Collaborative Research: Integrating Genetically Informed Models of Germination and Flowering to Predict Life History Responses to Changing Climate

物候学--生物事件的季节性时间--是生物体对气候变化最重要的反应之一。对于一年生植物物种来说，种子萌发和开花的季节性时间至关重要。萌发和开花时间相互作用，决定了生长、开花和结实的模式。因此，一个包括这些事件及其相互作用的综合生命周期模型对于在自然条件下预测每个物候转变、整个生命周期和环境扰动影响的持续性是必要的。利用拟南芥开花和萌发的分子遗传学基础上的丰富遗传信息，该项目将开发综合的生活史模型，以预测不同气候情景下的地理范围内的基因型特定表现。这些预测将使用不同发芽和开花等位基因组合的独特遗传物质在季节性不同的田间地点进行验证。这项工作直接关系到预测植物对气候变化的反应。它的目的是预测不同气候条件下的萌发时间和同步性，这在农业环境中是直接相关的。该模型还将预测发芽时间的变化如何影响生殖时间和产量，这对于预测作物物种以及与其一起生长的杂草的反应非常重要。最后，它使用包含用于休眠操作的候选遗传位点的基因类型来评估这些基因将如何对变化的气候做出反应。

Phenology - the seasonal timing of biological events - is one of the most important organismal responses to climate change. For annual plant species, the seasonal timing of seed germination and flowering is crucial. Germination and flowering time interact to determine patterns of growth, flowering and seed set. Thus, an integrated life-cycle model that includes these events and their interactions is necessary for predicting under natural conditions each phenological transition, the overall life cycle, and the persistence of effects of environmental perturbations. Using the abundant genetic information on the molecular-genetic basis of flowering and germination in Arabidopsis thaliana, this project will develop integrated life-history models to predict genotype-specific performance across a geographic range with different climatic scenarios. These predictions will be tested using unique genetic material of different combinations of germination and flowering alleles in seasonally contrasting field sites. This work directly pertains to predicting plant responses to climate change. It aims to predict germination timing and synchrony under various climatic conditions, which is of direct interest in agricultural settings. The model will also predict how changes in germination timing affect reproductive timing and yield, which is important for predicting responses of crop species as well as the weeds that grow with them. Finally, it uses genotypes containing candidate genetic loci for dormancy manipulations to assess how those genes will respond to altered climates.