Reconstructing the history of forest fire frequency: Identifying hazard rate change points using the bayes information criterion

2000 ◽  
Vol 28 (2) ◽  
pp. 353-365 ◽  
Author(s):  
William J. Reed
2021 ◽  
Author(s):  
Andri A Wibowo

Felids are mammal groups that also experiencing the effects of forest fire and deforestation rate. By using camera detection method, two felid species, Prionailurus bengalensis and Pardofelis marmorata, of tropical rainforests in SE Asia have been studied. The studied area was a rainforest in Sumatra that has experienced several forest fires with annual deforestation rates of 1.69%-2.89%. Occupancy model using Akaike Information Criterion (AIC) is in agreement that deforestation rate is the best explanatory covariate explaining the declining occupancy of those felid species. P. marmorata was known more sensitive to the both deforestation rate and forest fire frequency covariate effects since it has similar AIC values. While P. bengalensis was slightly affected by forest fires. Values of Area Under The Curve (AUC) of Receiver Operating Characteristic (ROC) were >0.5 and these indicate adequate probability of forest fire effects on felid occupancy. Cut off value of occupancy of P. bengalensis was higher than P. marmorata. For P. bengalensis, the cut off value was 1.75 leading to a sensitivity and specificity of 62%. This is the threshold value for the prediction of numbers of P. bengalensis individual occurred where both sensitivity and specificity are maximized and as an effect of forest fire, and this can be used to classify areas as occupied by P. bengalensis.


Risks ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
Karim Barigou ◽  
Stéphane Loisel ◽  
Yahia Salhi

Predicting the evolution of mortality rates plays a central role for life insurance and pension funds. Standard single population models typically suffer from two major drawbacks: on the one hand, they use a large number of parameters compared to the sample size and, on the other hand, model choice is still often based on in-sample criterion, such as the Bayes information criterion (BIC), and therefore not on the ability to predict. In this paper, we develop a model based on a decomposition of the mortality surface into a polynomial basis. Then, we show how regularization techniques and cross-validation can be used to obtain a parsimonious and coherent predictive model for mortality forecasting. We analyze how COVID-19-type effects can affect predictions in our approach and in the classical one. In particular, death rates forecasts tend to be more robust compared to models with a cohort effect, and the regularized model outperforms the so-called P-spline model in terms of prediction and stability.


Metrika ◽  
2021 ◽  
Author(s):  
Andreas Anastasiou ◽  
Piotr Fryzlewicz

AbstractWe introduce a new approach, called Isolate-Detect (ID), for the consistent estimation of the number and location of multiple generalized change-points in noisy data sequences. Examples of signal changes that ID can deal with are changes in the mean of a piecewise-constant signal and changes, continuous or not, in the linear trend. The number of change-points can increase with the sample size. Our method is based on an isolation technique, which prevents the consideration of intervals that contain more than one change-point. This isolation enhances ID’s accuracy as it allows for detection in the presence of frequent changes of possibly small magnitudes. In ID, model selection is carried out via thresholding, or an information criterion, or SDLL, or a hybrid involving the former two. The hybrid model selection leads to a general method with very good practical performance and minimal parameter choice. In the scenarios tested, ID is at least as accurate as the state-of-the-art methods; most of the times it outperforms them. ID is implemented in the R packages IDetect and breakfast, available from CRAN.


2019 ◽  
Vol 74 (8) ◽  
pp. 2440-2450 ◽  
Author(s):  
Victoria Palin ◽  
Anna Mölter ◽  
Miguel Belmonte ◽  
Darren M Ashcroft ◽  
Andrew White ◽  
...  

Abstract Objectives To examine variations across general practices and factors associated with antibiotic prescribing for common infections in UK primary care to identify potential targets for improvement and optimization of prescribing. Methods Oral antibiotic prescribing for common infections was analysed using anonymized UK primary care electronic health records between 2000 and 2015 using the Clinical Practice Research Datalink (CPRD). The rate of prescribing for each condition was observed over time and mean change points were compared with national guideline updates. Any correlation between the rate of prescribing for each infectious condition was estimated within a practice. Predictors of prescribing were estimated using logistic regression in a matched patient cohort (1:1 by age, sex and calendar time). Results Over 8 million patient records were examined in 587 UK general practices. Practices varied considerably in their propensity to prescribe antibiotics and this variance increased over time. Change points in prescribing did not reflect updates to national guidelines. Prescribing levels within practices were not consistent for different infectious conditions. A history of antibiotic use significantly increased the risk of receiving a subsequent antibiotic (by 22%–48% for patients with three or more antibiotic prescriptions in the past 12 months), as did higher BMI, history of smoking and flu vaccinations. Other drivers for receiving an antibiotic varied considerably for each condition. Conclusions Large variability in antibiotic prescribing between practices and within practices was observed. Prescribing guidelines alone do not positively influence a change in prescribing, suggesting more targeted interventions are required to optimize antibiotic prescribing in the UK.


