Lambert Amaury
Laboratoire de Probabilités et Modèles Aléatoires, UMR 7599 CNRS and UPMC Univ Paris 06, Case courrier 188, 4, Place Jussieu, 75252 Paris Cedex 05, France.
J Math Biol. 2011 Jul;63(1):57-72. doi: 10.1007/s00285-010-0361-9. Epub 2010 Aug 31.
We consider a general, neutral, dynamical model of biodiversity. Individuals have i.i.d. lifetime durations, which are not necessarily exponentially distributed, and each individual gives birth independently at constant rate λ. Thus, the population size is a homogeneous, binary Crump-Mode-Jagers process (which is not necessarily a Markov process). We assume that types are clonally inherited. We consider two classes of speciation models in this setting. In the immigration model, new individuals of an entirely new species singly enter the population at constant rate μ (e.g., from the mainland into the island). In the mutation model, each individual independently experiences point mutations in its germ line, at constant rate θ. We are interested in the species abundance distribution, i.e., in the numbers, denoted I(n)(k) in the immigration model and A(n)(k) in the mutation model, of species represented by k individuals, k = 1, 2, . . . , n, when there are n individuals in the total population. In the immigration model, we prove that the numbers (I(t)(k); k ≥ 1) of species represented by k individuals at time t, are independent Poisson variables with parameters as in Fisher's log-series. When conditioning on the total size of the population to equal n, this results in species abundance distributions given by Ewens' sampling formula. In particular, I(n)(k) converges as n → ∞ to a Poisson r.v. with mean γ/k, where γ : = μ/λ. In the mutation model, as n → ∞, we obtain the almost sure convergence of n (-1) A(n)(k) to a nonrandom explicit constant. In the case of a critical, linear birth-death process, this constant is given by Fisher's log-series, namely n(-1) A(n)(k) converges to α(k)/k, where α : = λ/(λ + θ). In both models, the abundances of the most abundant species are briefly discussed.
我们考虑一个通用的、中性的生物多样性动态模型。个体具有独立同分布的寿命时长,其不一定呈指数分布,且每个个体以恒定速率λ独立生育。因此,种群规模是一个齐次二元Crump - Mode - Jagers过程(其不一定是马尔可夫过程)。我们假设类型是克隆遗传的。在此设定下,我们考虑两类物种形成模型。在迁入模型中,全新物种的新个体以恒定速率μ单一个体地进入种群(例如,从大陆进入岛屿)。在突变模型中,每个个体在其生殖系中独立经历点突变,速率为恒定的θ。我们关注物种丰度分布,即在迁入模型中由k个个体代表的物种数量记为I(n)(k),在突变模型中记为A(n)(k),其中k = 1, 2, …, n,此时种群总数为n个个体。在迁入模型中,我们证明在时刻t由k个个体代表的物种数量(I(t)(k); k ≥ 1)是参数如费希尔对数级数中的独立泊松变量。当以种群总规模等于n为条件时,这会得到由尤恩斯抽样公式给出的物种丰度分布。特别地,当n → ∞时,I(n)(k)收敛到均值为γ/k的泊松随机变量,其中γ := μ/λ。在突变模型中,当n → ∞时,我们得到n^(-1)A(n)(k)几乎必然收敛到一个非随机显式常数。在临界线性生死过程的情况下,这个常数由费希尔对数级数给出,即n^(-1)A(n)(k)收敛到α(k)/k,其中α := λ/(λ + θ)。在这两个模型中,都简要讨论了最丰富物种的丰度情况。