If habitats contract or get fragmented, these reduced habitats cannot continue to support the same biodiversity as they did before, so they must lose species. While some species will be lost immediately, others can persist for a long time before going extinct. Indeed, areas recently protected may continue to lose species long after habitat loss has stopped. So, just because we don’t observe extinctions right away does not mean that everything is going to be OK. This phenomenon, often called “extinction debt”, also has implications for how ecosystems respond to climate change and to ecological invasions. A major scientific challenge is to understand the dynamics of this effect: how long before the extinctions are complete and which parameters drive it? Answering these depends to a large extent not only on having good empirical results but also on having a sound theoretical model of the community. I will be reviewing our current state of knowledge in this area and what case studies and larger meta-analyses have revealed. I will also discuss research on various models of the process and how our theoretical results can be used to design improved protected areas.

     Mutation rates are diversified within a species and across species. Why has the diversity of mutation rates evolved? What factors select high and low mutation rates? In this research, to elucidate the evolution of the diversity of the mutation rates and conditions selecting high and low mutation rates, we constructed a simulation model considering genes governing faithful DNA replication and growth rate.
     We considered a population consisted of monoploid unicellular asexual organisms. Each individual has two groups of genes: the repair genes and the competition genes. The repair genes govern DNA repair and replication speed. Here, we considered the trade-off between replication speed and fidelity; it is necessary to repair faithfully to suppress mutations, but it takes more time to repair faithfully. Thus, the higher fidelity, the lower replication speed is. The individuals with faster replication speed divides faster. The competition genes govern the competitive ability between individuals for survival. In DNA replication, replication errors occur in these two groups of genes and are partially repaired. The repairing probability of errors is determined by the repair genes and both of beneficial and deleterious replication errors are repaired at the same probability without discrimination. After that, individuals compete for survival. This process repeats until a stationary state. We analyzed the effects of genome size (the total size of the repair genes and the competition genes), probability of occurring beneficial and deleterious mutations, population size and others, on the evolution of mutation rate.
     In a population consisted of individuals with a large genome size, a high repair rate (consequently, a low mutation rate), a slow replication speed, and a large competitive ability evolved. Such a result may be because larger genome sizes potentially lead to large numbers of replication errors. Thus, to prevent considerable decrease in competitive ability by the large amount of deleterious mutations, even though the replication speed becomes late, a high repair rate and a consequent low mutation rate evolved. Furthermore, the lower mutation rate was, the larger competitive ability was; i.e., advantageous traits evolve when mutation rates are low. This result can be intuitively understood. If mutation rates are high, many mutations simultaneously occur in single individuals. Then, if beneficial mutations occur rarely, the fitnesses of these individuals should decrease due to the overall effects of mutations, and rare beneficial mutations cannot spread. On the other hand, if mutation rates are low, it is possible that individuals having only a beneficial mutation emerge in the population, though most other individuals should have low numbers of disadvantageous mutations. Then, the individuals having beneficial mutations are superior in the survival, spreading beneficial mutations to the population.
     Low mutation rate evolves in small genome size, and high mutation rate evolves in large genome size. Furthermore, high mutation rate evolves when high growth rate is advantageous, and low mutation rate evolve when individuals need to acquire beneficial mutations.

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