and stiffness controled by rate of infusion influence lava dome growth more significantly than coefficient of frictional of the talus.

Divergence in Patterns of Leaf Growth Polarity Is Associated with the Expression Divergence of miR396

PubMed Central

2015-01-01

Lateral appendages often show allometric growth with a specific growth polarity along the proximo-distal axis. Studies on leaf growth in model plants have identified a basipetal growth direction with the highest growth rate at the proximal end and progressively lower rates toward the distal end. Although the molecular mechanisms governing such a growth pattern have been studied recently, variation in leaf growth polarity and, therefore, its evolutionary origin remain unknown. By surveying 75 eudicot species, here we report that leaf growth polarity is divergent. Leaf growth in the proximo-distal axis is polar, with more growth arising from either the proximal or the distal end; dispersed with no apparent polarity; or bidirectional, with more growth contributed by the central region and less growth at either end. We further demonstrate that the expression gradient of the miR396-GROWTH-REGULATING FACTOR module strongly correlates with the polarity of leaf growth. Altering the endogenous pattern of miR396 expression in transgenic Arabidopsis thaliana leaves only partially modified the spatial pattern of cell expansion, suggesting that the diverse growth polarities might have evolved via concerted changes in multiple gene regulatory networks. PMID:26410303

Adjoint sensitivity analysis of a tumor growth model and its application to spatiotemporal radiotherapy optimization.

PubMed

Fujarewicz, Krzysztof; Lakomiec, Krzysztof

2016-12-01

We investigate a spatial model of growth of a tumor and its sensitivity to radiotherapy. It is assumed that the radiation dose may vary in time and space, like in intensity modulated radiotherapy (IMRT). The change of the final state of the tumor depends on local differences in the radiation dose and varies with the time and the place of these local changes. This leads to the concept of a tumor's spatiotemporal sensitivity to radiation, which is a function of time and space. We show how adjoint sensitivity analysis may be applied to calculate the spatiotemporal sensitivity of the finite difference scheme resulting from the partial differential equation describing the tumor growth. We demonstrate results of this approach to the tumor proliferation, invasion and response to radiotherapy (PIRT) model and we compare the accuracy and the computational effort of the method to the simple forward finite difference sensitivity analysis. Furthermore, we use the spatiotemporal sensitivity during the gradient-based optimization of the spatiotemporal radiation protocol and present results for different parameters of the model.

Velocity locking and pulsed invasions of fragmented habitats with seasonal growth

NASA Astrophysics Data System (ADS)

Korolev, Kirill; Wang, Ching-Hao

From crystal growth to epidemics, spatial spreading is a common mechanism of change in nature. Typically, spreading results from two processes: growth and dispersal in ecology or chemical reactions and diffusion in physics. These two processes combine to produce a reaction-diffusion wave, an invasion front advancing at a constant velocity. We show that the properties of these waves are remarkably different depending whether space and time are continuous, as they are for a chemical reaction, or discrete, as they are for a pest invading a patchy habitat in seasonal climates. For discrete space and time, we report a new type of expansions with velocities that can lock into specific values and become insensitive to changes in dispersal and growth, i.e. the dependence of the velocity on model parameters exhibits plateaus or pauses. As a result, the evolution and response to perturbations in locked expansions can be markedly different compared to the expectations based on continuous models. The phenomenon of velocity locking requires cooperative growth and does not occur when per capita growth rate decline monotonically with population density. We obtain both numerical and analytical results describing highly non-analytic properties of locked expansions.

Trapped in Place? Segmented Resilience to Hurricanes in the Gulf Coast, 1970-2005.

PubMed

Logan, John R; Issar, Sukriti; Xu, Zengwang

2016-10-01

Hurricanes pose a continuing hazard to populations in coastal regions. This study estimates the impact of hurricanes on population change in the years 1970-2005 in the U.S. Gulf Coast region. Geophysical models are used to construct a unique data set that simulates the spatial extent and intensity of wind damage and storm surge from the 32 hurricanes that struck the region in this period. Multivariate spatial time-series models are used to estimate the impacts of hurricanes on population change. Population growth is found to be reduced significantly for up to three successive years after counties experience wind damage, particularly at higher levels of damage. Storm surge is associated with reduced population growth in the year after the hurricane. Model extensions show that change in the white and young adult population is more immediately and strongly affected than is change for blacks and elderly residents. Negative effects on population are stronger in counties with lower poverty rates. The differentiated impact of hurricanes on different population groups is interpreted as segmented withdrawal-a form of segmented resilience in which advantaged population groups are more likely to move out of or avoid moving into harm's way while socially vulnerable groups have fewer choices.

Trapped in Place? Segmented Resilience to Hurricanes in the Gulf Coast, 1970–2005

PubMed Central

Logan, John R.; Issar, Sukriti; Xu, Zengwang

2016-01-01

Hurricanes pose a continuing hazard to populations in coastal regions. This study estimates the impact of hurricanes on population change in the years 1970–2005 in the U.S. Gulf Coast region. Geophysical models are used to construct a unique data set that simulates the spatial extent and intensity of wind damage and storm surge from the 32 hurricanes that struck the region in this period. Multivariate spatial time-series models are used to estimate the impacts of hurricanes on population change. Population growth is found to be reduced significantly for up to three successive years after counties experience wind damage, particularly at higher levels of damage. Storm surge is associated with reduced population growth in the year after the hurricane. Model extensions show that change in the white and young adult population is more immediately and strongly affected than is change for blacks and elderly residents. Negative effects on population are stronger in counties with lower poverty rates. The differentiated impact of hurricanes on different population groups is interpreted as segmented withdrawal—a form of segmented resilience in which advantaged population groups are more likely to move out of or avoid moving into harm’s way while socially vulnerable groups have fewer choices. PMID:27531504

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schweizer, M.

This report summarizes progress during the past year on maturing Boron-11 magnetic resonance imaging (MRI) methodology for noninvasive determination of BNCT agents (BSH) spatially in time. Three major areas are excerpted: (1) Boron-11 MRI of BSH distributions in a canine intracranial tumor model and the first human glioblastoma patient, (2) whole body Boron-11 MRI of BSH pharmacokinetics in a rat flank tumor model, and (3) penetration of gadolinium salts through the BBB as a function of tumor growth in the canine brain.

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters

USGS Publications Warehouse

Tinker, M. Timothy; Doak, Daniel F.; Estes, James A.; Hatfield, Brian B.; Staedler, Michelle M.; Gross, Arthur

2006-01-01

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks. ?? 2006 by the Ecological Society of America.

An optical assessment of the effects of glioma growth on resting state networks in mice (Conference Presentation)

NASA Astrophysics Data System (ADS)

Orukari, Inema E.; Bauer, Adam Q.; Baxter, Grant A.; Rubin, Joshua B.; Culver, Joseph P.

2017-02-01

Gliomas are known to cause significant changes in normal brain function that lead to cognitive deficits. Disruptions in resting state networks (RSNs) are thought to underlie these changes. However, investigating the effects of glioma growth on RSNs in humans is complicated by the heterogeneity in lesion size, type, and location across subjects. In this study, we evaluated the effects of tumor growth on RSNs over time in a controlled mouse model of glioma growth. Methods: Glioma cells (5x104-105 U87s) were stereotactically injected into the forepaw somatosensory cortex of adult nude mice (n=5). Disruptions in RSNs were evaluated weekly with functional connectivity optical intrinsic signal imaging (fcOIS). Tumor growth was monitored with MRI and weekly bioluminescence imaging (BLI). In order to characterize how tumor growth affected different RSNs over time, we calculated a number of functional connectivity (fc) metrics, including homotopic (bilateral) connectivity, spatial similarity, and node degree. Results: Deficits in fc initiate near the lesion, and over a period of several weeks, extend more globally. The reductions in spatial similarity were found to strongly correlate with the BLI signal indicating that increased tumor size is associated with increased RSN disruption. Conclusions: We have shown that fcOIS is capable of detecting alterations in mouse RSNs due to brain tumor growth. A better understanding of how RSN disruption contributes to the development of cognitive deficits in brain tumor patients may lead to better patient risk stratification and consequently improved cognitive outcomes.

DEVELOPMENT OF AN AGAR LIFT-DNA/DNA HYBRIDIZATION TECHNIQUE FOR USE IN VISUALIZATION OF THE SPATIAL DISTRIBUTION OF EUBACTERIA ON SOIL SURFACES. (R825415)

EPA Science Inventory

Abstract

While microbial growth is well-understood in pure culture systems, less is known about growth in intact soil systems. The objective of this work was to develop a technique to allow visualization of the two-dimensional spatial distribution of bacterial growth o...

Reduced Mastication Impairs Memory Function.

PubMed

Fukushima-Nakayama, Y; Ono, Takehito; Hayashi, M; Inoue, M; Wake, H; Ono, Takashi; Nakashima, T

2017-08-01

Mastication is an indispensable oral function related to physical, mental, and social health throughout life. The elderly tend to have a masticatory dysfunction due to tooth loss and fragility in the masticatory muscles with aging, potentially resulting in impaired cognitive function. Masticatory stimulation has influence on the development of the central nervous system (CNS) as well as the growth of maxillofacial tissue in children. Although the relationship between mastication and cognitive function is potentially important in the growth period, the cellular and molecular mechanisms have not been sufficiently elucidated. Here, we show that the reduced mastication resulted in impaired spatial memory and learning function owing to the morphological change and decreased activity in the hippocampus. We used an in vivo model for reduced masticatory stimuli, in which juvenile mice were fed with powder diet and found that masticatory stimulation during the growth period positively regulated long-term spatial memory to promote cognitive function. The functional linkage between mastication and brain was validated by the decrease in neurons, neurogenesis, neuronal activity, and brain-derived neurotrophic factor (BDNF) expression in the hippocampus. These findings taken together provide in vivo evidence for a functional linkage between mastication and cognitive function in the growth period, suggesting a need for novel therapeutic strategies in masticatory function-related cognitive dysfunction.

Shrub growth response to climate across the North Slope of Alaska

NASA Astrophysics Data System (ADS)

Ackerman, D.; Griffin, D.; Finlay, J. C.; Hobbie, S. E.

2016-12-01

Warmer temperatures at high latitudes are driving the expansion of woody shrubs in arctic tundra, yielding feedbacks to regional carbon cycling. Accounting for these feedbacks in global climate models will require accurate predictions of the spatial extent of shrub expansion within arctic tundra. While dendroecological approaches have proven useful in understanding how shrubs respond to climate, empirical studies to date are limited in spatial extent, often to just one or two sites within a landscape. A recent meta-analysis of such dendroecological studies hypothesizes that soil moisture is a key variable in determining climate sensitivity of arctic shrub growth. We present the first regional-scale empirical test of this hypothesis by analyzing inter-annual radial growth of deciduous shrubs across soil moisture gradients throughout the North Slope of Alaska. Contrary to expectation, riparian shrubs in high-moisture environments showed no climate sensitivity, while shrubs growing in drier upland sites showed a strong positive growth response to summer temperature. These results proved robust to a variety of detrending functions ranging from conservative (negative exponential) to data adaptive (20-year cubic smoothing spline). These findings call into question the role of soil moisture in determining the climate sensitivity of arctic shrubs and further highlight the importance of unified, regional-scale sampling strategies in understanding climate-vegetation links.

Focusing behavior of the fractal vector optical fields designed by fractal lattice growth model.

PubMed

Gao, Xu-Zhen; Pan, Yue; Zhao, Meng-Dan; Zhang, Guan-Lin; Zhang, Yu; Tu, Chenghou; Li, Yongnan; Wang, Hui-Tian

2018-01-22

We introduce a general fractal lattice growth model, significantly expanding the application scope of the fractal in the realm of optics. This model can be applied to construct various kinds of fractal "lattices" and then to achieve the design of a great diversity of fractal vector optical fields (F-VOFs) combinating with various "bases". We also experimentally generate the F-VOFs and explore their universal focusing behaviors. Multiple focal spots can be flexibly enginnered, and the optical tweezers experiment validates the simulated tight focusing fields, which means that this model allows the diversity of the focal patterns to flexibly trap and manipulate micrometer-sized particles. Furthermore, the recovery performance of the F-VOFs is also studied when the input fields and spatial frequency spectrum are obstructed, and the results confirm the robustness of the F-VOFs in both focusing and imaging processes, which is very useful in information transmission.

Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

NASA Astrophysics Data System (ADS)

Liu, Z.; Li, Y.

