scholarly journals Covariations in ecological scaling laws fostered by community dynamics

2017 ◽  
Vol 114 (40) ◽  
pp. 10672-10677 ◽  
Author(s):  
Silvia Zaoli ◽  
Andrea Giometto ◽  
Amos Maritan ◽  
Andrea Rinaldo
Keyword(s):  
Scaling Laws ◽  
Community Dynamics ◽  
Broad Class ◽  
Probability Distributions ◽  
Power Laws ◽  
Scaling Exponents ◽  
Functional Relationships ◽  
Resource Limited ◽  
Ecological Scaling ◽  
Species Abundances

Scaling laws in ecology, intended both as functional relationships among ecologically relevant quantities and the probability distributions that characterize their occurrence, have long attracted the interest of empiricists and theoreticians. Empirical evidence exists of power laws associated with the number of species inhabiting an ecosystem, their abundances, and traits. Although their functional form appears to be ubiquitous, empirical scaling exponents vary with ecosystem type and resource supply rate. The idea that ecological scaling laws are linked has been entertained before, but the full extent of macroecological pattern covariations, the role of the constraints imposed by finite resource supply, and a comprehensive empirical verification are still unexplored. Here, we propose a theoretical scaling framework that predicts the linkages of several macroecological patterns related to species’ abundances and body sizes. We show that such a framework is consistent with the stationary-state statistics of a broad class of resource-limited community dynamics models, regardless of parameterization and model assumptions. We verify predicted theoretical covariations by contrasting empirical data and provide testable hypotheses for yet unexplored patterns. We thus place the observed variability of ecological scaling exponents into a coherent statistical framework where patterns in ecology embed constrained fluctuations.

scholarly journals Intraspecific scaling laws are preserved in ventricular hypertrophy but not in heart failure

2016 ◽  
Vol 311 (5) ◽  
pp. H1108-H1117 ◽  
Author(s):  
Yanjun Gong ◽  
Yundi Feng ◽  
Xudong Chen ◽  
Wenchang Tan ◽  
Yunlong Huo ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ventricular Hypertrophy ◽  
Scaling Laws ◽  
Normal Growth ◽  
Power Laws ◽  
Scaling Analysis ◽  
Scaling Exponents ◽  
Theoretical Predictions ◽  
And Function ◽  
Vascular Trees

It is scientifically and clinically important to understand the structure-function scaling of coronary arterial trees in compensatory (e.g., left and right ventricular hypertrophy, LVH and RVH) and decompensatory vascular remodeling (e.g., congestive heart failure, CHF). This study hypothesizes that intraspecific scaling power laws of vascular trees are preserved in hypertrophic hearts but not in CHF swine hearts. To test the hypothesis, we carried out the scaling analysis based on morphometry and hemodynamics of coronary arterial trees in moderate LVH, severe RVH, and CHF compared with age-matched respective control hearts. The scaling exponents of volume-diameter, length-volume, and flow-diameter power laws in control hearts were consistent with the theoretical predictions (i.e., 3, 7/9, and 7/3, respectively), which remained unchanged in LVH and RVH hearts. The scaling exponents were also preserved with an increase of body weight during normal growth of control animals. In contrast, CHF increased the exponents of volume-diameter and flow-diameter scaling laws to 4.25 ± 1.50 and 3.15 ± 1.49, respectively, in the epicardial arterial trees. This study validates the predictive utility of the scaling laws to diagnose vascular structure and function in CHF hearts to identify the borderline between compensatory and decompensatory remodeling.

Scaling

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Distribution Function ◽  
Dynamical Systems ◽  
Complex Systems ◽  
Power Law ◽  
Scaling Laws ◽  
Power Laws ◽  
Distribution Functions ◽  
Temporal Process ◽  
Approximate Power

Scaling appears practically everywhere in science; it basically quantifies how the properties or shapes of an object change with the scale of the object. Scaling laws are always associated with power laws. The scaling object can be a function, a structure, a physical law, or a distribution function that describes the statistics of a system or a temporal process. We focus on scaling laws that appear in the statistical description of stochastic complex systems, where scaling appears in the distribution functions of observable quantities of dynamical systems or processes. The distribution functions exhibit power laws, approximate power laws, or fat-tailed distributions. Understanding their origin and how power law exponents can be related to the particular nature of a system, is one of the aims of the book.We comment on fitting power laws.

scholarly journals A Brief Review of Generalized Entropies

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 813 ◽  
Author(s):  
José Amigó ◽  
Sámuel Balogh ◽  
Sergio Hernández
Keyword(s):  
Diffusion Processes ◽  
Complex Dynamics ◽  
Probability Distributions ◽  
Point Of View ◽  
Scaling Exponent ◽  
Scaling Exponents ◽  
Physical Systems ◽  
New Phenomena ◽  
Generalized Entropies

