Likelihood and frequency of recurrent fire ignitions in highly urbanised Mediterranean landscapes

2020 ◽  
Vol 29 (2) ◽  
pp. 120 ◽  
Author(s):  
Mario Elia ◽  
Vincenzo Giannico ◽  
Giuseppina Spano ◽  
Raffaele Lafortezza ◽  
Giovanni Sanesi
Keyword(s):  
Negative Binomial ◽  
Negative Relationship ◽  
Mediterranean Ecosystems ◽  
Short Term ◽  
Local Data ◽  
Response Variable ◽  
Fire Recurrence ◽  
Mediterranean Landscapes ◽  
Fire Ignition ◽  
Road Distance

Fire recurrence plays a key role in shaping landscapes in Mediterranean ecosystems. Short-term recurrent fires, in particular, are increasingly affecting highly urbanised landscapes. Studies worldwide have addressed fire recurrence by analysing environmental, climatic and human-driven factors. Current models use fire recurrence polygons as the dependent variable; yet no published study has focused its analysis on fire recurrence considering recurrent ignition points as the response variable. To fill this gap, remote sensing and available local data were combined to analyse the influence of human and biophysical variables in predicting both the likelihood and frequency of recurrent fire ignition points over a 9-year period (2004–12) in southern Italy. For this purpose, we used the Negative Binomial Hurdle model owing to the stochastic nature of the phenomenon of fire recurrence and the (large) number of non-occurrences. Results on the likelihood and frequency of recurrent fire ignition points (dependent variables) suggested that road distance was the strongest predictor, followed by the presence of shrublands and grasslands. The response variable showed a negative relationship with population density and road distance and a positive relationship with land-cover variables. Vegetation indices were also good predictors of fire recurrence. More broadly, this study is intended to be a further experimental step in fire-management analysis characterised by the continuous interaction between human and natural systems. Constant changes between these systems due to causes such as urban sprawl and climate change can create the conditions for short-term-interval recurrent fires.

scholarly journals Modeling fire ignition probability and frequency using Hurdle models: a cross-regional study in Southern Europe

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Marina D’Este ◽  
Antonio Ganga ◽  
Mario Elia ◽  
Raffaella Lovreglio ◽  
Vincenzo Giannico ◽  
...  
Keyword(s):  
Mediterranean Basin ◽  
Negative Binomial ◽  
Pearson Correlation ◽  
Fire Occurrence ◽  
Ignition Probability ◽  
Hurdle Models ◽  
Mediterranean Landscapes ◽  
The Mediterranean ◽  
Fire Ignition ◽  
The Mediterranean Basin

Abstract Background Wildfires play a key role in shaping Mediterranean landscapes and ecosystems and in impacting species dynamics. Numerous studies have investigated the wildfire occurrences and the influence of their drivers in many countries of the Mediterranean Basin. However, in this regard, no studies have attempted to compare different Mediterranean regions, which may appear similar under many aspects. In response to this gap, climatic, topographic, anthropic, and landscape drivers were analyzed and compared to assess the patterns of fire ignition points in terms of fire occurrence and frequency in Catalonia (Spain), Sardinia, and Apulia (Italy). Therefore, the objectives of the study were to (1) assess fire ignition occurrence in terms of probability and frequency, (2) compare the main drivers affecting fire occurrence, and (3) produce fire probability and frequency maps for each region. Results In pursuit of the above, the probability of fire ignition occurrence and frequency was mapped using Negative Binomial Hurdle models, while the models’ performances were evaluated using several metrics (AUC, prediction accuracy, RMSE, and the Pearson correlation coefficient). The results showed an inverse correlation between distance from infrastructures (i.e., urban roads and areas) and the occurrence of fires in all three study regions. This relationship became more significant when the frequency of fire ignition points was assessed. Moreover, a positive correlation was found between fire occurrence and landscape drivers according to region. The land cover classes more significantly affected were forest, agriculture, and grassland for Catalonia, Sardinia, and Apulia, respectively. Conclusions Compared to the climatic, topographic, and landscape drivers, anthropic activity significantly influences fire ignition and frequency in all three regions. When the distance from urban roads and areas decreases, the probability of fire ignition occurrence and frequency increases. Consequently, it is essential to implement long- to medium-term intervention plans to reduce the proximity between potential ignition points and fuels. In this perspective, the present study provides an applicable decision-making tool to improve wildfire prevention strategies at the European level in an area like the Mediterranean Basin where a profuse number of wildfires take place.

