Distribution and habitat database of fluvial Plecoptera, Trichoptera and Coleoptera from Sierra Nevada, Spain

被引:0
|
作者
Lopez-Rodriguez, Manuel Jesus [1 ]
Ros-Candeira, Andrea [2 ]
Merlo, Maria del Carmen Fajardo [3 ]
Bariain, Marta Sainz [4 ]
Sainz-Cantero Caparros, Carmen Elisa [5 ]
de Figueroa, Jose Manuel Tierno [5 ]
Zamora-Munoz, Carmen [5 ]
机构
[1] Univ Granada, Fac Sci, Dept Ecol, Ave Fuente Nueva S-N, Granada 18071, Spain
[2] Univ Granada, Andalusian Inst Earth Syst Res IISTA CEAMA, Lab Ecol, Ave Mediterraneo S-N, Granada 18006, Spain
[3] Environm & Water Agcy, Dept Sustainabil Environm & Blue Econ Reg Govt And, C Minerva 7 Edificio Zeus 3, Granada 18014, Spain
[4] Spanish Natl Res Council IEO CSIC, Spanish Inst Oceanog, St ander Oceanog Ctr COST IEO, Ave Severiano Ballesteros 16, Santander 39004, Spain
[5] Univ Granada, Fac Sci, Dept Zool, Ave Fuente Nueva S-N, Granada 18071, Spain
关键词
SP-N;
D O I
10.1038/s41597-024-03652-y
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
Sierra Nevada (southern Iberian Peninsula) harbours a great biodiversity and the studies on some aquatic insect groups have been and continue to be numerous there. This database brings together information on Plecoptera, Trichoptera and Coleoptera inhabiting running waters of this mountain system above 800 m of altitude. It includes data on the number, life stage and sex of individuals as well as the available information on abiotic characteristics of their habitats. The dataset is composed of 1,718 sampling events carried out between 1901 and 2022 in approximately 60 different water bodies, 15,347 occurrences pertaining to more than 203,000 individuals, and 10,173 records of associated measurements (23 physico-chemical parameters). The dataset is the result of a comprehensive review of scientific literature and of integrating data from recent research projects and the Sierra Nevada Global-Change Observatory's long-term monitoring data. This information is valuable for those studying past distributions and abundances of the species in the dataset, for building predictive models or just studying temporal trends in the current context of climate change.
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页数:11
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