Fuel dynamics and vegetation recovery after fire in a semiarid Australian shrubland

2015 ◽  
Vol 24 (5) ◽  
pp. 613 ◽  
Author(s):  
Sarah A. Dalgleish ◽  
Eddie J. B. van Etten ◽  
William D. Stock ◽  
Chris Knuckey
Keyword(s):  
Vegetation Structure ◽  
Linear Models ◽  
Soil Depth ◽  
Fire Hazard ◽  
Information Criterion ◽  
Lag Effects ◽  
Time Since Fire ◽  
Fuel Dynamics ◽  
Fuel Accumulation ◽  
Negative Exponential

Understanding fuel dynamics in fire-prone ecosystems is important because fuels play a central role in shaping fire hazard and behaviour. There is ongoing debate over whether fire hazard continually increases with time since fire in shrublands of Mediterranean-type climates, and studies of the temporal changes in fuel loads can contribute to this discussion. We used a chronosequence of fire ages to investigate fuel dynamics and recovery of vegetation structure in the Acacia-dominated shrublands of interior south-west Western Australia. We collected and measured fuels from vegetation with fire ages ranging from 6 to 80+ years and then fitted linear, negative exponential, quadratic and logarithmic models to explore temporal patterns of fuel accumulation. Components of fine (<1 cm) fuel (ground, aerial live, aerial dead) and total fine fuel levels were found to accumulate rapidly in the first few years following a fire and then gradually increase for many decades thereafter. On average, total fine fuel was ~10 t ha–1 at 10 years post fire, and ~20 t ha–1 after 40–60 years. Akaike’s Information Criterion did not confidently discriminate between linear models and those that plateau at a certain fire age. However, all models showed gradual accumulation of fuel between 10 and 60 years post fire. Dead fine fuel (both litter and aerial) was virtually absent from young shrubland (<10 years) but accumulated slowly with age and comprised around 40% of total fine fuel in long-unburnt stands (>50 years). Although there is some evidence of shrub senescence in very long-unburnt vegetation (>60 years), no corresponding decline in fuel levels was detected, suggesting lag effects or inter-fire recruitment to maintain vegetation structure and fuel levels. Fuel structure and quantity varied considerably across the landscape, even within areas of the same landform and time since fire. We found that some of this variation was attributable to soil depth but suggest that other environmental factors may also cause variation in vegetation and fuel characteristics.

scholarly journals The Optimal Selection for Restricted Linear Models with Average Estimator

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Qichang Xie ◽  
Meng Du
Keyword(s):  
Model Selection ◽  
Linear Models ◽  
Weighted Average ◽  
Selection Procedure ◽  
Information Criterion ◽  
Optimal Weights ◽  
Model Average ◽  
Squared Error ◽  
Generalized Information Criterion ◽  
Risk Investment

The essential task of risk investment is to select an optimal tracking portfolio among various portfolios. Statistically, this process can be achieved by choosing an optimal restricted linear model. This paper develops a statistical procedure to do this, based on selecting appropriate weights for averaging approximately restricted models. The method of weighted average least squares is adopted to estimate the approximately restricted models under dependent error setting. The optimal weights are selected by minimizing ak-class generalized information criterion (k-GIC), which is an estimate of the average squared error from the model average fit. This model selection procedure is shown to be asymptotically optimal in the sense of obtaining the lowest possible average squared error. Monte Carlo simulations illustrate that the suggested method has comparable efficiency to some alternative model selection techniques.

scholarly journals A global scientific literature of research on water quality indices: trends, biases and future directions

2014 ◽  
Vol 26 (3) ◽  
pp. 245-253 ◽  
Author(s):  
Maria Tereza Ribeiro Alves ◽  
Fabrício Barreto Teresa ◽  
João Carlos Nabout
Keyword(s):  
Water Quality ◽  
Linear Models ◽  
Scientific Literature ◽  
Information Criterion ◽  
The United States ◽  
Water Index ◽  
Resource Managers ◽  
Quality Of Water ◽  
Number Of Publications