scholarly journals Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Mark Ashworth ◽  
◽  
Antonis Analitis ◽  
David Whitney ◽  
Evangelia Samoli ◽  
...  
Keyword(s):  
Primary Care ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Air Pollutant ◽  
Respiratory Morbidity ◽  
Short Term ◽  
Short Term Exposure ◽  
Short And Long Term ◽  
Spatio Temporal

Abstract Background Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. Methods Daily primary care data, for 2009–2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. Results The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 μg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. Conclusions We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

scholarly journals Short-Term N-Fertilization Differently Affects the Leaf and Leaf Litter Chemistry of the Dominant Species in a Mediterranean Forest under Drought Conditions

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 605
Author(s):  
Helena Vallicrosa ◽  
Jordi Sardans ◽  
Romà Ogaya ◽  
Pere Roc Fernández ◽  
Josep Peñuelas
Keyword(s):  
Leaf Litter ◽  
Dominant Species ◽  
Isotope Analysis ◽  
Mediterranean Ecosystems ◽  
N Fertilization ◽  
N Deposition ◽  
Mediterranean Forest ◽  
Short Term ◽  
Species Response ◽  
Drought Conditions

Nitrogen (N) deposition is a key driver of global change with significant effects on carbon (C) cycling, species fitness, and diversity; however, its effects on Mediterranean ecosystems are unclear. Here, we simulated N deposition in an N-fertilization experiment with 15N-labeled fertilizer in a montane evergreen Mediterranean holm oak forest, in central Catalonia, to quantify short-term impacts on leaf, leaf litter elemental composition, and resorption efficiency in three dominant species (Quercus ilex, Phillyrea latifolia, and Arbutus unedo). We found that even under drought conditions, 15N isotope analysis of leaf and leaf litter showed a rapid uptake of the added N, suggesting an N deficient ecosystem. Species responses to N fertilization varied, where A. unedo was unaffected and the responses in P. latifolia and Q. ilex were similar, albeit with contrasting magnitude. P. latifolia benefited the most from N fertilization under drought conditions of the experimental year. These differences in species response could indicate impacts on species fitness, competition, and abundance under increased N loads in Mediterranean forest ecosystems. Further research is needed to disentangle interactions between long-term N deposition and the drought predicted under future climate scenarios in Mediterranean ecosystems.

Athletic Scholarships in Intercollegiate Football

2011 ◽  
Vol 13 (5) ◽  
pp. 515-535 ◽  
Author(s):  
Joshua D. Pitts ◽  
Jon Paul Rezek
Keyword(s):  
High School ◽  
Intercollegiate Athletics ◽  
Negative Binomial ◽  
Negative Relationship ◽  
Field Performance ◽  
The United States ◽  
Football Players ◽  
High School Football ◽  
Football Coaches ◽  
Athletic Scholarships

Despite the financial and cultural importance of intercollegiate athletics in the United States, there is a paucity of research into how athletic scholarships are awarded. In this article, the authors empirically examine the factors that universities use in their decision to offer athletic scholarships to high school football players. Using a Zero-Inflated Negative Binomial (ZINB) model, the authors find a player’s weight, height, body mass index (BMI), race, speed, on-the-field performance, and his high school team’s success often have large and significant impacts on the number of scholarship offers he receives. There is also evidence of a negative relationship between academic performance and scholarship offers. In addition, the authors find evidence of a scholarship premium for players from Florida and Texas. The results also show that running backs, wide receivers, and defensive backs appear to generate the most attention from college football coaches, other things equal.

Helminth communities in amphibians from Latvia, with an emphasis on their connection to host ecology

2021 ◽  
Vol 95 ◽  
Author(s):  
A. Čeirāns ◽  
E. Gravele ◽  
I. Gavarane ◽  
M. Pupins ◽  
L. Mezaraupe ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Negative Relationship ◽  
Rank Correlation ◽  
Nematode Species ◽  
Bufo Bufo ◽  
Host Size ◽  
Trematode Species ◽  
Ecological Groups ◽  
Food Object ◽  
Linear Discriminant