2018-04-01

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

Modeling Urban Growth Spatial Dynamics: Case studies of Addis Ababa and Dar es Salaam

NASA Astrophysics Data System (ADS)

Buchta, Katja; Abo El Wafa, Hany; Printz, Andreas; Pauleit, Stephan

2013-04-01

Rapid urbanization, and consequently, the dramatic spatial expansion of mostly informal urban areas increases the vulnerability of African cities to the effects of climate change such as sea level rise, more frequent flooding, droughts and heat waves. The EU FP 7 funded project CLUVA (Climate Change and Urban Vulnerability in Africa, www.cluva.eu) aims to develop strategies for minimizing the risks of natural hazards caused by climate change and to improve the coping capacity of African cities. Green infrastructure may play a particular role in climate change adaptation by providing ecosystem services for flood protection, stormwater retention, heat island moderation and provision of food and fuel wood. In this context, a major challenge is to gain a better understanding of the spatial and temporal dynamics of the cities and how these impact on green infrastructure and hence their vulnerability. Urban growth scenarios for two African cities, namely Addis Ababa, Ethiopia and Dar es Salaam, Tanzania, were developed based on a characterization of their urban morphology. A population growth driven - GIS based - disaggregation modeling approach was applied. Major impact factors influencing the urban dynamics were identified both from literature and interviews with local experts. Location based factors including proximity to road infrastructure and accessibility, and environmental factors including slope, surface and flood risk areas showed a particular impact on urban growth patterns. In Addis Ababa and Dar es Salaam, population density scenarios were modeled comparing two housing development strategies. Results showed that a densification scenario significantly decreases the loss of agricultural and green areas such as forests, bushland and sports grounds. In Dar es Salaam, the scenario of planned new settlements with a population density of max. 350 persons per hectare would lead until 2025 to a loss of agricultural land (-10.1%) and green areas (-6.6%). On the other hand, 12.4% of agricultural land and 16.1% of green areas would be lost in the low density development scenario of unplanned settlements of max. 150 persons per hectare. Relocating the population living in flood prone areas in the case of Addis Ababa and keeping those areas free from further settlements in the case of Dar es Salaam would result in even lower losses (agricultural land: -10.0%, green areas: -5.6%) as some flood prone areas overlap with agricultural/ green areas. The scenario models introduced in this research can be used by planners as tools to understand and manage the different outcomes of distinctive urban development strategies on growth patterns and how they interact with different climate change drivers such as loss of green infrastructure and effects such as frequent flooding hazards. Due to the relative simplicity of their structure and the single modeling environment, the models can be transferred to similar cities with minor modifications accommodating the different conditions of each city. Already, in Addis Ababa the results of the model will be used in the current revision of the Master plan of the city. Keywords: GIS, modeling, Urban Dynamics, Dar es Salaam, Addis Ababa, urbanization

Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio

NASA Astrophysics Data System (ADS)

Aburas, Maher Milad; Ho, Yuek Ming; Ramli, Mohammad Firuz; Ash'aari, Zulfa Hanan

2017-07-01

The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning.

Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity

NASA Astrophysics Data System (ADS)

Holmes, Keith Richard

Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.

A public hedonic analysis of environmental attributes in an open space preservation program

NASA Astrophysics Data System (ADS)

Nordman, Erik E.

The Town of Brookhaven, on Long Island, NY, has implemented an open space preservation program to protect natural areas, and the ecosystem services they provide, from suburban growth. I used a public hedonic model of Brookhaven's open space purchases to estimate implicit prices for various environmental attributes, locational variables and spatial metrics. I also measured the correlation between cost per acre and non-monetary environmental benefit scores and tested whether including cost data, as opposed to non-monetary environmental benefit score alone, would change the prioritization ranks of acquired properties. The mean acquisition cost per acre was 82,501. I identified the key on-site environmental and locational variables using stepwise regression for four functional forms. The log-log specification performed best ( R2adj= 0.727). I performed a second stepwise regression (log-log form) which included spatial metrics, calculated from a high-resolution land cover classification, in addition to the environmental and locational variables. This markedly improved the model's performance ( R2adj=0.866). Statistically significant variables included the property size, location in the Pine Barrens Compatible Growth Area, location in a FEMA flood zone, adjacency to public land, and several other environmental dummy variables. The single significant spatial metric, the fractal dimension of the tree cover class, had the largest elasticity of any variable. Of the dummy variables, location within the Compatible Growth Area had the largest implicit price (298,792 per acre). The priority rank for the two methods, non-monetary environmental benefit score alone and the ratio of non-monetary environmental benefit score to acquisition cost were significantly positively correlated. This suggests that, despite the lack of cost data in their ranking method, Brookhaven does not suffer from efficiency losses. The economics literature encourages using both environmental benefits and acquisition costs to ensure cost-effective conservation programs. I recommend that Brookhaven consider acquisition costs in addition to environmental benefits to avert potential efficiency losses in future open space purchases. This dissertation shows that the addition of spatial metrics can enhance the performance of hedonic models. It also provides a baseline valuation for the environmental attributes of Brookhaven' open spaces and shows that location is critical when dealing with open space preservation programs.

Monte-Carlo Simulations of Drug Delivery on Biofilms

NASA Astrophysics Data System (ADS)

Buldum, Alper; Simpson, Andrew

2013-03-01

The focus of this work is on biofilms that grow in the lungs of cystic fibrosis (CF) patients. A discrete model which describes the nutrient and biomass as discrete particles is created. Diffusion of the nutrient, consumption of the nutrient by microbial particles, and growth and decay of microbial particles are simulated using stochastic processes. Our model extends the complexity of the biofilm system by including the conversion and reversion of living bacteria into a hibernated state, known as persister bacteria. Another new contribution is the inclusion of antimicrobial in two forms: an aqueous solution and encapsulated in biodegradable nanoparticles. The bacteria population growth and spatial variation of drugs and their effectiveness are investigated in this work. Supported by NIH

Influence of diffusion and convective transport on dendritic growth in dilute alloys

NASA Technical Reports Server (NTRS)

Glicksman, M. E.; Singh, N. B.; Chopra, M.

1982-01-01

Experimentation has been carried out in which the kinetics and morphology of dendritic growth were measured as a function of thermal supercooling, solute concentration, and spatial orientation of the dendritic growth axis. The crystal growth system studied is succinonitrile, NC(CH2)2CN, with additions of argon (up to 0.1 mole percent). This system is especially useful as a model for alloy studies because kinetic data are available for high purity (7-9's) succinonitrile. The influence of the solute, at fixed thermal supercooling, is to increase the growth velocity and correspondingly decrease intrinsic crystal dimensions. Morphological measurements are described in detail relating tip size, perturbation wavelength, supercooling, and solute concentration. The analysis of these effects based on morphological stability theory is also discussed, and experiments permitting the separation of convective and diffusive heat transport during crystal growth of succinonitrile are described. The studies underscore the importance of gravitationally-induced buoyancy effects on crystal growth.

Predicting the response of the deep-ocean microbiome to geochemical perturbations by hydrothermal vents.

PubMed

Reed, Daniel C; Breier, John A; Jiang, Houshuo; Anantharaman, Karthik; Klausmeier, Christopher A; Toner, Brandy M; Hancock, Cathrine; Speer, Kevin; Thurnherr, Andreas M; Dick, Gregory J

2015-08-01

Submarine hydrothermal vents perturb the deep-ocean microbiome by injecting reduced chemical species into the water column that act as an energy source for chemosynthetic organisms. These systems thus provide excellent natural laboratories for studying the response of microbial communities to shifts in marine geochemistry. The present study explores the processes that regulate coupled microbial-geochemical dynamics in hydrothermal plumes by means of a novel mathematical model, which combines thermodynamics, growth and reaction kinetics, and transport processes derived from a fluid dynamics model. Simulations of a plume located in the ABE vent field of the Lau basin were able to reproduce metagenomic observations well and demonstrated that the magnitude of primary production and rate of autotrophic growth are largely regulated by the energetics of metabolisms and the availability of electron donors, as opposed to kinetic parameters. Ambient seawater was the dominant source of microbes to the plume and sulphur oxidisers constituted almost 90% of the modelled community in the neutrally-buoyant plume. Data from drifters deployed in the region allowed the different time scales of metabolisms to be cast in a spatial context, which demonstrated spatial succession in the microbial community. While growth was shown to occur over distances of tens of kilometers, microbes persisted over hundreds of kilometers. Given that high-temperature hydrothermal systems are found less than 100 km apart on average, plumes may act as important vectors between different vent fields and other environments that are hospitable to similar organisms, such as oil spills and oxygen minimum zones.

Predicting the response of the deep-ocean microbiome to geochemical perturbations by hydrothermal vents

PubMed Central

Reed, Daniel C; Breier, John A; Jiang, Houshuo; Anantharaman, Karthik; Klausmeier, Christopher A; Toner, Brandy M; Hancock, Cathrine; Speer, Kevin; Thurnherr, Andreas M; Dick, Gregory J

2015-01-01

Submarine hydrothermal vents perturb the deep-ocean microbiome by injecting reduced chemical species into the water column that act as an energy source for chemosynthetic organisms. These systems thus provide excellent natural laboratories for studying the response of microbial communities to shifts in marine geochemistry. The present study explores the processes that regulate coupled microbial-geochemical dynamics in hydrothermal plumes by means of a novel mathematical model, which combines thermodynamics, growth and reaction kinetics, and transport processes derived from a fluid dynamics model. Simulations of a plume located in the ABE vent field of the Lau basin were able to reproduce metagenomic observations well and demonstrated that the magnitude of primary production and rate of autotrophic growth are largely regulated by the energetics of metabolisms and the availability of electron donors, as opposed to kinetic parameters. Ambient seawater was the dominant source of microbes to the plume and sulphur oxidisers constituted almost 90% of the modelled community in the neutrally-buoyant plume. Data from drifters deployed in the region allowed the different time scales of metabolisms to be cast in a spatial context, which demonstrated spatial succession in the microbial community. While growth was shown to occur over distances of tens of kilometers, microbes persisted over hundreds of kilometers. Given that high-temperature hydrothermal systems are found less than 100 km apart on average, plumes may act as important vectors between different vent fields and other environments that are hospitable to similar organisms, such as oil spills and oxygen minimum zones. PMID:25658053

Density dependence, spatial scale and patterning in sessile biota.

PubMed

Gascoigne, Joanna C; Beadman, Helen A; Saurel, Camille; Kaiser, Michel J

2005-09-01

Sessile biota can compete with or facilitate each other, and the interaction of facilitation and competition at different spatial scales is key to developing spatial patchiness and patterning. We examined density and scale dependence in a patterned, soft sediment mussel bed. We followed mussel growth and density at two spatial scales separated by four orders of magnitude. In summer, competition was important at both scales. In winter, there was net facilitation at the small scale with no evidence of density dependence at the large scale. The mechanism for facilitation is probably density dependent protection from wave dislodgement. Intraspecific interactions in soft sediment mussel beds thus vary both temporally and spatially. Our data support the idea that pattern formation in ecological systems arises from competition at large scales and facilitation at smaller scales, so far only shown in vegetation systems. The data, and a simple, heuristic model, also suggest that facilitative interactions in sessile biota are mediated by physical stress, and that interactions change in strength and sign along a spatial or temporal gradient of physical stress.

Resolving runaway electron distributions in space, time, and energy

NASA Astrophysics Data System (ADS)

Paz-Soldan, C.; Cooper, C. M.; Aleynikov, P.; Eidietis, N. W.; Lvovskiy, A.; Pace, D. C.; Brennan, D. P.; Hollmann, E. M.; Liu, C.; Moyer, R. A.; Shiraki, D.

2018-05-01

Areas of agreement and disagreement with present-day models of runaway electron (RE) evolution are revealed by measuring MeV-level bremsstrahlung radiation from runaway electrons (REs) with a pinhole camera. Spatially resolved measurements localize the RE beam, reveal energy-dependent RE transport, and can be used to perform full two-dimensional (energy and pitch-angle) inversions of the RE phase-space distribution. Energy-resolved measurements find qualitative agreement with modeling on the role of collisional and synchrotron damping in modifying the RE distribution shape. Measurements are consistent with predictions of phase-space attractors that accumulate REs, with non-monotonic features observed in the distribution. Temporally resolved measurements find qualitative agreement with modeling on the impact of collisional and synchrotron damping in varying the RE growth and decay rate. Anomalous RE loss is observed and found to be largest at low energy. Possible roles for kinetic instability or spatial transport to resolve these anomalies are discussed.

Double plasma resonance instability as a source of solar zebra emission

NASA Astrophysics Data System (ADS)

Benáček, J.; Karlický, M.

2018-03-01

Context. The double plasma resonance (DPR) instability plays a basic role in the generation of solar radio zebras. In the plasma, consisting of the loss-cone type distribution of hot electrons and much denser and colder background plasma, this instability generates the upper-hybrid waves, which are then transformed into the electromagnetic waves and observed as radio zebras. Aims: In the present paper we numerically study the double plasma resonance instability from the point of view of the zebra interpretation. Methods: We use a 3-dimensional electromagnetic particle-in-cell (3D PIC) relativistic model. We use this model in two versions: (a) a spatially extended "multi-mode" model and (b) a spatially limited "specific-mode" model. While the multi-mode model is used for detailed computations and verifications of the results obtained by the "specific-mode" model, the specific-mode model is used for computations in a broad range of model parameters, which considerably save computational time. For an analysis of the computational results, we developed software tools in Python. Results: First using the multi-mode model, we study details of the double plasma resonance instability. We show how the distribution function of hot electrons changes during this instability. Then we show that there is a very good agreement between results obtained by the multi-mode and specific-mode models, which is caused by a dominance of the wave with the maximal growth rate. Therefore, for computations in a broad range of model parameters, we use the specific-mode model. We compute the maximal growth rates of the double plasma resonance instability with a dependence on the ratio between the upper-hybrid ωUH and electron-cyclotron ωce frequency. We vary temperatures of both the hot and background plasma components and study their effects on the resulting growth rates. The results are compared with the analytical ones. We find a very good agreement between numerical and analytical growth rates. We also compute saturation energies of the upper-hybrid waves in a very broad range of parameters. We find that the saturation energies of the upper-hybrid waves show maxima and minima at almost the same values of ωUH/ωce as the growth rates, but with a higher contrast between them than the growth rate maxima and minima. The contrast between saturation energy maxima and minima increases when the temperature of hot electrons increases. Furthermore, we find that the saturation energy of the upper-hybrid waves is proportional to the density of hot electrons. The maximum saturated energy can be up to one percent of the kinetic energy of hot electrons. Finally we find that the saturation energy maxima in the interval of ωUH/ωce = 3-18 decrease according to the exponential function. All these findings can be used in the interpretation of solar radio zebras.

Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting.

PubMed

Jahanishakib, Fatemeh; Mirkarimi, Seyed Hamed; Salmanmahiny, Abdolrassoul; Poodat, Fatemeh

2018-05-08

Efficient land use management requires awareness of past changes, present actions, and plans for future developments. Part of these requirements is achieved using scenarios that describe a future situation and the course of changes. This research aims to link scenario results with spatially explicit and quantitative forecasting of land use development. To develop land use scenarios, SMIC PROB-EXPERT and MORPHOL methods were used. It revealed eight scenarios as the most probable. To apply the scenarios, we considered population growth rate and used a cellular automata-Markov chain (CA-MC) model to implement the quantified changes described by each scenario. For each scenario, a set of landscape metrics was used to assess the ecological integrity of land use classes in terms of fragmentation and structural connectivity. The approach enabled us to develop spatial scenarios of land use change and detect their differences for choosing the most integrated landscape pattern in terms of landscape metrics. Finally, the comparison between paired forecasted scenarios based on landscape metrics indicates that scenarios 1-1, 2-2, 3-2, and 4-1 have a more suitable integrity. The proposed methodology for developing spatial scenarios helps executive managers to create scenarios with many repetitions and customize spatial patterns in real world applications and policies.

Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

PubMed

Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

2015-06-01

Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. © 2015 International Society for Advancement of Cytometry.

Growth-mediated autochemotactic pattern formation in self-propelling bacteria

NASA Astrophysics Data System (ADS)

Mukherjee, Mrinmoy; Ghosh, Pushpita

2018-01-01

Bacteria, while developing a multicellular colony or biofilm, can undergo pattern formation by diverse intricate mechanisms. One such route is directional movement or chemotaxis toward or away from self-secreted or externally employed chemicals. In some bacteria, the self-produced signaling chemicals or autoinducers themselves act as chemoattractants or chemorepellents and thereby regulate the directional movements of the cells in the colony. In addition, bacteria follow a certain growth kinetics which is integrated in the process of colony development. Here, we study the interplay of bacterial growth dynamics, cell motility, and autochemotactic motion with respect to the self-secreted diffusive signaling chemicals in spatial pattern formation. Using a continuum model of motile bacteria, we show growth can act as a crucial tuning parameter in determining the spatiotemporal dynamics of a colony. In action of growth dynamics, while chemoattraction toward autoinducers creates arrested phase separation, pattern transitions and suppression can occur for a fixed chemorepulsive strength.

Multi-scaling allometric analysis for urban and regional development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2017-01-01

The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.

A time series of urban extent in China using DSMP/OLS nighttime light data

PubMed Central

Chen, Dongsheng; Chen, Le; Wang, Huan; Guan, Qingfeng

2018-01-01

Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning. PMID:29795685

Optimal control of anthracnose using mixed strategies.

PubMed

Fotsa Mbogne, David Jaures; Thron, Christopher

2015-11-01

In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.

SALMOD: A population model for salmonids: user's manual. Version W3

USGS Publications Warehouse

Bartholow, John; Heasley, John; Laake, Jeff; Sandelin, Jeff; Coughlan, Beth A.K.; Moos, Alan

2002-01-01

SALMOD is a computer model that simulates the dynamics of freshwater salmonid populations, both anadromous and resident. The conceptual model was developed in a workshop setting (Williamson et al. 1993) using fish experts concerned with Trinity River chinook restoration. The model builds on the foundation laid by similar models (see Cheslak and Jacobson 1990). The model’s premise that that egg and fish mortality are directly related to spatially and temporally variable micro- and macrohabitat limitations, which themselves are related to the timing and amount of streamflow and other meteorological variables. Habitat quality and capacity are characterized by the hydraulic and thermal properties of individual mesohabitats, which we use as spatial “computation units” in the model. The model tracks a population of spatially distinct cohorts that originate as gees and grow from one life stage to another as a function of local water temperature. Individual cohorts either remain in the computational unit in which they emerged or move, in whole or in part, to nearby units (see McCormick et al. 1998). Model processes include spawning (with red superimposition and incubation losses), growth (including egg maturation), mortality, and movement (freshet-induced, habitat-induced, and seasonal). Model processes are implemented such that the user (modeler) has the ability to more-or-less program the model on the fly to create the dynamics thought to animate the population. SALMOD then tabulates the various causes of mortality and the whereabouts of fish.

Time in tortoiseshell: a bomb radiocarbon-validated chronology in sea turtle scutes.

PubMed

Van Houtan, Kyle S; Andrews, Allen H; Jones, T Todd; Murakawa, Shawn K K; Hagemann, Molly E

2016-01-13

Some of the most basic questions of sea turtle life history are also the most elusive. Many uncertainties surround lifespan, growth rates, maturity and spatial structure, yet these are critical factors in assessing population status. Here we examine the keratinized hard tissues of the hawksbill (Eretmochelys imbricata) carapace and use bomb radiocarbon dating to estimate growth and maturity. Scutes have an established dietary record, yet the large keratin deposits of hawksbills evoke a reliable chronology. We sectioned, polished and imaged posterior marginal scutes from 36 individual hawksbills representing all life stages, several Pacific populations and spanning eight decades. We counted the apparent growth lines, microsampled along growth contours and calibrated Δ(14)C values to reference coral series. We fit von Bertalanffy growth function (VBGF) models to the results, producing a range of age estimates for each turtle. We find Hawaii hawksbills deposit eight growth lines annually (range 5-14), with model ensembles producing a somatic growth parameter (k) of 0.13 (range 0.1-0.2) and first breeding at 29 years (range 23-36). Recent bomb radiocarbon values also suggest declining trophic status. Together, our results may reflect long-term changes in the benthic community structure of Hawaii reefs, and possibly shed light on the critical population status for Hawaii hawksbills. © 2016 The Author(s).

Time in tortoiseshell: a bomb radiocarbon-validated chronology in sea turtle scutes

PubMed Central

Van Houtan, Kyle S.; Andrews, Allen H.; Jones, T. Todd; Murakawa, Shawn K. K.; Hagemann, Molly E.

2016-01-01

Some of the most basic questions of sea turtle life history are also the most elusive. Many uncertainties surround lifespan, growth rates, maturity and spatial structure, yet these are critical factors in assessing population status. Here we examine the keratinized hard tissues of the hawksbill (Eretmochelys imbricata) carapace and use bomb radiocarbon dating to estimate growth and maturity. Scutes have an established dietary record, yet the large keratin deposits of hawksbills evoke a reliable chronology. We sectioned, polished and imaged posterior marginal scutes from 36 individual hawksbills representing all life stages, several Pacific populations and spanning eight decades. We counted the apparent growth lines, microsampled along growth contours and calibrated Δ14C values to reference coral series. We fit von Bertalanffy growth function (VBGF) models to the results, producing a range of age estimates for each turtle. We find Hawaii hawksbills deposit eight growth lines annually (range 5–14), with model ensembles producing a somatic growth parameter (k) of 0.13 (range 0.1–0.2) and first breeding at 29 years (range 23–36). Recent bomb radiocarbon values also suggest declining trophic status. Together, our results may reflect long-term changes in the benthic community structure of Hawaii reefs, and possibly shed light on the critical population status for Hawaii hawksbills. PMID:26740617

Current advancements and challenges in soil-root interactions modelling

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Huber, Katrin; Abesha, Betiglu; Meunier, Felicien; Leitner, Daniel; Roose, Tiina; Javaux, Mathieu; Vanderborght, Jan; Vereecken, Harry

2015-04-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Current Advancements and Challenges in Soil-Root Interactions Modelling

NASA Astrophysics Data System (ADS)

Schnepf, A.; Huber, K.; Abesha, B.; Meunier, F.; Leitner, D.; Roose, T.; Javaux, M.; Vanderborght, J.; Vereecken, H.

2014-12-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

New solution to the problem of the tension between the high-redshift and low-redshift measurements of the Hubble constant

NASA Astrophysics Data System (ADS)

Bolejko, Krzysztof

2018-01-01

During my talk I will present results suggesting that the phenomenon of emerging spatial curvature could resolve the conflict between Planck's (high-redshift) and Riess et al. (low-redshift) measurements of the Hubble constant. The phenomenon of emerging spatial curvature is absent in the Standard Cosmological Model, which has a flat and fixed spatial curvature (small perturbations are considered in the Standard Cosmological Model but their global average vanishes, leading to spatial flatness at all times).In my talk I will show that with the nonlinear growth of cosmic structures the global average deviates from zero. As a result, the spatial curvature evolves from spatial flatness of the early universe to a negatively curved universe at the present day, with Omega_K ~ 0.1. Consequently, the present day expansion rate, as measured by the Hubble constant, is a few percent higher compared to the high-redshift constraints. This provides an explanation why there is a tension between high-redshift (Planck) and low-redshift (Riess et al.) measurements of the Hubble constant. In the presence of emerging spatial curvature these two measurements should in fact be different: high redshift measurements should be slightly lower than the Hubble constant inferred from the low-redshift data.The presentation will be based on the results described in arXiv:1707.01800 and arXiv:1708.09143 (which discuss the phenomenon of emerging spatial curvature) and on a paper that is still work in progress but is expected to be posted on arxiv by the AAS meeting (this paper uses mock low-redshift data to show that starting from the Planck's cosmological models (in the early universe) but with the emerging spatial curvature taken into account, the low-redshift Hubble constant should be 72.4 km/s/Mpc.

Heterogeneous water supply affects growth and benefits of clonal integration between co-existing invasive and native Hydrocotyle species.

PubMed

Wang, Yong-Jian; Bai, Yun-Fei; Zeng, Shi-Qi; Yao, Bin; Wang, Wen; Luo, Fang-Li

2016-07-21

Spatial patchiness and temporal variability in water availability are common in nature under global climate change, which can remarkably influence adaptive responses of clonal plants, i.e. clonal integration (translocating resources between connected ramets). However, little is known about the effects of spatial patchiness and temporal heterogeneity in water on growth and clonal integration between congeneric invasive and native Hydrocotyle species. In a greenhouse experiment, we subjected severed or no severed (intact) fragments of Hydrocotyle vulgaris, a highly invasive species in China, and its co-existing, native congener H. sibthorpioides to different spatial patchiness (homogeneous and patchy) and temporal interval (low and high interval) in water supply. Clonal integration had significant positive effects on growth of both species. In the homogeneous water conditions, clonal integration greatly improved the growth in fragments of both species under low interval in water. However, in the patchy water conditions, clonal integration significantly increased growth in both ramets and fragments of H. vulgaris under high interval in water. Therefore, spatial patchiness and temporal interval in water altered the effects of clonal integration of both species, especially for H. vulgaris. The adaptation of H. vulgaris might lead to invasive growth and potential spread under the global water variability.

A cellular automata model for avascular solid tumor growth under the effect of therapy

NASA Astrophysics Data System (ADS)

Reis, E. A.; Santos, L. B. L.; Pinho, S. T. R.

2009-04-01

Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.

Incorporating landscape fuel treatment modeling into the Forest Vegetation Simulator

Treesearch

Robert C. Seli; Alan A. Ager; Nicholas L. Crookston; Mark A. Finney; Berni Bahro; James K. Agee; Charles W. McHugh

2008-01-01

A simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of several command line programs linked together: (1) FVS with the Parallel Processor (PPE) and Fire and Fuels (FFE)...

A model for managing edge effects in harvest scheduling using spatial optimization

Treesearch

Kai L. Ross; Sándor F. Tóth

2016-01-01

Actively managed forest stands can create new forest edges. If left unchecked over time and across space, forest operations such as clear-cuts can create complex networks of forest edges. Newly created edges alter the landscape and can affect many environmental factors. These altered environmental factors have a variety of impacts on forest growth and structure and can...

Exploring spatial and temporal variations of cadmium concentrations in pacific oysters from british columbia.

