Ergon Rolf
University of South-Eastern Norway Porsgrunn Norway.
Ecol Evol. 2022 Apr 17;12(4):e8836. doi: 10.1002/ece3.8836. eCollection 2022 Apr.
It is well documented that individuals of wild populations can adjust to climate change by means of phenotypic plasticity, but few reports on adaptation by means of genetically based microevolution caused by selection. Disentanglement of these separate effects requires that the reference environment (the environmental zero point) is defined, and this should not be done arbitrarily. The problem is that an error in the reference environment may lead to large errors in predicted microevolution. Together with parameter values and initial mean trait values, the reference environment can be estimated from environmental, phenotypic and fitness data. A prediction error method for this purpose is described, with the feasibility shown by simulations. As shown in a toy example, an estimated reference environment may have large errors, especially for small populations. This may still be a better choice than use of an initial environmental value in a recorded time series, or the mean value, which is often used. Another alternative may be to use the mean value of a past and stationary stochastic environment, which the population is judged to have been fully adapted to, in the sense that the expected geometric mean fitness was at a global maximum. Exceptions are cases with constant phenotypic plasticity, where the microevolutionary changes per generation follow directly from phenotypic and environmental data, independent of the chosen reference environment.
有充分文献记载,野生种群个体可通过表型可塑性来适应气候变化,但关于因选择导致的基于基因的微进化适应的报道却很少。要区分这些不同的影响,需要定义参考环境(环境零点),且不应随意定义。问题在于参考环境中的误差可能导致预测微进化出现大的误差。参考环境可与参数值和初始平均性状值一起,根据环境、表型和适合度数据进行估计。本文描述了一种用于此目的的预测误差方法,并通过模拟展示了其可行性。如一个简单示例所示,估计的参考环境可能存在较大误差,尤其是对于小种群。这可能仍比在记录的时间序列中使用初始环境值或常用的平均值更好。另一种选择可能是使用过去稳定随机环境的平均值,从预期几何平均适合度处于全局最大值的意义上说,种群被认为已完全适应该环境。恒定表型可塑性的情况除外,在这种情况下,每代的微进化变化可直接从表型和环境数据得出,与所选参考环境无关。