Model selection results from cubic spline model fitted to female chamois body mass data.

Models are distinguished by the functional forms of α0 and β0. Specifically, we allowed α0 and β0 to be constant across years (α0; β0), vary linearly with year (α0(y); β0(y)), quadratically with year (α0(y2); β0(y2)) or linearly with population density (α0(d); β0(d)). Maximum log-likelihoods (LL) and ΔAICs are shown for each site. The most parsimonious models for each site are highlighted in bold (i.e. have a ΔAIC value that is ≤6 and lower than all simpler nested versions; see Richards [40]). n is sample size for each site.

模型依据α₀与β₀的函数形式进行区分。具体而言，我们设置α₀和β₀可呈现以下四种形式：不随年份变化的常数（α₀; β₀）、随年份线性变化（α₀(y); β₀(y)）、随年份二次变化（α₀(y²); β₀(y²)），以及随人口密度线性变化（α₀(d); β₀(d)）。各站点的最大对数似然值（log-likelihood，LL）与ΔAIC均已给出。各站点的最优简约模型已以粗体标注（即其ΔAIC值≤6，且低于所有更简单的嵌套模型；详见Richards [40]）。n为各站点的样本量。