PubMed

Feng, Cindy Xin; Cao, Jiguo; Bendell, Leah

2011-09-01

Oysters from the Pacific Northwest coast of British Columbia, Canada, contain high levels of cadmium, in some cases exceeding some international food safety guidelines. A primary goal of this article is the investigation of the spatial and temporal variation in cadmium concentrations for oysters sampled from coastal British Columbia. Such information is important so that recommendations can be made as to where and when oysters can be cultured such that accumulation of cadmium within these oysters is minimized. Some modern statistical methods are applied to achieve this goal, including monotone spline smoothing, functional principal component analysis, and semi-parametric additive modeling. Oyster growth rates are estimated as the first derivatives of the monotone smoothing growth curves. Some important patterns in cadmium accumulation by oysters are observed. For example, most inland regions tend to have a higher level of cadmium concentration than most coastal regions, so more caution needs to be taken for shellfish aquaculture practices occurring in the inland regions. The semi-parametric additive modeling shows that oyster cadmium concentration decreases with oyster length, and oysters sampled at 7 m have higher average cadmium concentration than those sampled at 1 m. © 2010, The International Biometric Society.

Regulation of planar growth by the Arabidopsis AGC protein kinase UNICORN.

PubMed

Enugutti, Balaji; Kirchhelle, Charlotte; Oelschner, Maxi; Torres Ruiz, Ramón Angel; Schliebner, Ivo; Leister, Dario; Schneitz, Kay

2012-09-11

The spatial coordination of growth is of central importance for the regulation of plant tissue architecture. Individual layers, such as the epidermis, are clonally propagated and structurally maintained by symmetric cell divisions that are oriented along the plane of the layer. The developmental control of this process is poorly understood. The simple cellular basis and sheet-like structure of Arabidopsis integuments make them an attractive model system to address planar growth. Here we report on the characterization of the Arabidopsis UNICORN (UCN) gene. Analysis of ucn integuments reveals localized distortion of planar growth, eventually resulting in an ectopic multicellular protrusion. In addition, ucn mutants exhibit ectopic growth in filaments and petals, as well as aberrant embryogenesis. We further show that UCN encodes an active AGC VIII kinase. Genetic, biochemical, and cell biological data suggest that UCN suppresses ectopic growth in integuments by directly repressing the KANADI transcription factor ABERRANT TESTA SHAPE. Our findings indicate that UCN represents a unique plant growth regulator that maintains planar growth of integuments by repressing a developmental regulator involved in the control of early integument growth and polarity.

Landscape Level Carbon and Water Balances and Agricultural Production in Mountainous Terrain of the Haean Basin, South Korea

NASA Astrophysics Data System (ADS)

Lee, B.; Geyer, R.; Seo, B.; Lindner, S.; Walther, G.; Tenhunen, J. D.

2009-12-01

The process-based spatial simulation model PIXGRO was used to estimate gross primary production, ecosystem respiration, net ecosystem CO2 exchange and water use by forest and crop fields of Haean Basin, South Korea at landscape scale. Simulations are run for individual years from early spring to late fall, providing estimates for dry land crops and rice paddies with respect to carbon gain, biomass and leaf area development, allocation of photoproducts to the belowground ecosystem compartment, and harvest yields. In the case of deciduous oak forests, gas exchange is estimated, but spatial simulation of growth over the single annual cycles is not included. Spatial parameterization of the model is derived for forest LAI based on remote sensing, for forest and cropland fluxes via eddy covariance and chamber studies, for soil characteristics by generalization from spatial surveys, for climate drivers by generalizing observations at ca. 20 monitoring stations distributed throughout the basin and along the elevation gradient from 500 to 1000 m, and for incident radiation via modelling of the radiation components in complex terrain. Validation of the model is being carried out at point scale based on comparison of model output at selected locations with observations as well as with known trends in ecosystem response documented in the literature. The resulting modelling tool is useful for estimation of ecosystem services at landscape scale, first expressed as kg ha-1 crop yield, but via future cooperative studies also in terms of monetary gain to individual farms and farming cooperatives applying particular management strategies.

Interference competition and invasion: spatial structure, novel weapons and resistance zones.

PubMed

Allstadt, Andrew; Caraco, Thomas; Molnár, F; Korniss, G

2012-08-07

Certain invasive plants may rely on interference mechanisms (e.g., allelopathy) to gain competitive superiority over native species. But expending resources on interference presumably exacts a cost in another life-history trait, so that the significance of interference competition for invasion ecology remains uncertain. We model ecological invasion when combined effects of preemptive and interference competition govern interactions at the neighborhood scale. We consider three cases. Under "novel weapons," only the initially rare invader exercises interference. For "resistance zones" only the resident species interferes, and finally we take both species as interference competitors. Interference increases the other species' mortality, opening space for colonization. However, a species exercising greater interference has reduced propagation, which can hinder its colonization of open sites. Interference never enhances a rare invader's growth in the homogeneously mixing approximation to our model. But interference can significantly increase an invader's competitiveness, and its growth when rare, if interactions are structured spatially. That is, interference can increase an invader's success when colonization of open sites depends on local, rather than global, species densities. In contrast, interference enhances the common, resident species' resistance to invasion independently of spatial structure, unless the propagation-cost is too great. The particular combination of propagation and interference producing the strongest biotic resistance in a resident species depends on the shape of the tradeoff between the two traits. Increases in background mortality (i.e., mortality not due to interference) always reduce the effectiveness of interference competition. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatiotemporal variation in survival rates: implications for population dynamics of yellow-bellied marmots.

PubMed

Ozgul, Arpat; Armitage, Kenneth B; Blumstein, Daniel T; Oli, Madan K

2006-04-01

Spatiotemporal variation in age-specific survival rates can profoundly influence population dynamics, but few studies of vertebrates have thoroughly investigated both spatial and temporal variability in age-specific survival rates. We used 28 years (1976-2003) of capture-mark-recapture (CMR) data from 17 locations to parameterize an age-structured Cormack-Jolly-Seber model, and investigated spatial and temporal variation in age-specific annual survival rates of yellow-bellied marmots (Marmota flaviventris). Survival rates varied both spatially and temporally, with survival of younger animals exhibiting the highest degree of variation. Juvenile survival rates varied from 0.52 +/- 0.05 to 0.78 +/- 0.10 among sites and from 0.15 +/- 0.14 to 0.89 +/- 0.06 over time. Adult survival rates varied from 0.62 +/- 0.09 to 0.80 +/- 0.03 among sites, but did not vary significantly over time. We used reverse-time CMR models to estimate the realized population growth rate (lamda), and to investigate the influence of the observed variation in age-specific survival rates on lamda. The realized growth rate of the population closely covaried with, and was significantly influenced by, spatiotemporal variation in juvenile survival rate. High variability in juvenile survival rates over space and time clearly influenced the dynamics of our study population and is also likely to be an important determinant of the spatiotemporal variation in the population dynamics of other mammals with similar life history characteristics.

Integrating global socio-economic influences into a regional land use change model for China

NASA Astrophysics Data System (ADS)

Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li

2014-03-01

With rapid economic development and urbanization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model (GLOBFOOD) and regional spatial allocation model (CLUE). The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge about the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socioeconomic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Increase of flood exposure on the Spanish Mediterranean coast over the last decades. The influence of spatial planning.

NASA Astrophysics Data System (ADS)

Lopez-Martinez, Francisco; Perez-Morales, Alfredo; Gil-Guirado, Salvador; Illan-Fernandez, Emilio Jose

2017-04-01

Since the 1960's, the Spanish Mediterranean coastal area is one of the main tourist destinations in the world and one of the highest rates of population, building and economic growth of Spain. Despite this growth have involved a lot of preventive flood management measures, especially structural measures (dams, water derivations, channelling, etc…), the area has registered an increase in the intensity, frequency and economic losses related to floods in recent decades. However, according to climatic records, this trend is more related to an exposure multiplication derived from economic growth than with the increase of extreme rainfall events produced by climate change. Within this framework it is interesting to evaluate how local governments (institution responsible for the process of spatial planning) have influence on exposure through allowing the construction in flood-prone areas. In this regard, this study quantifies the evolution of number of housing in flood-prone areas according to the cadastral information and the hydrological modelling data for the return periods of 10, 50, 100 and 500 years, respectively. Results highlight an increase in the number of building in flood-prone areas over the years. This increase in physical and economic exposure without any non-structural risk mitigation measure is one of the main factors for flood events. Therefore, results report that local governments did not consider the floodable areas into spatial planning and have made future scenarios characterized by an increase in the number of floods and their consequential damages.

Application of LiDAR to hydrologic flux estimation in Australian eucalypt forests (Invited)

NASA Astrophysics Data System (ADS)

Lane, P. N.; Mitchell, P. J.; Jaskierniak, D.; Hawthorne, S. N.; Griebel, A.

2013-12-01

The potential of LiDAR in ecohydrology is significant as characterising catchment vegetation is crucial to accurate estimation of evapotranspiration (ET). While this may be done at large scales for model parameterisation, stand-scale applications are equally appropriate where traditional methods of measurement of LAI or sapwood areas are time consuming and reliant on assumptions of representative sampling. This is particularly challenging in mountain forests where aspect, soil properties and energy budgets can vary significantly, reflected in the vegetation or where there are changes in the spatial distribution of structural attributes following disturbance. Recent research has investigated the spatial distribution of ET in a eucalypt forest in SE Australia using plot-scale sapflow, interception and forest floor ET measurements. LiDAR was used scale up these measurements. LiDAR (0.16 m scanner footprint) canopy indices were correlated via stepwise regression with 4 water use scalars: basal area (BA), sapwood area (SA), leaf area index (LAI) and canopy coverage (C), with Hmed, Hmean, H80, H95 the best predictors. Combining these indices with empirical relationships between SA and BA, and SA and transpiration (T), and inventory plot 'ground truthing' transpiration was estimated across the 1.3 km2 catchment. Interception was scaled via the Gash model with LiDAR derived inputs. The up-scaling showed a significant variability in the spatial distribution of ET, related to the distribution of SA. The use of LiDAR meant scaling could be achieved at an appropriate spatial scale (20 x 20 m) to the measurements. The second example is the use of airborne LiDAR in developing growth forest models for hydrologic modeling. LiDAR indices were used to stratify multilayered forests using mixed-effect models with a wide range of theoretical distribution functions. When combined with historical plot-scale inventory data we show demonstrated improved growth modeling over traditional inventory methods.These models can be used to parameterize hydrologic models to explore disturbance and age-related ET changes, and develop spatial-temporal maps of ET based on accurate representation of sapwood areas in complex terrain. The third example involves analyses of stand growth and long term streamflow response to thinning treatments in eucalyptus regnans forests. These forests have a strong age-streamflow relationship that can lead to streamflow declines as disturbed stands regrow. A set of thinning treatments in small experimental catchments (uniform, strip and understorey removal) were implemented in 1978-1982. The streamflow analysis supported early findings that flows increase and then relaxed, but also detected a flow decline below expected undisturbed levels for most catchments. Airborne LiDAR was used to analyse the structural recovery of treated stands, estimate LAI and canopy coverage via gap-fraction analysis, and scale ET measurements. The LiDAR data revealed the association of treatment type and regrowth and demonstrated that despite a net reduction in overstorey stem density, stand LAI had recovered and may explain the flow response. Finally, new terrestrial LiDAR instruments are being used in conjunction with eddy-covariance flux tower and sapflow measurement to measure fine temporal scale carbon-water dynamics. These instruments can be combined with airborne derived data to produce 3 dimensional canopy profile for linkage with ET processes.

Correlates of individual, and age-related, differences in short-term learning.

PubMed

Zhang, Zhiyong; Davis, Hasker P; Salthouse, Timothy A; Tucker-Drob, Elliot M

2007-07-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability.

In Situ Visualization of the Growth and Fluctuations of Nanoparticle Superlattice in Liquids

NASA Astrophysics Data System (ADS)

Ou, Zihao; Shen, Bonan; Chen, Qian

We use liquid phase transmission electron microscopy to image and understand the crystal growth front and interfacial fluctuation of a nanoparticle superlattice. With single particle resolution and hundreds of nanoscale building blocks in view, we are able to identify the interface between ordered lattice and disordered structure and visualize the kinetics of single building block attachment at the lattice growth front. The spatial interfacial fluctuation profiles support the capillary wave theory, from which we derive a surface stiffness value consistent with scaling analysis. Our experiments demonstrate the potential of extending model study on collective systems to nanoscale with single particle resolution and testing fundamental theories of condensed matter at a length scale linking atoms and micron-sized colloids.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Intra-specific competition (crowding) of giant sequoias (Sequoiadendron giganteum)

USGS Publications Warehouse

Stohlgren, Thomas J.

1993-01-01

Information on the size and location of 1916 giant sequoias (Sequoiadendron giganteum (Lindl.) Buchholz) in Muir Grove, Sequoia National Park, in the southern Sierra Nevada of California was used to assess intra-specific crowding. Study objectives were to: (1) determine which parameters associated with intra-specific competition (i.e. size and distance to nearest neighbor, crowding/root system area overlap, or number of neighbors) might be important in spatial pattern development, growth, and survivorship of established giant sequoias; (2) quantify the level of intra-specific crowding of different sized live sequoias based on a model of estimated overlapping root system areas (i.e. an index of relative crowding); (3) compare the level of intra-specific crowding of similarly sized live and dead giant sequoias (less than 30 cm diameter at breast height (dbh) at the time of inventory (1969). Mean distances to the nearest live giant sequoia neighbor were not significantly different (at α = 0.05) for live and dead sequoias in similar size classes. A zone of influence competition model (i.e. index of crowding) based on horizontal overlap of estimated root system areas was developed for 1753 live sequoias. The model, based only on the spatial arrangement of live sequoias, was then tested on dead sequoias of less than 30 cm dbh (n = 163 trees; also recorded in 1969). The dead sequoias had a significantly higher crowding index than 561 live trees of similar diameter. Results showed that dead sequoias of less than 16.6 cm dbh had a significantly greater mean number of live neighbors and mean crowding index than live sequoias of similar size. Intra-specific crowding may be an important mechanism in determining the spatial distribution of sequoias in old-growth forests.

