The Influence of Vegetation Height Heterogeneity on Forest and Woodland Bird Species Richness across the United States

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 (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼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.鸟类多样性正面临日益加剧的生存压力。因此，明确影响鸟类物种多样性大尺度空间分布的生态变量至关重要。传统上，相关研究主要依赖二维生境结构来构建大尺度物种丰富度模型；植被垂直结构虽在局域尺度的应用愈发广泛，但此前的研究从未考虑植被高度的空间排布特征。本研究旨在探究三维森林结构——尤其是植被高度空间异质性——对提升美国森林生态区鸟类丰富度模型性能的作用。研究团队基于2000年国家生物量与碳储量数据集（National Biomass and Carbon Dataset, NBCD），构建了用于表征植被高度空间排布的新型生境指标。研究将该高度结构化指标与其他生境指标进行对比，分析其与繁殖鸟类调查（Breeding Bird Survey, BBS）路线上三类森林繁殖鸟类类群的物种丰富度之间的统计相关性：这三类类群分别为广义林地类群，以及分别偏好林缘生境与林内生境的两类森林繁殖类群。研究构建参数化与非参数化模型，以验证预测性能的提升效果。结果显示，高度结构化指标与物种丰富度的相关性最强，可有效提升两类类群的丰富度模型预测性能：其中林地类群模型的参数化模型决定系数（r²）约为0.53，非参数化模型则达0.63；林缘类群模型的参数化模型r²约为0.34，非参数化模型达0.47。除1个线性模型外，所有纳入高度结构化指标的线性模型，其校正决定系数（adjusted-r²）均显著高于未添加该类指标的对照模型。林内生境类群的物种丰富度与高度结构化指标则始终呈现较弱的相关性。研究结果表明，相较于仅考量冠层高度，植被高度异质性可进一步完善森林鸟类的生境表征与物种丰富度模型。本研究构建的指标与模型，为利用三维植被数据优化物种丰富度空间分布特征的表征提供了可行的实践范例。