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Effects of flower and seed predators and pollinators on fruit production in two sequentially flowering congeners
Authors:Mahoro  Suzuki
Institution:(1) Department of Environmental and Plant Biology, Ohio University, 317 Porter Hall, Athens, 45701, USA
Abstract:We examined spatial and temporal variability of understory herbaceousvegetation on opposing north- and south-facing slopes in an eastern deciduousold-growth forest in southeastern Ohio, USA. Secondly, we explored theinfluenceof sampling scale and analytical technique on our assessment of diversitypatterns. The influence of aspect and seasonality were examined at varyingsampling scales using observed richness, evenness, andHprime diversity measures, non-parametric richnessestimators, species-area curves, and SHE analysis. Herb layer composition,abundance, and diversity were strongly influenced by location (north slope vs.south slope), seasonal sampling period (April, June, August), and plot size(micro (2 m2)- vs. meso (70m2)-scale samples). Although north and south plots werecompositionally distinct, they followed similar courses of change through thegrowing season. Richness, evenness, and Hprime diversitywere generally greater on the south plot whereas herbaceous abundance wasgreater on the north plot. Species composition and diversity showed markedphenological (temporal) changes, and comparison of diversity measures at micro-and meso-scales produced markedly different results. Minimum sample areas of150–200 m2 were needed to evaluate micro-scalerichness in these species rich communities, suggesting that forest understoriesmay be frequently undersampled in ecological studies. Comparison of observedandestimated meso-scale richness also suggested underestimation of richness in thenorth plot, particularly earlier in the growing season. Thus, sample size,area,and time of sampling appear critical to assessment of diversity in spatiallyandtemporally variable communities such as herbaceous forest understories.
Keywords:Diversity assessment  Non-parametric richness estimators  Sampling scale  Seasonal variability  Topographic aspect  Understory vegetation
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