Entropy appears in many contexts (thermodynamics, statistical mechanics, information theory, measure-preserving dynamical systems, topological dynamics, etc.) as a measure of different properties (energy that cannot produce work, disorder, uncertainty, randomness, complexity, etc.). In this review, we focus on the so-called generalized entropies, which from a mathematical point of view are nonnegative functions defined on probability distributions that satisfy the first three Shannon–Khinchin axioms: continuity, maximality and expansibility. While these three axioms are expected to be satisfied by all macroscopic physical systems, the fourth axiom (separability or strong additivity) is in general violated by non-ergodic systems with long range forces, this having been the main reason for exploring weaker axiomatic settings. Currently, non-additive generalized entropies are being used also to study new phenomena in complex dynamics (multifractality), quantum systems (entanglement), soft sciences, and more. Besides going through the axiomatic framework, we review the characterization of generalized entropies via two scaling exponents introduced by Hanel and Thurner. In turn, the first of these exponents is related to the diffusion scaling exponent of diffusion processes, as we also discuss. Applications are addressed as the description of the main generalized entropies advances.

scholarly journals Solar wind low-frequency magnetohydrodynamic turbulence: extended self-similarity and scaling laws

1996 ◽  
Vol 3 (4) ◽  
pp. 247-261 ◽  
Author(s):  
V. Carbone ◽  
P. Veltri ◽  
R. Bruno
Keyword(s):  
Solar Wind ◽  
Scaling Laws ◽  
Velocity Structure ◽  
Fluid Flows ◽  
Structure Functions ◽  
Point Of View ◽  
Self Similarity ◽  
Extended Self ◽  
Scaling Exponents ◽  
Magnetohydrodynamic Turbulence

Abstract. In this paper we review some of the work done in investigating the scaling properties of Magnetohydrodynamic turbulence, by using velocity fluctuations measurements performed in the interplanetary space plasma by the Helios spacecraft. The set of scaling exponents ξq for the q-th order velocity structure functions, have been determined by using the Extended Self-Similarity hypothesis. We have found that the q-th order velocity structure function, when plotted vs. the 4-th order structure function, displays a range of self-similarity which extends over all the lengths covered by measurements, thus allowing for a very good determination of ξq. Moreover the results seem to show that the scaling exponents are the same regardless the various observation periods considered. The obtained scaling exponents have been compared with the results of some intermittency models for Kraichnan's turbulence, derived in the framework of infinitely divisible fragmentation processes, showing the good agreement between these models and our observations. Finally, on the basis of the actually available data sets, we show that scaling laws in Solar Wind turbulence seem to be different from turbulent scaling laws in the ordinary fluid flows. This is true for high-order velocity structure functions, while low-order velocity structure functions show the same scaling laws. Since our measurements involve length scales which extend over many order of magnitude where dissipation is practically absent, our results show that Solar Wind turbulence can be regarded as a testing bench for the investigation of general scaling behaviour in turbulent flows. In particular our results strongly support the point of view which attributes a key role to the inertial range dynamics in determining the intermittency characteristics in fluid flows, in contrast with the point of view which attributes intermittency to a finite Reynolds number effect.

scholarly journals What drives interaction strengths in complex food webs? A test with feeding rates of a generalist stream predator

2018 ◽  
Author(s):  
Daniel L. Preston ◽  
Jeremy S. Henderson ◽  
Landon P. Falke ◽  
Leah M. Segui ◽  
Tamara J. Layden ◽  
...  
Keyword(s):  
Food Webs ◽  
Body Mass ◽  
Prey Density ◽  
Scaling Laws ◽  
Community Dynamics ◽  
Abiotic Factors ◽  
Interaction Strength ◽  
Feeding Rates ◽  
Predator Prey ◽  
Mass Ratios

AbstractDescribing the mechanisms that drive variation in species interaction strengths is central to understanding, predicting, and managing community dynamics. Multiple factors have been linked to trophic interaction strength variation, including species densities, species traits, and abiotic factors. Yet most empirical tests of the relative roles of multiple mechanisms that drive variation have been limited to simplified experiments that may diverge from the dynamics of natural food webs. Here, we used a field-based observational approach to quantify the roles of prey density, predator density, predator-prey body-mass ratios, prey identity, and abiotic factors in driving variation in feeding rates of reticulate sculpin (Cottus perplexus). We combined data on over 6,000 predator-prey observations with prey identification time functions to estimate 289 prey-specific feeding rates at nine stream sites in Oregon. Feeding rates on 57 prey types showed an approximately log-normal distribution, with few strong and many weak interactions. Model selection indicated that prey density, followed by prey identity, were the two most important predictors of prey-specific sculpin feeding rates. Feeding rates showed a positive, accelerating relationship with prey density that was inconsistent with predator saturation predicted by current functional response models. Feeding rates also exhibited four orders-of-magnitude in variation across prey taxonomic orders, with the lowest feeding rates observed on prey with significant anti-predator defenses. Body-mass ratios were the third most important predictor variable, showing a hump-shaped relationship with the highest feeding rates at intermediate ratios. Sculpin density was negatively correlated with feeding rates, consistent with the presence of intraspecific predator interference. Our results highlight how multiple co-occurring drivers shape trophic interactions in nature and underscore ways in which simplified experiments or reliance on scaling laws alone may lead to biased inferences about the structure and dynamics of species-rich food webs.

