Ades: New Ecological Families of Species-Specific Frequency Distributions that Describe Repeated Spatial Samples with an Intrinsic Power-Law Variance-Mean Property

10.2307/4388 ◽  
1985 ◽  
Vol 54 (3) ◽  
pp. 931 ◽  
Author(s):  
J. N. Perry ◽  
L. R. Taylor
Keyword(s):  
Power Law ◽  
Frequency Distributions ◽  
Specific Frequency ◽  
Species Specific

scholarly journals Spatial Heterogeneity of the Incidence of Powdery Mildew on Hop Cones

Plant Disease ◽  
2006 ◽  
Vol 90 (11) ◽  
pp. 1433-1440 ◽  
Author(s):  
David H. Gent ◽  
Walter F. Mahaffee ◽  
William W. Turechek
Keyword(s):  
Powdery Mildew ◽  
Spatial Heterogeneity ◽  
Power Law ◽  
Binomial Distribution ◽  
Disease Incidence ◽  
Disease Assessment ◽  
Cluster Sampling ◽  
Data Sets ◽  
Ratio Test ◽  
Frequency Distributions

The spatial heterogeneity of the incidence of hop cones with powdery mildew (Podosphaera macularis) was characterized from transect surveys of 41 commercial hop yards in Oregon and Washington from 2000 to 2005. The proportion of sampled cones with powdery mildew ( p) was recorded for each of 221 transects, where N = 60 sampling units of n = 25 cones assessed in each transect according to a cluster sampling strategy. Disease incidence ranged from 0 to 0.92 among all yards and dates. The binomial and beta-binomial frequency distributions were fit to the N sampling units in a transect using maximum likelihood. The estimation procedure converged for 74% of the data sets where p > 0, and a loglikelihood ratio test indicated that the beta-binomial distribution provided a better fit to the data than the binomial distribution for 46% of the data sets, indicating an aggregated pattern of disease. Similarly, the C(α) test indicated that 54% could be described by the beta-binomial distribution. The heterogeneity parameter of the beta-binomial distribution, θ, a measure of variation among sampling units, ranged from 0.01 to 0.20, with a mean of 0.037 and a median of 0.015. Estimates of the index of dispersion ranged from 0.79 to 7.78, with a mean of 1.81 and a median of 1.37, and were significantly greater than 1 for 54% of the data sets. The binary power law provided an excellent fit to the data, with slope and intercept parameters significantly greater than 1, which indicated that heterogeneity varied systematically with the incidence of infected cones. A covariance analysis indicated that the geographic location (region) of the yards and the type of hop cultivar had little effect on heterogeneity; however, the year of sampling significantly influenced the intercept and slope parameters of the binary power law. Significant spatial autocorrelation was detected in only 11% of the data sets, with estimates of first-order autocorrelation, r1, ranging from -0.30 to 0.70, with a mean of 0.06 and a median of 0.04; however, correlation was detected in only 20 and 16% of the data sets by median and ordinary runs analysis, respectively. Together, these analyses suggest that the incidence of powdery mildew on cones was slightly aggregated among plants, but patterns of aggregation larger than the sampling unit were rare (20% or less of data sets). Knowledge of the heterogeneity of diseased cones was used to construct fixed sampling curves to precisely estimate the incidence of powdery mildew on cones at varying disease intensities. Use of the sampling curves developed in this research should help to improve sampling methods for disease assessment and management decisions.

The breakdown of the power-law frequency distributions for the hard X-ray peak count rates of solar flares

2013 ◽  
Vol 13 (12) ◽  
pp. 1482-1492 ◽  
Author(s):  
You-Ping Li ◽  
Wei-Qun Gan ◽  
Li Feng ◽  
Si-Ming Liu ◽  
A. Struminsky
Keyword(s):  
Power Law ◽  
Solar Flares ◽  
Frequency Distributions ◽  
X Ray ◽  
Peak Count

scholarly journals How does seasonal variability in growth, recruitment, and mortality affect the performance of length-based mortality and asymptotic length estimates in aquatic resources?