Abstract Helminth infracommunities were studied at 174 sites of Latvia in seven hosts from six amphibian taxa of different taxonomical, ontogenic and ecological groups. They were described using a standard set of parasitological parameters, compared by ecological indices and linear discriminant analysis. Their species associations were identified by Kendall's rank correlation, but relationships with host size and waterbody area were analysed by zero-inflated Poisson and zero-inflated negative binomial regressions. The richest communities (25 species) were found in post-metamorphic semi-aquatic Pelophylax spp. frogs, which were dominated by trematode species of both adult and larval stages. Both larval and terrestrial hosts yielded depauperate trematode communities with accession of aquatic and soil-transmitted nematode species, respectively. Nematode loads peaked in terrestrial Bufo bufo. Helminth infracommunities suggested some differences in host microhabitat or food object selection not detected by their ecology studies. Associations were present in 96% of helminth species (on average, 7.3 associations per species) and dominated positive ones. Species richness and abundances, in most cases, were positively correlated with host size, which could be explained by increasing parasite intake rates over host ontogeny (trematode adult stages) or parasite accumulation (larval Alaria alata). Two larval diplostomid species (Strigea strigis, Tylodelphys excavata) had a negative relationship with host size, which could be caused by parasite-induced host mortality. The adult trematode abundances were higher in larger waterbodies, most likely due to their ecosystem richness, while higher larval abundances in smaller waterbodies could be caused by elevated infection rates under high host densities.

scholarly journals PERBANDINGAN REGRESI ZERO INFLATED POISSON (ZIP) DAN REGRESI ZERO INFLATED NEGATIVE BINOMIAL (ZINB) PADA DATA OVERDISPERSION (Studi Kasus: Angka Kematian Ibu di Provinsi Bali)

2016 ◽  
Vol 5 (4) ◽  
pp. 133
Author(s):  
NI PUTU PREMA DEWANTI ◽  
MADE SUSILAWATI ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Mortality Rate ◽  
Maternal Mortality ◽  
Regression Models ◽  
Negative Binomial ◽  
Mean Value ◽  
Response Variable ◽  
Maternal Mortality Rate ◽  
Excess Zeros ◽  
Zero Values ◽  
Independent Variable

Poisson regression is a nonlinear regression which is often used for count data and has equidispersion assumption (variance value equal to mean value). However in practice, equidispersion assumption is often violated. One of it violations is overdispersion (variance value greater than the mean value). One of the causes of overdipersion is excessive number of zero values on the response variable (excess zeros). There are many methods to handle overdispersion because of excess zeros. Two of them are Zero Inflated Poisson (ZIP) regression and Zero Inflated Negative Binomial (ZINB) regression. The purpose of this research is to determine which regression models is better in handling overdispersion data. The data that can be analyzed using the ZIP and ZINB regression is maternal mortality rate in the Province of Bali. Maternal mortality rate data has proportion of zeros value more than 50% on the response variable.  In this research, ZINB regression better than ZIP regression for modeling maternal mortality rate. The independent variable that affects the number of maternal mortality rate in the Province of Bali  is the percentage of mothers who carry a pregnancy visit, with ZINB regression models and . 

scholarly journals Kecerdasan Emosi Dan Depresi Pada Mahasiswa Yang Sudah Menikah

2019 ◽  
Vol 6 (2) ◽  
pp. 146
Author(s):  
Azizah Fitriah
Keyword(s):  
Emotional Intelligence ◽  
Hypothesis Test ◽  
Negative Relationship ◽  
Field Research ◽  
Short Term ◽  
Significant Negative Relationship ◽  
Correlational Approach ◽  
The Individual ◽  
Married Students ◽  
The Relationship

Every human being will one day experience a tense period in the short term when facing known problems such as career pressures, family disputes or quarrels, material pressures, and personal despair, and we will think that this is depression, which is not is an important problem because it will resolve itself, but none of these fleeting conditions is depression. Good emotional intelligence can reduce aggression, especially in adolescents. Therefore, if emotions are managed successfully, the individual will be able to entertain themselves when overwritten by sadness, can release anxiety, moodiness or offense and rise quickly again from it all. This research is field research with a correlational approach, exploring the relationship between depression and emotional intelligence in married students. The results of the hypothesis test show that between emotional intelligence and depression in married students has a significant negative relationship (XY = -0.411; sig = 0.014 <0.05). This is in accordance with the data obtained from the SPSS 19 for Windows program, stating that r table 0.334 and r xy (r hit) -0.411, said to be significant if r xy = 0.411> r table = 0.334. In other words, the higher the emotional intelligence of students who are married, the lower the possibility of depression.

scholarly journals Effects of seasonality and land use on the abundance and distribution of mosquitoes on St. Kitts, West Indies

2020 ◽  
Author(s):  
Matthew J. Valentine ◽  
Brenda Ciraola ◽  
Gregory R. Jacobs ◽  
Charlie Arnot ◽  
Patrick J. Kelly ◽  
...  
Keyword(s):  
Land Cover ◽  
Disease Transmission ◽  
Negative Binomial ◽  
Mosquito Control ◽  
Mosquito Species ◽  
Negative Binomial Regression ◽  
Common Species ◽  
Negative Binomial Regression Model ◽  
Local Data ◽  
Land Covers