Identifying suitable land for alternative crops in a drying climate: soil salinity, texture and topographic conditions for the growth of old man saltbush (Atriplex nummularia)

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Barrett-Lennard, E. G.; Altman, M.

2011-12-01

Experiments conducted under controlled conditions clearly show that the growth and survival of plants on saltland is affected by both the levels of salinity and waterlogging (or depth to water-table) in the soil. Different plant species thrive under varying combinations of these growth constraints. However in natural settings, short distance spatial variability in soil properties and subtle topographic features often complicate the definition of saline and soil hydrological conditions; additional factors may also overprint the trends identified under controlled conditions, making it difficult to define the physical settings where planting is economically viable. We investigated the establishment and growth of old man saltbush (Atriplex nummularia) in relation to variable soil-landscape conditions across an experimental site in southwestern Australia where the combination of high salinity and occasional seasonal waterlogging ruled out the growth of traditional crops and pastures. Saltbush can be critical supplemental feed in the dry season, providing essential nutrients for sheep in combination with sufficient water and dry feed (hay). We applied a range of modeling approaches including classification and regression trees and generalized linear models to statistically characterize these plant-environment relationships, and extend them spatially using full cover raster covariate datasets. Plant deaths could be consistently predicted (97% correct classification of independent dataset) using a combination of topographic variables, salinity, soil mineralogical information, and depth to the water table. Plant growth patterns were more difficult to predict, particularly after several years of grazing, however variation in plant volume was well-explained with a linear model (r2 = 0.6, P < 0.0001). All types of environmental data were required, supporting the starting hypothesis that saltland pasture success is driven by water movement in the landscape. The final selected covariates for modeling were a digital elevation model and derivatives, soil mineralogy, competitors for water (adjacent trees) and soil salinity (measured with an EM38). Our exploration of strengths and weaknesses of extrapolating simple relationships determined under controlled conditions to the field vindicates the importance of both approaches. Landholders often view the idea of the productive use of saltland with skepticism. The challenge is to use the combined datasets from glasshouse and field experiments to develop information guidelines for landholders that maximize the chances of revegetation success. Water availability, waterlogging, quality of the shallow groundwater, and secondary salinity are dominant processes that impact on agriculture in southwestern Australia. Improving our understanding of their interactions and effect on productivity will help adapt agricultural management to changing environmental conditions in the future.

The spatial-temporal characteristics of type I collagen-based extracellular matrix.

PubMed

Jones, Christopher Allen Rucksack; Liang, Long; Lin, Daniel; Jiao, Yang; Sun, Bo

2014-11-28

Type I collagen abounds in mammalian extracellular matrix (ECM) and is crucial to many biophysical processes. While previous studies have mostly focused on bulk averaged properties, here we provide a comprehensive and quantitative spatial-temporal characterization of the microstructure of type I collagen-based ECM as the gelation temperature varies. The structural characteristics including the density and nematic correlation functions are obtained by analyzing confocal images of collagen gels prepared at a wide range of gelation temperatures (from 16 °C to 36 °C). As temperature increases, the gel microstructure varies from a "bundled" network with strong orientational correlation between the fibers to an isotropic homogeneous network with no significant orientational correlation, as manifested by the decaying of length scales in the correlation functions. We develop a kinetic Monte-Carlo collagen growth model to better understand how ECM microstructure depends on various environmental or kinetic factors. We show that the nucleation rate, growth rate, and an effective hydrodynamic alignment of collagen fibers fully determines the spatiotemporal fluctuations of the density and orientational order of collagen gel microstructure. Also the temperature dependence of the growth rate and nucleation rate follow the prediction of classical nucleation theory.

Epidemiological, evolutionary and co-evolutionary implications of context-dependent parasitism

PubMed Central

Vale, Pedro F.; Wilson, Alastair J.; Best, Alex; Boots, Mike; Little, Tom J.

2013-01-01

Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster growing parasites do not appear to cause more damage and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa we show how easily an interaction can shift from a severe interaction, i.e. when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modelling pathogen evolution and disease spread under different levels of infection severity, and find that environmental shifts that promote tolerance ultimately result in populations harbouring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus our results suggest two mechanisms that could underlie co-evolutionary hot- and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection. PMID:21460572

Epidemiological, evolutionary, and coevolutionary implications of context-dependent parasitism.

PubMed

Vale, Pedro F; Wilson, Alastair J; Best, Alex; Boots, Mike; Little, Tom J

2011-04-01

Abstract Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster-growing parasites do not appear to cause more damage, and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa, we show how easily an interaction can shift from a severe interaction, that is, when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modeling pathogen evolution and disease spread under different levels of infection severity and found that environmental shifts that promote tolerance ultimately result in populations harboring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus, our results suggest two mechanisms that could underlie coevolutionary hotspots and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection.

Simulating imaging spectrometer data of a mixed old-growth forest: A parameterization of a 3D radiative transfer model based on airborne and terrestrial laser scanning

NASA Astrophysics Data System (ADS)

Schneider, F. D.; Leiterer, R.; Morsdorf, F.; Gastellu-Etchegorry, J.; Lauret, N.; Pfeifer, N.; Schaepman, M. E.

2013-12-01

Remote sensing offers unique potential to study forest ecosystems by providing spatially and temporally distributed information that can be linked with key biophysical and biochemical variables. The estimation of biochemical constituents of leaves from remotely sensed data is of high interest revealing insight on photosynthetic processes, plant health, plant functional types, and speciation. However, the scaling of observations at the canopy level to the leaf level or vice versa is not trivial due to the structural complexity of forests. Thus, a common solution for scaling spectral information is the use of physically-based radiative transfer models. The discrete anisotropic radiative transfer model (DART), being one of the most complete coupled canopy-atmosphere 3D radiative transfer models, was parameterized based on airborne and in-situ measurements. At-sensor radiances were simulated and compared with measurements from an airborne imaging spectrometer. The study was performed on the Laegern site, a temperate mixed forest characterized by steep slopes, a heterogeneous spectral background, and deciduous and coniferous trees at different development stages (dominated by beech trees; 47°28'42.0' N, 8°21'51.8' E, 682 m asl, Switzerland). It is one of the few studies conducted on an old-growth forest. Particularly the 3D modeling of the complex canopy architecture is crucial to model the interaction of photons with the vegetation canopy and its background. Thus, we developed two forest reconstruction approaches: 1) based on a voxel grid, and 2) based on individual tree detection. Both methods are transferable to various forest ecosystems and applicable at scales between plot and landscape. Our results show that the newly developed voxel grid approach is favorable over a parameterization based on individual trees. In comparison to the actual imaging spectrometer data, the simulated images exhibit very similar spatial patterns, whereas absolute radiance values are partially differing depending on the respective wavelength. We conclude that our proposed method provides a representation of the 3D radiative regime within old-growth forests that is suitable for simulating most spectral and spatial features of imaging spectrometer data. It indicates the potential of simulating future Earth observation missions, such as ESA's Sentinel-2. However, the high spectral variability of leaf optical properties among species has to be addressed in future radiative transfer modeling. The results further reveal that research emphasis has to be put on the accurate parameterization of small-scale structures, such as the clumping of needles into shoots or the distribution of leaf angles.

Charecterisation and Modelling Urbanisation Pattern in Sillicon Valley of India

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Urbanisation and Urban sprawl has led to environmental problems and large losses of arable land in India. In this study, we characterise pattern of urban growth and model urban sprawl by means of a combination of remote sensing, geographical information system, spatial metrics and CA based modelling. This analysis uses time-series data to explore and derive the potential political-socio-economic- land based driving forces behind urbanisation and urban sprawl, and spatial models in different scenarios to explore the spatio-temporal interactions and development. The study area applied is Greater Bangalore, for the period from 1973 to 2015. Further water bodies depletion, vegetation depletion, tree cover were also analysed to obtain specific region based results effecting global climate and regional balance. Agents were integrated successfully into modelling aspects to understand and foresee the landscape pattern change in urban morphology. The results reveal built-up paved surfaces has expanded towards the outskirts and have expanded into the buffer regions around the city. Population growth, economic, industrial developments in the city core and transportation development are still the main causes of urban sprawl in the region. Agent based model are considered to be to the traditional models. Agent Based modelling approach as seen in this paper clearly shown its effectiveness in capturing the micro dynamics and influence in its neighbourhood mapping. Greenhouse gas emission inventory has shown important aspects such as domestic sector to be one of the major impact categories in the region. Further tree cover reduced drastically and is evident from the statistics and determines that if city is in verge of creating a chaos in terms of human health and desertification. Study concludes that integration of remote sensing, GIS, and agent based modelling offers an excellent opportunity to explore the spatio-temporal variation and visulaisation of sprawling metropolitan region. This study give a complete overview of urbanisation and effects being caused due to urban sprawl in the region and help planners and city managers in understanding the future pockets and scenarios of urban growth.

A Phase Field Study of the Effect of Microstructure Grain Size Heterogeneity on Grain Growth

NASA Astrophysics Data System (ADS)

Crist, David J. D.

Recent studies conducted with sharp-interface models suggest a link between the spatial distribution of grain size variance and average grain growth rate. This relationship and its effect on grain growth rate was examined using the diffuse-interface Phase Field Method on a series of microstructures with different degrees of grain size gradation. Results from this work indicate that the average grain growth rate has a positive correlation with the average grain size dispersion for phase field simulations, confirming previous observations. It is also shown that the grain growth rate in microstructures with skewed grain size distributions is better measured through the change in the volume-weighted average grain size than statistical mean grain size. This material is based upon work supported by the National Science Foundation under Grant No. 1334283. The NSF project title is "DMREF: Real Time Control of Grain Growth in Metals" and was awarded by the Civil, Mechanical and Manufacturing Innovation division under the Designing Materials to Revolutionize and Engineer our Future (DMREF) program.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Bryan A.; Rougier, Esteban; O’Malley, Daniel

We use simulation data from a high delity Finite-Discrete Element Model to build an e cient Machine Learning (ML) approach to predict fracture growth and coalescence. Our goal is for the ML approach to be used as an emulator in place of the computationally intensive high delity models in an uncertainty quanti cation framework where thousands of forward runs are required. The failure of materials with various fracture con gurations (size, orientation and the number of initial cracks) are explored and used as data to train our ML model. This novel approach has shown promise in predicting spatial (path tomore » failure) and temporal (time to failure) aspects of brittle material failure. Predictions of where dominant fracture paths formed within a material were ~85% accurate and the time of material failure deviated from the actual failure time by an average of ~16%. Additionally, the ML model achieves a reduction in computational cost by multiple orders of magnitude.« less

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

DOE PAGES

Moore, Bryan A.; Rougier, Esteban; O’Malley, Daniel; ...

2018-02-22

We use simulation data from a high delity Finite-Discrete Element Model to build an e cient Machine Learning (ML) approach to predict fracture growth and coalescence. Our goal is for the ML approach to be used as an emulator in place of the computationally intensive high delity models in an uncertainty quanti cation framework where thousands of forward runs are required. The failure of materials with various fracture con gurations (size, orientation and the number of initial cracks) are explored and used as data to train our ML model. This novel approach has shown promise in predicting spatial (path tomore » failure) and temporal (time to failure) aspects of brittle material failure. Predictions of where dominant fracture paths formed within a material were ~85% accurate and the time of material failure deviated from the actual failure time by an average of ~16%. Additionally, the ML model achieves a reduction in computational cost by multiple orders of magnitude.« less

Impact of spatial organization on a novel auxotrophic interaction among soil microbes

DOE PAGES

Jiang, Xue; ZerfaB, Christian; Feng, Song; ...

2018-03-23

Here, a key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species–species and species–environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indicamore » under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.« less

Impact of spatial organization on a novel auxotrophic interaction among soil microbes.

PubMed

Jiang, Xue; Zerfaß, Christian; Feng, Song; Eichmann, Ruth; Asally, Munehiro; Schäfer, Patrick; Soyer, Orkun S

2018-06-01

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species-species and species-environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.

Impact of spatial organization on a novel auxotrophic interaction among soil microbes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Xue; ZerfaB, Christian; Feng, Song

Here, a key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species–species and species–environment interactions in spatially organized environments requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a defined system to study the metabolic interactions in a spatial context among the plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indicamore » under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant seed treatments and for vertical farming under defined conditions.« less

Formation of natural gas hydrates in marine sediments. Gas hydrate growth and stability conditioned by host sediment properties

USGS Publications Warehouse

Clennell, M.B.; Henry, P.; Hovland, M.; Booth, J.S.; Winters, W.J.; Thomas, M.

