Is the Uncertainty about Climate Change Too Large for Expected Cost-Benefit Analysis?

Cost-benefit analysis is only applicable if the variances of both costs and benefits are finite. In the case of climate change, the variances of the net present marginal costs and benefits of greenhouse gas emission reduction need to be finite. Finiteness is hard, if not impossible to prove. The opposite is easier to establish as one needs to shows that there is one, not impossible representation of the climate change with infinite variance. The paper shows that all relevant current variables of the FUND model have finite variances. However, there is a small chance that climate change reverses economic growth in some regions. In that case, the discount rate becomes negative and the net present marginal benefits of greenhouse gas emission reduction becomes very large. So large, that its variance is unbounded.Climate change, cost-benefit analysis, uncertainty

The evolution of immigration strategies facilitates niche expansion by divergent adaptation in a structured metapopulation model

Local adaptation and habitat choice are two key factors that control the distribution and diversification of species. Here we model habitat choice mechanistically as the outcome of dispersal with nonrandom immigration. We consider a structured metapopulation with a continuous distribution of patch types and determine the evolutionarily stable immigration strategy as the function linking patch type to the probability of settling in the patch on encounter. We uncover a novel mechanism whereby coexisting strains that only slightly differ in their local adaptation trait can evolve substantially different immigration strategies. In turn, different habitat use selects for divergent adaptations in the two strains. We propose that the joint evolution of immigration and local adaptation can facilitate diversification and discuss our results in the light of niche conservatism versus niche expansion.Peer reviewe

Joint evolution of altruistic cooperation and dispersal in a metapopulation of small local populations

We investigate the joint evolution of public goods cooperation and dispersal in a metapopulation model with small local populations. Altruistic cooperation can evolve due to assortment and kin selection, and dispersal can evolve because of demographic stochasticity, catastrophes and kin selection. Metapopulation structures resulting in assortment have been shown to make selection for cooperation possible. But how does dispersal affect cooperation and vice versa, when both are allowed to evolve as continuous traits? We found four qualitatively different evolutionary outcomes. (1) Monomorphic evolution to full defection with positive dispersal. (2) Monomorphic evolution to an evolutionarily stable state with positive cooperation and dispersal. In this case, parameter changes selecting for increased cooperation typically also select for increased dispersal. (3) Evolutionary branching can result in the evolutionarily stable coexistence of defectors and cooperators. Although defectors could be expected to disperse more than cooperators, here we show that also the opposite case is possible: Defectors tend to disperse less than cooperators when the total amount of cooperation in the dimorphic population is low enough. (4) Selection for too low cooperation can cause the extinction of the evolving population. For moderate catastrophe rates dispersal needs to be initially very frequent for evolutionary suicide to occur. Although selection for less dispersal in principle could prevent such evolutionary suicide, in most cases this rescuing effect is not sufficient, because selection in the cooperation trait is typically much stronger. If the catastrophe rate is large enough, a part of the boundary of viability can be evolutionarily attracting with respect to both strategy components, in which case evolutionary suicide is expected from all initial conditions

Biogeography-Based Optimization

Biogeography is the study of the geographical distribution of biological organisms. Mathematical equations that govern the distribution of organisms were first discovered and developed during the 1960s. The mindset of the engineer is that we can learn from nature. This motivates the application of biogeography to optimization problems. Just as the mathematics of biological genetics inspired the development of genetic algorithms (GAs), and the mathematics of biological neurons inspired the development of artificial neural networks, this paper considers the mathematics of biogeography as the basis for the development of a new field: biogeography-based optimization (BBO). We discuss natural biogeography and its mathematics, and then discuss how it can be used to solve optimization problems. We see that BBO has features in common with other biology-based optimization methods, such as GAs and particle swarm optimization (PSO). This makes BBO applicable to many of the same types of problems that GAs and PSO are used for, namely high-dimension problems with multiple local optima. However, BBO also has some features that are unique among biology-based optimization methods. We demonstrate the performance of BBO on a set of 14 standard benchmarks and compare it with seven other biology-based optimization algorithms. We also demonstrate BBO on a real-world sensor selection problem for aircraft engine health estimation

INFINITE UNCERTAINTY, FORGOTTEN FEEDBACKS, AND COST-BENEFIT ANALYSIS OF CLIMATE POLICY

Tol (2003) found evidence that the uncertainty that surrounds estimates of the marginal damage of climate change may be infinite even if total damages are finite and questioned the applicability of expected cost-benefit analysis to global mitigation policy. Yohe (2003) suggested that this problem could be alleviated if international development aid were directed at eliminating the source of the problem – climate induced negative growth rates in a few regions along a handful of troublesome scenarios. The hypothesis about adding a second policy lever to the climate policy calculus is shown to hold, but not as robustly as perhaps expected. Infinite uncertainty and its implications for global mitigation policy can be avoided for a reasonable price in the relatively unlikely event that climate change can cause negative economic growth in a region or two when the portfolio of international policies includes at least two tools.climate policy, development aid, equity weighting, expected cost-benefit analysis

Climate change and human migration: managing the cascade effects initiated by natural disasters

The potential links between climate change, human migration and conflict have been receiving an increasing amount of attention since the turn of the century. Up-to-date reports that address the most recent understanding of climate change and environmental hazards indicate that humans have undeniably contributed to the rising global temperature and will continue to do so if lower pollution thresholds are not maintained. While this enacts a multitude of physical, biological, chemical, and societal changes, it is imperative to analyze and address the impact of climate change on human migration trends. Human migrants face several types of problems ranging from environmental issues related to climate change (sea-level rise, more frequent and intense storms and floods, drought, wildfires, etc.), to conflicts from physical migration into neighboring towns, cities, regions, or countries. These types of physical migration that are climate change driven, which can be referred to as “adaptation migration” can be capable of snowballing from a human-to-environment issue into a human-to-human conflict; usually involving some type of violence or political discrimination/persecution. The aim of this study is to analyze how climate change is impacting human migration trends, the possible percolating effects that can result from human migration, and how these factors have influenced and will continue to influence governments and governance in the coastal area. The information in this report will be able to provide a greater understanding of adaptation migration through the use of differential equations, how these trends can be modeled, and how Game Theory can be used as a strategic tool for policymakers moving forward.I would like to thank the WACOMA program and all of its coordinators, past and present, as they have all played an essential role in helping not only myself, but all of the students develop into the people we are today. Thank you all for everything you have done throughout this entire process

INFINITE UNCERTAINTY, FORGOTTEN FEEDBACKS, AND COST-BENEFIT ANALYSIS OF CLIMATE POLICY

Tol (2003) found evidence that the uncertainty that surrounds estimates of the marginal damage of climate change may be infinite even if total damages are finite and questioned the applicability of expected cost-benefit analysis to global mitigation policy. Yohe (2003) suggested that this problem could be alleviated if international development aid were directed at eliminating the source of the problem – climate induced negative growth rates in a few regions along a handful of troublesome scenarios. The hypothesis about adding a second policy lever to the climate policy calculus is shown to hold, but not as robustly as perhaps expected. Infinite uncertainty and its implications for global mitigation policy can be avoided for a reasonable price in the relatively unlikely event that climate change can cause negative economic growth in a region or two when the portfolio of international policies includes at least two tools.climate policy, development aid, equity weighting, expected cost-benefit analysis