The second Southern African Bird Atlas Project: Causes and consequences of geographical sampling bias.

摘要: Using the Southern African Bird Atlas Project (SABAP2) as a case study, we examine possible determinants of spatial bias in volunteer sampling effort and how well such biased data represent environmental gradients across area covered by atlas. For each province South Africa, used generalized linear mixed models to determine combination variables that explain variation (number visits per 5′ × 5′ grid cell, or “pentad”). The explanatory were distance major road exceptional birding locations “sampling hubs,” percentage cover protected, urban, cultivated area, climate mean annual precipitation, winter temperatures, summer temperatures. Further, plant biomes define subsets pentads representing zones Lesotho, Swaziland. zone, quantified intensity, assessed completeness with species accumulation curves fitted asymptotic Lomolino model. Sampling was highest close hubs, roads, urban areas, protected areas. Cultivated less important. not evenly represented current varied amount required are present. SABAP2 volunteers' preferences cause dataset should be taken into account when analyzing these data. Large parts Africa remain underrepresented, which may restrict kind ecological questions addressed. However, improved directing volunteers toward undersampled regions while taking preferences.