2000-01-01

The stability conditions of submarine gas hydrates (methane clathrates) are largely dictated by pressure, temperature, gas composition, and pore water salinity. However, the physical properties and surface chemistry of the host sediments also affect the thermodynamic state, growth kinetics, spatial distributions, and growth forms of clathrates. Our model presumes that gas hydrate behaves in a way analogous to ice in the pores of a freezing soil, where capillary forces influence the energy balance. Hydrate growth is inhibited within fine-grained sediments because of the excess internal phase pressure of small crystals with high surface curvature that coexist with liquid water in small pores. Therefore, the base of gas hydrate stability in a sequence of fine sediments is predicted by our model to occur at a lower temperature, and so nearer to the seabed than would be calculated from bulk thermodynamic equilibrium. The growth forms commonly observed in hydrate samples recovered from marine sediments (nodules, sheets, and lenses in muds; cements in sand and ash layers) can be explained by a requirement to minimize the excess of mechanical and surface energy in the system.

Simulation of Bacillus subtilis biofilm growth on agar plate by diffusion-reaction based continuum model

NASA Astrophysics Data System (ADS)

Zhang, Xianlong; Wang, Xiaoling; Nie, Kai; Li, Mingpeng; Sun, Qingping

2016-08-01

Various species of bacteria form highly organized spatially-structured aggregates known as biofilms. To understand how microenvironments impact biofilm growth dynamics, we propose a diffusion-reaction continuum model to simulate the formation of Bacillus subtilis biofilm on an agar plate. The extended finite element method combined with level set method are employed to perform the simulation, numerical results show the quantitative relationship between colony morphologies and nutrient depletion over time. Considering that the production of polysaccharide in wild-type cells may enhance biofilm spreading on the agar plate, we inoculate mutant colony incapable of producing polysaccharide to verify our results. Predictions of the glutamate source biofilm’s shape parameters agree with the experimental mutant colony better than that of glycerol source biofilm, suggesting that glutamate is rate limiting nutrient for Bacillus subtilis biofilm growth on agar plate, and the diffusion-limited is a better description to the experiment. In addition, we find that the diffusion time scale is of the same magnitude as growth process, and the common-employed quasi-steady approximation is not applicable here.

Simulation of Bacillus subtilis biofilm growth on agar plate by diffusion-reaction based continuum model.

PubMed

Zhang, Xianlong; Wang, Xiaoling; Nie, Kai; Li, Mingpeng; Sun, Qingping

2016-07-19

Various species of bacteria form highly organized spatially-structured aggregates known as biofilms. To understand how microenvironments impact biofilm growth dynamics, we propose a diffusion-reaction continuum model to simulate the formation of Bacillus subtilis biofilm on an agar plate. The extended finite element method combined with level set method are employed to perform the simulation, numerical results show the quantitative relationship between colony morphologies and nutrient depletion over time. Considering that the production of polysaccharide in wild-type cells may enhance biofilm spreading on the agar plate, we inoculate mutant colony incapable of producing polysaccharide to verify our results. Predictions of the glutamate source biofilm's shape parameters agree with the experimental mutant colony better than that of glycerol source biofilm, suggesting that glutamate is rate limiting nutrient for Bacillus subtilis biofilm growth on agar plate, and the diffusion-limited is a better description to the experiment. In addition, we find that the diffusion time scale is of the same magnitude as growth process, and the common-employed quasi-steady approximation is not applicable here.

Bacterial finite-size effects for population expansion under flow

NASA Astrophysics Data System (ADS)

Toschi, Federico; Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc

2016-11-01

For organisms living in a liquid ecosystem, flow and flow gradients have a dual role as they transport nutrient while, at the same time, dispersing the individuals. In absence of flow and under homogeneous conditions, the growth of a population towards an empty region is usually described by a reaction-diffusion equation. The effect of fluid flow is not yet well understood and the interplay between transport of individuals and growth opens a wide scenario of possible behaviors. In this work, we study experimentally the dynamics of non-motile E. coli bacteria colonies spreading inside rectangular channels, in PDMS microfluidic devices. By use of a fluorescent microscope we analyze the dynamics of the population density subjected to different co- and counter-flow conditions and shear rates. A simple model incorporating growth, dispersion and drift of finite size beads is able to explain the experimental findings. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) may have to be supplemented with bacterial finite-size effects in order to be able to accurately reproduce experimental results for population spatial growth.

Divergence in Patterns of Leaf Growth Polarity Is Associated with the Expression Divergence of miR396.

PubMed

Das Gupta, Mainak; Nath, Utpal

2015-10-01

Lateral appendages often show allometric growth with a specific growth polarity along the proximo-distal axis. Studies on leaf growth in model plants have identified a basipetal growth direction with the highest growth rate at the proximal end and progressively lower rates toward the distal end. Although the molecular mechanisms governing such a growth pattern have been studied recently, variation in leaf growth polarity and, therefore, its evolutionary origin remain unknown. By surveying 75 eudicot species, here we report that leaf growth polarity is divergent. Leaf growth in the proximo-distal axis is polar, with more growth arising from either the proximal or the distal end; dispersed with no apparent polarity; or bidirectional, with more growth contributed by the central region and less growth at either end. We further demonstrate that the expression gradient of the miR396-GROWTH-REGULATING FACTOR module strongly correlates with the polarity of leaf growth. Altering the endogenous pattern of miR396 expression in transgenic Arabidopsis thaliana leaves only partially modified the spatial pattern of cell expansion, suggesting that the diverse growth polarities might have evolved via concerted changes in multiple gene regulatory networks. © 2015 American Society of Plant Biologists. All rights reserved.

Diatom-sedimentation feedback generates a self-organized geomorphic landscape on intertidal mudflats (Invited)

NASA Astrophysics Data System (ADS)

van de Koppel, J.; Weerman, E.; Herman, P.

2010-12-01

During spring, intertidal flats can exhibit strikingly regular spatial patterns of diatom-covered hummocks alternating with almost bare, water-filled hollows. We hypothesize that 1) the formation of this geomorphic landscape is caused by a strong interaction between benthic diatoms and sediment dynamics, inducing spatial self-organization, and 2) that self-organization affects ecosystem functioning by increasing the net average sedimentation on the tidal flat. We present a combined empirical and mathematical study to test the first hypothesis. We determined how the sediment erosion threshold varied with diatom cover and elevation. Our results were incorporated into a mathematical model to investigate whether the proposed mechanism could explain the formation of the observed patterns. Our mathematical model confirmed that the interaction between sedimentation, diatom growth and water redistribution could induce the formation of regular patterns on the intertidal mudflat. The model predicts that areas exhibiting spatially-self-organized patterns have increased sediment accretion and diatom biomass compared with areas lacking spatial patterns. We tested this prediction by following the sediment elevation during the season on both patterned and unpatterned parts of the mudflat. The results of our study confirmed our model prediction, as more sediment was found to accumulate in patterned parts of the mudflat, revealing how self-organization affected the functioning of mudflat ecosystems. Our study on intertidal mudflats provides a simple but clear-cut example of how the interaction between biological and geomorphological processes, through the process of self-organization, induces a self-organized geomorphic landscape.

Effects of the distant population density on spatial patterns of demographic dynamics

NASA Astrophysics Data System (ADS)

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Effects of the distant population density on spatial patterns of demographic dynamics.

PubMed

Tamura, Kohei; Masuda, Naoki

2017-08-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500  m ) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km.

Climate-driven endemic cholera is modulated by human mobility in a megacity

NASA Astrophysics Data System (ADS)

Perez-Saez, Javier; King, Aaron A.; Rinaldo, Andrea; Yunus, Mohammad; Faruque, Abu S. G.; Pascual, Mercedes

2017-10-01

Although a differential sensitivity of cholera dynamics to climate variability has been reported in the spatially heterogeneous megacity of Dhaka, Bangladesh, the specific patterns of spread of the resulting risk within the city remain unclear. We build on an established probabilistic spatial model to investigate the importance and role of human mobility in modulating spatial cholera transmission. Mobility fluxes were inferred using a straightforward and generalizable methodology that relies on mapping population density based on a high resolution urban footprint product, and a parameter-free human mobility model. In accordance with previous findings, we highlight the higher sensitivity to the El Niño Southern Oscillation (ENSO) in the highly populated urban center than in the more rural periphery. More significantly, our results show that cholera risk is largely transmitted from the climate-sensitive core to the periphery of the city, with implications for the planning of control efforts. In addition, including human mobility improves the outbreak prediction performance of the model with an 11 month lead. The interplay between climatic and human mobility factors in cholera transmission is discussed from the perspective of the rapid growth of megacities across the developing world.

Spatial analysis of relative humidity during ungauged periods in a mountainous region

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Kim, Yeonjoo

2017-08-01

Although atmospheric humidity influences environmental and agricultural conditions, thereby influencing plant growth, human health, and air pollution, efforts to develop spatial maps of atmospheric humidity using statistical approaches have thus far been limited. This study therefore aims to develop statistical approaches for inferring the spatial distribution of relative humidity (RH) for a mountainous island, for which data are not uniformly available across the region. A multiple regression analysis based on various mathematical models was used to identify the optimal model for estimating monthly RH by incorporating not only temperature but also location and elevation. Based on the regression analysis, we extended the monthly RH data from weather stations to cover the ungauged periods when no RH observations were available. Then, two different types of station-based data, the observational data and the data extended via the regression model, were used to form grid-based data with a resolution of 100 m. The grid-based data that used the extended station-based data captured the increasing RH trend along an elevation gradient. Furthermore, annual RH values averaged over the regions were examined. Decreasing temporal trends were found in most cases, with magnitudes varying based on the season and region.

Effects of the distant population density on spatial patterns of demographic dynamics

PubMed Central

2017-01-01

Spatio-temporal patterns of population changes within and across countries have various implications. Different geographical, demographic and econo-societal factors seem to contribute to migratory decisions made by individual inhabitants. Focusing on internal (i.e. domestic) migration, we ask whether individuals may take into account the information on the population density in distant locations to make migratory decisions. We analyse population census data in Japan recorded with a high spatial resolution (i.e. cells of size 500×500 m) for the entirety of the country, and simulate demographic dynamics induced by the gravity model and its variants. We show that, in the census data, the population growth rate in a cell is positively correlated with the population density in nearby cells up to a distance of 20 km as well as that of the focal cell. The ordinary gravity model does not capture this empirical observation. We then show that the empirical observation is better accounted for by extensions of the gravity model such that individuals are assumed to perceive the attractiveness, approximated by the population density, of the source or destination cell of migration as the spatial average over a circle of radius ≈1 km. PMID:28878987

The development of wing shape in Lepidoptera: mitotic density, not orientation, is the primary determinant of shape.

PubMed

Nijhout, H Frederik; Cinderella, Margaret; Grunert, Laura W

2014-03-01

The wings of butterflies and moths develop from imaginal disks whose structure is always congruent with the final adult wing. It is therefore possible to map every point on the imaginal disk to a location on the adult wing throughout ontogeny. We studied the growth patterns of the wings of two distantly related species with very different adult wing shapes, Junonia coenia and Manduca sexta. The shape of the wing disks change throughout their growth phase in a species-specific pattern. We measured mitotic densities and mitotic orientation in successive stages of wing development approximately one cell division apart. Cell proliferation was spatially patterned, and the density of mitoses was highly correlated with local growth. Unlike other systems in which the direction of mitoses has been viewed as the primary determinant of directional growth, we found that in these two species the direction of growth was only weakly correlated with the orientation of mitoses. Directional growth appears to be imposed by a constantly changing spatial pattern of cell division coupled with a weak bias in the orientation of cell division. Because growth and cell division in imaginal disk require ecdysone and insulin signaling, the changing spatial pattern of cell division may due to a changing pattern of expression of receptors or downstream elements in the signaling pathways for one or both of these hormones. Evolution of wing shape comes about by changes in the progression of spatial patterns of cell division. © 2014 Wiley Periodicals, Inc.

The role of spatial dynamics in modulating metabolic interactions in biofilm development

NASA Astrophysics Data System (ADS)

Bocci, Federico; Lu, Mingyang; Suzuki, Yoko; Onuchic, Jose

Cell phenotypic expression is substantially affected by the presence of environmental stresses and cell-cell communication mechanisms. We study the metabolic interactions of the glutamate synthesis pathway to explain the oscillation of growth rate observed in a B. Subtilis colony. Previous modelling schemes had failed in fully reproducing quantitative experimental observations as they did not explicitly address neither the diffusion of small metabolites nor the spatial distribution of phenotypically distinct bacteria inside the colony. We introduce a continuous space-temporal framework to explain how biofilm development dynamics is influenced by the metabolic interplay between two bacterial phenotypes composing the interior and the peripheral layer of the biofilm. Growth oscillations endorse the preservation of a high level of nutrients in the interior through diffusion and colony expansion in the periphery altogether. Our findings point out that perturbations of environmental conditions can result in the interruption of the interplay between cell populations and advocate alternative approaches to biofilm control strategies.