AbstractBackgroundHigh quality mosquito surveys that collect fine resolution local data on mosquito species’ abundances provide baseline data to help us understand potential host-pathogen-mosquito relationships, accurately predict disease transmission, and target mosquito control efforts in areas at risk of mosquito borne diseases.MethodsAs part of an investigation into arboviral sylvatic cycles on the Caribbean island of St. Kitts, we carried out an island wide mosquito survey from November 2017 to March 2019. Using Biogents Sentinel 2 and miniature CDC light traps that were set monthly and run for 48 hour intervals, we collected mosquitoes from a total of 30 sites distributed across the five common land covers on the island (agricultural, mangrove, rainforest, scrub, and urban). We developed a mixed effects negative binomial regression model to predict the effects of land cover, seasonality, and precipitation on observed counts of the most abundant mosquito species we found.ResultsWe captured 10 of the 14 mosquito species reported on the island, the four most abundant being Aedes taeniorhynchus, Culex quinquefasciatus, Aedes aegpyti, and Deinocerites magnus. Sampling in the mangroves yielded the most mosquitoes, with Ae. taeniorhynchus, Cx. quinquefasciatus, and De. magnus predominating. Aedes aegypti was recovered primarily from urban and agricultural habitats, but also at lower frequency in other land covers. Psorophora pygmaea and Toxorhynchites guadeloupensis were only captured in scrub habitat. Capture rates in rainforests were low. Our models indicated the relative abundance of the four most common species varied seasonally and with land cover. They also suggested that the extent to which monthly average precipitation influenced counts varied according to species.ConclusionsThis study demonstrates there is high seasonality in mosquito abundances and that land cover influenced the distribution and abundance of mosquito species on St. Kitts. Further, human-adapted mosquito species (e.g. Ae. aegypti and Cx. quinquefasciatus) that are known vectors for many human relevant pathogens are the most wide-spread (across land covers) and the least responsive to seasonal variation in precipitation.

scholarly journals Capital Structure and The Profitability of Listed Retail Firms

2018 ◽  
Vol 10 (1(J)) ◽  
pp. 171-181
Author(s):  
Jason Stephen Kasozi
Keyword(s):  
Capital Structure ◽  
Negative Relationship ◽  
Order Theory ◽  
Debt Financing ◽  
Retail Sector ◽  
Short Term ◽  
Return On Assets ◽  
Pecking Order Theory ◽  
Policy Interventions

The South African retail sector continues to experience a decline in sales and returns amidst growing external competition and a drop in consumer confidence stemming from the recent credit downgrades in the country. Yet, firms in this sector appear to maintain high debt to equity levels. This study investigated whether the capital structure practices of these firms influence their profitability. A Panel data methodology, using three regression estimators, is applied to a balanced sample of 16 retail firms listed on the Johannesburg Securities Exchange (JSE) during the period 2008-2016. The analysis estimates functions relating capital structure composition with the return on assets (ROA). Results reveal a statistically significant but negative relationship between all measures of debt (short-term, long-term, total debt) with profitability, suggesting a possible inclination towards the pecking order theory of financing behaviour, for listed retail firms. Additionally, retail firms are highly leveraged yet over 75% of this debt is short-term in nature. Policy interventions need to investigate the current restrictions on long-term debt financing which offers longerterm and affordable financing, to boost returns. While this study’s methodology differs slightly from earlier studies, it incorporates vital aspects from these studies, and simultaneously specifies a possible model fit.  This helps to capture unique but salient characteristics like the transitional effects of debt financing on firm profitability.  It therefore delivers some unique findings on the financing behaviour of retail firms that both in form policy change, while stimulating further research on the phenomenon. 

scholarly journals PENERAPAN REGRESI BINOMIAL NEGATIF UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON

2013 ◽  
Vol 2 (2) ◽  
pp. 6
Author(s):  
PUTU SUSAN PRADAWATI ◽  
KOMANG GDE SUKARSA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Poisson Regression ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Poisson Regression Model ◽  
Response Variable ◽  
Poisson Regression Analysis ◽  
Binomial Regression ◽  
The Mean

Poisson regression was used to analyze the count data which Poisson distributed. Poisson regression analysis requires state equidispersion, in which the mean value of the response variable is equal to the value of the variance. However, there are deviations in which the value of the response variable variance is greater than the mean. This is called overdispersion. If overdispersion happens and Poisson Regression analysis is being used, then underestimated standard errors will be obtained. Negative Binomial Regression can handle overdispersion because it contains a dispersion parameter. From the simulation data which experienced overdispersion in the Poisson Regression model it was found that the Negative Binomial Regression was better than the Poisson Regression model.

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