scholarly journals Extreme climatic events in relation to global change and their impact on life histories

2011 ◽  
Vol 57 (3) ◽  
pp. 375-389 ◽  
Author(s):  
Juan Moreno ◽  
Anders Pape Møller
Keyword(s):  
Environmental Conditions ◽  
Life Histories ◽  
Reproductive Effort ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Reproductive Failure ◽  
Adult Survival ◽  
Extreme Climatic Events ◽  
Empirical Tests ◽  
Living Organisms

Abstract Extreme weather conditions occur at an increasing rate as evidenced by higher frequency of hurricanes and more extreme precipitation and temperature anomalies. Such extreme environmental conditions will have important implications for all living organisms through greater frequency of reproductive failure and reduced adult survival. We review examples of reproductive failure and reduced survival related to extreme weather conditions. Phenotypic plasticity may not be sufficient to allow adaptation to extreme weather for many animals. Theory predicts reduced reproductive effort as a response to increased stochasticity. We predict that patterns of natural selection will change towards truncation selection as environmental conditions become more extreme. Such changes in patterns of selection may facilitate adaptation to extreme events. However, effects of selection on reproductive effort are difficult to detect. We present a number of predictions for the effects of extreme weather conditions in need of empirical tests. Finally, we suggest a number of empirical reviews that could improve our ability to judge the effects of extreme environmental conditions on life history.

scholarly journals The influence of weather conditions during gestation on life histories in a wild Arctic ungulate

2016 ◽  
Vol 283 (1841) ◽  
pp. 20161760 ◽  
Author(s):  
Mathieu Douhard ◽  
Leif Egil Loe ◽  
Audun Stien ◽  
Christophe Bonenfant ◽  
R. Justin Irvine ◽  
...  
Keyword(s):  
Life History ◽  
Reproductive Success ◽  
Environmental Conditions ◽  
Early Life ◽  
Life Histories ◽  
Weather Conditions ◽  
Later Life ◽  
Svalbard Reindeer ◽  
Long Term Study ◽  
Age Related

The internal predictive adaptive response (internal PAR) hypothesis predicts that individuals born in poor conditions should start to reproduce earlier if they are likely to have reduced performance in later life. However, whether this is the case remains unexplored in wild populations. Here, we use longitudinal data from a long-term study of Svalbard reindeer to examine age-related changes in adult female life-history responses to environmental conditions experienced in utero as indexed by rain-on-snow (ROS utero ). We show that females experiencing high ROS utero had reduced reproductive success only from 7 years of age, independent of early reproduction. These individuals were able to maintain the same annual reproductive success between 2 and 6 years as phenotypically superior conspecifics that experienced low ROS utero . Young females born after high ROS utero engage in reproductive events at lower body mass (about 2.5 kg less) than those born after low ROS utero . The mean fitness of females that experienced poor environmental conditions in early life was comparable with that of females exposed to good environmental conditions in early life. These results are consistent with the idea of internal PAR and suggest that the life-history responses to early-life conditions can buffer the delayed effects of weather on population dynamics.

scholarly journals Environmental Conditions Affect Offspring Sex-Ratio Variation and Adult Survival in Tawny Owls

The Condor ◽  
2005 ◽  
Vol 107 (2) ◽  
pp. 321-326
Author(s):  
Lajos Sasvári ◽  
Isao Nishiumi
Keyword(s):  
Sex Ratio ◽  
Environmental Conditions ◽  
Weather Conditions ◽  
Egg Laying ◽  
Adult Survival ◽  
Offspring Sex Ratio ◽  
Strix Aluco ◽  
Breeding Populations ◽  
Offspring Sex ◽  
Female Survival

