Communities worldwide are critically re-examining their seasonal cultures and calendars. As cultural frameworks, seasons have long patterned community life and provided repertoires for living by annual rhythms. In a chaotic world, the seasons - winter, the monsoon and so on - can feel like stable cultural landmarks for reckoning time and orienting our communities. Seasons are rooted in our pasts and reproduced in our present. They act as schemes for synchronising community activities and professional practices, and as symbol systems for interpreting what happens in the world. But on closer inspection, seasons can be unstable and unreliable. Their meanings can change over time. Seasonal cultures evolve with environments and communities' worldviews, values, technologies and practices, affecting how people perceive seasonal patterns and behave accordingly. Calendars are contested, especially now. Communities today find themselves in a moment of accelerated and intersecting changes - from climate to social, political, and technological - that are destabilizing seasonal cultures. How they reorient themselves to shifting patterns may affect whether seasonal rhythms serve as resources, or lead people down maladaptive pathways. A focus on seasonal cultures builds on multi-disciplinary work. The social sciences, from anthropology to sociology, have long studied how seasons order people's sense of time, social life, relationship to the environment, and politics. In the humanities, seasons play an important role in literature, art, archaeology and history. This book advances scholarship in these fields, and enriches it with extrascientific insights from practice, to open up exiting new directions in climate adaptation.

Predicting Future Oceans: Sustainability of Ocean and Human Systems Amidst Global Environmental Change provides a synthesis of our knowledge of the future state of the oceans. The editors undertake the challenge of integrating diverse perspectives—from oceanography to anthropology—to exhibit the changes in ecological conditions and their socioeconomic implications. Each contributing author provides a novel perspective, with the book as a whole collating scholarly understandings of future oceans and coastal communities across the world. The diverse perspectives, syntheses and state-of-the-art natural and social sciences contributions are led by past and current research fellows and principal investigators of the Nereus Program network. This includes members at 17 leading research institutes, addressing themes such as oceanography, biodiversity, fisheries, mariculture production, economics, pollution, public health and marine policy. This book is a comprehensive resource for senior undergraduate and postgraduate readers studying social and natural science, as well as practitioners working in the field of natural resources management and marine conservation. - Provides a synthesis of our knowledge on the future state of the oceans - Includes recommendations on how to move forwards - Highlights key social aspects linked to ocean ecosystems, including health, equity and sovereignty

The seasonal nature of tourism is increasingly receiving the attention of various actors: tourism destination planners and economic development strategists at all levels, tour operators and the diverse businesses that significantly depend on tourism, and the host communities who negotiate tourism’s potential to have both positive and negative impacts. The research report at hand identifies and discusses four main perspectives on the issues of seasonal tourism in the Arctic: local community perspectives; employment and workforce issues; the Arctification of northern tourism; and global environmental change. These themes form the key issues around which the challenges and opportunities related to seasonality of tourism can be placed and worked with. Based on the discussion, the report outlines recommendations related to developing a thriving and sustainable tourism sector in Arctic Europe.

Seasonality is a severe constraint to sustainable rural livelihoods and a driver of poverty and hunger, particularly in the tropics. Many poor people in developing countries are ill equipped to cope with seasonal variations which can lead to drought or flood and consequences for agriculture, employment, food supply and the spread of disease. The subject has assumed increasing importance as climate change and other forms of development disrupt established seasonal patterns and variations. This book is the first systematic study of seasonality for over twenty years, and it aims to revive academic interest and policy awareness of this crucial but neglected issue. Thematic chapters explore recent shifts with profound implications for seasonality, including climate change, HIV/AIDS, and social protection. Case study chapters explore seasonal dimensions of livelihoods in Africa (Ethiopia, Kenya, Malawi), Asia (Bangladesh, China, India), and Latin America (Peru). Others assess policy responses to adverse seasonality, for example through irrigation, migration and seasonally-sensitive education. The book also includes innovative tools for monitoring seasonality, which should enable more appropriate responses.

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Seasonal fluctuations in mortality are a persistent phenomenon, but variations from culture to culture pose fascinating questions. This book investigates whether sociodemographic and socioeconomic factors play a role as important for seasonal mortality as they do for mortality in general. Using modern statistical methods, the book shows, for example, that in the United States the fluctuations between winter and summer mortality are smaller the more years someone has spent in school.

This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.

This book explores how seasonal variation in resource abundance might have driven primate and human evolution.

This volume brings together leading papers on the existing standard economic theory of seasonality as well as papers which apply newer statistical tools to the modelling of seasonal phenomena. It includes a discussion of the X-11 method of seasonal adjustment, as well as an assessment ofrecent developments in the field.

1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical and economic issues are involved. The main problems is that these issues are so interrelated that it does not seem sensible to address them one at a time. As soon as one sets about the making of a model of macroeconomic time series one has to choose which problems one will try to tackle oneself and which problems one will leave unresolved or to be solved by others. From a theoretic point of view it can be fruitful to concentrate oneself on only one problem. If one follows this strategy in empirical application one runs a serious risk of making a seemingly interesting model, that is just a corollary of some important mistake in the handling of other problems. Two well known examples of statistical artifacts are the finding of Kuznets "pseudo-waves" of about 20 years in economic activity (Sargent (1979, p. 248)) and the "spurious regression" of macroeconomic time series described in Granger and Newbold (1986, §6. 4). The easiest way to get away with possible mistakes is to admit they may be there in the first place, but that time constraints and unfamiliarity with the solution do not allow the researcher to do something about them. This can be a viable argument.