Estimating species distribution and abundance in river networks using environmental DNA

被引:133
作者
Carraro, Luca [1 ]
Hartikainen, Hanna [2 ,3 ]
Jokela, Jukka [2 ,3 ]
Bertuzzo, Enrico [4 ]
Rinaldo, Andrea [1 ,5 ]
机构
[1] Ecole Polytech Fed Lausanne, Lab Ecohydrol, CH-1015 Lausanne, Switzerland
[2] Swiss Fed Inst Aquat Sci & Technol, Aquat Ecol Grp, CH-8600 Dubendorf, Switzerland
[3] Eidgenoss TH Zurich, Inst Integrat Biol, CH-8092 Zurich, Switzerland
[4] Univ Ca Foscari Venezia, Dipartimento Sci Ambientali Informat & Stat, IT-30170 Venice, Italy
[5] Univ Padua, Dipartimento Ingn Civile Edile & Ambientale, IT-35131 Padua, Italy
基金
瑞士国家科学基金会;
关键词
species distribution model; ecohydrology; proliferative kidney disease; TRANSPORT; BIGHEAD; TRACER; RATES; DECAY; RARE;
D O I
10.1073/pnas.1813843115
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
All organisms leave traces of DNA in their environment. This environmental DNA (eDNA) is often used to track occurrence patterns of target species. Applications are especially promising in rivers, where eDNA can integrate information about populations upstream. The dispersion of eDNA in rivers is modulated by complex processes of transport and decay through the dendritic river network, and we currently lack a method to extract quantitative information about the location and density of populations contributing to the eDNA signal. Here, we present a general framework to reconstruct the upstream distribution and abundance of a target species across a river network, based on observed eDNA concentrations and hydro-geomorphological features of the network. The model captures well the catchment-wide spatial biomass distribution of two target species: a sessile invertebrate (the bryozoan Fredericella sultana) and its parasite (the myxozoan Tetracapsuloides bryosalmonae). Our method is designed to easily integrate general biological and hydrological data and to enable spatially explicit estimates of the distribution of sessile and mobile species in fluvial ecosystems based on eDNA sampling.
引用
收藏
页码:11724 / 11729
页数:6
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