Data from: From a line in the sand to a landscape of decisions: a Hierarchical Diversity Decision Framework (HiDDeF) for estimating and communicating biodiversity loss along anthropogenic gradients

1. In setting water quality criteria, managers must choose thresholds for stressors that are protective of aquatic biodiversity. Setting such thresholds requires making implicit judgments about the degree of biodiversity loss that managers are willing to accept. 2. We present a new modeling approach, the Hierarchical Diversity Decision Framework model (HiDDeF) that explicitly communicates the sensitivity of water quality benchmarks to these implicit judgements. We apply HiDDeF to a dataset of stream macroinvertebrate abundances across 218 sites in southwestern West Virginia, USA where alkaline mine drainage increases streamwater conductivity and leads to the loss of sensitive taxa throughout regional river networks. 3. By integrating responses of individual taxa within a flexible hierarchical framework, HiDDeF reliably predicts macroinvertebrate assemblages across the full range of conductivities observed in the training dataset but requires only a fraction of the sites required in previous studies. HiDDeF results suggest that the current conductivity benchmark (300 μS/cm) for regional streams translates to 50% loss in abundance for at least one-quarter of regional macroinvertebrate taxa. 4. HiDDeF produces a “decision landscape” that allows decision makers to assess sensitivity of proposed benchmarks to their choice of protective level. HiDDeF allows users to investigate both individual and community level responses to environmental gradients and generates output that includes a comprehensive summary of uncertainty in model parameters.

1. 在制定水质标准时，管理者需选取可保护水生生物多样性的胁迫因子阈值。设定此类阈值，需要管理者就自身可接受的生物多样性损失程度做出隐性判断。2. 本研究提出一种全新建模方法——分层多样性决策框架模型（Hierarchical Diversity Decision Framework model, HiDDeF），可明确阐释水质基准对上述隐性判断的敏感性。我们将HiDDeF应用于美国西弗吉尼亚州西南部218个监测点的溪流大型底栖无脊椎动物丰度数据集，该区域内碱性矿山排水会提升河流水体电导率，并导致整个区域河网中敏感类群的消失。3. 通过在灵活的分层框架内整合单个类群的响应特征，HiDDeF可在训练数据集观测到的全电导率范围内可靠预测大型底栖无脊椎动物群落组成，且仅需以往研究所需监测点数量的一小部分。HiDDeF的分析结果显示，当前区域溪流的电导率基准（300 μS/cm）会导致至少四分之一的区域大型底栖无脊椎动物类群的丰度下降50%。4. HiDDeF可生成“决策景观”，帮助决策者评估拟议基准对其所选取的保护水平的敏感性。该模型支持用户探究单个类群与群落水平对环境梯度的响应，并输出包含模型参数不确定性的全面汇总结果。