Data from: The effect of cost surface parameterization on landscape resistance estimates

A cost or resistance surface is a representation of a landscape’s permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization.

成本表面或阻力表面（cost or resistance surface）是表征景观对动物移动或基因流渗透性的空间表达形式，同时也是景观生态学与遗传学研究中用于量化功能连通性的核心工具。然而，通过为不同景观要素赋予权重以参数化阻力表面的研究路径始终颇具挑战：真实的成本值鲜少可被精准获知，因此学界常借助专家意见推导相对权重。若能明确不同景观阻力估计值对相对权重的敏感性，便可大幅简化权重赋值的工作流程。我们针对三种阻力表面参数化方法与两类景观渗透性模型——最小成本路径（least cost path）与有效阻力（effective resistance）——开展了敏感性分析，研究结果显示，针对成本权重的变化存在两种质上截然不同的响应模式：线性变化与渐近变化。其中敏感性最高的模型（即呈现线性变化的模型）为基于阻力编码表面的累积最小成本与有效阻力估计值（即高质量景观要素保持为低值，低质量景观要素取更高值）；其余所有阻力表面场景均呈现渐近变化的响应特征。构建可使景观阻力估计值随成本权重变化呈线性响应的阻力表面，将有效提升功能连通性估计的准确性，尤其当成本权重通过统计模型拟合流程进行选取时，该优势更为显著。与之相对，在成本权重未知且未采用模型选择的研究中，阻力估计值随成本权重变化呈渐近变化的方法或许更为适配，因其对参数化过程具备相对的不敏感性。