scholarly journals Statistical Modeling of Non-Stationary Heatwave Hazard

2021 ◽  
Author(s):  
Peng Zhong ◽  
Raphael Huser ◽  
Thomas Opitz
Keyword(s):  
Temporal Dynamics ◽  
Temporal Trends ◽  
Stable Process ◽  
Climatic Conditions ◽  
Mitigation Measures ◽  
Asymptotic Independence ◽  
Modeling Framework ◽  
Infinitely Divisible ◽  
Health Related ◽  
Spatio Temporal

<p>The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate, as well as their environmental, societal, economic and global health-related risks. Here, we study annual temperature maxima over Southern Europe using a century-spanning dataset observed at 44 monitoring stations. Extending the spectral representation of max-stable processes, our modeling framework relies on a novel construction of max-infinitely divisible processes, which include covariates to capture spatio-temporal non-stationarities. Our new model keeps a popular max-stable process on the boundary of the parameter space, while flexibly capturing weakening extremal dependence at increasing quantile levels and asymptotic independence. It clearly outperforms natural alternative models. Results show that the spatial extent of heatwaves is smaller for more severe events at higher altitudes and that recent heatwaves are moderately wider. Our probabilistic assessment of the 2019 annual maxima confirms the severity of the 2019 heatwaves both spatially and at individual sites, especially when compared to climatic conditions prevailing in 1950-1975. Our applied results may be exploited in practice to understand the spatio-temporal dynamics, severity, and frequency of extreme heatwaves, and design suitable regional mitigation measures.</p>

Geo-Informatics for Land Use and Biodiversity Studies

2011 ◽  
pp. 52-77
Author(s):  
P. K. Joshi ◽  
Neena Priyanka
Keyword(s):  
Land Use ◽  
Temporal Dynamics ◽  
Mitigation Measures ◽  
Conservation Strategies ◽  
Ecological Processes ◽  
Holistic Understanding ◽  
Global Positioning ◽  
Geospatial Tools ◽  
Spatio Temporal ◽  
Impact On Biodiversity

The dynamics of land use/land cover (LU/LC) is a manifestation of the cyclic correlation among the kind and magnitude of causes, impacts, responses and resulting ecological processes of the ecosystem. Thus, the holistic understanding of the complex mechanisms that control LU/LC requires synergetic adoption of measurement approaches, addressing issues, and identifying drivers of change and state of art technologies for mitigation measures. As the spatio-temporal heterogeneity of the LU/LC increases, its impact on biodiversity becomes even more difficult to anticipate. Thus, in order to understand the spatio-temporal dynamics of change in landscape and its relationship to biodiversity, it is necessary to reliably identify and quantify the indicators of change. In addition, it is also important to have better understanding of the technologies and techniques that serve as complimentary tool for land mitigation and conservation planning. Against this background, the chapter aims to synthesize LU/LC studies worldwide and their impacts on biodiversity. This chapter explores identification and analysis of key natural, socio-economic and regulatory drivers for LU/LC. Finally, it attempts to collate some LU/LC studies involving usage of geospatial tools, such as satellite remote sensing, Geographic Information System (GIS), Global Positioning System (GPS), and integrative tools, besides conventional approaches that could assist decision makers, land managers, stakeholders and researchers in better management and formulation of conservation strategies based on scientific grounds.

scholarly journals Spatio-Temporal Patterns of the 2019-nCoV Epidemic at the County Level in Hubei Province, China

2020 ◽  
Vol 17 (7) ◽  
pp. 2563 ◽  
Author(s):  
Wentao Yang ◽  
Min Deng ◽  
Chaokui Li ◽  
Jincai Huang
Keyword(s):  
Temporal Dynamics ◽  
Spatial Interaction ◽  
Temporal Trends ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Hubei Province ◽  
Incidence Rates ◽  
County Level ◽  
Spatial Clusters ◽  
Spatio Temporal

Understanding the spatio-temporal characteristics or patterns of the 2019 novel coronavirus (2019-nCoV) epidemic is critical in effectively preventing and controlling this epidemic. However, no research analyzed the spatial dependency and temporal dynamics of 2019-nCoV. Consequently, this research aims to detect the spatio-temporal patterns of the 2019-nCoV epidemic using spatio-temporal analysis methods at the county level in Hubei province. The Mann–Kendall and Pettitt methods were used to identify the temporal trends and abrupt changes in the time series of daily new confirmed cases, respectively. The local Moran’s I index was applied to uncover the spatial patterns of the incidence rate, including spatial clusters and outliers. On the basis of the data from January 26 to February 11, 2020, we found that there were 11 areas with different types of temporal patterns of daily new confirmed cases. The pattern characterized by an increasing trend and abrupt change is mainly attributed to the improvement in the ability to diagnose the disease. Spatial clusters with high incidence rates during the period were concentrated in Wuhan Metropolitan Area due to the high intensity of spatial interaction of the population. Therefore, enhancing the ability to diagnose the disease and controlling the movement of the population can be confirmed as effective measures to prevent and control the regional outbreak of the epidemic.

