A design-based view of species richness estimation in environmental surveys
从抽样设计的角度研究物种丰富度估计，发现SPADE软件中的估计器存在严重负偏差，通过整合稀有物种列表来减少低估，并在残差群落上应用自助法均方误差估计，模拟和案例研究结果令人鼓舞。
Abstract In this work, the estimation of species richness is approached from a design-based perspective, considering the probabilistic sampling of species and checking the performance of the estimators automated in the SPADE software. As shown theoretically and by a simulation study, these estimators are affected by a massive negative bias. To reduce the underestimation of species richness, data integration is attempted, by exploiting the list of rare species compiled by purposive surveys. Richness estimation is then performed on the residual community of species not in the list, and a bootstrap mean squared error estimator is applied. A simulation study and the application to four case studies produce encouraging results.