Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes
Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will info...
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creator | Docherty, Kathryn M Borton, Hannah M Espinosa, Noelle Gebhardt, Martha Gil-Loaiza, Juliana Gutknecht, Jessica L M Maes, Patrick W Mott, Brendon M Parnell, John Jacob Purdy, Gayle Rodrigues, Pedro A P Stanish, Lee F Walser, Olivia N Gallery, Rachel E |
description | Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpr |
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Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0135352</identifier><identifier>PMID: 26536666</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acidobacteria - genetics ; Alaska ; Bacteria - genetics ; Carbon ; Cation exchange ; Cation exchanging ; Classrooms ; Climate Change ; Climate effects ; Collaboration ; Colleges & universities ; Communities ; Community composition ; Community structure ; Coniferous forests ; Data analysis ; Data processing ; Data retrieval ; Datasets ; DNA, Bacterial - isolation & purification ; Ecological monitoring ; Ecology ; Ecosystem ; Ecosystems ; Environmental changes ; Fatty acids ; Fatty Acids - analysis ; Florida ; Forest communities ; Forests ; Gene sequencing ; Genetic diversity ; Grasslands ; Hawaii ; Influence ; Interdisciplinary aspects ; Lipids - analysis ; Microbial activity ; Microbiomes ; Microorganisms ; Model testing ; Moisture content ; Natural resources ; Neon ; Observatories ; Phospholipids ; RNA, Ribosomal, 16S - analysis ; rRNA 16S ; Science ; Seasonal variations ; Seasons ; Soil - chemistry ; Soil analysis ; Soil environment ; Soil Microbiology ; Soil microorganisms ; Soil structure ; Soil temperature ; Soil water ; Soil water storage ; Storage temperature ; Subgroups ; Taiga ; Temperature ; Temporal variability ; Transformation ; Tropical forests ; Utah ; Variability ; Water content</subject><ispartof>PloS one, 2015-11, Vol.10 (11), p.e0135352-e0135352</ispartof><rights>2015 Docherty et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Docherty et al 2015 Docherty et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-3ae9027dbe194c9f290ad7c46aee9d67933a422d7611580c8a7f59bd73550f8f3</citedby><cites>FETCH-LOGICAL-c526t-3ae9027dbe194c9f290ad7c46aee9d67933a422d7611580c8a7f59bd73550f8f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4633200/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4633200/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26536666$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Docherty, Kathryn M</creatorcontrib><creatorcontrib>Borton, Hannah M</creatorcontrib><creatorcontrib>Espinosa, Noelle</creatorcontrib><creatorcontrib>Gebhardt, Martha</creatorcontrib><creatorcontrib>Gil-Loaiza, Juliana</creatorcontrib><creatorcontrib>Gutknecht, Jessica L M</creatorcontrib><creatorcontrib>Maes, Patrick W</creatorcontrib><creatorcontrib>Mott, Brendon M</creatorcontrib><creatorcontrib>Parnell, John Jacob</creatorcontrib><creatorcontrib>Purdy, Gayle</creatorcontrib><creatorcontrib>Rodrigues, Pedro A P</creatorcontrib><creatorcontrib>Stanish, Lee F</creatorcontrib><creatorcontrib>Walser, Olivia N</creatorcontrib><creatorcontrib>Gallery, Rachel E</creatorcontrib><title>Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers.</description><subject>Acidobacteria - genetics</subject><subject>Alaska</subject><subject>Bacteria - genetics</subject><subject>Carbon</subject><subject>Cation exchange</subject><subject>Cation exchanging</subject><subject>Classrooms</subject><subject>Climate Change</subject><subject>Climate effects</subject><subject>Collaboration</subject><subject>Colleges & universities</subject><subject>Communities</subject><subject>Community composition</subject><subject>Community structure</subject><subject>Coniferous forests</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Data retrieval</subject><subject>Datasets</subject><subject>DNA, Bacterial - isolation & purification</subject><subject>Ecological monitoring</subject><subject>Ecology</subject><subject>Ecosystem</subject><subject>Ecosystems</subject><subject>Environmental changes</subject><subject>Fatty acids</subject><subject>Fatty Acids - analysis</subject><subject>Florida</subject><subject>Forest communities</subject><subject>Forests</subject><subject>Gene sequencing</subject><subject>Genetic diversity</subject><subject>Grasslands</subject><subject>Hawaii</subject><subject>Influence</subject><subject>Interdisciplinary aspects</subject><subject>Lipids - analysis</subject><subject>Microbial activity</subject><subject>Microbiomes</subject><subject>Microorganisms</subject><subject>Model testing</subject><subject>Moisture content</subject><subject>Natural resources</subject><subject>Neon</subject><subject>Observatories</subject><subject>Phospholipids</subject><subject>RNA, Ribosomal, 16S - analysis</subject><subject>rRNA 16S</subject><subject>Science</subject><subject>Seasonal variations</subject><subject>Seasons</subject><subject>Soil - chemistry</subject><subject>Soil analysis</subject><subject>Soil environment</subject><subject>Soil Microbiology</subject><subject>Soil microorganisms</subject><subject>Soil structure</subject><subject>Soil temperature</subject><subject>Soil water</subject><subject>Soil water