scholarly journals Interactions between ecological, evolutionary, and environmental processes unveil complex dynamics of island biodiversity

2017 ◽  
Author(s):  
Juliano Sarmento Cabral ◽  
Kerstin Wiegand ◽  
Holger Kreft
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Temporal Trends ◽  
Oceanic Islands ◽  
Potential Range ◽  
Full Model ◽  
Field Station ◽  
Environmental Processes ◽  
Organizational Levels ◽  
Spatio Temporal

ABSTRACTAimsUnderstanding how biodiversity emerges and varies in space and time is central to ecology and biogeography. Multiple processes affect biodiversity at different scales and organizational levels, hence progress in understanding biodiversity dynamics requires the integration of these underlying processes. Here we present BioGEEM (BioGeographical Eco-Evolutionary Model), a spatially-explicit, process-based model that integrates all processes hypothesized to be relevant for biodiversity dynamics and that can be used to evaluate their relative roles.LocationHypothetical oceanic islandsMethodsThe model is stochastic, grid-based, and integrates ecological (metabolic constraints, demography, dispersal, and competition), evolutionary (mutation and speciation), and environmental (geo-climatic dynamics) processes. Plants on oceanic islands served as model system. We used the full model to test hypotheses about emergent patterns at different spatio-temporal scales and organizational levels (populations, species, communities, and assemblages), switching off processes to assess the importance 1) of competition for realistic population and range dynamics; 2) metabolic constraints for endemism and community composition; 3) environmental dynamics and 4) speciation for biogeographical patterns.ResultsThe full model generated multiple patterns matching empirical and theoretical expectations. For example, populations were largest on young, species-poor islands. Species, particularly endemics, were better able to fill their potential range on small, species-poor islands. Richness gradients peaked at mid-elevations. The proportion of endemics was highest on old, large, and isolated environments within the islands. Species and trait richness showed unimodal temporal trends. Switching off selected processes affected these patterns, and we found most of our hypotheses supported.Main conclusionsIntegrating ecological, evolutionary, and environmental processes is essential to simultaneously generate realistic spatio-temporal dynamics at population, species, community, and assemblage level. Finally, large-scale biodiversity dynamics emerged directly from biological processes which make this mechanistic model a valuable ‘virtual long-term field station’ to study the linkages between biogeography and ecology.

Long-term spatio-temporal dynamics of the mosquito Aedes aegypti in temperate Argentina

2016 ◽  
Vol 107 (2) ◽  
pp. 225-233 ◽  
Author(s):  
S. Fischer ◽  
M.S. De Majo ◽  
L. Quiroga ◽  
M. Paez ◽  
N. Schweigmann
Keyword(s):  
Aedes Aegypti ◽  
Buenos Aires ◽  
Temporal Dynamics ◽  
Spatial Dynamics ◽  
Climatic Conditions ◽  
Buenos Aires Province ◽  
Southern Limit ◽  
Spatio Temporal ◽  
Lower Temperature

AbstractBuenos Aires city is located near the southern limit of the distribution of Aedes aegypti (Diptera: Culicidae). This study aimed to assess long-term variations in the abundance of Ae. aegypti in Buenos Aires in relation to changes in climatic conditions. Ae. aegypti weekly oviposition activity was analyzed and compared through nine warm seasons from 1998 to 2014, with 200 ovitraps placed across the whole extension of the city. The temporal and spatial dynamics of abundances were compared among seasons, and their relation with climatic variables were analyzed. Results showed a trend to higher peak abundances, a higher number of infested sites, and longer duration of the oviposition season through subsequent years, consistent with a long-term colonization process. In contrast, thermal favorability and rainfall pattern did not show a consistent trend of changes. The long-term increase in abundance, and the recently documented expansion of Ae. aegypti to colder areas of Buenos Aires province suggest that local populations might be adapting to lower temperature conditions. The steadily increasing abundances may have implications on the risk of dengue transmission.

Geo-Informatics for Land Use and Biodiversity Studies

2013 ◽  
pp. 1913-1939 ◽  
Author(s):  
P. K. Joshi ◽  
Neena Priyanka
Keyword(s):  
Land Use ◽  
Temporal Dynamics ◽  
Mitigation Measures ◽  
Conservation Strategies ◽  
Ecological Processes ◽  
Holistic Understanding ◽  
Global Positioning ◽  
Geospatial Tools ◽  
Spatio Temporal ◽  
Impact On Biodiversity

