scholarly journals Genetic and life-history consequences of extreme climate events

2017 ◽  
Vol 284 (1848) ◽  
pp. 20162118 ◽  
Author(s):  
Simone Vincenzi ◽  
Marc Mangel ◽  
Dusan Jesensek ◽  
John Carlos Garza ◽  
Alain J. Crivelli

Climate change is predicted to increase the frequency and intensity of extreme climate events. Tests on empirical data of theory-based predictions on the consequences of extreme climate events are thus necessary to understand the adaptive potential of species and the overarching risks associated with all aspects of climate change. We tested predictions on the genetic and life-history consequences of extreme climate events in two populations of marble trout Salmo marmoratus that have experienced severe demographic bottlenecks due to flash floods. We combined long-term field and genotyping data with pedigree reconstruction in a theory-based framework. Our results show that after flash floods, reproduction occurred at a younger age in one population. In both populations, we found the highest reproductive variance in the first cohort born after the floods due to a combination of fewer parents and higher early survival of offspring. A small number of parents allowed for demographic recovery after the floods, but the genetic bottleneck further reduced genetic diversity in both populations. Our results also elucidate some of the mechanisms responsible for a greater prevalence of faster life histories after the extreme event.

2021 ◽  
Vol 15 (3) ◽  
pp. e0009182
Author(s):  
Cameron Nosrat ◽  
Jonathan Altamirano ◽  
Assaf Anyamba ◽  
Jamie M. Caldwell ◽  
Richard Damoah ◽  
...  

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.


2008 ◽  
Vol 340 (9-10) ◽  
pp. 564-574 ◽  
Author(s):  
Serge Planton ◽  
Michel Déqué ◽  
Fabrice Chauvin ◽  
Laurent Terray

Author(s):  
Vahid M Nik ◽  
A T D Perera ◽  
Deliang Chen

Abstract Climate change and increased urban population are two major concerns for society. Moving towards more sustainable energy solutions in the urban context by integrating renewable energy technologies supports decarbonizing the energy sector and climate change mitigation. A successful transition also needs adequate consideration of climate change including extreme events to ensure the reliable performance of energy systems in the long run. This review provides an overview of and insight into the progress achieved in the energy sector to adapt to climate change, focusing on the climate resilience of urban energy systems. The state-of-the-art methodology to assess impacts of climate change including extreme events and uncertainties on the design and performance of energy systems is described and discussed. Climate resilience is an emerging concept that is increasingly used to represent the durability and stable performance of energy systems against extreme climate events. However, it has not yet been adequately explored and widely used, as its definition has not been clearly articulated and assessment is mostly based on qualitative aspects. This study reveals that a major limitation in the state-of-the-art is the inadequacy of climate change adaptation approaches in designing and preparing urban energy systems to satisfactorily address plausible extreme climate events. Furthermore, the complexity of the climate and energy models and the mismatch between their temporal and spatial resolutions are the major limitations in linking these models. Therefore, few studies have focused on the design and operation of urban energy infrastructure in terms of climate resilience. Considering the occurrence of extreme climate events and increasing demand for implementing climate adaptation strategies, the study highlights the importance of improving energy system models to consider future climate variations including extreme events to identify climate resilient energy transition pathways.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Negev ◽  
H Levine ◽  
T Zohar ◽  
H Nouman ◽  
M Zohar ◽  
...  

Abstract Background Extreme climate events (wildfires, floods, heatwaves, cold spells) are becoming more frequent in the Mediterranean, but adaptation levels in the health and welfare sectors remain low. The city of Haifa in northern Israel is prone to both war and extreme climate events. Focusing on Haifa, we aim to 1) examine local officials' risk perceptions of different extreme events, 2) compare preparedness to war vs. climate events, and 3) conduct a spatial analysis of climate and health vulnerabilities. Methods Mixed-Methods: a qualitative component including 30 in-depth interviews with local government health and welfare officials, and a qualitative component that includes mapping vulnerability indicators such as socio-economic status, recipients of welfare allowances, and temperature, focusing on urban heat islands. Results The city of Haifa developed a comprehensive resilience policy for war and wildfire. However, there is no awareness or preparedness for other climate events that have not yet been experienced. Similarly, hospitals are prepared for emergencies, but not for extreme climate events. There are no national budget or guidelines for climate adaptation at the city level or in hospitals. Correspondingly, risk perceptions of climate change among health and welfare officials remain low. At the city level, social and climatic vulnerabilities are correlated, so that downtown neighborhoods are characterized by poorer socio-economic, health and welfare conditions, and higher summer temperatures. Conclusions Haifa has good preparedness for events that had been experienced in the past. While emergency preparedness provides a good infrastructure for climate change preparedness, awareness and adaptation to the unique aspects of climate change preparations are needed, including reference to related spatial dimensions. Identifying the gaps between preparedness to various emergency events, can contribute to better climate change preparedness at the local level. Key messages In the city of Haifa, emergency preparedness exists but is not extended to extreme climate events, and awareness to health risks of climate change remains low in the health and welfare agencies. Learning from emergency preparedness to wars, wildfires and earthquakes may contribute to enhancing preparedness to extreme climate events at the local level.


2021 ◽  
Vol 9 ◽  
Author(s):  
Ruixin Duan ◽  
Guohe Huang ◽  
Yongping Li ◽  
Rubing Zheng ◽  
Guoqing Wang ◽  
...  

Climate change has broadly impacted on the China areas. There will be severe challenges due to the variations of precipitation and temperature in the future. Therefore, a comprehensive understanding of the future climate change over China areas is desired. In this study, future annual precipitation and annual mean temperature under two SSPs over China areas were projected through multiple global climate models. Meanwhile, to explore the sources of uncertainty in projecting future climate change, the multi-factorial analysis was conducted through GCMs (five levels) and SSPs (two levels). This study can help us understand the possible changes in precipitation, temperature, and the potential extreme climate events over the China area. The results indicate that China would have more annual precipitation and higher annual mean temperature in the future. Compared with the historical period, the annual mean temperature would face a continuously increasing trend under SSPs. Regardless of SSP245 or SSP585, the growth rate of annual precipitation and annual mean temperature increase in the northern region (e.g., Northeast China, North China, and Northwest China) are higher than those in the southern parts (e.g., East China, South China, and Central China). The future temperature rise may increase the frequency of heat-related extreme climate events, which needs to be focused on in future research. Moreover, GCM was the main contributing factor to the sources of uncertainty in projecting future precipitation and SSP was the main factor for future temperature. Overall, climate change is an indisputable fact in China. The annual precipitation and annual mean temperature would increase to varying degrees in the future. Reducing the systemic bias of the climate model itself will undoubtedly be the top priority, and it would help to improve the projection and evaluation effects of relevant climate variables.


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