(A) Comparison of models of the relationship between total annual mortality and human-caused mortality for wolves in North America.

1Expanded model descriptions:(i) Generalized linear model (binomial errors with identity link) that allowed different slopes and intercepts for the relationship between total mortality and human offtake for two regions (wolves in the Northern Rocky Mountains (NRM) recovery area and wolves in previously-studied populations),(ii) General additive model that allowed regional differences, fit in the ‘mgcv’ package of R with cross-validation used to determine the optimum amount of smoothing. GAM models allow curvilinear functions if the data support curvature.(iii) Generalized linear model (binomial errors with identity link) that allowed the slope to change at a breakpoint and allowed regional differences,(iv) Generalized linear model (binomial errors with identity link) with no regional effect.(v) Generalized linear model (binomial errors with identity link) that allowed the slope to change at a breakpoint with no regional effect,(vi) Constant total mortality (no effect of human offtake on total mortality).2Number of parameters in the model (non-integer values are expected for general additive models).3*QAICc calculated using c-hat = 4, the estimated overdispersion value obtained from a quasi-binomial model and using the number of mortality rates (N = 48) as the sample size.4Akaike model weight.1. 扩展模型说明： (i) 广义线性模型（Generalized Linear Model, GLM），采用二项误差族与恒等联系函数，针对北落基山脉（Northern Rocky Mountains, NRM）恢复区灰狼种群，以及此前已被研究的灰狼种群这两个区域，允许其总死亡率与人类猎捕量之间的关系拥有不同的斜率和截距； (ii) 广义可加模型（General Additive Model, GAM），允许区域差异，通过R语言的`mgcv`包拟合，使用交叉验证确定最优平滑参数；当数据支持曲率特征时，GAM模型可拟合曲线函数； (iii) 广义线性模型（二项误差族与恒等联系函数），允许斜率在某一断点处发生变化，且支持区域差异； (iv) 广义线性模型（二项误差族与恒等联系函数），无区域效应； (v) 广义线性模型（二项误差族与恒等联系函数），允许斜率在某一断点处发生变化，但无区域效应； (vi) 恒定总死亡率模型，即人类猎捕对总死亡率无影响。 2. 模型参数数量：广义可加模型的参数值通常为非整数。 3. QAICc值计算：以准二项模型得到的估计过度离散值ĉ=4作为校正参数，以死亡率数量（N=48）作为样本量进行测算。 4. 赤池模型权重（Akaike model weight）。