2008 ◽  
Vol 80 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Mauro B. de Toledo ◽  
Mark B. Bush

The main goal of this study was to investigate how climate and human activities may have influenced ecotonal areas of disjoint savannas within Brazilian Amazonia. The fossil pollen and charcoal records of Lake Márcio (Amapá) were used to provide a Holocene palaeoecological history of this region. Detrended correspondence analysis (DCA) was used to enhance the patterns of sample distribution along the sediment core. A marked vegetation change from closed forests with swamp elements to open flooded savanna at c. 5000 yrs BP was evident from the pollen record. Charcoal analysis revealed a pattern of increased accumulation of particles coincident with the establishment of savannas, suggesting higher fire frequency and human impacts near the lake. A 550-year sedimentary hiatus suggests that the lake depended heavily on floodwaters from the Amazon River, and that it became suddenly isolated from it. When sedimentation restarted in the lake, the environment had changed. A combination of factors, such as reduced river flooding, palaeofires and human occupation may have had a tremendous impact on the environment. As there are no other major changes in vegetation, after 4700 yrs BP, it is plausible to assume that the modern mosaic vegetation formed at that time.


2020 ◽  
Vol 148 ◽  
pp. 106820
Author(s):  
Manuelita Sotelo-Muñoz ◽  
Marcos Maldonado-Coelho ◽  
Maria Svensson-Coelho ◽  
Sidnei S. dos Santos ◽  
Cristina Y. Miyaki

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 471
Author(s):  
Dariusz Kulak ◽  
Janusz M. Sowa ◽  
Grzegorz Szewczyk ◽  
Arkadiusz Stańczykiewicz

In 1992, in Southern Poland, large areas of Silesian forests were affected by the country’s largest forest fire. Stands introduced in the 9000-ha post-fire region are currently undergoing early thinning. Due to the scope of these treatments, the chance for their timely implementation is ensured only by the application of cut-to-length (CTL) technologies, i.e., with the use of harvesters and forwarders. The use of CTL technologies may, however, be difficult due to the fire history of these stands, which could affect the bearing capacity of their soils. The objective of this study is to determine the accessibility of stands for forest machines in relation to the bearing capacity of the soils and changes in soil compaction in the post-fire sites. Soil compaction was measured in terms of penetrometer resistance in the stands introduced in the post-fire area in question, as well as in control stands growing on five different soil types. It was shown that in the topsoil layer—from 8 to 18 cm thick depending on the soil type—differences in soil compaction in the post-fire and control areas were relatively small. The impacts of the forest fire—manifested as a significant increase in the compaction of the forest soils—were still visible, but only in the deeper layers of the soil profile. In all of the compared pairs of forest compartments located in the stands regenerated after the fire, significantly higher values of cone indexes (CI) were found. The average value of this index in the post-fire stands was 2.15 MPa, while in the control stands it was 1.60 MPa, which indicates that in both groups of stands the bearing capacity of the soils should not limit the accessibility for vehicles used for timber harvesting and extraction.


2012 ◽  
Vol 77 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Damien Rius ◽  
Boris Vanniére ◽  
Didier Galop

Located on a mountain pass in the west-central Pyrenees, the Col d'Ech peat bog provides a Holocene fire and vegetation record based upon nine 14C (AMS) dates. We aim to compare climate-driven versus human-driven fire regimes in terms of frequency, fire episodes distribution, and impact on vegetation. Our results show the mid-Holocene (8500–5500 cal yr BP) to be characterized by high fire frequency linked with drier and warmer conditions. However, fire occurrences appear to have been rather stochastic as underlined by a scattered chronological distribution. Wetter and colder conditions at the mid-to-late Holocene transition (4000–3000 cal yr BP) led to a decrease in fire frequency, probably driven by both climate and a subsequent reduction in human land use. On the contrary, from 3000 cal yr BP, fire frequency seems to be driven by agro-pastoral activities with a very regular distribution of events. During this period fire was used as a prominent agent of landscape management.


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