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.

本研究采用2017至2020年的性状测定数据，对四个嵌套尺度下的性状方差开展分解。随后，针对池塘尺度下测定或计算得到的非生物变量与生物变量，本研究检验了其对2020年11月测定、并以池塘为单位平均得到的所有物种所有分株的性状值的影响。此外，本研究采用结构方程模型（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。