TY - JOUR
T1 - Marine bacterial, archaeal and protistan association networks reveal ecological linkages
AU - Steele, Joshua A.
AU - Countway, Peter D.
AU - Xia, Li
AU - Vigil, Patrick D.
AU - Beman, J. Michael
AU - Kim, Diane Y.
AU - Chow, Cheryl Emiliane T.
AU - Sachdeva, Rohan
AU - Jones, Adriane C.
AU - Schwalbach, Michael S.
AU - Rose, Julie M.
AU - Hewson, Ian
AU - Patel, Anand
AU - Sun, Fengzhu
AU - Caron, David A.
AU - Fuhrman, Jed A.
N1 - Funding Information:
We thank the captain and crew of the R/V Seawatch, M Neumann and R Smith for oxygen, salinity and chlorophyll data; Z Zheng for nutrient data. We thank D Capone, W Ziebis, J Devinny D Keifer and E Berlow for helpful comments on earlier versions of this manuscript, and anonymous reviewers for their careful reading and excellent comments that improved this paper. The US National Science Foundation Microbial Observatories and Biological Oceanography programs funded this research, grants 0703159, 0623575 and 0648581.
PY - 2011/9
Y1 - 2011/9
N2 - Microbes have central roles in ocean food webs and global biogeochemical processes, yet specific ecological relationships among these taxa are largely unknown. This is in part due to the dilute, microscopic nature of the planktonic microbial community, which prevents direct observation of their interactions. Here, we use a holistic (that is, microbial system-wide) approach to investigate time-dependent variations among taxa from all three domains of life in a marine microbial community. We investigated the community composition of bacteria, archaea and protists through cultivation-independent methods, along with total bacterial and viral abundance, and physico-chemical observations. Samples and observations were collected monthly over 3 years at a well-described ocean time-series site of southern California. To find associations among these organisms, we calculated time-dependent rank correlations (that is, local similarity correlations) among relative abundances of bacteria, archaea, protists, total abundance of bacteria and viruses and physico-chemical parameters. We used a network generated from these statistical correlations to visualize and identify time-dependent associations among ecologically important taxa, for example, the SAR11 cluster, stramenopiles, alveolates, cyanobacteria and ammonia-oxidizing archaea. Negative correlations, perhaps suggesting competition or predation, were also common. The analysis revealed a progression of microbial communities through time, and also a group of unknown eukaryotes that were highly correlated with dinoflagellates, indicating possible symbioses or parasitism. Possible keystone species were evident. The network has statistical features similar to previously described ecological networks, and in network parlance has non-random, small world properties (that is, highly interconnected nodes). This approach provides new insights into the natural history of microbes.
AB - Microbes have central roles in ocean food webs and global biogeochemical processes, yet specific ecological relationships among these taxa are largely unknown. This is in part due to the dilute, microscopic nature of the planktonic microbial community, which prevents direct observation of their interactions. Here, we use a holistic (that is, microbial system-wide) approach to investigate time-dependent variations among taxa from all three domains of life in a marine microbial community. We investigated the community composition of bacteria, archaea and protists through cultivation-independent methods, along with total bacterial and viral abundance, and physico-chemical observations. Samples and observations were collected monthly over 3 years at a well-described ocean time-series site of southern California. To find associations among these organisms, we calculated time-dependent rank correlations (that is, local similarity correlations) among relative abundances of bacteria, archaea, protists, total abundance of bacteria and viruses and physico-chemical parameters. We used a network generated from these statistical correlations to visualize and identify time-dependent associations among ecologically important taxa, for example, the SAR11 cluster, stramenopiles, alveolates, cyanobacteria and ammonia-oxidizing archaea. Negative correlations, perhaps suggesting competition or predation, were also common. The analysis revealed a progression of microbial communities through time, and also a group of unknown eukaryotes that were highly correlated with dinoflagellates, indicating possible symbioses or parasitism. Possible keystone species were evident. The network has statistical features similar to previously described ecological networks, and in network parlance has non-random, small world properties (that is, highly interconnected nodes). This approach provides new insights into the natural history of microbes.
KW - SAR11
KW - co-occurrence patterns
KW - cyanobacteria
KW - dinoflagellates
KW - stramenopiles
KW - time series
UR - http://www.scopus.com/inward/record.url?scp=80052061077&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052061077&partnerID=8YFLogxK
U2 - 10.1038/ismej.2011.24
DO - 10.1038/ismej.2011.24
M3 - Article
C2 - 21430787
AN - SCOPUS:80052061077
SN - 1751-7362
VL - 5
SP - 1414
EP - 1425
JO - ISME Journal
JF - ISME Journal
IS - 9
ER -