Huang Qiongyu, Swatantran Anu, Dubayah Ralph, Goetz Scott J
Department of Geographical Sciences, University of Maryland, College Park, Maryland, United States of America.
Woods Hole Research Center, Falmouth, Massachusetts, United States of America.
PLoS One. 2014 Aug 7;9(8):e103236. doi: 10.1371/journal.pone.0103236. eCollection 2014.
Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.
鸟类多样性正面临着越来越大的压力。因此,了解影响鸟类物种多样性大规模空间分布的生态变量至关重要。传统上,研究主要依赖二维栖息地结构来模拟广泛尺度的物种丰富度。植被垂直结构在局部尺度上的应用越来越多。然而,植被高度的空间排列从未被考虑在内。我们的目标是研究三维森林结构的有效性,特别是植被高度的空间异质性,以改进美国森林生态区域的鸟类丰富度模型。我们利用2000年的国家生物量和碳数据集(NBCD)开发了新的栖息地指标来表征植被高度的空间排列。将高度结构指标与其他栖息地指标进行比较,以统计它们与繁殖鸟类调查(BBS)路线上三个森林繁殖鸟类 guild 的丰富度之间的关联:一个广泛分类的林地 guild,以及两个分别偏好森林边缘和森林内部的森林繁殖 guild。构建了参数模型和非参数模型来检验预测能力的提高。高度结构指标与物种丰富度的关联最强,对林地 guild 丰富度模型(参数模型的r(2)约为0.53,非参数模型为0.63)和森林边缘 guild 模型(参数模型的r(2)约为0.34,非参数模型为0.47)的预测能力有显著提高。除了一个包含高度结构指标的线性模型外,所有其他模型的调整r2值都显著高于没有额外指标的对应模型。森林内部 guild 的丰富度与高度结构指标的关联一直较低。我们的结果表明,除了树冠高度之外,高度异质性补充了森林鸟类物种的栖息地特征和丰富度模型。本研究中得出的指标和模型展示了利用三维植被数据改进物种丰富度空间模式表征的实际例子。