globalchange  > 全球变化的国际研究计划
DOI: 10.1111/geb.12974
WOS记录号: WOS:000477231600001
论文题名:
Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing
作者: Lembrechts, Jonas J.1; Lenoir, Jonathan2; Roth, Nina3; Hattab, Tarek2,4; Milbau, Ann5; Haider, Sylvia6,7; Pellissier, Loic8,9; Pauchard, Anibal10,11; Backes, Amanda Ratier6,7; Dimarco, Romina D.12; Nunez, Martin A.13; Aalto, Juha14,15; Nijs, Ivan1
通讯作者: Lembrechts, Jonas J.
刊名: GLOBAL ECOLOGY AND BIOGEOGRAPHY
ISSN: 1466-822X
EISSN: 1466-8238
出版年: 2019
语种: 英语
英文关键词: bioclimatic envelope modelling ; bioclimatic variables ; climate change ; growth forms ; land surface temperature ; microclimate ; mountains ; soil temperature ; species distribution modelling
WOS关键词: CLIMATE-CHANGE ; SURFACE TEMPERATURES ; PLANT-DISTRIBUTION ; SOIL-TEMPERATURE ; STEPPING-STONES ; SNOW COVER ; LAND-COVER ; FINE-GRAIN ; RESOLUTION ; DISTURBANCE
WOS学科分类: Ecology ; Geography, Physical
WOS研究方向: Environmental Sciences & Ecology ; Physical Geography
英文摘要:

Aim Although species distribution models (SDMs) traditionally link species occurrences to free-air temperature data at coarse spatio-temporal resolution, the distribution of organisms might instead be driven by temperatures more proximal to their habitats. Several solutions are currently available, such as downscaled or interpolated coarse-grained free-air temperatures, satellite-measured land surface temperatures (LST) or in-situ-measured soil temperatures. A comprehensive comparison of temperature data sources and their performance in SDMs is, however, currently lacking. Location Northern Scandinavia. Time period 1970-2017. Major taxa studied Higher plants. Methods We evaluated different sources of temperature data (WorldClim, CHELSA, MODIS, E-OBS, topoclimate and soil temperature from miniature data loggers), differing in spatial resolution (from 1 '' to 0.1 degrees), measurement focus (free-air, ground-surface or soil temperature) and temporal extent (year-long versus long-term averages), and used them to fit SDMs for 50 plant species with different growth forms in a high-latitudinal mountain region. Results Differences between these temperature data sources originating from measurement focus and temporal extent overshadow the effects of temporal climatic differences and spatio-temporal resolution, with elevational lapse rates ranging from -0.6 degrees C per 100 m for long-term free-air temperature data to -0.2 degrees C per 100 m for in-situ soil temperatures. Most importantly, we found that the performance of the temperature data in SDMs depended on the growth forms of species. The use of in-situ soil temperatures improved the explanatory power of our SDMs (R-2 on average +16%), especially for forbs and graminoids (R-2 +24 and +21% on average, respectively) compared with the other data sources. Main conclusions We suggest that future studies using SDMs should use the temperature dataset that best reflects the ecology of the species, rather than automatically using coarse-grained data from WorldClim or CHELSA.


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被引频次[WOS]:90   [查看WOS记录]     [查看WOS中相关记录]
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/143655
Appears in Collections:全球变化的国际研究计划

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作者单位: 1.Univ Antwerp, Ctr Excellence Plants & Ecosyst PLECO, B-2610 Antwerp, Belgium
2.UPJV, UR Ecol & Dynam Syst Anthropises EDYSAN, UMR 7058, CNRS, Amiens 1, France
3.Stockholm Univ, Dept Phys Geog, Biogeog & Geomat, Stockholm, Sweden
4.Univ Montpellier, CNRS, IFREMER, MARBEC,IRD, Sete, France
5.Res Inst Nat & Forest INBO, Brussels, Belgium
6.Martin Luther Univ Halle Wittenberg, Inst Biol Geobot & Bot Garden, Halle, Saale, Germany
7.German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany
8.Swiss Fed Inst Technol, Inst Terr Ecosyst, Dept Environm Syst Sci, Landscape Ecol, Zurich, Switzerland
9.Swiss Fed Res Inst WSL, Birmensdorf, Switzerland
10.Univ Concepcion, Fac Ciencias Forestales, Lab Invas Biol, Concepcion, Chile
11.IEB, Santiago, Chile
12.Consejo Nacl Invest Cient & Tecn, INTA, Grp Ecol Poblac Insectos, San Carlos De Bariloche, Rio Negro, Argentina
13.Univ Nacl Comahue, CONICET, INIBIOMA, Grp Ecol Invas, San Carlos De Bariloche, Rio Negro, Argentina
14.Univ Helsinki, Dept Geosci & Geog, FIN-00014 Helsinki, Finland
15.Finnish Meteorol Inst, Helsinki, Finland

Recommended Citation:
Lembrechts, Jonas J.,Lenoir, Jonathan,Roth, Nina,et al. Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing[J]. GLOBAL ECOLOGY AND BIOGEOGRAPHY,2019-01-01
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