The dynamics of land use/land cover (LU/LC) is a manifestation of the cyclic correlation among the kind and magnitude of causes, impacts, responses and resulting ecological processes of the ecosystem. Thus, the holistic understanding of the complex mechanisms that control LU/LC requires synergetic adoption of measurement approaches, addressing issues, and identifying drivers of change and state of art technologies for mitigation measures. As the spatio-temporal heterogeneity of the LU/LC increases, its impact on biodiversity becomes even more difficult to anticipate. Thus, in order to understand the spatio-temporal dynamics of change in landscape and its relationship to biodiversity, it is necessary to reliably identify and quantify the indicators of change. In addition, it is also important to have better understanding of the technologies and techniques that serve as complimentary tool for land mitigation and conservation planning. Against this background, the chapter aims to synthesize LU/LC studies worldwide and their impacts on biodiversity. This chapter explores identification and analysis of key natural, socio-economic and regulatory drivers for LU/LC. Finally, it attempts to collate some LU/LC studies involving usage of geospatial tools, such as satellite remote sensing, Geographic Information System (GIS), Global Positioning System (GPS), and integrative tools, besides conventional approaches that could assist decision makers, land managers, stakeholders and researchers in better management and formulation of conservation strategies based on scientific grounds.

scholarly journals Increasing temperatures and fruit phenology – Comparing spatio-temporal trends for apple and pear in Belgium

2020 ◽  
Author(s):  
Bianca Drepper ◽  
Anne Gobin ◽  
Wim Verjans ◽  
Jos Van Orshoven
Keyword(s):  
Temporal Trends ◽  
Model Performance ◽  
Fruit Trees ◽  
Mitigation Measures ◽  
Research Centre ◽  
North East ◽  
Cultivar Selection ◽  
Before And After ◽  
Spatio Temporal ◽  
The One

<p>For several cultivars of Malus domestica (apple) and Pyrus communis (pear), records of seven decades (1950-2019) from the Research Centre for Fruit in north-east Belgium revealed that flowering occurred on average 9.5 (apple) and 11.5 (pear) days earlier following dormancy periods (October to April) that were warmer than the average (Drepper et al., 2020). However, the relationship between winter temperature and flowering date is not linear and relative delays of flowering following the warmest winters suggest that increasing temperatures before and after dormancy break (so-called chilling and forcing periods) have respectively delaying or advancing effects on the time of flowering of fruit trees in temperate regions (Drepper et al., 2020).</p><p>Well calibrated phenological models are potentially usable to support decision-making regarding (new) orchard locations, cultivar selection and frost mitigation measures. To this end a dynamic chill model was coupled to a growing degree day forcing model, calibrated and validated to the local cultivars for the Research Centre’s conditions. The combined model was applied for apple and pear on a 5km X 5km grid covering the region of Flanders in Belgium and run based on observed temperatures since 1950 from the Belgian Meteorological Institute on the one hand and regionally downscaled and adjusted temperature projections from the CORDEX project for the near future (up to 2060) on the other hand. This temporal horizon is farm practice driven and covers the lifespan of orchards planted in 2020.</p><p>The results (forthcoming) allow to investigate spatial patterns of (i) date of start of flowering, (ii) the occurrence of frost during sensitive stages around the flowering time, (iii) timing of dormancy break as well as (iv) its interaction with forcing completion.    </p><p> </p><p>Drepper, Bianca, Anne Gobin, Serge Remy, and Jos Van Orshoven. “Comparing Apple and Pear Phenology and Model Performance: What Seven Decades of Observations Reveal.” Agronomy 10, no. 1 (January 4, 2020): 73. https://doi.org/10.3390/agronomy10010073.</p><p> </p>

scholarly journals Mapping Violent Presence of Armed Actors in Colombia

2019 ◽  
Vol 1 ◽  
pp. 1-9 ◽  
Author(s):  
Javier Osorio ◽  
Mohamed Mohamed ◽  
Viveca Pavon ◽  
Susan Brewer-Osorio
Keyword(s):  
Civil War ◽  
Political Violence ◽  
Language Processing ◽  
Temporal Dynamics ◽  
Early Stage ◽  
Temporal Trends ◽  
Early Warning Systems ◽  
Spatio Temporal ◽  
Interactive Map ◽  
Armed Actors

<p><strong>Abstract.</strong> Heat maps and Early Warning Systems have traditionally contributed to identifying and managing risks associated with crime trends, health hazards, and natural disasters. However, their application to analyzing civil war dynamics still is at an early stage. To address this need, this research integrates Natural Language Processing (NLP) tools and Geographic Information Systems (GIS) to generate an interactive map of the violent presence of armed actors in the Colombian civil war between 1988 and 2017. The NLP component generates fine-grained geo-location data of armed actors' violent presence. The GIS component then uses the geo-referenced data to present dynamic clusters of four main types of actors: Government forces, Insurgent organizations, Paramilitary groups, and Criminal organizations. Each type of actors is further disaggregated into a multitude of specific armed organizations. Based on anomalies in the spatio-temporal trends identified in the data, we develop an EWS methodology to detect “emerging”, “intense”, and “critical” cases. This application contributes to the efforts of the academic and policy communities to understanding the spatio-temporal dynamics of political violence and promoting sustainable peace in civil war settings.</p>

Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

Sign in / Sign up

Export Citation Format

Share Document