scholarly journals Simulating the effects of weather and climate on large wildfires in France

2018 ◽  
Author(s):  
Renaud Barbero ◽  
Thomas Curt ◽  
Anne Ganteaume ◽  
Eric Maillé ◽  
Marielle Jappiot ◽  
...  
Keyword(s):  
Linear Models ◽  
Weather Conditions ◽  
Historical Period ◽  
Natural Ecosystem ◽  
Atmospheric Variability ◽  
Modeling Framework ◽  
Weather And Climate ◽  
Change Context ◽  
Spatio Temporal

Abstract. Large wildfires across parts of France can cause devastating damages which put lives, infrastructures, and natural ecosystem at risk. One of the most challenging questions in the climate change context is how these large wildfires relate to weather and climate and how they might change in a warmer world. Such projections rely on the development of a robust modeling framework linking wildfires to atmospheric variability. Drawing from a MODIS product and a gridded meteorological dataset, we derived a suite of biophysical and fire danger indices and developed generalized linear models simulating the probability of large wildfires (> 100 ha) at 8-km spatial and daily temporal resolutions across the entire country over the MODIS period. The models were skillful in reproducing the main spatio-temporal patterns of large wildfires across different environmental regions. Long-term drought was found to be a significant predictor of large wildfires in flammability-limited systems such as the Alpine and Southwest regions. In the Mediterranean, large wildfires were found to be associated with both short-term fire weather conditions and longer-term soil moisture deficits, collectively facilitating the occurrence of large wildfires. Simulated probabilities during the day of large wildfires were on average 2–3 times higher than normal with respect to the mean seasonal cycle. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis to estimate future changes to large wildfire from climate scenarios.

scholarly journals Simulating the effects of weather and climate on large wildfires in France

2019 ◽  
Vol 19 (2) ◽  
pp. 441-454 ◽  
Author(s):  
Renaud Barbero ◽  
Thomas Curt ◽  
Anne Ganteaume ◽  
Eric Maillé ◽  
Marielle Jappiot ◽  
...  
Keyword(s):  
Linear Models ◽  
Weather Conditions ◽  
Historical Period ◽  
Natural Ecosystem ◽  
Atmospheric Variability ◽  
Modeling Framework ◽  
Spatial And Temporal Scales ◽  
Weather And Climate ◽  
Change Context ◽  
Wildfire Spread

Abstract. Large wildfires across parts of France can cause devastating damage which puts lives, infrastructure, and the natural ecosystem at risk. In the climate change context, it is essential to better understand how these large wildfires relate to weather and climate and how they might change in a warmer world. Such projections rely on the development of a robust modeling framework linking large wildfires to present-day atmospheric variability. Drawing from a MODIS product and a gridded meteorological dataset, we derived a suite of biophysical and fire danger indices and developed generalized linear models simulating the probability of large wildfires (>100 ha) at 8 km spatial and daily temporal resolutions across the entire country over the last two decades. The models were able to reproduce large-wildfire activity across a range of spatial and temporal scales. Different sensitivities to weather and climate were detected across different environmental regions. Long-term drought was found to be a significant predictor of large wildfires in flammability-limited systems such as the Alpine and southwestern regions. In the Mediterranean, large wildfires were found to be associated with both short-term fire weather conditions and longer-term soil moisture deficits, collectively facilitating the occurrence of large wildfires. Simulated probabilities on days with large wildfires were on average 2–3 times higher than normal with respect to the mean seasonal cycle, highlighting the key role of atmospheric variability in wildfire spread. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis on which to estimate future changes to large wildfires from climate scenarios.

scholarly journals Spatio-temporal associations between deforestation and malaria incidence in Lao PDR

2020 ◽  
Author(s):  
Francois Rerolle ◽  
Emily Dantzer ◽  
Andrew A. Lover ◽  
John M. Marshall ◽  
Bouasy Hongvanthong ◽  
...  
Keyword(s):  
Forest Cover ◽  
Malaria Incidence ◽  
Lao Pdr ◽  
Short Term ◽  
Modeling Framework ◽  
Temporal Modeling ◽  
Forested Areas ◽  
Spatio Temporal ◽  
The Relationship