AIM: Water quality has been the subject of many recent studies, moreover, the physical, chemical and biological parameters of water are used to investigate water quality and can be combined into a single index, the Water Quality Index (WQI), for use by water resource managers and the general public. The aim of this study was to use scientometrics to evaluate how water quality has been addressed in the international scientific literature. METHOD: For the quantitative analysis of the publications on WQI, we used the search database SCOPUS (http://www.scopus.com). The search was performed using the words "QUALIT* WATER* INDEX*" in papers published in all databases (through 2011). RESULTS: We found 554 articles that dealt with the use of WQI the number of publications has increased significantly over the last 20 years. India had the most studies, with 177 articles, followed by China, Brazil and the United States. These four countries together published 57% of studies on WQI. We generated 15 linear models to explain the number of publication by study sit (country). According to the Akaike Information Criterion (AIC), the best model to explain the number of publications by country was the model that combined Sanitation and Public Supply. CONCLUSION: Finally, this paper presents the state of scientific literature on WQI and demonstrates the growing interest of the scientific community in this issue, which is certainly due to the importance of the quantity and quality of water for human supply, economics, health and the conservation of water resources.

scholarly journals Nonlinear modeling growth body weight of Mangalarga Marchador horses

2017 ◽  
Vol 47 (4) ◽  
Author(s):  
Felipe Amorim Caetano Souza ◽  
Tales Jesus Fernandes ◽  
Raquel Silva de Moura ◽  
Sarah Laguna Conceição Meirelles ◽  
Rafaela Aparecida Ribeiro ◽  
...  
Keyword(s):  
Body Weight ◽  
Linear Models ◽  
Nonlinear Modeling ◽  
Growth Curves ◽  
Live Weight ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Cross Sectional ◽  
Adult Body Weight ◽  
The Cross

ABSTRACT: The analysis of the growth and development of various species has been done using the growth curves of the specific animal based on non-linear models. The objective of the current study was to evaluate the fit of the Brody, Gompertz, Logistic and von Bertalanffy models to the cross-sectional data of the live weight of the MangalargaMarchador horses to identify the best model and make accurate predictions regarding the growth and maturity in the males and females of this breed. The study involved recording the weight of 214 horses, of which 94 were males and 120 were non-pregnant females, between 6 and 153 months of age. The parameters of the model were estimated by employing the method of least squares, using the iteratively regularized Gauss-Newton method and the R software package. Comparison of the models was done based on the following criteria: coefficient of determination (R²); Residual Standard Deviation (RSD); corrected Akaike Information Criterion (AICc). The estimated weight of the adult horses by the models ranged between 431kg and 439kg for males and between 416kg and 420kg for females. The growth curves were studied using the cross-sectional data collection method. For males the von Bertalanffymodel was found to be the most effective in expressing growth, while in females the Brody model was more suitable. The MangalargaMarchador females achieve adult body weight earlier than the males.

scholarly journals Flame Temperatures Saturate with Increasing Dead Material in Ulex europaeus, but Flame Duration, Fuel Consumption and Overall Flammability Continue to Increase

Fire ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 6 ◽  
Author(s):  
Jennifer Dent ◽  
Hannah Buckley ◽  
Audrey Lustig ◽  
Timothy Curran
Keyword(s):  
Linear Relationship ◽  
Fire Hazard ◽  
Maximum Temperature ◽  
Ulex Europaeus ◽  
Plant Trait ◽  
Non Linear ◽  
Dead Material ◽  
Components Analysis ◽  
Fuel Accumulation ◽  
The Relationship

A key determinant of wildfire behaviour is the flammability of constituent plants. One plant trait that influences flammability is the retention of dead biomass, as the low moisture content of dead material means less energy is required to achieve combustion. However, the effect of the dead-to-live ratio of fuel on plant flammability has rarely been experimentally quantified. Here we examine the nature of the relationship between dead fuel accumulation and flammability in Ulex europaeus (common gorse). Shoots with varying proportions of dead material were ignited in a purpose-built plant-burner. Three components of flammability were measured: sustainability (flame duration), consumability (proportion burnt biomass) and combustibility (maximum temperature). While flame duration and proportion burnt biomass had a positive linear relationship with the proportion of dead material, the response of maximum temperature was positive but non-linear. All three flammability components were reduced to a single variable using principal components analysis; this had a non-linear relationship with the proportion of dead material. The response of maximum temperature to dead material plateaued at 39%. These findings have implications for the management of habitats invaded by gorse; to mitigate fire hazard associated with gorse, stands should be kept at a relatively young age when dead fuel is less prevalent.

