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In How Population Will Transform Our World, Sarah Harper looks at fertility rates and age structures of populations in different regions of the world against the backdrop of urbanization and climate change, drawing out the profound implications and challenges for societies, economies, and the environment in the decades to come.

\"This volume provides evidence from many of Australia’s leading scholars from a range of social science disciplines to support policies that address challenges presented by Australia’s ageing population. It builds on presentations made to the 2014 Symposium of the Academy of the Social Sciences in Australia. The material is in four parts: Perspectives on Ageing; Population Ageing: Global, regional and Australian perspectives; Improving Health and Wellbeing; Responses by Government and Families/Individuals. ‘The Academy of the Social Sciences in Australia sees this volume as a major contribution to improving our understanding of Australia’s population ageing. Social science research in this area truly underpins our ability as a nation to manage such demographic change, and its consequences for the economy and society. Such knowledge helps ensure that our citizens can live even better lives.’ — Glenn Withers, President, ASSA\"

The projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatially explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.

In mid-demographic-transition, many Asian countries enjoyed a large demographic 'dividend': extra economic growth owing to falling dependant/workforce ratios, or slower natural increase, or both. We estimate the dividend, 1985-2025, in sub-Saharan Africa and its populous countries. Dependency and natural increase peaked around 1985, 20 years after Asia. The UN projects an acceleration of the subsequent slow falls but disregards slowish declines in young-age mortality and thus, we argue, overestimates future fertility decline. Even if one accepts their projection, arithmetical and econometric evidence suggests an annual, if not total, dividend well below Asia's. The dividend arises more from falling dependency than reduced natural increase, and could be increased by accelerating the fertility decline (e.g., by reducing young-age mortality) or by employing a larger workforce productively. Any dividend from transition apart, low saving in much of Africa (unlike Asia) means that, given likely natural increase, current consumption per person is unsustainable because it depletes capital per person.

The human population is at the centre of research on global environmental change. On the one hand, population dynamics influence the environment and the global climate system through consumption-based carbon emissions. On the other hand, the health and well-being of the population are already being affected by climate change. A knowledge of population dynamics and population heterogeneity is thus fundamental to improving our understanding of how population size, composition, and distribution influence global environmental change and how these changes affect population subgroups differentially by demographic characteristics and spatial distribution. The increasing relevance of demographic research on the topic, coupled with availability of theoretical concepts and advancement in data and computing facilities, has contributed to growing engagement of demographers in this field. In the past 25 years, demographic research has enriched climate change research-with the key contribution being in moving beyond the narrow view that population matters only in terms of population size-by putting a greater emphasis on population composition and distribution, through presenting both empirical evidence and advanced population forecasting to account for demographic and spatial heterogeneity. What remains missing in the literature is research that investigates how global environmental change affects current and future demographic processes and, consequently, population trends. If global environmental change does influence fertility, mortality, and migration, then population estimates and forecasts need to adjust for climate feedback in population projections. Indisputably, this is the area of new research that directly requires expertise in population science and contribution from demographers.

The notion of a potential-growth indicator came to being in the field of matrix population models long ago, almost simultaneously with the pioneering Leslie model for age-structured population dynamics, although the term has been given and the theory developed only in recent years. The indicator represents an explicit function, R(L), of matrix L elements and indicates the position of the spectral radius of L relative to 1 on the real axis, thus signifying the population growth, or decline, or stabilization. Some indicators turned out to be useful in theoretical layouts and practical applications prior to calculating the spectral radius itself. The most senior (1994) and popular indicator, R0(L), is known as the net reproductive rate, and we consider two others, R1(L) and RRT(A), developed later on. All the three are different in terms of their simplicity and the level of generality, and we illustrate them with a case study of Calamagrostis epigeios, a long-rhizome perennial weed actively colonizing open spaces in the temperate zone. While the R0(L) and R1(L) fail, respectively, because of complexity and insufficient generality, the RRT(L) does succeed, justifying the merit of indication.

Immigration will be the key factor determining whether populations in the developed world increase or decrease over the coming century. New policy-based population projections illustrate this for the United States. Expansive immigration policies could increase the US population by hundreds of millions by 2100, while more restrictive policies could lead to population stabilisation or significant reductions. For the US, there is no plausible high-immigration path to a sustainable population. Because larger populations increase human environmental impacts, sustainability advocates in the US and other countries with high net immigration levels have strong prima facie reasons to support immigration reductions. Such reductions could achieve smaller populations in receiver countries and encourage smaller populations in sender countries, contributing to global ecological sustainability.

Population projections provide predictions of future population sizes for an area. Historically, most population projections have been produced using deterministic or scenario-based approaches and have not assessed uncertainty about future population change. Starting in 2015, however, the United Nations (UN) has produced probabilistic population projections for all countries using a Bayesian approach. There is also considerable interest in subnational probabilistic population projections, but the UN's national approach cannot be used directly for this purpose, because within-country correlations in fertility and mortality are generally larger than between-country ones, migration is not constrained in the same way, and there is a need to account for college and other special populations, particularly at the county level. We propose a Bayesian method for producing subnational population projections, including migration and accounting for college populations, by building on but modifying the UN approach. We illustrate our approach by applying it to the counties of Washington State and comparing the results with extant deterministic projections produced by Washington State demographers. Out-of-sample experiments show that our method gives accurate and well-calibrated forecasts and forecast intervals. In most cases, our intervals were narrower than the growth-based intervals issued by the state, particularly for shorter time horizons.

Mast seeding in temperate oak populations shapes the dynamics of seed consumers and numerous communities. Mast seeding responds positively to warm spring temperatures and is therefore expected to increase under global warming. We investigated the potential effects of changes in oak mast seeding on wild boar population dynamics, a widespread and abundant consumer species. Using long-term monitoring data, we showed that abundant acorn production enhances the proportion of breeding females. With a body-mass-structured population model and a fixed hunting rate of 0.424, we showed that high acorn production over time would lead to an average wild boar population growth rate of 1.197 whereas non-acorn production would lead to a stable population. Finally, using climate projections and a mechanistic model linking weather data to oak reproduction, we predicted that mast seeding frequency might increase over the next century, which would lead to increase in both wild boar population size and the magnitude of its temporal variation. Our study provides rare evidence that some species could greatly benefit from global warming thanks to higher food availability and therefore highlights the importance of investigating the cascading effects of changing weather conditions on the dynamics of wild animal populations to reliably assess the effects of climate change.

Within the next decade India is expected to surpass China as the world’s most populous country due to still higher fertility and a younger population. Around 2025 each country will be home to around 1.5 billion people. India is demographically very heterogeneous with some rural illiterate populations still having more than four children on average while educated urban women have fewer than 1.5 children and with great differences between states. We show that the population outlook greatly depends on the degree to which this heterogeneity is explicitly incorporated into the population projection model used. The conventional projection model, considering only the age and sex structures of the population at the national level, results in a lower projected population than the same model applied at the level of states because over time the high-fertility states gain more weight, thus applying the higher rates to more people. The opposite outcome results from an explicit consideration of education differentials because over time the proportion of more educated women with lower fertility increases, thus leading to lower predicted growth than in the conventional model. To comprehensively address this issue, we develop a five-dimensional model of India’s population by state, rural/urban place of residence, age, sex, and level of education and show the impacts of different degrees of aggregation. We also provide human capital scenarios for all Indian states that suggest that India will rapidly catch upwith other more developed countries in Asia if the recent pace of education expansion is maintained.