scholarly journals Visualizing Microbial Community Dynamics via a Controllable Soil Environment

mSystems ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Arunima Bhattacharjee ◽  
Dusan Velickovic ◽  
Thomas W. Wietsma ◽  
Sheryl L. Bell ◽  
Janet K. Jansson ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Microbial Community ◽  
Microbial Communities ◽  
Community Dynamics ◽  
Soil Microbial Communities ◽  
Soil Microbiome ◽  
Soil Core ◽  
Soil Microbial ◽  
Functional Relationships ◽  
Microbial Community Dynamics

ABSTRACT Understanding the basic biology that underpins soil microbiome interactions is required to predict the metaphenomic response to environmental shifts. A significant knowledge gap remains in how such changes affect microbial community dynamics and their metabolic landscape at microbially relevant spatial scales. Using a custom-built SoilBox system, here we demonstrated changes in microbial community growth and composition in different soil environments (14%, 24%, and 34% soil moisture), contingent upon access to reservoirs of nutrient sources. The SoilBox emulates the probing depth of a common soil core and enables determination of both the spatial organization of the microbial communities and their metabolites, as shown by confocal microscopy in combination with mass spectrometry imaging (MSI). Using chitin as a nutrient source, we used the SoilBox system to observe increased adhesion of microbial biomass on chitin islands resulting in degradation of chitin into N-acetylglucosamine (NAG) and chitobiose. With matrix-assisted laser desorption/ionization (MALDI)-MSI, we also observed several phospholipid families that are functional biomarkers for microbial growth on the chitin islands. Fungal hyphal networks bridging different chitin islands over distances of 27 mm were observed only in the 14% soil moisture regime, indicating that such bridges may act as nutrient highways under drought conditions. In total, these results illustrate a system that can provide unprecedented spatial information about interactions within soil microbial communities as a function of changing environments. We anticipate that this platform will be invaluable in spatially probing specific intra- and interkingdom functional relationships of microbiomes within soil. IMPORTANCE Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved.

DBN Models for Visual Tracking and Prediction

2007 ◽  
pp. 176-193
Author(s):  
Qian Diao ◽  
Jianye Lu ◽  
Wei Hu ◽  
Yimin Zhang ◽  
Gary Bradski
Keyword(s):  
Visual Tracking ◽  
General Framework ◽  
Broad Class ◽  
Probability Distributions ◽  
Prediction Method ◽  
Dynamic Bayesian Networks ◽  
Time Series Models ◽  
Complex Environments ◽  
Inference Algorithms ◽  
Background Clutter

In a visual tracking task, the object may exhibit rich dynamic behavior in complex environments that can corrupt target observations via background clutter and occlusion. Such dynamics and background induce nonlinear, nonGaussian and multimodal observation densities. These densities are difficult to model with traditional methods such as Kalman filter models (KFMs) due to their Gaussian assumptions. Dynamic Bayesian networks (DBNs) provide a more general framework in which to solve these problems. DBNs generalize KFMs by allowing arbitrary probability distributions, not just (unimodal) linear-Gaussian. Under the DBN umbrella, a broad class of learning and inference algorithms for time-series models can be used in visual tracking. Furthermore, DBNs provide a natural way to combine multiple vision cues. In this chapter, we describe some DBN models for tracking in nonlinear, nonGaussian and multimodal situations, and present a prediction method to assist feature extraction part by making a hypothesis for the new observations.

scholarly journals Eulerian and Lagrangian Structure Function’s Scaling Exponents in Turbulent Channel Flow

2006 ◽  
Vol 61 (12) ◽  
pp. 624-628
Author(s):  
Jian-Ping Luo ◽  
Tatsuo Ushijima ◽  
Osami Kitoh ◽  
Zhi-Ming Lu ◽  
Yu-Lu Liu ◽  
...  
Keyword(s):  
Channel Flow ◽  
Scaling Laws ◽  
Turbulent Channel Flow ◽  
Self Similarity ◽  
Extended Self ◽  
Scaling Exponents ◽  
Turbulent Channel Flows ◽  
Frame Work ◽  
Simulation Results ◽  
Similarity Method

The relation between Eulerian structure function’s scaling exponents and Lagrangian ones in turbulent channel flows is explored both theoretically and numerically. A nonlinear parametric transformation between Eulerian structure function’s scaling exponents and Lagrangian ones is derived, following Landau and Novikov’s frame work. This relation is then compared to some known experimental and numerical results, but mainly to our DNS (direct numerical simulation) results of a fully developed channel flow with Reτ = 100. The scaling exponents are evaluated in terms of the ESS (extended self-similarity) method, since the Reynolds number is too low to make the standard scaling laws applicable. The agreement between theory and simulation is satisfactory

Sign in / Sign up

Export Citation Format

Share Document