Population scenarios based on probabilistic projections: An application for the Millennium Ecosystem Assessment

O'Neill, B.C. (2005). Population scenarios based on probabilistic projections: An application for the Millennium Ecosystem Assessment. Population and Environment 26 (3) 229-254. 10.1007/s11111-005-1876-7.

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Probabilistic population forecasts offer a number of advantages to users. However, in some cases population is one component of a larger analysis that may take a different approach to uncertainty. For example, integrated assessments of environmental issues such as climate change or ecosystem degradation have typically used a small number of alternative scenarios to explore uncertainty in future environmental outcomes. In such cases, population projections that are provided only as probability distributions are difficult to use. I present a method of employing probabilistic population projections to derive individual, deterministic projections that can be used within scenarios for integrated assessments. The principal advantages of this approach are that (1) it provides a less ad hoc way of defining deterministic projections intended to be consistent with more comprehensive scenarios that describe, among other things, future socio-economic developments; (2) it provides more flexibility in specifying input assumptions for deterministic projections as compared to choosing off-the-shelf projections, allowing population assumptions to be tailored to the scenario; and (3) it provides a quantitative assessment of the uncertainty associated with any given deterministic projection. I describe the application of the method to the development of population projections used in integrated scenarios for the Millennium Ecosystem Assessment, an international scientific effort to assess the current conditions of and future outlook for global ecosystem goods and services. Results show that the MA scenarios are each consistent with a relatively wide range of demographic outcomes. For some scenarios, ranges of plausible outcomes in some regions overlap substantially, indicating that particular population projections could be consistent with more than one scenario. In other cases, uncertainty ranges for different scenarios are distinct, indicating that a projection consistent with one scenario is unlikely to be also consistent with another. Comparing variances of the conditional projections also provides insight into how much different storylines constrain future demographic developments. The development of the MA projections points to important areas of future research on correlations among demographic rates and on uncertainty across scales. It also serves as an illustration of how probabilistic and alternative scenario-based approaches to uncertainty can be combined within a single integrated analysis.

Item Type: Article
Uncontrolled Keywords: Projections; Uncertainty; Scenarios; Integrated assessment; Probabilistic
Research Programs: Population and Climate Change (PCC)
Bibliographic Reference: Population and Environment; 26(3):229-254 (January 2005)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:17
Last Modified: 27 Aug 2021 17:37
URI: https://pure.iiasa.ac.at/7526

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