Long-term thermal acclimation drives adaptive physiological adjustments of a marine gastropod to reduce sensitivity to climate change

2021 ◽  
Vol 771 ◽  
pp. 145208
Author(s):  
Jonathan Y.S. Leung ◽  
Bayden D. Russell ◽  
Melinda A. Coleman ◽  
Brendan P. Kelaher ◽  
Sean D. Connell
Author(s):  
Wolf U. Blanckenhorn

Organisms can respond to environmental change by modifying their behavior to obtain an instant response, through short-term phenotypically plastic, often physiological, adjustments, and/or by adapting their life history through a more long-term evolutionary response. Behavioural and physiological responses, in fact, can occur at all these three temporal scales. Examples of behaviors so affected include congregation, dispersal, foraging, migration, or mating. Such responses have consequences at the population and community levels, and ultimately for the evolution of species. This chapter discusses insect examples of these kinds, with an emphasis on human-induced factors, such as (primarily) climate change, pollution, fragmentation, and urbanization.


Author(s):  
Nguyen Thi Thuc An ◽  
Dau Kieu Ngoc Anh

The 2018 Nobel Economics Prize was awarded to two American economists - William D. Nordhaus and Paul M. Romer - who designed methods for better assessing environmental issues and technological advances on growth. This year’s Laureates, Nordhaus was the first person to create an intergrated model to assess interactions between society and nature and Romer laid the foundation for what is now called endogenous growth theory. According to the Swedish Royal Academy of Sciences, these two macroeconomists’ research have helped “significantly broaden the scope of economic analysis by constructing models that explain how the market economy interacts with nature and knowledge” which integrates climate change measures into long-term sustainable economic growth. Keywords Nobel in economics, William D. Nordhaus, Paul M. Romer, climate change, endogenous growth theory, economic growth References [1] Y Vân (2018), “Lý lịch 'khủng' của hai nhà khoa học vừa giành giải Nobel Kinh tế 2018”, Vietnambiz, đăng tải ngày 08/10/2018, https://vietnambiz.vn/ly-lich-khung-cua-hai-nha-khoa-hoc-vua-gianh-giai-nobel-kinh-te-2018-95776.html[2] Jonas O. Bergman, Rich Miller (2018), “Nordhaus, Romer Win Nobel for Thinking on Climate, Innovation”, đăng tải ngày 8/10/2018, https://www.bloomberg.com/news/articles/2018-10-08/nordhaus-romer-win-2018-nobel-prize-in-economic-sciences [3] Antonin Pottier (2018), “Giải Nobel” William Nordhaus có thật sự nghiêm túc?”, Nguyễn Đôn Phước dịch, đăng tải ngày 11/10/2018, http://www.phantichkinhte123.com/2018/10/giai-nobel-william-nordhaus-co-that-su.html[4] Thăng Điệp (2018), “Giải Nobel kinh tế 2018 về tay hai người Mỹ”, đăng tải ngày 8/10/2018, http://vneconomy.vn/giai-nobel-kinh-te-2018-ve-tay-hai-nguoi-my-20181008185809239.htm[5] Lars P. Syll (2018), “Cuối cùng - Paul Romer cũng có được giải thưởng Nobel”, Huỳnh Thiện Quốc Việt dịch, đăng tải ngày 14/10/2018, http://www.phantichkinhte123.com/2018/10/cuoi-cung-paul-romer-cung-co-uoc-giai.html[6] Phương Võ (2018), “Nobel Kinh tế 2018: Chạm tới bài toán khó của thời đại”, đăng tải ngày 9/10/2018, https://nld.com.vn/thoi-su-quoc-te/nobel-kinh-te-2018-cham-toi-bai-toan-kho-cua-thoi-dai-20181008221734228.htm[7] Đông Phong (2018), “Nobel Kinh tế cho giải pháp phát triển bền vững và phúc lợi người dân”, đăng tải ngày 8/10/2018, https://news.zing.vn/nobel-kinh-te-cho-giai-phap-phat-trien-ben-vung-va-phuc-loi-nguoi-dan-post882860.html[8] Thanh Trúc (2018), “Giải Nobel kinh tế 2018: Thay đổi tư duy về biến đổi khí hậu”, https://tusach.thuvienkhoahoc.com/wiki/Gi%E1%BA%A3i_Nobel_kinh_t%E1%BA%BF_2018:_Thay_%C4%91%E1%BB%95i_t%C6%B0_duy_v%E1%BB%81_bi%E1%BA%BFn_%C4%91%E1%BB%95i_kh%C3%AD_h%E1%BA%ADu[9] Cẩm Anh (2018), “Nobel kinh tế 2018: Lời giải cho tăng trưởng kinh tế bền vững”, đăng tải ngày 11/10/2018, http://enternews.vn/nobel-kinh-te-2018-loi-giai-cho-tang-truong-kinh-te-ben-vung-137600.html.


2019 ◽  
pp. 79-95
Author(s):  
N.E. Terentiev

Based on the latest data, paper investigates the dynamics of global climate change and its impact on economic growth in the long-term. The notion of climate risk is considered. The main directions of climate risk management policies are analyzed aimed, first, at reducing anthropogenic greenhouse gas emissions through technological innovation and structural economic shifts; secondly, at adaptation of population, territories and economic complexes to the irreparable effects of climate change. The problem of taking into account the phenomenon of climate change in the state economic policy is put in the context of the most urgent tasks of intensification of long-term socio-economic development and parrying strategic challenges to the development of Russia.


2021 ◽  
pp. 108602662110316
Author(s):  
Tiziana Russo-Spena ◽  
Nadia Di Paola ◽  
Aidan O’Driscoll

An effective climate change action involves the critical role that companies must play in assuring the long-term human and social well-being of future generations. In our study, we offer a more holistic, inclusive, both–and approach to the challenge of environmental innovation (EI) that uses a novel methodology to identify relevant configurations for firms engaging in a superior EI strategy. A conceptual framework is proposed that identifies six sets of driving characteristics of EI and two sets of beneficial outcomes, all inherently tensional. Our analysis utilizes a complementary rather than an oppositional point of view. A data set of 65 companies in the ICT value chain is analyzed via fuzzy-set comparative analysis (fsQCA) and a post-QCA procedure. The results reveal that achieving a superior EI strategy is possible in several scenarios. Specifically, after close examination, two main configuration groups emerge, referred to as technological environmental innovators and organizational environmental innovators.


2021 ◽  
pp. 1-3
Author(s):  
Anda David ◽  
Frédéric Docquier

How do weather shocks influence human mobility and poverty, and how will long-term climate change affect future migration over the course of the 21st century? These questions have gained unprecedented attention in public debates as global warming is already having severe impacts around the world, and prospects for the coming decades get worse. Low-latitude countries in general, and their agricultural areas in particular, have contributed the least to climate change but are the most adversely affected. The effect on people's voluntary and forced displacements is of major concern for both developed and developing countries. On 18 October 2019, Agence Française de Développement (AFD) and Luxembourg Institute of Socio-Economic Research (LISER) organized a workshop on Climate Migration with the aim of uncovering the mechanisms through which fast-onset variables (such as weather anomalies, storms, hurricanes, torrential rains, floods, landslides, etc.) and slow-onset variables (such as temperature trends, desertification, rising sea level, coastal erosion, etc.) influence both people's incentives to move and mobility constraints. This special issue gathers five papers prepared for this workshop, which shed light on (or predict) the effect of extreme weather shocks and long-term climate change on human mobility, and stress the implications for the development community.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.


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