scholarly journals DELINEATION OF HOMOGENEOUS ZONES BASED ON GEOSTATISTICAL MODELS ROBUST TO OUTLIERS

2019 ◽  
Vol 32 (2) ◽  
pp. 472-481
Author(s):  
DANILO PEREIRA BARBOSA ◽  
EDUARDO LEONEL BOTTEGA ◽  
DOMINGOS SÁRVIO MAGALHÃES VALENTE ◽  
NERILSON TERRA SANTOS ◽  
WELLINGTON DONIZETE GUIMARÃES
Keyword(s):  
Linear Models ◽  
Information Criterion ◽  
Physicochemical Characteristics ◽  
Parameter Estimates ◽  
Mixed Linear Models ◽  
Management Zones ◽  
Geostatistical Models ◽  
Apparent Electrical Conductivity ◽  
External Drift ◽  
Theory And Model

ABSTRACT Measures of the apparent electrical conductivity (ECa) of soil are used in many studies as indicators of spatial variability in physicochemical characteristics of production fields. Based on these measures, management zones (MZs) are delineated to improve agricultural management. However, these measures include outliers. The presence or incorrect identification and exclusion of outliers affect the variogram function and result in unreliable parameter estimates. Thus, the aim of this study was to model ECa data with outliers using methods based on robust approximation theory and model-based geostatistics to delineate MZs. Robust estimators developed by Cressie-Hawkins, Genton and MAD Dowd were tested. The Cressie-Hawkins semivariance estimator was selected, followed by the semivariogram cubic fit using Akaike information criterion (AIC). The robust kriging with an external drift plug-in was applied to fitted estimates, and the fuzzy k-means classifier was applied to the resulting ECa kriging map. Models with multiple MZs were evaluated using fuzzy k-means, and a map with two MZs was selected based on the fuzzy performance index (FPI), modified partition entropy (MPE) and Fukuyama-Sugeno and Xie-Beni indices. The defined MZs were validated based on differences between the ECa means using mixed linear models. The independent errors model was chosen for validation based on its AIC value. Thus, the results demonstrate that it is possible to delineate an MZ map without outlier exclusion, evidencing the efficacy of this methodology.

scholarly journals Prerecruit survival and recruitment of northern Gulf of St Lawrence Atlantic cod

2008 ◽  
Vol 65 (6) ◽  
pp. 946-952 ◽  
Author(s):  
Daniel E. Duplisea ◽  
Dominique Robert
Keyword(s):  
Linear Models ◽  
Atlantic Cod ◽  
Information Criterion ◽  
Factors Affecting ◽  
Control Rules ◽  
Strategy Evaluation ◽  
Stock Biomass ◽  
Spawning Stock ◽  
Long Time ◽  
Parsimonious Model

Abstract Duplisea, D. E., and Robert, D. 2008. Prerecruit survival and recruitment of northern Gulf of St Lawrence Atlantic cod. – ICES Journal of Marine Science, 65: 946–952. Recruitment (R) of exploited marine fish populations is usually modelled exclusively as a function of spawning-stock biomass (SSB). A problem arising when modelling over long time-series is that the nature of the R–SSB relationship is unlikely to be stationary. Changes are often interpreted as productivity regime shifts and are linked to alterations in prerecruit survival rate. We examine the role of environment and predation by fish and harp seals as factors affecting the R–SSB relationship in the northern Gulf of St Lawrence cod, by fitting linear models using combinations of covariates to explain cod prerecruit survival. The most parsimonious model (based on a Bayesian Information Criterion, BIC) included cod, mackerel, and temperature, whereas redfish and seals did not appear in any of the best-fit models. Recruitment models derived from this analysis could be used in operating models for management strategy evaluation simulations for northern Gulf cod, so one could develop harvest control rules that are robust to changes in recruitment productivity regimes.