AbstractAs countries in the Greater Mekong Sub-region (GMS) increasingly focus their malaria control and elimination efforts on forest-going populations, greater understanding of the relationship between deforestation and malaria incidence will be essential for programs to assess and meet their 2030 elimination goals. Leveraging village-level health facility surveillance data and forest cover data in a spatio-temporal modeling framework, we found evidence that deforestation is associated with short-term increases, but long-term decreases in confirmed malaria case incidence in Lao People’s Democratic Republic (Lao PDR). We identified strong associations with deforestation measured within 30 km of villages but not with deforestation in the near (10 km) and immediate (1 km) vicinity. Results appear driven by deforestation in densely forested areas and were more pronounced for infections with Plasmodium falciparum (P. falciparum) than for Plasmodium vivax (P. vivax). These findings highlight the influence of forest-going populations on malaria transmission in the GMS.

scholarly journals Spatio-temporal associations between deforestation and malaria incidence in Lao PDR

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Francois Rerolle ◽  
Emily Dantzer ◽  
Andrew A Lover ◽  
John M Marshall ◽  
Bouasy Hongvanthong ◽  
...  
Keyword(s):  
Forest Cover ◽  
Malaria Incidence ◽  
Lao Pdr ◽  
Short Term ◽  
Modeling Framework ◽  
Temporal Modeling ◽  
Forested Areas ◽  
Spatio Temporal ◽  
The Relationship

As countries in the Greater Mekong Sub-region (GMS) increasingly focus their malaria control and elimination efforts on reducing forest-related transmission, greater understanding of the relationship between deforestation and malaria incidence will be essential for programs to assess and meet their 2030 elimination goals. Leveraging village-level health facility surveillance data and forest cover data in a spatio-temporal modeling framework, we found evidence that deforestation is associated with short-term increases, but long-term decreases confirmed malaria case incidence in Lao People’s Democratic Republic (Lao PDR). We identified strong associations with deforestation measured within 30 km of villages but not with deforestation in the near (10 km) and immediate (1 km) vicinity. Results appear driven by deforestation in densely forested areas and were more pronounced for infections with Plasmodium falciparum (P. falciparum) than for Plasmodium vivax (P. vivax). These findings highlight the influence of forest activities on malaria transmission in the GMS.

scholarly journals Correlated Functional Models with Derivative Information for Modeling Microfading Spectrometry Data on Rock Art Paintings

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2141
Author(s):  
Gabriel Riutort-Mayol ◽  
Virgilio Gómez-Rubio ◽  
José Luis Lerma ◽  
Julio M. del Hoyo-Meléndez
Keyword(s):  
Time Series ◽  
Rock Art ◽  
High Sensitivity ◽  
Modeling Framework ◽  
Spatially Correlated ◽  
Functional Models ◽  
Color Fading ◽  
Spatio Temporal ◽  
Derivative Information

Rock art paintings present high sensitivity to light, and an exhaustive evaluation of the potential color degradation effects is essential for further conservation and preservation actions on these rock art systems. Microfading spectrometry (MFS) is a technique that provides time series of stochastic observations that represent color fading over time at the measured points on the surface under study. In this work, a reliable and robust modeling framework for a short and greatly fluctuating observation dataset collected over the surfaces of rock art paintings located on the walls of Cova Remigia in Ares del Maestrat, Castellón, Spain, is presented. The model is based on a spatially correlated spline-based time series model that takes into account prior information in the form of model derivatives to guarantee monotonicity and long-term saturation for predictions of new color fading estimates at unobserved locations on the surface. The correlation among the (spatially located) time series is modeled by defining Gaussian process (GP) priors over the spline coefficients across time series. The goal is to obtain a complete spatio-temporal mapping of color fading estimates for the study area, which results in very important and useful information that will potentially serve to create better policies and guidelines for heritage preservation and sustainable rock art cultural tourism.

scholarly journals Contrasting large fire regimes in the French Mediterranean

2018 ◽  
Author(s):  
Anne Ganteaume ◽  
Renaud Barbero
Keyword(s):  
Fire Suppression ◽  
Sharp Decrease ◽  
Weather Conditions ◽  
Fire Regimes ◽  
Temporal Variations ◽  
Burned Area ◽  
Prone Area ◽  
Large Fires ◽  
Spatio Temporal