Optimized growth and reorientation of anisotropic material based on evolution equations

NASA Astrophysics Data System (ADS)

Jantos, Dustin R.; Junker, Philipp; Hackl, Klaus

2018-07-01

Modern high-performance materials have inherent anisotropic elastic properties. The local material orientation can thus be considered to be an additional design variable for the topology optimization of structures containing such materials. In our previous work, we introduced a variational growth approach to topology optimization for isotropic, linear-elastic materials. We solved the optimization problem purely by application of Hamilton's principle. In this way, we were able to determine an evolution equation for the spatial distribution of density mass, which can be evaluated in an iterative process within a solitary finite element environment. We now add the local material orientation described by a set of three Euler angles as additional design variables into the three-dimensional model. This leads to three additional evolution equations that can be separately evaluated for each (material) point. Thus, no additional field unknown within the finite element approach is needed, and the evolution of the spatial distribution of density mass and the evolution of the Euler angles can be evaluated simultaneously.

Population stress: A spatiotemporal analysis of population change and land development at the county level in the contiguous United States, 2001-2011.

PubMed

Chi, Guangqing; Ho, Hung Chak

2018-01-01

The past century has witnessed rapidly increasing population-land conflicts due to exponential population growth and its many consequences. Although the measures of population-land conflicts are many, there lacks a model that appropriately considers both the social and physical contexts of population-land conflicts. In this study we introduce the concept of population stress , which identifies areas with populations growing faster than the lands available for sustainable development. Specifically, population stress areas are identified by comparing population growth and land development as measured by land developability in the contiguous United States from 2001 to 2011. Our approach is based on a combination of spatial multicriteria analysis, zonal statistics, and spatiotemporal modeling. We found that the population growth of a county is associated with the decrease of land developability, along with the spatial influences of surrounding counties. The Midwest and the traditional "Deep South" counties would have less population stress with future land development, whereas the Southeast Coast, Washington State, Northern Texas, and the Southwest would face more stress due to population growth that is faster than the loss of suitable lands for development. The factors contributing to population stress may differ from place to place. Our population stress concept is useful and innovative for understanding population stress due to land development and can be applied to other regions as well as global research. It can act as a basis towards developing coherent sustainable land use policies. Coordination among local governments and across different levels of governments in the twenty-first century is a must for effective land use planning.

Population Growth Types in India, 1961-71

ERIC Educational Resources Information Center

Chakravarti, A. K.

1976-01-01

An effective means of cartographic representation of India's population growth and its spatial characteristics is the focus of this paper. A population growth index and population growth types are discussed. (Author/ND)

Modeling mangrove biomass using remote sensing based age and growth estimates

NASA Astrophysics Data System (ADS)

Lagomasino, D.; Fatoyinbo, T. E.; Feliciano, E. A.; Lee, S. K.; Trettin, C.; Mangora, M.; Rahman, M.

2016-12-01

Mangroves are highly regarded coastal forests because of their ecosystem services and high carbon storage potential. In addition, these forests can develop rapidly in locations where congenial environmental conditions and sediment supply are available. Monitoring the growth and age of developing mangrove forests is crucial for sustainable management and estimating carbon stocks. Combining imagery from radar and optical satellites (e.g., TanDEM-X and Landsat), we can estimate young mangrove growth and age at regional and continental scales. We used TanDEM-X radar interferometry for modeling canopy height in 2013 and Landsat to measure land cover change from 1990 to 2013. Annual NDVI composites were determined for each calendar year between 1990 and 2013. New land areas gained from the transition of water to vegetation were determined by the differences in annual NDVI composites and the reference year 2013. The year of the greatest NDVI difference that met the threshold criteria was used as the initial tree height (0 m). Annual canopy height growth rates were estimated by the duration between land generation times and 2013 canopy height models derived from TanDEM-X and very-high resolution optical data. In this presentation, we compare growth rates and biomass accumulation in mangrove forests at four river deltas; the Zambezi (Mozambique), Rufiji (Tanzania), Ganges (Bangladesh), and Mekong (Vietnam). The spatial patterns of growth rates coincided with characteristic successional paradigms and stream morphology, where the maximum growth rates typically occurred along prograding creek banks. Initial comparisons between height-only and growth-age biomass indicate that the latter tend to overestimate biomass for younger forest stands of similar height. Both the vertical (e.g., canopy height) and horizontal (e.g., expansion) growth rates measured from remote sensing can garner important information regarding mangrove succession and primary productivity. Continued research will combine mangrove growth-age and biomass modeling in other mangrove ecosystems order to resolve the development patterns between different geomorphologies.

Correlation functions in first-order phase transitions

NASA Astrophysics Data System (ADS)

Garrido, V.; Crespo, D.

1997-09-01

Most of the physical properties of systems underlying first-order phase transitions can be obtained from the spatial correlation functions. In this paper, we obtain expressions that allow us to calculate all the correlation functions from the droplet size distribution. Nucleation and growth kinetics is considered, and exact solutions are obtained for the case of isotropic growth by using self-similarity properties. The calculation is performed by using the particle size distribution obtained by a recently developed model (populational Kolmogorov-Johnson-Mehl-Avrami model). Since this model is less restrictive than that used in previously existing theories, the result is that the correlation functions can be obtained for any dependence of the kinetic parameters. The validity of the method is tested by comparison with the exact correlation functions, which had been obtained in the available cases by the time-cone method. Finally, the correlation functions corresponding to the microstructure developed in partitioning transformations are obtained.

Spatiotemporal Distribution of β-Amyloid in Alzheimer Disease Is the Result of Heterogeneous Regional Carrying Capacities.

PubMed

Whittington, Alex; Sharp, David J; Gunn, Roger N

2018-05-01

β-amyloid (Aβ) accumulation in the brain is 1 of 2 pathologic hallmarks of Alzheimer disease (AD), and the spatial distribution of Aβ has been studied extensively ex vivo. Methods: We applied mathematical modeling to Aβ in vivo PET imaging data to investigate competing theories of Aβ spread in AD. Results: Our results provided evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is due to heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than to longer-term spreading from seed regions. Conclusion: The in vivo spatiotemporal distribution of Aβ in AD can be mathematically modeled using a logistic growth model in which the Aβ carrying capacity is heterogeneous across the brain but the exponential growth rate and time of half maximal Aβ concentration are constant. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Larval connectivity of pearl oyster through biophysical modelling; evidence of food limitation and broodstock effect

NASA Astrophysics Data System (ADS)

Thomas, Yoann; Dumas, Franck; Andréfouët, Serge

2016-12-01

The black-lip pearl oyster (Pinctada margaritifera) is cultured extensively to produce black pearls, especially in French Polynesia atoll lagoons. This aquaculture relies on spat collection, a process that experiences spatial and temporal variability and needs to be optimized by understanding which factors influence recruitment. Here, we investigate the sensitivity of P. margaritifera larval dispersal to both physical and biological factors in the lagoon of Ahe atoll. Coupling a validated 3D larval dispersal model, a bioenergetics larval growth model following the Dynamic Energy Budget (DEB) theory, and a population dynamics model, the variability of lagoon-scale connectivity patterns and recruitment potential is investigated. The relative contribution of reared and wild broodstock to the lagoon-scale recruitment potential is also investigated. Sensitivity analyses pointed out the major effect of the broodstock population structure as well as the sensitivity to larval mortality rate and inter-individual growth variability to larval supply and to the subsequent settlement potential. The application of the growth model clarifies how trophic conditions determine the larval supply and connectivity patterns. These results provide new cues to understand the dynamics of bottom-dwelling populations in atoll lagoons, their recruitment, and discuss how to take advantage of these findings and numerical models for pearl oyster management.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

Flow and active mixing have a strong impact on bacterial growth dynamics in the proximal large intestine

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Segota, Igor; Yang, Chih-Yu; Arnoldini, Markus; Groisman, Alex; Hwa, Terence

2016-11-01

More than half of fecal dry weight is bacterial mass with bacterial densities reaching up to 1012 cells per gram. Mostly, these bacteria grow in the proximal large intestine where lateral flow along the intestine is strong: flow can in principal lead to a washout of bacteria from the proximal large intestine. Active mixing by contractions of the intestinal wall together with bacterial growth might counteract such a washout and allow high bacterial densities to occur. As a step towards understanding bacterial growth in the presence of mixing and flow, we constructed an in-vitro setup where controlled wall-deformations of a channel emulate contractions. We investigate growth along the channel under a steady nutrient inflow. Depending on mixing and flow, we observe varying spatial gradients in bacterial density along the channel. Active mixing by deformations of the channel wall is shown to be crucial in maintaining a steady-state bacterial population in the presence of flow. The growth-dynamics is quantitatively captured by a simple mathematical model, with the effect of mixing described by an effective diffusion term. Based on this model, we discuss bacterial growth dynamics in the human large intestine using flow- and mixing-behavior having been observed for humans.

Using minimalist self-assembling peptides as hierarchical scaffolds to stabilise growth factors and promote stem cell integration in the injured brain.

PubMed

Rodriguez, A L; Bruggeman, K F; Wang, Y; Wang, T Y; Williams, R J; Parish, C L; Nisbet, D R

2018-03-01

Neurotrophic growth factors are effective in slowing progressive degeneration and/or promoting neural repair through the support of residual host and/or transplanted neurons. However, limitations including short half-life and enzyme susceptibility of growth factors highlight the need for alternative strategies to prolong localised delivery at a site of injury. Here, we establish the utility of minimalist N-fluorenylmethyloxycarbonyl (Fmoc) self-assembling peptides (SAPs) as growth factor delivery vehicle, targeted at supporting neural transplants in an animal model of Parkinson's disease. The neural tissue-specific SAP, Fmoc-DIKVAV, demonstrated sustained release of glial cell line derived neurotrophic factor, up to 172 hr after gel loading. This represents a significant advance in drug delivery, because its lifetime in phosphate buffered saline was less than 1 hr. In vivo transplantation of neural progenitor cells, together with our growth factor-loaded material, into the injured brain improved graft survival compared with cell transplants alone. We show for the first time the use of minimalist Fmoc-SAP in an in vivo disease model for sustaining the delivery of neurotrophic growth factors, facilitating their spatial and temporal delivery in vivo, whilst also providing an enhanced niche environment for transplanted cells. Copyright © 2017 John Wiley & Sons, Ltd.

Spatial control of translation repression and polarized growth by conserved NDR kinase Orb6 and RNA-binding protein Sts5.

PubMed

Nuñez, Illyce; Rodriguez Pino, Marbelys; Wiley, David J; Das, Maitreyi E; Chen, Chuan; Goshima, Tetsuya; Kume, Kazunori; Hirata, Dai; Toda, Takashi; Verde, Fulvia

2016-07-30

RNA-binding proteins contribute to the formation of ribonucleoprotein (RNP) granules by phase transition, but regulatory mechanisms are not fully understood. Conserved fission yeast NDR (Nuclear Dbf2-Related) kinase Orb6 governs cell morphogenesis in part by spatially controlling Cdc42 GTPase. Here we describe a novel, independent function for Orb6 kinase in negatively regulating the recruitment of RNA-binding protein Sts5 into RNPs to promote polarized cell growth. We find that Orb6 kinase inhibits Sts5 recruitment into granules, its association with processing (P) bodies, and degradation of Sts5-bound mRNAs by promoting Sts5 interaction with 14-3-3 protein Rad24. Many Sts5-bound mRNAs encode essential factors for polarized cell growth, and Orb6 kinase spatially and temporally controls the extent of Sts5 granule formation. Disruption of this control system affects cell morphology and alters the pattern of polarized cell growth, revealing a role for Orb6 kinase in the spatial control of translational repression that enables normal cell morphogenesis.

Local Soils Information Needed to Define the Root Zone in Process Models on the Gulf Coastal Plain

Treesearch

Mary Anne Sword Sayer; Allan E. Tiarks

2002-01-01

We combined published information and our own experimental results from the Gulf Coastal Plain to evaluate how soil aeration and strength interact with loblolly pine root growth. Our results demonstrate that soil aeration and strength differ by soil series and year and are subject to vertical and horizontal spatial variation. Comparison of loblolly pine root phenology...

The Forest Vegetation Simulator: A review of its structure, content, and applications

Treesearch

Nicholas L. Crookston; Gary E. Dixon

2005-01-01

The Forest Vegetation Simulator (FVS) is a distance-independent, individual-tree forest growth model widely used in the United States to support management decisionmaking. Stands are the basic projection unit, but the spatial scope can be many thousands of stands. The temporal scope is several hundred years at a resolution of 5­10 years. Projections start with a...

Multi-scale drivers of spatial variation in old-growth forest carbon density disentangled with Lidar and an individual-based landscape model

Treesearch

Rupert Seidl; Thomas A. Spies; Werner Rammer; E. Ashley Steel; Robert J. Pabst; Keith. Olsen

2012-01-01

Forest ecosystems are the most important terrestrial carbon (C) storage globally, and presently mitigate anthropogenic climate change by acting as a large and persistent sink for atmospheric CO2. Yet, forest C density varies greatly in space, both globally and at stand and landscape levels. Understanding the multi-scale drivers of this variation...

