Assessing the potential for developing internal diatom-based transfer functions for Lake Baikal

摘要: We explore possible quantitative relationships between diatom species and environmental data for Lake Baikal using multivariate techniques. Our approach differs from published studies in other regions (on training sets transfer functions) because (1) although only one lake is examined, we use the internal gradients rather than among lakes (2) majority of dominant taxa are endemic. Canonical correspondence analysis on 93 surface sediment assemblages reveals that major show distinct with measured variables. Five significant variables were identified: snow thickness ice (which accumulates frozen January April/May), water depth, suspended matter, annual solar radiation, mean July temperature waters. The strongest relationship thickness, which influences light levels below ice. A diatom-based inference model has been developed to predict weighted averaging (WA) WA tolerance down-weighting (WA tol ) models. Results suggest sediments can be used develop a robust estimating across (r 2 jack = 0.607, RMSEP 0.138 log cm). This potential applications recent paleoclimate this region continental Eurasia.