Abstract. In the French Mediterranean, large fires have significant socio-economic and environmental impacts. We used a long-term geo-referenced fire time series (1958–2017) to analyze spatio-temporal variations of large fires (LF; ≥ 100 ha) throughout a fire-prone area of this region. This area was impacted in some locations up to 5 or 6 times by recurrent LF and 21 % of the total area burned by LF occurred on a surface that previously burned in the past. We found distinct patterns between the East and the West of the study area, the former experiencing fewer LF but of a larger extent compared to the latter, with an average time of occurrence between LF exceeding 4000 ha  50 years, respectively. This longitudinal gradient in LF extent contrasts with what was expected from mean fire weather conditions strongly decreasing eastwards but is consistent with larger fuel cover in the East. The temporal variation of LF, featuring a sharp decrease in both frequency and burned area in the early 1990s, highlighted the efficiency of fire suppression and prevention, reinforced at that time. However, the LF outbreak in 2003 due to the exceptional heat wave remains of major concern in the context of climate change.

scholarly journals Documentary data and the study of past droughts: a global state of the art

2018 ◽  
Vol 14 (12) ◽  
pp. 1915-1960 ◽  
Author(s):  
Rudolf Brázdil ◽  
Andrea Kiss ◽  
Jürg Luterbacher ◽  
David J. Nash ◽  
Ladislava Řezníčková
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Drought Indices ◽  
Documentary Evidence ◽  
Climatic Trends ◽  
Instrumental Observations ◽  
Spatio Temporal ◽  
Epigraphic Evidence ◽  
Administrative Evidence

Abstract. The use of documentary evidence to investigate past climatic trends and events has become a recognised approach in recent decades. This contribution presents the state of the art in its application to droughts. The range of documentary evidence is very wide, including general annals, chronicles, memoirs and diaries kept by missionaries, travellers and those specifically interested in the weather; records kept by administrators tasked with keeping accounts and other financial and economic records; legal-administrative evidence; religious sources; letters; songs; newspapers and journals; pictographic evidence; chronograms; epigraphic evidence; early instrumental observations; society commentaries; and compilations and books. These are available from many parts of the world. This variety of documentary information is evaluated with respect to the reconstruction of hydroclimatic conditions (precipitation, drought frequency and drought indices). Documentary-based drought reconstructions are then addressed in terms of long-term spatio-temporal fluctuations, major drought events, relationships with external forcing and large-scale climate drivers, socio-economic impacts and human responses. Documentary-based drought series are also considered from the viewpoint of spatio-temporal variability for certain continents, and their employment together with hydroclimate reconstructions from other proxies (in particular tree rings) is discussed. Finally, conclusions are drawn, and challenges for the future use of documentary evidence in the study of droughts are presented.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

Seabird bycatch vulnerability in pelagic longline fisheries based on modelling of a long-term dataset

2021 ◽  
pp. 1-16
Author(s):  
CAN ZHOU ◽  
NIGEL BROTHERS
Keyword(s):  
Capture Event ◽  
Retrieval Rate ◽  
Competitive Environments ◽  
Global Concern ◽  
Competitive Species ◽  
Spatio Temporal ◽  
Longline Fisheries ◽  
Pelagic Longline

Summary The incidental mortality of seabirds in fisheries remains a serious global concern. Obtaining unbiased and accurate estimates of bycatch rates is a priority for seabird bycatch mitigation and demographic research. For measuring the capture risk of seabird interactions in fisheries, the rate of carcass retrieval from hauled gear is commonly used. However, reliability can be limited by a lack of direct capture observations and the substantial pre-haul bycatch losses known to occur, meaning incidence of seabird bycatch is underestimated. To solve this problem, a new measure (bycatch vulnerability) that links an observed interaction directly to the underlying capture event is proposed to represent the capture risk of fishery interactions by seabirds. The new measure is not affected by subsequent bycatch loss. To illustrate how to estimate and analyse bycatch vulnerability, a case study based on a long-term dataset of seabird interactions and capture confirmation is provided. Bayesian modelling and hypothesis testing were conducted to identify important bycatch risk factors. Competition was found to play a central role in determining seabird bycatch vulnerability. More competitive environments were riskier for seabirds, and larger and thus more competitive species were more at risk than smaller sized and less competitive species. Species foraging behaviour also played a role. On the other hand, no additional effect of physical oceanic condition and spatio-temporal factors on bycatch vulnerability was detected. Bycatch vulnerability is recommended as a replacement for the commonly used bycatch rate or carcass retrieval rate to measure the capture risk of an interaction. Combined with a normalized contact rate, bycatch vulnerability offers an unbiased estimate of seabird bycatch rate in pelagic longline fisheries.

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