2012 ◽  
Vol 70 (2) ◽  
pp. 329-341 ◽  
Author(s):  
Marc Hufnagl ◽  
Klaus B. Huebert ◽  
Axel Temming
Keyword(s):  
Seasonal Variability ◽  
Total Mortality ◽  
Growth Parameter ◽  
Brown Shrimp ◽  
Aquatic Resources ◽  
Frequency Distributions ◽  
Mortality Estimate ◽  
Species Specific ◽  
Method Bias ◽  
General Guidance

Abstract Hufnagl, M., Huebert, K. B., and Temming, A. 2013. How does seasonal variability in growth, recruitment, and mortality affect the performance of length-based mortality and asymptotic length estimates in aquatic resources? – ICES Journal of Marine Science, 70: 329–341. We tested the sensitivity of eight methods for estimating total mortality from size frequencies (modified Wetherall; Powell; Beverton and Holt; Jones and van Zalinge; Hoenig; Ssentongo and Larkin; seasonal and non-seasonal Length Converted Catch Curve) to violations of basic assumptions, such as seasonal growth, mortality, recruitment and variable asymptotic length L∞ or growth parameter K. For each method, bias was estimated by simulating length frequency distributions with different combinations of known L∞, Z and K values, calculating θ (Z/K) and L∞ estimates, and comparing the true input with the estimated output values. Input mortality was generally underestimated by all methods and in 27% of all simulations no method provided estimates within θ ± 1. Spring recruitment especially negatively influenced the mortality estimate. A decision tree was developed that provides general guidance in selecting appropriate methods despite violated assumptions, but species-specific case studies are recommended. An example of a species-specific study is provided for the brown shrimp, Crangon crangon. Despite inherent limitations for all methods, the results illustrate that estimates of θ and Z for brown shrimp can be improved substantially by selecting suitable methods and correcting for observed bias.

scholarly journals Midbrain auditory selectivity to natural sounds

2016 ◽  
Vol 113 (9) ◽  
pp. 2508-2513 ◽  
Author(s):  
Melville J. Wohlgemuth ◽  
Cynthia F. Moss
Keyword(s):  
Generalized Linear Model ◽  
Sensory Information ◽  
Natural Sounds ◽  
Acoustic Stimuli ◽  
Big Brown Bat ◽  
Specific Frequency ◽  
Response Profiles ◽  
Single Unit Recordings ◽  
Species Specific ◽  
Natural Statistics

This study investigated auditory stimulus selectivity in the midbrain superior colliculus (SC) of the echolocating bat, an animal that relies on hearing to guide its orienting behaviors. Multichannel, single-unit recordings were taken across laminae of the midbrain SC of the awake, passively listening big brown bat, Eptesicus fuscus. Species-specific frequency-modulated (FM) echolocation sound sequences with dynamic spectrotemporal features served as acoustic stimuli along with artificial sound sequences matched in bandwidth, amplitude, and duration but differing in spectrotemporal structure. Neurons in dorsal sensory regions of the bat SC responded selectively to elements within the FM sound sequences, whereas neurons in ventral sensorimotor regions showed broad response profiles to natural and artificial stimuli. Moreover, a generalized linear model (GLM) constructed on responses in the dorsal SC to artificial linear FM stimuli failed to predict responses to natural sounds and vice versa, but the GLM produced accurate response predictions in ventral SC neurons. This result suggests that auditory selectivity in the dorsal extent of the bat SC arises through nonlinear mechanisms, which extract species-specific sensory information. Importantly, auditory selectivity appeared only in responses to stimuli containing the natural statistics of acoustic signals used by the bat for spatial orientation—sonar vocalizations—offering support for the hypothesis that sensory selectivity enables rapid species-specific orienting behaviors. The results of this study are the first, to our knowledge, to show auditory spectrotemporal selectivity to natural stimuli in SC neurons and serve to inform a more general understanding of mechanisms guiding sensory selectivity for natural, goal-directed orienting behaviors.

scholarly journals Boron Oxide Nanoparticles Exhibit Minor, Species-Specific Acute Toxicity to North-Temperate and Amazonian Freshwater Fishes

2021 ◽  
Vol 9 ◽  
Author(s):  
Tyson J. MacCormack ◽  
Patrick T. Gormley ◽  
B. Ninh Khuong ◽  
Olivia A. Adams ◽  
Susana Braz-Mota ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Acute Toxicity ◽  
Boron Oxide ◽  
Model Systems ◽  
Oxide Nanoparticles ◽  
Frequency Distributions ◽  
Aerobic Activity ◽  
The North ◽  
Aquatic Vertebrates ◽  
Species Specific

