Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

被引:51
作者
Brennan, Sean R. [1 ]
Torgersen, Christian E. [2 ,3 ]
Hollenbeck, Jeff P. [2 ]
Fernandez, Diego P. [4 ]
Jensen, Carrie K. [5 ]
Schindler, Daniel E. [1 ]
机构
[1] Univ Washington, Sch Aquat & Fishery Sci, Seattle, WA 98195 USA
[2] US Geol Survey, Forest & Rangeland Ecosyst Sci Ctr, Cascadia Field Stn, Corvallis, OR USA
[3] Univ Washington, Sch Environm & Forest Sci, Seattle, WA 98195 USA
[4] Univ Utah, Dept Geol & Geophys, Salt Lake City, UT 84112 USA
[5] Virginia Polytech Inst & State Univ, Dept Forest Resources & Environm Conservat, Blacksburg, VA 24061 USA
基金
美国国家科学基金会;
关键词
SPATIAL STATISTICAL-MODELS; MOVING-AVERAGE APPROACH; WATER; PATTERN;
D O I
10.1002/2016GL068904
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called "isoscapes," form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.
引用
收藏
页码:5043 / 5051
页数:9
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