Phenomenological Models of the Global Demographic Dynamics and Their Usage for Forecasting in 21st Century

A great discovery made by H. von Foerster, P. M. Mora and L. W. Amiot was published in a 1960 issue of “Science”. The authors showed that existing data for calculating the Earth’s population in the new era (from 1 to 1958) could be described with incredibly high proximity by a hyperbolic function with the point of singularity on 13 November 2026. Thus, empirical regularity of the rise of the human population was established, which was marked by explosive demographic growth in the 20th century when during only one century it almost quadrupled: from 1.656 billion in 1900 to 6.144 billion in 2000. Nowadays, the world population has already overcome 7.8 billion people. Immediately after 1960, an active search for phenomenological models began to explain the mechanism of the hyperbolic population growth and the following demographic transition designed to stabilize its population. A significant role in explaining the mechanism of the hyperbolic growth of the world population was played by S. Kuznets (1960) and E. Boserup (1965), who found out that the rates of technological progress historically increased in proportion to the Earth’s population. It meant that the growth of the population led to raising the level of life-supporting technologies, and the latter in its turn enlarged the carrying capacity of the Earth, making it possible for the world population to expand. Proceeding from the information imperative, we have developed the model of the demographic dynamics for the 21st century for the first time. The model shows that with the development and spread of Intelligent Machines (IM), the number of the world population reaching a certain maximum will then irreversibly decline. Human depopulation will largely touch upon the most developed countries, where IM is used intensively nowadays. Until a certain moment in time, this depopulation in developed countries will be compensated by the explosive growth of the population in African countries located south of the Sahara. Calculations in our model reveal that the peak of the human population of 8.52 billion people will be reached in 2050, then it will irreversibly go down to 7.9 billion people by 2100, if developed countries do not take timely effective measures to overcome the process of information depopulation.

Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types(PFTs)and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

Projecting the distribution and abundance of Mediterranean tree species under climate change:a demographic approach

Distribution and abundance patterns of species arise from the spatiotemporal dynamics of demographic processes.Population rates of birth,death,growth and patterns of dispersal are,in turn,influenced by environmental conditions and biotic interactions.However,current approaches for modelling large-scale geographical patterns often bypass these simple premises.centred in the mainland territory of Spain and using Pinus halepensis as a case study,our goal was to gain insight into the main driv-ers affecting local demographic processes,and how large-scale distribution and abundance patterns are shaped by these local variations in vital rates.Methods We applied the integral projection methodology to develop a spa-tially explicit demographic model of tree species in mainland Spain,using individual-level data from a national forest inventory.In our integral projection model,environmental conditions and competi-tive interactions influence the survival,growth and reproduction of trees,and we model explicitly the dynamic colonization of new patches.With this framework,the projected distribution and abun-dance patterns of P.halepensis up to 2090 were evaluated under two different climate scenarios.Important Findings When environmental conditions were kept constant,popula-tions tended to decrease in net number of adults and to increase in net basal area,thus consisting in fewer and bigger individuals.Accounting for climate change in our simulations exacerbated the trend in mortality,causing widespread losses in number of trees,and few locations maintained populations of>100 adult individu-als per hectare.the expected increase in mortality under climate change,on the other hand,prompted a higher degree of regeneration via the release of niche space,although not enough to maintain current abundance levels.colonization spatial patterns did not vary significantly with climatic conditions,but the species was able to increase its distribution under climate change more than in a constant climate scenario.Our approach yields relevant information at different spatial scales,from plot-level processes to large-scale abundance patterns.With it,we clearly indicate the strong role that climate change could have in shaping future forest communities through its differential influence on demographic processes.

Spatial microsimulation modeling for residential energy demand of England in an uncertain future

High quality infrastructure is crucial to economic success and the sustainability of society.Infrastructures for services,such as transport,energy,and water supply,also have long lead times,and therefore require effective long-term planning.In this paper,we report on work undertaken as part of the UK Infrastructure Transitions Research Consortium to construct long-term models of demographic change which can help to inform infrastructure planning for transport,energy,and water as well as IT and waste.A set of demographic microsimulation models(MSM),which are spatially disaggregate to the geography of UK Local Authorities,provides a high level of detail for understanding the drivers of changing patterns of demand.However,although robust forecasting models are required to support projections based on the notion of‘predict-and-provide,’the potential for behavioral adaptation is also an important consideration in this context.In this paper,we therefore establish a framework for linkage of a MSM of household composition,with behavior relating to the consumption of energy.We will investigate variations in household energy consumption within and between different household groups.An appropriate range of household types will be defined through the application of decision trees to consumption data from a detailed survey produced by the UK Department of Energy and Climate Change.From this,analysis conclusions will be drawn about the impact of changing demographics at both household and individual level,and about the potential effect of behavioral adjustments for different household groups.