Palaeoclimate explains a unique proportion of the global variation in soil bacterial communities

被引:85
作者
Delgado-Baquerizo, Manuel [1 ,2 ]
Bissett, Andrew [3 ]
Eldridge, David J. [4 ]
Maestre, Fernando T. [5 ]
He, Ji-Zheng [6 ,7 ]
Wang, Jun-Tao [6 ]
Hamonts, Kelly [2 ]
Liu, Yu-Rong [6 ]
Singh, Brajesh K. [2 ,8 ]
Fierer, Noah [1 ,9 ]
机构
[1] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA
[2] Western Sydney Univ, Hawkesbury Inst Environm, Penrith, NSW 2751, Australia
[3] CSIRO, Oceans & Atmosphere, Hobart, Tas 7000, Australia
[4] Univ New South Wales, Ctr Ecosyst Sci, Sch Biol Earth & Environm Sci, Sydney, NSW 2052, Australia
[5] Univ Rey Juan Carlos, Dept Biol & Geol, Fis & Quim Inorgan, Escuela Super Ciencias Expt & Tecnol, Calle Tulipan Sin, Mostoles 28933, Spain
[6] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China
[7] Univ Melbourne, Fac Vet & Agr Sci, Parkville, Vic 3010, Australia
[8] Western Sydney Univ, Global Ctr Land Based Innovat, Bldg L9,Locked Bag 1797, Penrith, NSW 2751, Australia
[9] Univ Colorado, Dept Ecol & Evolut Biol, Boulder, CO 80309 USA
基金
澳大利亚研究理事会; 欧洲研究理事会; 美国国家科学基金会;
关键词
MICROBIAL COMMUNITIES; CLIMATE VARIABILITY; PLANT DIVERSITY; PRODUCTIVITY; GRASSLANDS; BETA;
D O I
10.1038/s41559-017-0259-7
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The legacy impacts of past climates on the current distribution of soil microbial communities are largely unknown. Here, we use data from more than 1,000 sites from five separate global and regional datasets to identify the importance of palaeoclimatic conditions (Last Glacial Maximum and mid-Holocene) in shaping the current structure of soil bacterial communities in natural and agricultural soils. We show that palaeoclimate explains more of the variation in the richness and composition of bacterial communities than current climate. Moreover, palaeoclimate accounts for a unique fraction of this variation that cannot be predicted from geographical location, current climate, soil properties or plant diversity. Climatic legacies (temperature and precipitation anomalies from the present to -20 kyr ago) probably shape soil bacterial communities both directly and indirectly through shifts in soil properties and plant communities. The ability to predict the distribution of soil bacteria from either palaeoclimate or current climate declines greatly in agricultural soils, highlighting the fact that anthropogenic activities have a strong influence on soil bacterial diversity. We illustrate how climatic legacies can help to explain the current distribution of soil bacteria in natural ecosystems and advocate that climatic legacies should be considered when predicting microbial responses to climate change.
引用
收藏
页码:1339 / 1347
页数:9
相关论文
共 50 条
[1]  
[Anonymous], 2016, mBio, DOI DOI 10.1128/MBIO.02200-15
[2]  
[Anonymous], 2002, UN ENV PROGRAMME WOR
[3]  
[Anonymous], 2008, WORLD DEV REP AGR DE
[4]  
Archer E, 2016, RFPERMUTE ESTIMATE
[5]   SEASONAL TEMPERATURES IN BRITAIN DURING THE PAST 22,000 YEARS, RECONSTRUCTED USING BEETLE REMAINS [J].
ATKINSON, TC ;
BRIFFA, KR ;
COOPE, GR .
NATURE, 1987, 325 (6105) :587-592
[6]   Bacterial Communities Associated with the Lichen Symbiosis [J].
Bates, Scott T. ;
Cropsey, Garrett W. G. ;
Caporaso, J. Gregory ;
Knight, Rob ;
Fierer, Noah .
APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2011, 77 (04) :1309-1314
[7]   Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database [J].
Bissett, Andrew ;
Fitzgerald, Anna ;
Meintjes, Thys ;
Mele, Pauline M. ;
Reith, Frank ;
Dennis, Paul G. ;
Breed, Martin F. ;
Brown, Belinda ;
Brown, Mark V. ;
Brugger, Joel ;
Byrne, Margaret ;
Caddy-Retalic, Stefan ;
Carmody, Bernie ;
Coates, David J. ;
Correa, Carolina ;
Ferrari, Belinda C. ;
Gupta, Vadakattu V. S. R. ;
Hamonts, Kelly ;
Haslem, Asha ;
Hugenholtz, Philip ;
Karan, Mirko ;
Koval, Jason ;
Lowe, Andrew J. ;
Macdonald, Stuart ;
McGrath, Leanne ;
Martin, David ;
Morgan, Matt ;
North, Kristin I. ;
Paungfoo-Lonhienne, Chanyarat ;
Pendall, Elise ;
Phillips, Lori ;
Pirzl, Rebecca ;
Powell, Jeff R. ;
Ragan, Mark A. ;
Schmidt, Susanne ;
Seymour, Nicole ;
Snape, Ian ;
Stephen, John R. ;
Stevens, Matthew ;
Tinning, Matt ;
Williams, Kristen ;
Yeoh, Yun Kit ;
Zammit, Carla M. ;
Young, Andrew .
GIGASCIENCE, 2016, 5
[8]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[9]  
Bystriakova N., 2013, ANN BOT, V13, P453
[10]   QIIME allows analysis of high-throughput community sequencing data [J].
Caporaso, J. Gregory ;
Kuczynski, Justin ;
Stombaugh, Jesse ;
Bittinger, Kyle ;
Bushman, Frederic D. ;
Costello, Elizabeth K. ;
Fierer, Noah ;
Pena, Antonio Gonzalez ;
Goodrich, Julia K. ;
Gordon, Jeffrey I. ;
Huttley, Gavin A. ;
Kelley, Scott T. ;
Knights, Dan ;
Koenig, Jeremy E. ;
Ley, Ruth E. ;
Lozupone, Catherine A. ;
McDonald, Daniel ;
Muegge, Brian D. ;
Pirrung, Meg ;
Reeder, Jens ;
Sevinsky, Joel R. ;
Tumbaugh, Peter J. ;
Walters, William A. ;
Widmann, Jeremy ;
Yatsunenko, Tanya ;
Zaneveld, Jesse ;
Knight, Rob .
NATURE METHODS, 2010, 7 (05) :335-336