Operator Spreading in Random Unitary Circuits

NASA Astrophysics Data System (ADS)

Nahum, Adam; Vijay, Sagar; Haah, Jeongwan

2018-04-01

Random quantum circuits yield minimally structured models for chaotic quantum dynamics, which are able to capture, for example, universal properties of entanglement growth. We provide exact results and coarse-grained models for the spreading of operators by quantum circuits made of Haar-random unitaries. We study both 1 +1 D and higher dimensions and argue that the coarse-grained pictures carry over to operator spreading in generic many-body systems. In 1 +1 D , we demonstrate that the out-of-time-order correlator (OTOC) satisfies a biased diffusion equation, which gives exact results for the spatial profile of the OTOC and determines the butterfly speed vB. We find that in 1 +1 D , the "front" of the OTOC broadens diffusively, with a width scaling in time as t1 /2. We address fluctuations in the OTOC between different realizations of the random circuit, arguing that they are negligible in comparison to the broadening of the front within a realization. Turning to higher dimensions, we show that the averaged OTOC can be understood exactly via a remarkable correspondence with a purely classical droplet growth problem. This implies that the width of the front of the averaged OTOC scales as t1 /3 in 2 +1 D and as t0.240 in 3 +1 D (exponents of the Kardar-Parisi-Zhang universality class). We support our analytic argument with simulations in 2 +1 D . We point out that, in two or higher spatial dimensions, the shape of the spreading operator at late times is affected by underlying lattice symmetries and, in general, is not spherical. However, when full spatial rotational symmetry is present in 2 +1 D , our mapping implies an exact asymptotic form for the OTOC, in terms of the Tracy-Widom distribution. For an alternative perspective on the OTOC in 1 +1 D , we map it to the partition function of an Ising-like statistical mechanics model. As a result of special structure arising from unitarity, this partition function reduces to a random walk calculation which can be performed exactly. We also use this mapping to give exact results for entanglement growth in 1 +1 D circuits.

Diverse Responses of Global Vegetation to Climate Changes: Spatial Patterns and Time-lag Effects

NASA Astrophysics Data System (ADS)

Wu, D.; Zhao, X.; Zhou, T.; Huang, K.; Xu, W.

2014-12-01

Global climate changes have enormous influences on vegetation growth, meanwhile, response of vegetation to climate express space diversity and time-lag effects, which account for spatial-temporal disparities of climate change and spatial heterogeneity of ecosystem. Revelation of this phenomenon will help us further understanding the impact of climate change on vegetation. Assessment and forecast of global environmental change can be also improved under further climate change. Here we present space diversity and time-lag effects patterns of global vegetation respond to three climate factors (temperature, precipitation and solar radiation) based on quantitative analysis of satellite data (NDVI) and Climate data (Climate Research Unit). We assessed the time-lag effects of global vegetation to main climate factors based on the great correlation fitness between NDVI and the three climate factors respectively among 0-12 months' temporal lags. On this basis, integrated response model of NDVI and the three climate factors was built to analyze contribution of different climate factors to vegetation growth with multiple regression model and partial correlation model. In the result, different vegetation types have distinct temporal lags to the three climate factors. For the precipitation, temporal lags of grasslands are the shortest while the evergreen broad-leaf forests are the longest, which means that grasslands are more sensitive to precipitation than evergreen broad-leaf forests. Analysis of different climate factors' contribution to vegetation reveal that vegetation are dominated by temperature in the high northern latitudes; they are mainly restricted by precipitation in arid and semi-arid areas (Australia, Western America); in humid areas of low and intermediate latitudes (Amazon, Eastern America), vegetation are mainly influenced by solar radiation. Our results reveal the time-lag effects and major driving factors of global vegetation growth and explain the spatiotemporal variations of global vegetation in last 30 years. Significantly, it is as well as in forecasting and assessing the influences of future climate change on the vegetation dynamics. This work was supported by the High Technology Research and Development Program of China (Grant NO.2013AA122801).

Absolute and convective instabilities and their roles in the forecasting of large frontal meanderings

NASA Astrophysics Data System (ADS)

Liang, X. San; Robinson, Allan R.

2013-10-01

Frontal meanderings are generally difficult to predict. In this study, we demonstrate through an exercise with the Iceland-Faeroe Front (IFF) that satisfactory predictions may be achieved with the aid of hydrodynamic instability analysis. As discovered earlier on, underlying the IFF meandering is a convective instability in the western boundary region followed by an absolute instability in the interior; correspondingly the disturbance growth reveals a switch of pattern from spatial amplification to temporal amplification. To successfully forecast the meandering, the two instability processes must be faithfully reproduced. This sets stringent constraints for the tunable model parameters, e.g., boundary relaxation, temporal relaxation, eddy diffusivity, etc. By analyzing the instability dispersion properties, these parameters can be rather accurately set and their respective ranges of sensitivity estimated. It is shown that too much relaxation inhibits the front from varying; on the other hand, too little relaxation may have the model completely skip the spatial growth phase, leading to a meandering way more upstream along the front. Generally speaking, dissipation/diffusion tends to stabilize the simulation, but unrealistically large dissipation/diffusion could trigger a spurious absolute instability, and hence a premature meandering intrusion. The belief that taking in more data will improve the forecast does not need to be true; it depends on whether the model setup admits the two instabilities. This study may help relieve modelers from the laborious and tedious work of parameter tuning; it also provides us criteria to distinguish a physically relevant forecast from numerical artifacts.

Spatially resolved, in-situ monitoring of crack growth via the coupling current in aluminum alloy 5083

NASA Astrophysics Data System (ADS)

Williams, Krystaufeux D.

The work discussed in this dissertation is an experimental validation of a body of research that was created to model stress corrosion cracking phenomenon for 304 stainless steels in boiling water reactors. This coupled environment fracture model (CEFM) incorporates the natural laws of the conservation of charge and the differential aeration hypothesis to predict the amount of stress corrosion crack growth as a function of many external environmental variables, including potential, stress intensity, solution conductivity, oxidizer concentrations, and various other environmental parameters. Out of this approach came the concept of the coupling current; a local corrosion current that flows from within cracks, crevices, pits, etc... of a metal or alloy to the external surface. Because of the deterministic approach taken in the mentioned research, the coupling current analysis and CEFM model can be applied to the specific problem of SCC in aluminum alloy 5083 (the alloy of interest for this dissertation that is highly sought after today because of its corrosion resistance and high strength to weight ratio). This dissertation research is specifically devoted to the experimental verification of the coupling current, which results from a coupling between the crack's internal and external environments, by spatially resolving them using the scanning vibrating probe (SVP) as a tool. Hence, through the use of a unique fracture mechanics setup, simultaneous mechanical and local electrochemical data may be obtained, in situ..

Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

NASA Astrophysics Data System (ADS)

Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

2014-12-01

Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

PubMed Central

Diago, Maria P.; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψs) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction (RP2) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture. PMID:29441086

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy.

PubMed

Diago, Maria P; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψ s ) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction ([Formula: see text]) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

Phage-Bacterial Dynamics with Spatial Structure: Self Organization around Phage Sinks Can Promote Increased Cell Densities

PubMed Central

Bull, James J.; Christensen, Kelly A.; Scott, Carly; Crandall, Cameron J.; Krone, Stephen M.

2018-01-01

Bacteria growing on surfaces appear to be profoundly more resistant to control by lytic bacteriophages than do the same cells grown in liquid. Here, we use simulation models to investigate whether spatial structure per se can account for this increased cell density in the presence of phages. A measure is derived for comparing cell densities between growth in spatially structured environments versus well mixed environments (known as mass action). Maintenance of sensitive cells requires some form of phage death; we invoke death mechanisms that are spatially fixed, as if produced by cells. Spatially structured phage death provides cells with a means of protection that can boost cell densities an order of magnitude above that attained under mass action, although the effect is sometimes in the opposite direction. Phage and bacteria self organize into separate refuges, and spatial structure operates so that the phage progeny from a single burst do not have independent fates (as they do with mass action). Phage incur a high loss when invading protected areas that have high cell densities, resulting in greater protection for the cells. By the same metric, mass action dynamics either show no sustained bacterial elevation or oscillate between states of low and high cell densities and an elevated average. The elevated cell densities observed in models with spatial structure do not approach the empirically observed increased density of cells in structured environments with phages (which can be many orders of magnitude), so the empirical phenomenon likely requires additional mechanisms than those analyzed here. PMID:29382134

Spatial decision supporting for winter wheat irrigation and fertilizer optimizing in North China Plain

NASA Astrophysics Data System (ADS)

Yang, Xiaodong; Yang, Hao; Dong, Yansheng; Yu, Haiyang

2014-11-01

Production management of winter wheat is more complicated than other crops since its growth period is covered all four seasons and growth environment is very complex with frozen injury, drought, insect or disease injury and others. In traditional irrigation and fertilizer management, agricultural technicians or farmers mainly make decision based on phenology, planting experience to carry out artificial fertilizer and irrigation management. For example, wheat needs more nitrogen fertilizer in jointing and booting stage by experience, then when the wheat grow to the two growth periods, the farmer will fertilize to the wheat whether it needs or not. We developed a spatial decision support system for optimizing irrigation and fertilizer measures based on WebGIS, which monitoring winter wheat growth and soil moisture content by combining a crop model, remote sensing data and wireless sensors data, then reasoning professional management schedule from expert knowledge warehouse. This system is developed by ArcIMS, IDL in server-side and JQuery, Google Maps API, ASP.NET in client-side. All computing tasks are run on server-side, such as computing 11 normal vegetable indexes (NDVI/ NDWI/ NDWI2/ NRI/ NSI/ WI/ G_SWIR/ G_SWIR2/ SPSI/ TVDI/ VSWI) and custom VI of remote sensing image by IDL; while real-time building map configuration file and generating thematic map by ArcIMS.

Characterization of inhomogeneous and anisotropic steel welds by ultrasonic array measurements

NASA Astrophysics Data System (ADS)

Fan, Z.; Lowe, M. J. S.

2013-01-01

Austenitic welds are difficult to inspect non-destructively by ultrasound due to the anisotropic and inhomogeneous material in the weld, which causes spatial deviation of ultrasonic beams. A common way to describe such material is to consider it as transversely isotropic, in which the plane perpendicular to the direction of the grain growth is considered to be isotropic. Therefore a weld performance map which indicates the orientation of the grain growth can be used to describe the material properties in the weld. In our work, we have chosen a weld map based on the parameters of the MINA model which uses the information of the welding procedure and rules for crystalline growth to predict the orientations, and thus has a good physical foundation. We have compared the measured grain orientations for a realistic weld with the predictions from the model. With this model, only a small number of parameters are used to describe the weld properties, therefore enabling the possibility of a well conditioned refining process to determine the weld map from ultrasonic measurements. We have demonstrated the feasibility of doing this, using a ray tracing model, and both simulated and experimental measurements.

Accelerated transport and growth with symmetrized dynamics

NASA Astrophysics Data System (ADS)

Merikoski, Juha

2013-12-01

In this paper we consider a model of accelerated dynamics with the rules modified from those of the recently proposed [Dong et al., Phys. Rev. Lett. 109, 130602 (2012), 10.1103/PhysRevLett.109.130602] accelerated exclusion process (AEP) such that particle-vacancy symmetry is restored to facilitate a mapping to a solid-on-solid growth model in 1+1 dimensions. In addition to kicking a particle ahead of the moving particle, as in the AEP, in our model another particle from behind is drawn, provided it is within the "distance of interaction" denoted by ℓmax. We call our model the doubly accelerated exclusion process (DAEP). We observe accelerated transport and interface growth and widening of the cluster size distribution for cluster sizes above ℓmax, when compared with the ordinary totally asymmetric exclusion process (TASEP). We also characterize the difference between the TASEP, AEP, and DAEP by computing a "staggered" order parameter, which reveals the local order in the steady state. This order in part explains the behavior of the particle current as a function of density. The differences of the steady states are also reflected by the behavior of the temporal and spatial correlation functions in the interface picture.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

USGS Publications Warehouse

Ross, Beth; Haukos, David A.; Hagen, Christian A.; Pitman, James

2018-01-01

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

Spatial regulation of controlled bioactive factor delivery for bone tissue engineering

PubMed Central

Samorezov, Julia E.; Alsberg, Eben

2015-01-01

Limitations of current treatment options for critical size bone defects create a significant clinical need for tissue engineered bone strategies. This review describes how control over the spatiotemporal delivery of growth factors, nucleic acids, and drugs and small molecules may aid in recapitulating signals present in bone development and healing, regenerating interfaces of bone with other connective tissues, and enhancing vascularization of tissue engineered bone. State-of-the-art technologies used to create spatially controlled patterns of bioactive factors on the surfaces of materials, to build up 3D materials with patterns of signal presentation within their bulk, and to pattern bioactive factor delivery after scaffold fabrication are presented, highlighting their applications in bone tissue engineering. As these techniques improve in areas such as spatial resolution and speed of patterning, they will continue to grow in value as model systems for understanding cell responses to spatially regulated bioactive factor signal presentation in vitro, and as strategies to investigate the capacity of the defined spatial arrangement of these signals to drive bone regeneration in vivo. PMID:25445719