scholarly journals Describing the growth curve of local turkey using non-linear models

2018 ◽  
pp. 7104-7107
Author(s):  
Aureliano Juárez-Caratachea ◽  
Iván Delgado-Hurtado ◽  
Ernestina Gutiérrez-Vázquez ◽  
Guillermo Salas-Razo ◽  
Ruy Ortiz-Rodríguez ◽  
...  
Keyword(s):  
Growth Curve ◽  
Visual Analysis ◽  
Linear Models ◽  
Logistic Models ◽  
Information Criterion ◽  
Von Bertalanffy ◽  
Commercial Feed ◽  
Non Linear ◽  
Best Fitting ◽  
Multiple Determination

Objective. Determine the best non-linear model to fit the growth curve of local turkeys managed under confinement in Michoacan, Mexico. Material and methods. Twenty-four and 43 female and male turkeys, reared under commercial conditions were given commercial feed. Birds were weighed weekly from hatch to 29 weeks of age. The Gompertz, Brody, Richards, von Bertalanffy and Logistic models were chosen to describe the age-weight relationship. Results. The best fitting model was selected based on the multiple determination coefficient (R2), the Akaike information criterion (AIC) and visual analysis of the observed and predicted curves. In both female and male, von Bertalanffy was the best model. The highest estimates of parameter A (mature weight) for both females and males were obtained with the von Bertalanffy model followed by the Gompertz and Logistic. The estimates of A were higher for males than for females. The highest estimates of parameter k (rate of maturity) for both females and males were, in decreasing order, for the Logistic, Gompertz, and von Bertalanffy models. k values for female turkeys was higher than for males. The age at the point of inflection (TI) and body weight at the age of point of inflection (WI) varied with the model used. The largest values of TI and WI corresponded to the Logistic model. Between sexes, the largest TI and WI values corresponded to males. Conclusions. The best models to describe turkey growth was the von Bertalanffy because it present the highest R2 and lowest AIC values.

scholarly journals Habitat is More Important Than Climate and Animal Richness in Shaping Latitudinal Variation in Plant Diversity

2018 ◽  
Author(s):  
Gao Jie ◽  
Liu Yanhong ◽  
Du Xue ◽  
Marc Bogonovich
Keyword(s):  
Plant Diversity ◽  
Linear Models ◽  
Information Criterion ◽  
Variance Partitioning ◽  
Latitudinal Gradients ◽  
Total Species Richness ◽  
Plant Groups ◽  
Energy Variable ◽  
Independent Effects ◽  
Habitat Variables

Species data of 249 National Nature Reserves in China was used to identify potential underlying drivers of latitudinal gradients in plant diversity. We used generalized linear models (GLMs) to assess the correlations between predictor and response variables. We also used SAM (Spatial Analysis in Macroecology) to eliminate autocorrelation along each of the 249 studied locations. We used the Akaike information criterion (AICc; Montoya et al. 2007) to select the independent variables were those included in the best models from different combinations of climate, habitat and animal variables. Variance partitioning was used to decompose the variation in plant richness across different taxonomic levels among the three groups of predictors. We found that: Total plant species, gymnosperms, angiosperms and ferns showed significant latitudinal trends in richness (p &lt; 0.001). Water-energy and habitat variables generally explained more variation in richness across different plant groups than did animal richness. Annual precipitation was selected as the best water-energy variable across different taxonomic plants groups, soil PH and elevation range were selected as the best habitat variables across different taxonomic plant groups. The independent effects of habitatvariables were higher than that of water-energy and animal variables across different taxonomic plants groups. Water-energy, habitat heterogeneity, and animal variables explain 48.8% of the variation in total species richness, 28.2% in gymnosperm richness, 44.2% in angiosperm richness, and 38.9% in fern richness.Plants showed significant latitudinal trends in richness (p &lt; 0.001). Water-energy and habitat variables generally explained more variation in richness across different taxonomic plants groups than did animal variables. The independent effects of habitat variables were higher than those of water-energy and animal variables across different taxonomic plants groups.