Abstract We studied survival of adult Tawny Owls (Strix aluco), number of breeding pairs, breeding performance, and offspring sex ratio in relation to the number of snowy days in the preceding winter in Duna-Ipoly National Park, Hungary. A new male was more likely to be present after a winter with many snowy days, although female survival was not affected by weather. Number of breeding pairs and number of fledglings declined with increasing number of snowy days. Offspring sex ratio varied according to whether snow cover was present during the egg-laying period, with broods being male biased during adverse conditions but female biased during mild conditions. Also, female nestlings were more likely to die before fledging than male nestlings. These data suggest that female Tawny Owls are able to adjust the sex ratio of their brood according to the expected differential success of nestlings under the prevailing weather conditions. This adjustment in relation to environmental conditions has important implications for the demography of Tawny Owl breeding populations. Las Condiciones Ambientales Afectan la Variación en el Cociente de Sexos de las Crías y la Supervivencia de los Adultos en Strix aluco Resumen. Estudiamos la supervivencia de los adultos de Strix aluco, el número de parejas reproductivas, el desempeño reproductivo y el cociente de sexos de las crías con relación al número de días con nieve en el invierno precedente en el Parque Nacional Duna-Ipoly, Hungría. Un macho nuevo tuvo mayor probabilidad de estar presente luego de un invierno con muchos días con nieve, aunque la supervivencia de las hembras no estuvo afectada por el clima. El número de parejas reproductivas y el número de volantones disminuyeron con un incremento en el número de días con nieve. El cociente de sexos de las crías varió de acuerdo con la presencia de cobertura de nieve durante el período de puesta de los huevos: las nidadas estuvieron sesgadas hacia los machos durante períodos de condiciones adversas y sesgadas hacia las hembras durante períodos de condiciones moderadas. Además, los pichones hembra tuvieron mayor probabilidad de morir antes de dejar el nido que los machos. Estos datos sugieren que las hembras de S. aluco son capaces de ajustar el cociente de sexos de sus nidadas de acuerdo al éxito diferencial esperado de los pichones bajo las condiciones climáticas dominantes. Este ajuste relacionado con las condiciones ambientales tiene implicancias importantes para la demografía de las poblaciones reproductivas de S. aluco.

scholarly journals Bayesian hierarchical modelling of North Atlantic windiness

2013 ◽  
Vol 13 (3) ◽  
pp. 545-557 ◽  
Author(s):  
E. Vanem ◽  
O. N. Breivik
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
North Atlantic ◽  
Environmental Conditions ◽  
Significant Wave Height ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Bayesian Hierarchical ◽  
Significant Wave

Abstract. Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

scholarly journals Precipitation Modeling for Extreme Weather Based on Sparse Hybrid Machine Learning and Markov Chain Random Field in a Multi-Scale Subspace

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1241
Author(s):  
Ming-Hsi Lee ◽  
Yenming J. Chen
Keyword(s):  
Machine Learning ◽  
Markov Chain ◽  
Random Field ◽  
Long Range ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Prediction Algorithm ◽  
Learning Method ◽  
Multi Scale ◽  
Hybrid Machine

This paper proposes to apply a Markov chain random field conditioning method with a hybrid machine learning method to provide long-range precipitation predictions under increasingly extreme weather conditions. Existing precipitation models are limited in time-span, and long-range simulations cannot predict rainfall distribution for a specific year. This paper proposes a hybrid (ensemble) learning method to perform forecasting on a multi-scaled, conditioned functional time series over a sparse l1 space. Therefore, on the basis of this method, a long-range prediction algorithm is developed for applications, such as agriculture or construction works. Our findings show that the conditioning method and multi-scale decomposition in the parse space l1 are proved useful in resisting statistical variation due to increasingly extreme weather conditions. Because the predictions are year-specific, we verify our prediction accuracy for the year we are interested in, but not for other years.

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

2021 ◽  
Vol 129 ◽  
pp. 106824
Author(s):  
Rahman Ashrafi ◽  
Meysam Amirahmadi ◽  
Mohammad Tolou-Askari ◽  
Vahid Ghods
Keyword(s):  
Smart Grids ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective

scholarly journals Extreme weather conditions and dengue outbreak in Guangdong, China: spatial heterogeneity based on climate variability

2021 ◽  
pp. 110900
Author(s):  
Jian Cheng ◽  
Hilary Bambrick ◽  
Laith Yakob ◽  
Gregor Devine ◽  
Francesca D. Frentiu ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Heterogeneity ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Dengue Outbreak

scholarly journals Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Living Room ◽  
Extra Energy ◽  
Cooling Unit ◽  
Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

