Suppr超能文献

北美东部跨生物群落的成像光谱学叶功能性状

Foliar functional traits from imaging spectroscopy across biomes in eastern North America.

作者信息

Wang Zhihui, Chlus Adam, Geygan Ryan, Ye Zhiwei, Zheng Ting, Singh Aditya, Couture John J, Cavender-Bares Jeannine, Kruger Eric L, Townsend Philip A

机构信息

Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA.

Department of Agricultural and Biological Engineering, University of Florida, 1741 Museum Rd, Gainesville, FL, 32611, USA.

出版信息

New Phytol. 2020 Oct;228(2):494-511. doi: 10.1111/nph.16711. Epub 2020 Jun 23.

Abstract

Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1-19.4%; coefficient of determination, 0.28-0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28-81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.

摘要

叶功能性状被广泛用于表征驱动生态系统过程的叶片和冠层特性,并用于推断地球系统模型中的生理过程。成像光谱技术为绘制叶性状图谱以表征连续的功能变异和多样性提供了巨大潜力,但很少有研究展示出在不同生物群落中绘制多种性状的一致方法。利用来自19个站点的航空成像光谱数据和实地数据,我们使用偏最小二乘回归开发了性状模型,并在包括北美东部温带和亚热带森林及草原在内的7个NEON(国家生态观测网络)生态区(域)绘制了26种叶性状图谱。模型验证精度因性状而异(归一化均方根误差为9.1 - 19.4%;决定系数为0.28 - 0.82),其中酚类物质浓度、单位面积叶质量和等效水厚度在各区域表现最佳。在所有性状图谱中,90%的植被像素对于一种性状具有合理的值,28 - 81%的像素同时为多种性状提供了高置信度。美国东部NEON站点的26种性状图谱及其不确定性可供下载,并且正在扩展到美国西部以及苔原/北方针叶林带。这些数据有助于更好地理解大面积区域内的性状变异和关系、校准生态系统模型以及评估大陆尺度的功能多样性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验