storage</subject><subject>Storage temperature</subject><subject>Subgroups</subject><subject>Taiga</subject><subject>Temperature</subject><subject>Temporal variability</subject><subject>Transformation</subject><subject>Tropical forests</subject><subject>Utah</subject><subject>Variability</subject><subject>Water 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Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Docherty, Kathryn M</au><au>Borton, Hannah M</au><au>Espinosa, Noelle</au><au>Gebhardt, Martha</au><au>Gil-Loaiza, Juliana</au><au>Gutknecht, Jessica L M</au><au>Maes, Patrick W</au><au>Mott, Brendon M</au><au>Parnell, John Jacob</au><au>Purdy, Gayle</au><au>Rodrigues, Pedro A P</au><au>Stanish, Lee F</au><au>Walser, Olivia N</au><au>Gallery, Rachel E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2015-11-04</date><risdate>2015</risdate><volume>10</volume><issue>11</issue><spage>e0135352</spage><epage>e0135352</epage><pages>e0135352-e0135352</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Soil microbial communities play a critical role in nutrient transformation and storage in all ecosystems. Quantifying the seasonal and long-term temporal extent of genetic and functional variation of soil microorganisms in response to biotic and abiotic changes within and across ecosystems will inform our understanding of the effect of climate change on these processes. We examined spatial and seasonal variation in microbial communities based on 16S rRNA gene sequencing and phospholipid fatty acid (PLFA) composition across four biomes: a tropical broadleaf forest (Hawaii), taiga (Alaska), semiarid grassland-shrubland (Utah), and a subtropical coniferous forest (Florida). In this study, we used a team-based instructional approach leveraging the iPlant Collaborative to examine publicly available National Ecological Observatory Network (NEON) 16S gene and PLFA measurements that quantify microbial diversity, composition, and growth. Both profiling techniques revealed that microbial communities grouped strongly by ecosystem and were predominately influenced by three edaphic factors: pH, soil water content, and cation exchange capacity. Temporal variability of microbial communities differed by profiling technique; 16S-based community measurements showed significant temporal variability only in the subtropical coniferous forest communities, specifically through changes within subgroups of Acidobacteria. Conversely, PLFA-based community measurements showed seasonal shifts in taiga and tropical broadleaf forest systems. These differences may be due to the premise that 16S-based measurements are predominantly influenced by large shifts in the abiotic soil environment, while PLFA-based analyses reflect the metabolically active fraction of the microbial community, which is more sensitive to local disturbances and biotic interactions. To address the technical issue of the response of soil microbial communities to sample storage temperature, we compared 16S-based community structure in soils stored at -80°C and -20°C and found no significant differences in community composition based on storage temperature. Free, open access datasets and data sharing platforms are powerful tools for integrating research and teaching in undergraduate and graduate student classrooms. They are a valuable resource for fostering interdisciplinary collaborations, testing ecological theory, model development and validation, and generating novel hypotheses. Training in data analysis and interpretation of large datasets in university classrooms through project-based learning improves the learning experience for students and enables their use of these significant resources throughout their careers.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>26536666</pmid><doi>10.1371/journal.pone.0135352</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2015-11, Vol.10 (11), p.e0135352-e0135352 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_1730269610 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
subjects | Acidobacteria - genetics Alaska Bacteria - genetics Carbon Cation exchange Cation exchanging Classrooms Climate Change Climate effects Collaboration Colleges & universities Communities Community composition Community structure Coniferous forests Data analysis Data processing Data retrieval Datasets DNA, Bacterial - isolation & purification Ecological monitoring Ecology Ecosystem Ecosystems Environmental changes Fatty acids Fatty Acids - analysis Florida Forest communities Forests Gene sequencing Genetic diversity Grasslands Hawaii Influence Interdisciplinary aspects Lipids - analysis Microbial activity Microbiomes Microorganisms Model testing Moisture content Natural resources Neon Observatories Phospholipids RNA, Ribosomal, 16S - analysis rRNA 16S Science Seasonal variations Seasons Soil - chemistry Soil analysis Soil environment Soil Microbiology Soil microorganisms Soil structure Soil temperature Soil water Soil water storage Storage temperature Subgroups Taiga Temperature Temporal variability Transformation Tropical forests Utah Variability Water content |
title | Key Edaphic Properties Largely Explain Temporal and Geographic Variation in Soil Microbial Communities across Four Biomes |
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