Data_ponds_Kerguelen

We used traits measurements from 2017 to 2020 to partition trait variances across four nested scales. Next, we tested for the effects of abiotic and biotic variables measured or calculated at pond scale, on trait values measured in November 2020 and averaged at pond scale, on all ramets of all species. More, we tested for the direct and indirect effects of the seven traits on individual performance (dry biomass) using a Structural Equation Modeling (SEM) procedure.

我们采用2017至2020年的性状测量数据，对四个嵌套尺度下的性状方差进行分解。随后，我们针对池塘尺度下实测或计算得到的非生物与生物变量，检验其对所有物种所有分株的、2020年11月测定并以池塘为单位平均的性状值的影响。此外，我们采用结构方程模型（Structural Equation Modeling, SEM）方法，检验了7个性状对个体表现（干生物量）的直接与间接效应。