The impact of ‘Cash for Clunkers’ on greenhouse gas emissions: a life cycle perspective

One of the goals of the US Consumer Assistance to Recycle and Save (CARS) Act of 2009, more commonly known as 'Cash for Clunkers', was to improve the US vehicle fleet fuel efficiency. Previous studies of the program's environmental impact have focused mainly on the effect of improved fuel economy, and the resulting reductions in fuel use and emissions during the vehicle use phase. We propose and apply a method for analyzing the net effect of CARS on greenhouse gas emissions from a full vehicle life cycle perspective, including the impact of premature production and retirement of vehicles. We find that CARS had a one-time effect of preventing 4.4 million metric tons of CO2-equivalent emissions, about 0.4% of US annual light-duty vehicle emissions. Of these, 3.7 million metric tons are avoided during the period of the expected remaining life of the inefficient 'clunkers'. 1.5 million metric tons are avoided as consumers purchase vehicles that are more efficient than their next replacement vehicle would otherwise have been. An additional 0.8 million metric tons are emitted as a result of premature manufacturing and disposal of vehicles. These results are sensitive to the remaining lifetime of the 'clunkers' and to the fuel economy of new vehicles in the absence of CARS, suggesting important considerations for policymakers deliberating on the use of accelerated vehicle retirement programs as a part of the greenhouse gas emissions policy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85437/1/erl10_4_044003.pd

Life Cycle Environmental and Economic Impacts of "Cash for Clunkers"

Through the $3 billion US Consumer Assistance to Recycle and Save (CARS) Act of 2009, or “Cash for Clunkers” program, nearly 700,000 consumers scrapped fuel-inefficient vehicles in exchange for rebates of$3,500 or $4,500 toward the purchase of a new, more fuel-efficient vehicle. This research aims to provide a more comprehensive, life cycle accounting of environmental and economic benefits associated with CARS. Environmental benefits included reduction in both greenhouse gas and criteria pollutant emissions. A life cycle accounting suggests that CARS prevented 4.4 million metric tons of CO2-equivalent greenhouse gas emissions. This is substantially lower than estimates in previous studies, which failed to include the life cycle effect of additional emissions produced during new vehicle production and overestimated vehicle-miles remaining in the life of ‘clunkers’. Using previously estimated damage costs of$21 per metric ton of CO2, this benefit is worth $93 million. About 20,000 metric tons of criteria pollutant emissions were also avoided. Damage costs from criteria pollutants vary by geographic location and source height, which previous studies do not account for. Incorporating these factors suggests the benefits from avoided criteria pollutants were worth$17 million (two to six times greater than estimates using simple average or median damage costs). CARS also provided economic stimulus on a macroeconomic level and for participants. The economic literature suggests the program induced sales of up to 450,000 new vehicles; provided up to 62,000 job-years; and contributed up to $4 billion in gross domestic product. Comparing the market value of scrapped vehicles to the rebate from CARS, the consumer surplus or “gift” to participants is calculated to be up to$2 billion (about $2,000 to$3,000 per vehicle). This is significantly more than offered in previous vehicle scrappage programs, and suggests opportunities to get more environmental and economic “bang for the buck” with lower rebates, an alternate mechanism for setting rebate values, and/or more specific targeting of vehicles for participation.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/83513/1/Lenski_thesis_final.pd

Does the Red Queen reign in the kingdom of digital organisms?

In competition experiments between two RNA viruses of equal or almost equal fitness, often both strains gain in fitness before one eventually excludes the other. This observation has been linked to the Red Queen effect, which describes a situation in which organisms have to constantly adapt just to keep their status quo. I carried out experiments with digital organisms (self-replicating computer programs) in order to clarify how the competing strains' location in fitness space influences the Red-Queen effect. I found that gains in fitness during competition were prevalent for organisms that were taken from the base of a fitness peak, but absent or rare for organisms that were taken from the top of a peak or from a considerable distance away from the nearest peak. In the latter two cases, either neutral drift and loss of the fittest mutants or the waiting time to the first beneficial mutation were more important factors. Moreover, I found that the Red-Queen dynamic in general led to faster exclusion than the other two mechanisms.Comment: 10 pages, 5 eps figure

Diversity in CRISPR-based immunity protects susceptible genotypes by restricting phage spread and evolution.

This is the final version. Available from the publisher via the DOI in this record.Data deposited at dryad: https://doi.org/10.5061/dryad.66t1g1k00.Diversity in host resistance often associates with reduced pathogen spread. This may result from ecological and evolutionary processes, likely with feedback between them. Theory and experiments on bacteria-phage interactions have shown that genetic diversity of the bacterial adaptive immune system can limit phage evolution to overcome resistance. Using the CRISPR-Cas bacterial immune system and lytic phage, we engineered a host-pathogen system where each bacterial host genotype could be infected by only one phage genotype. With this model system, we explored how CRISPR diversity impacts the spread of phage when they can overcome a resistance allele, how immune diversity affects the evolution of the phage to increase its host range, and if there was feedback between these processes. We show that increasing CRISPR diversity benefits susceptible bacteria via a dilution effect, which limits the spread of the phage. We suggest that this ecological effect impacts the evolution of novel phage genotypes, which then feeds back into phage population dynamics

Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability

The evolution of complex organismal traits is obvious as a historical fact, but the underlying causes—including the role of natural selection—are contested. Gould argued that a random walk from a necessarily simple beginning would produce the appearance of increasing complexity over time. Others contend that selection, including coevolutionary arms races, can systematically push organisms toward more complex traits. Methodological challenges have largely precluded experimental tests of these hypotheses. Using the Avida platform for digital evolution, we show that coevolution of hosts and parasites greatly increases organismal complexity relative to that otherwise achieved. As parasites evolve to counter the rise of resistant hosts, parasite populations retain a genetic record of past coevolutionary states. As a consequence, hosts differentially escape by performing progressively more complex functions. We show that coevolution's unique feedback between host and parasite frequencies is a key process in the evolution of complexity. Strikingly, the hosts evolve genomes that are also more phenotypically evolvable, similar to the phenomenon of contingency loci observed in bacterial pathogens. Because coevolution is ubiquitous in nature, our results support a general model whereby antagonistic interactions and natural selection together favor both increased complexity and evolvability

A soluble model of evolution and extinction dynamics in a rugged fitness landscape

We consider a continuum version of a previously introduced and numerically studied model of macroevolution (PRL 75, 2055, (1995)) in which agents evolve by an optimization process in a rugged fitness landscape and die due to their competitive interactions. We first formulate dynamical equations for the fitness distribution and the survival probability. Secondly we analytically derive the $t^{-2}$ law which characterizes the life time distribution of biological genera. Thirdly we discuss other dynamical properties of the model such as the rate of extinction and conclude with a brief discussion.Comment: 6 pages LaTeX source with 2 figures. Submitted to PRL (Jan. 97

Evolution Equation of Phenotype Distribution: General Formulation and Application to Error Catastrophe

An equation describing the evolution of phenotypic distribution is derived using methods developed in statistical physics. The equation is solved by using the singular perturbation method, and assuming that the number of bases in the genetic sequence is large. Applying the equation to the mutation-selection model by Eigen provides the critical mutation rate for the error catastrophe. Phenotypic fluctuation of clones (individuals sharing the same gene) is introduced into this evolution equation. With this formalism, it is found that the critical mutation rate is sometimes increased by the phenotypic fluctuations, i.e., noise can enhance robustness of a fitted state to mutation. Our formalism is systematic and general, while approximations to derive more tractable evolution equations are also discussed.Comment: 22 pages, 2 figure

Evolutionary instability of Zero Determinant strategies demonstrates that winning isn't everything

Zero Determinant (ZD) strategies are a new class of probabilistic and conditional strategies that are able to unilaterally set the expected payoff of an opponent in iterated plays of the Prisoner's Dilemma irrespective of the opponent's strategy, or else to set the ratio between a ZD player's and their opponent's expected payoff. Here we show that while ZD strategies are weakly dominant, they are not evolutionarily stable and will instead evolve into less coercive strategies. We show that ZD strategies with an informational advantage over other players that allows them to recognize other ZD strategies can be evolutionarily stable (and able to exploit other players). However, such an advantage is bound to be short-lived as opposing strategies evolve to counteract the recognition.Comment: 14 pages, 4 figures. Change in title (again!) to comply with Nature Communications requirements. To appear in Nature Communication

Scaling laws in bacterial genomes: A side-effect of selection of mutational robustness?

In the past few years, numerous research projects have focused on identifying and understanding scaling properties in the gene content of prokaryote genomes and the intricacy of their regulation networks. Yet, and despite the increasing amount of data available, the origins of these scalings remain an open question. The RAevol model, a digital genetics model, provides us with an insight into the mechanisms involved in an evolutionary process. The results we present here show that (i) our model reproduces qualitatively these scaling laws and that (ii) these laws are not due to differences in lifestyles but to differences in the spontaneous rates of mutations and rearrangements. We argue that this is due to an indirect selective pressure for robustness that constrains the genome size

Cryptic Population Dynamics: Rapid Evolution Masks Trophic Interactions

Trophic relationships, such as those between predator and prey or between pathogen and host, are key interactions linking species in ecological food webs. The structure of these links and their strengths have major consequences for the dynamics and stability of food webs. The existence and strength of particular trophic links has often been assessed using observational data on changes in species abundance through time. Here we show that very strong links can be completely missed by these kinds of analyses when changes in population abundance are accompanied by contemporaneous rapid evolution in the prey or host species. Experimental observations, in rotifer-alga and phage-bacteria chemostats, show that the predator or pathogen can exhibit large-amplitude cycles while the abundance of the prey or host remains essentially constant. We know that the species are tightly linked in these experimental microcosms, but without this knowledge, we would infer from observed patterns in abundance that the species are weakly or not at all linked. Mathematical modeling shows that this kind of cryptic dynamics occurs when there is rapid prey or host evolution for traits conferring defense against attack, and the cost of defense (in terms of tradeoffs with other fitness components) is low. Several predictions of the theory that we developed to explain the rotifer-alga experiments are confirmed in the phage-bacteria experiments, where bacterial evolution could be tracked. Modeling suggests that rapid evolution may also confound experimental approaches to measuring interaction strength, but it identifies certain experimental designs as being more robust against potential confounding by rapid evolution