A spatio-temporal modelling framework for assessing the fluctuations of avalanche occurrence resulting from climate change: application to 60 years of data in the northern French Alps

2009 ◽  
Vol 101 (3-4) ◽  
pp. 515-553 ◽  
Author(s):  
Nicolas Eckert ◽  
E. Parent ◽  
R. Kies ◽  
H. Baya
Keyword(s):  
Climate Change ◽  
French Alps ◽  
Modelling Framework ◽  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals An integrated, spatio-temporal modelling framework for analysing biological invasions

2018 ◽  
Vol 24 (5) ◽  
pp. 652-665 ◽  
Author(s):  
Thomas Mang ◽  
Franz Essl ◽  
Dietmar Moser ◽  
Ingrid Kleinbauer ◽  
Stefan Dullinger
Keyword(s):  
Biological Invasions ◽  
Modelling Framework ◽  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals Linking external components to a spatio-temporal modelling framework: Coupling MODFLOW and PCRaster

2009 ◽  
Vol 24 (9) ◽  
pp. 1088-1099 ◽  
Author(s):  
O. Schmitz ◽  
D. Karssenberg ◽  
W.P.A. van Deursen ◽  
C.G. Wesseling
Keyword(s):  
Modelling Framework ◽  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals Imaging with spatio-temporal modelling to characterize the dynamics of plant-pathogen lesions

2022 ◽  
Author(s):  
Melen Leclerc ◽  
Stéphane Jumel ◽  
Frédéric M. Hamelin ◽  
Rémi Treilhaud ◽  
Nicolas Parisey ◽  
...  
Keyword(s):  
Plant Pathogen ◽  
Temporal Dynamics ◽  
Spatial Models ◽  
Model Parameters ◽  
Local Growth ◽  
Modelling Framework ◽  
Temporal Modelling ◽  
Spatio Temporal ◽  
Plant Pathogen Interactions ◽  
Host Tissues

Within-host spread of pathogens is an important process for the study of plant-pathogen interactions. However, the development of plant-pathogen lesions remains practically difficult to characterize and quantify beyond the common traits such as lesion area. We tackle the spatio-temporal dynamics of interactions by combining image-based phenotyping with mathematical modelling. We consider the spread of Peyronellaea pinodes on pea stipules that were monitored daily with visible imaging. We assume that pathogen propagation on host-tissues can be described by the Fisher-KPP model where lesion spread depends on both a logistic local growth and an homogeneous diffusion. Model parameters are estimated using a variational data assimilation approach on sets of registered images. This modelling framework is used to compare the spread of an aggressive isolate on two pea cultivars with contrasted levels of partial resistance. We show that the expected slower spread on the most resistant cultivar is actually due to a decrease of diffusion and, to a lesser extent, local growth. These results demonstrate that spatial models with imaging allows one to disentangle the processes involved in host-pathogen interactions. Hence, promoting model-based phenotyping of interactions would allow a better identification of quantitative traits thereafter used in genetics and ecological studies.

Spatio-temporal modelling of heat stress and climate change implications for the Murray dairy region, Australia

2013 ◽  
Vol 58 (6) ◽  
pp. 1095-1108 ◽  
Author(s):  
Uday Nidumolu ◽  
Steven Crimp ◽  
David Gobbett ◽  
Alison Laing ◽  
Mark Howden ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals Spatio-temporal modelling of PM10 daily concentrations in Italy using the SPDE approach

2021 ◽  
Vol 248 ◽  
pp. 118192
Author(s):  
Guido Fioravanti ◽  
Sara Martino ◽  
Michela Cameletti ◽  
Giorgio Cattani
Keyword(s):  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Kapitza ◽  
Pham Van Ha ◽  
Tom Kompas ◽  
Nick Golding ◽  
Natasha C. R. Cadenhead ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Integrated Modelling ◽  
Land Use Patterns ◽  
Economic Changes ◽  
Use Patterns ◽  
Modelling Framework ◽  
Avian Biodiversity ◽  
Biodiversity Change ◽  
Impacts Of Climate Change

AbstractClimate change threatens biodiversity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

scholarly journals Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

2011 ◽  
Vol 37 (3) ◽  
pp. 371-381 ◽  
Author(s):  
Rachel Lowe ◽  
Trevor C. Bailey ◽  
David B. Stephenson ◽  
Richard J. Graham ◽  
Caio A.S. Coelho ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Disease Risk ◽  
Warning System ◽  
Temporal Modelling ◽  
Spatio Temporal

scholarly journals Decreasing spatial dependence in extreme snowfall in the French Alps since 1958 under climate change

2016 ◽  
Vol 121 (14) ◽  
pp. 8297-8310 ◽  
Author(s):  
G. Nicolet ◽  
N. Eckert ◽  
S. Morin ◽  
J. Blanchet
Keyword(s):  
Climate Change ◽  
Spatial Dependence ◽  
French Alps

scholarly journals Quantification of potential recruitment of large woody debris in mountain catchments considering the effects of vegetation on hydraulic and geotechnical bank erosion and shallow landslides

2018 ◽  
Vol 40 ◽  
pp. 02046 ◽  
Author(s):  
Eric Gasser ◽  
Andrew Simon ◽  
Paolo Perona ◽  
Luuk Dorren ◽  
Johannes Hübl ◽  
...  
Keyword(s):  
Woody Debris ◽  
Probabilistic Approach ◽  
Temporal Distribution ◽  
Bank Erosion ◽  
Shallow Landslides ◽  
Large Woody Debris ◽  
Correction Coefficient ◽  
Model Framework ◽  
Modelling Framework ◽  
Spatio Temporal

Large woody debris (LWD) exacerbates flood damages near civil structures and in urbanized areas and the awareness of LWD as a risk is becoming more and more relevant. The recruitment of “fresh” large woody debris has been documented to play a significant role of the total amount of wood transported during flood events in mountain catchments. Predominately, LWD recruitment due to hydraulic and geotechnical bank erosion and shallow landslides contribute to high volumes of wood during floods. Quantifying the effects of vegetation on channel and slope processes is extremely complex. This manuscript therefore presents the concepts that are being implemented in a new modelling framework that aims to improve the quantification of vegetation effects on LWD recruitment processes. One of the focuses of the model framework is the implementation of the effect of spatio-temporal distribution of root reinforcement in recruitment processes such as bank erosion and shallow landslides in mountain catchments. Further, spatio-temporal precipitation patterns will be considered using a probabilistic approach to account for the spatio-temporal precipitation variability to estimate a LWD recruitment correction coefficient. Preliminary results are herein presented and discussed in form of a case study in the Swiss Prealps.

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