Boron oxide nanoparticles (nB2O3) are manufactured for structural, propellant, and clinical applications and also form spontaneously through the degradation of bulk boron compounds. Bulk boron is not toxic to vertebrates but the distinctive properties of its nanostructured equivalent may alter its biocompatibility. Few studies have addressed this possibility, thus our goal was to gain an initial understanding of the potential acute toxicity of nB2O3 to freshwater fish and we used a variety of model systems to achieve this. Bioactivity was investigated in rainbow trout (Oncorhynchus mykiss) hepatocytes and at the whole animal level in three other North and South American fish species using indicators of aerobic metabolism, behavior, oxidative stress, neurotoxicity, and ionoregulation. nB2O3 reduced O. mykiss hepatocyte oxygen consumption (ṀO2) by 35% at high doses but whole animal ṀO2 was not affected in any species. Spontaneous activity was assessed using ṀO2 frequency distribution plots from live fish. nB2O3 increased the frequency of high ṀO2 events in the Amazonian fish Paracheirodon axelrodi, suggesting exposure enhanced spontaneous aerobic activity. ṀO2 frequency distributions were not affected in the other species examined. Liver lactate accumulation and significant changes in cardiac acetylcholinesterase and gill Na+/K+-ATPase activity were noted in the north-temperate Fundulus diaphanus exposed to nB2O3, but not in the Amazonian Apistogramma agassizii or P. axelrodi. nB2O3 did not induce oxidative stress in any of the species studied. Overall, nB2O3 exhibited modest, species-specific bioactivity but only at doses exceeding predicted environmental relevance. Chronic, low dose exposure studies are required for confirmation, but our data suggest that, like bulk boron, nB2O3 is relatively non-toxic to aquatic vertebrates and thus represents a promising formulation for further development.

scholarly journals Scalable statistics of correlated random variables and extremes applied to deep borehole porosities

2015 ◽  
Vol 19 (2) ◽  
pp. 729-745 ◽  
Author(s):  
A. Guadagnini ◽  
S. P. Neuman ◽  
T. Nan ◽  
M. Riva ◽  
C. L. Winter
Keyword(s):  
Power Law ◽  
Heavy Tails ◽  
Structure Functions ◽  
Separation Distance ◽  
Depositional Environments ◽  
Frequency Distributions ◽  
Scale Mixtures ◽  
Log Structure ◽  
Linear Relationships ◽  
Non Gaussian

Abstract. We analyze scale-dependent statistics of correlated random hydrogeological variables and their extremes using neutron porosity data from six deep boreholes, in three diverse depositional environments, as example. We show that key statistics of porosity increments behave and scale in manners typical of many earth and environmental (as well as other) variables. These scaling behaviors include a tendency of increments to have symmetric, non-Gaussian frequency distributions characterized by heavy tails that decay with separation distance or lag; power-law scaling of sample structure functions (statistical moments of absolute increments) in midranges of lags; linear relationships between log structure functions of successive orders at all lags, known as extended self-similarity or ESS; and nonlinear scaling of structure function power-law exponents with function order, a phenomenon commonly attributed in the literature to multifractals. Elsewhere we proposed, explored and demonstrated a new method of geostatistical inference that captures all of these phenomena within a unified theoretical framework. The framework views data as samples from random fields constituting scale mixtures of truncated (monofractal) fractional Brownian motion (tfBm) or fractional Gaussian noise (tfGn). Important questions not addressed in previous studies concern the distribution and statistical scaling of extreme incremental values. Of special interest in hydrology (and many other areas) are statistics of absolute increments exceeding given thresholds, known as peaks over threshold or POTs. In this paper we explore the statistical scaling of data and, for the first time, corresponding POTs associated with samples from scale mixtures of tfBm or tfGn. We demonstrate that porosity data we analyze possess properties of such samples and thus follow the theory we proposed. The porosity data are of additional value in revealing a remarkable cross-over from one scaling regime to another at certain lags. The phenomena we uncover are of key importance for the analysis of fluid flow and solute as well as particulate transport in complex hydrogeologic environments.

scholarly journals Scaling laws of ambush predator ‘waiting’ behaviour are tuned to a common ecology