scholarly journals Comparación entre dos modelos estructurados por edades, aplicados a la pesquería de langosta, Panulirus Argus (Latreille, 1804), en la región suroriental de Cuba

2012 ◽  
Vol 3 ◽  
pp. 131
Author(s):  
Romina Alzugaray Martínez ◽  
Rafael Puga Millán
Keyword(s):  
Linear Models ◽  
Population Analysis ◽  
Spiny Lobster ◽  
Information Criterion ◽  
Fishing Effort ◽  
Panulirus Argus ◽  
Catch Per Unit Effort ◽  
Raw Data ◽  
Linear Relationships ◽  
Exploitation Status

La langosta común, Panulirus argus, es una de las especies con mayor valor comercial en el Atlántico Centro Occidental. En Cuba se han realizado numerosos estudios para conocer y actualizar su estado de explotación y recomendar medidas de manejo. A pesar de estas medidas, las capturas continúan disminuyendo, por lo que el objetivo del presente estudio consistió en evaluar la dinámica de la población de langosta en la región suroriental de Cuba, a través de dos estrategias analíticas diferentes. A partir de datos de captura y esfuerzo pesquero de 1979-2010, se aplicaron un análisis de población virtual (VPA) y un análisis estadístico de captura por edades (SCA). Se examinó la relación lineal entre los datos primarios y las variables estimadas por los modelos. El ajuste de los modelos lineales de los datos se evaluó mediante el Criterio de Información de Akaike corregido (AICc). Según ambos métodos de captura por edades, el tamaño poblacional y el reclutamiento de langostas con un año de edad han disminuido en la región en el período estudiado, aunque el SCA muestra estabilización en la última década. Mientras, la biomasa poblacional disminuyó hasta estabilizarse en la última década, lo cual puede relacionarse con el comportamiento histórico de la captura por unidad de esfuerzo. Existen asociaciones lineales significativas entre los datos primarios y las variables estimadas. Según los valores de Δi, el modelo VPA garantiza el mejor ajuste de las variables a las relaciones lineales estimadas. Abstract Spiny lobster, Panulirus argus, is one of the most commercially valuable species in the Western Central Atlantic. Although numerous studies have been conducted in Cuba to learn and update its exploitation status and to recommend management measures, catches continue to decline. Consequently, the objective of this study was to evaluate the dynamics of the lobster population in Cuba’s southeastern region, through two different analytical strategies. Using catch and fishing effort data from 1979-2010, a Virtual Population Analysis (VPA) and a Statistical Catch-at-age Analysis (SCA) were applied. We examined the linear relationship between raw data and the variables estimated by the models. The fit of the linear models to data was assessed using the corrected Akaike Information Criterion (AICc). According to both age-structured methods, population size and recruitment of one year old lobster have declined in the region during the study period, although the SCA shows stabilization in the last decade. Population biomass decreased to stabilize in the last decade, this may relate to the historical behavior of the catch per unit effort. There are significant linear associations between raw data and estimated variables. According to Δi values, the VPA model ensures the best fit for the variables of estimated linear relationships.

scholarly journals Why analyze germination experiments using Generalized Linear Models?

2018 ◽  
Vol 40 (3) ◽  
pp. 281-287 ◽  
Author(s):  
Fábio Janoni Carvalho ◽  
Denise Garcia de Santana ◽  
Lúcio Borges de Araújo
Keyword(s):  
Generalized Linear Models ◽  
Binomial Distribution ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Binomial Model ◽  
Inappropriate Use ◽  
Copaiba Oil ◽  
Germination Experiments ◽  
Combined Data

Abstract: We compared the goodness of fit and efficiency of models for germination. Generalized Linear Models (GLMs) were performed with a randomized component corresponding to the percentage of germination for a normal distribution or to the number of germinated seeds for a binomial distribution. Lower levels of Akaikes’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) combined, data adherence to simulated envelopes of normal plots and corrected confidence intervals for the means guaranteed the binomial model a better fit, justifying the importance of GLMs with binomial distribution. Some authors criticize the inappropriate use of analysis of variance (ANOVA) for discrete data such as copaiba oil, but we noted that all model assumptions were met, even though the species had dormant seeds with irregular germination.

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