Potential Impacts of Extreme Heat and Bushfires on Dementia

2021 ◽  
Vol 79 (3) ◽  
pp. 969-978
Author(s):  
Taya L. Farugia ◽  
Carla Cuni-Lopez ◽  
Anthony R. White
Keyword(s):  
Rural Communities ◽  
Natural Disasters ◽  
Low Socioeconomic Status ◽  
Forest Fires ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Extreme Heat ◽  
Indigenous Populations ◽  
Future Research ◽  
Diagnosis Of Dementia

Australia often experiences natural disasters and extreme weather conditions such as: flooding, sandstorms, heatwaves, and bushfires (also known as wildfires or forest fires). The proportion of the Australian population aged 65 years and over is increasing, alongside the severity and frequency of extreme weather conditions and natural disasters. Extreme heat can affect the entire population but particularly at the extremes of life, and patients with morbidities. Frequently identified as a vulnerable demographic in natural disasters, there is limited research on older adults and their capacity to deal with extreme heat and bushfires. There is a considerable amount of literature that suggests a significant association between mental disorders such as dementia, and increased vulnerability to extreme heat. The prevalence rate for dementia is estimated at 30%by age 85 years, but there has been limited research on the effects extreme heat and bushfires have on individuals living with dementia. This review explores the differential diagnosis of dementia, the Australian climate, and the potential impact Australia’s extreme heat and bushfires have on individuals from vulnerable communities including low socioeconomic status Indigenous and Non-Indigenous populations living with dementia, in both metropolitan and rural communities. Furthermore, we investigate possible prevention strategies and provide suggestions for future research on the topic of Australian bushfires and heatwaves and their impact on people living with dementia. This paper includes recommendations to ensure rural communities have access to appropriate support services, medical treatment, awareness, and information surrounding dementia.

scholarly journals Autonomous flight cycles and extreme landings of airliners beyond the current limits and capabilities using artificial neural networks

2021 ◽  
Author(s):  
Haitham Baomar ◽  
Peter J. Bentley
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Training Data ◽  
Aviation Industry ◽  
Control Models ◽  
Novel Approach ◽  
Network Modules ◽  
Artificial Neural

AbstractWe describe the Intelligent Autopilot System (IAS), a fully autonomous autopilot capable of piloting large jets such as airliners by learning from experienced human pilots using Artificial Neural Networks. The IAS is capable of autonomously executing the required piloting tasks and handling the different flight phases to fly an aircraft from one airport to another including takeoff, climb, cruise, navigate, descent, approach, and land in simulation. In addition, the IAS is capable of autonomously landing large jets in the presence of extreme weather conditions including severe crosswind, gust, wind shear, and turbulence. The IAS is a potential solution to the limitations and robustness problems of modern autopilots such as the inability to execute complete flights, the inability to handle extreme weather conditions especially during approach and landing where the aircraft’s speed is relatively low, and the uncertainty factor is high, and the pilots shortage problem compared to the increasing aircraft demand. In this paper, we present the work done by collaborating with the aviation industry to provide training data for the IAS to learn from. The training data is used by Artificial Neural Networks to generate control models automatically. The control models imitate the skills of the human pilot when executing all the piloting tasks required to pilot an aircraft between two airports. In addition, we introduce new ANNs trained to control the aircraft’s elevators, elevators’ trim, throttle, flaps, and new ailerons and rudder ANNs to counter the effects of extreme weather conditions and land safely. Experiments show that small datasets containing single demonstrations are sufficient to train the IAS and achieve excellent performance by using clearly separable and traceable neural network modules which eliminate the black-box problem of large Artificial Intelligence methods such as Deep Learning. In addition, experiments show that the IAS can handle landing in extreme weather conditions beyond the capabilities of modern autopilots and even experienced human pilots. The proposed IAS is a novel approach towards achieving full control autonomy of large jets using ANN models that match the skills and abilities of experienced human pilots and beyond.

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