2014 ◽  
Vol 281 (1782) ◽  
pp. 20132997 ◽  
Author(s):  
Victoria J. Wearmouth ◽  
Matthew J. McHugh ◽  
Nicolas E. Humphries ◽  
Aurore Naegelen ◽  
Mohammed Z. Ahmed ◽  
...  
Keyword(s):  
Power Law ◽  
Scaling Laws ◽  
Group Formation ◽  
Waiting Times ◽  
Natural Environments ◽  
Scale Invariant ◽  
Foraging Mode ◽  
Predator Species ◽  
Magnitude Scaling ◽  
Species Specific

The decisions animals make about how long to wait between activities can determine the success of diverse behaviours such as foraging, group formation or risk avoidance. Remarkably, for diverse animal species, including humans, spontaneous patterns of waiting times show random ‘burstiness’ that appears scale-invariant across a broad set of scales. However, a general theory linking this phenomenon across the animal kingdom currently lacks an ecological basis. Here, we demonstrate from tracking the activities of 15 sympatric predator species (cephalopods, sharks, skates and teleosts) under natural and controlled conditions that bursty waiting times are an intrinsic spontaneous behaviour well approximated by heavy-tailed (power-law) models over data ranges up to four orders of magnitude. Scaling exponents quantifying ratios of frequent short to rare very long waits are species-specific, being determined by traits such as foraging mode (active versus ambush predation), body size and prey preference. A stochastic–deterministic decision model reproduced the empirical waiting time scaling and species-specific exponents, indicating that apparently complex scaling can emerge from simple decisions. Results indicate temporal power-law scaling is a behavioural ‘rule of thumb’ that is tuned to species’ ecological traits, implying a common pattern may have naturally evolved that optimizes move–wait decisions in less predictable natural environments.

Distribution pattern of benthic invertebrates in Danish estuaries: The use of Taylor's power law as a species-specific indicator of dispersion and behavior

2013 ◽  
Vol 77 ◽  
pp. 70-78 ◽  
Author(s):  
Erik Kristensen ◽  
Matthieu Delefosse ◽  
Cintia O. Quintana ◽  
Gary T. Banta ◽  
Hans Christian Petersen ◽  
...  
Keyword(s):  
Distribution Pattern ◽  
Power Law ◽  
Benthic Invertebrates ◽  
Taylor’S Power Law ◽  
Taylor's Power Law ◽  
Species Specific ◽  
And Behavior

Spatial and Temporal Dynamics of the Weed Community in a Seashore Paspalum Turf

Weed Science ◽  
2009 ◽  
Vol 57 (3) ◽  
pp. 248-255 ◽  
Author(s):  
Xin-Ming Xie ◽  
You-Zhi Jian ◽  
Xiao-Na Wen
Keyword(s):  
Spatial Heterogeneity ◽  
Power Law ◽  
Temporal Dynamics ◽  
Line Transect ◽  
Frequency Of Occurrence ◽  
Power Law Model ◽  
Seashore Paspalum ◽  
Frequency Distributions ◽  
Weed Communities ◽  
Spatial And Temporal Dynamics

The temporal dynamics of spatial heterogeneity was studied for the weed communities in a seashore paspalum turf with the use of a power-law model. Surveys were conducted in January, March, May, July, September, and November in 2007. In every survey, we set 100 quadrats (50 by 50 cm) referred to as L quadrats on a 50-m line transect at the same position in the turf. Each L quadrat was then divided into four S quadrats (25 by 25 cm) and all plant species occurring in each of these S quadrats were identified and recorded. These data were summarized into frequency distributions and the percentage of S quadrats containing a given species, and the variance of each species was estimated. The power law was used to evaluate the spatial heterogeneity (δ) and frequency of occurrence (p) for each species in the weed communities in six survey months. The results showed that weeds emerged more frequently in the summer–spring season than in winter–autumn, and the spatial heterogeneity was much higher in summer–spring than winter–autumn, especially in summer. The Shannon–Wiener diversity indexes (H') from large to small were July (5.9202) > May (5.6775) > September (5.6631) > March (5.5727) > January (5.1742) > November (4.9668). Likewise, the spatial heterogeneity index (δc) of the whole community was also different in different months. The biggest δc (0.2790) was in July, and the smallest (0.1811) in November. Meanwhile, manilagrass had a high p (= 1.0), indicating that it occurred in all S quadrats in every weed community of every month. However, the turfgrass, seashore paspalum, only emerged in March, May, July, and November, and possessed a low p, indicating the seashore paspalum turf has been naturally replaced by manilagrass.

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