A bacterial index to estimate lake trophic level: National scale validation

John K. Pearman; Susanna A. Wood; Marcus J. Vandergoes; Javier Atalah; Sean Waters; Janet Adamson; Georgia Thomson-Laing; Lucy Thompson; Jamie D. Howarth; David P. Hamilton; Xavier Pochon; Laura Biessy; Katie A. Brasell; Jenny Dahl; Riki Ellison; Sean J. Fitzsimons; Henry Gard; Tania Gerrard; Rose Gregersen; McKayla Holloway; Xun Li; David J. Kelly; Reece Martin; Kiely McFarlane; Nicholas P. McKay; Adelaine Moody; Chris M. Moy; Sebastian Naeher; Rewi Newnham; Russleigh Parai; Maïlys Picard; Jonathan Puddick; Andrew B.H. Rees; Lizette Reyes; Marc Schallenberg; Claire Shepherd; Julia Short; Kevin S. Simon; Konstanze Steiner; Charlotte Šunde; Marianna Terezow; John Tibby

doi:10.1016/j.scitotenv.2021.152385

A bacterial index to estimate lake trophic level: National scale validation

John K. Pearman, Susanna A. Wood, Marcus J. Vandergoes, Javier Atalah, Sean Waters, Janet Adamson, Georgia Thomson-Laing, Lucy Thompson, Jamie D. Howarth, David P. Hamilton, Xavier Pochon, Laura Biessy, Katie A. Brasell, Jenny Dahl, Riki Ellison, Sean J. Fitzsimons, Henry Gard, Tania Gerrard, Rose Gregersen, McKayla HollowayXun Li, David J. Kelly, Reece Martin, Kiely McFarlane, Nicholas P. McKay, Adelaine Moody, Chris M. Moy, Sebastian Naeher, Rewi Newnham, Russleigh Parai, Maïlys Picard, Jonathan Puddick, Andrew B.H. Rees, Lizette Reyes, Marc Schallenberg, Claire Shepherd, Julia Short, Kevin S. Simon, Konstanze Steiner, Charlotte Šunde, Marianna Terezow, John Tibby

Earth and Sustainability

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Lakes and their catchments have been subjected to centuries to millennia of exploitation by humans. Efficient monitoring methods are required to promote proactive protection and management. Traditional monitoring is time consuming and expensive, which limits the number of lakes monitored. Lake surface sediments provide a temporally integrated representation of environmental conditions and contain high microbial biomass. Based on these attributes, we hypothesized that bacteria associated with lake trophic states could be identified and used to develop an index that would not be confounded by non-nutrient stressor gradients. Metabarcoding (16S rRNA gene) was used to assess bacterial communities present in surface sediments from 259 non-saline lakes in New Zealand encompassing a range of trophic states from alpine microtrophic lakes to lowland hypertrophic lakes. A subset of lakes (n = 96) with monitoring data was used to identify indicator amplicon sequence variants (ASVs) associated with different trophic states. A total of 10,888 indicator taxa were identified and used to develop a Sediment Bacterial Trophic Index (SBTI), which signficantly correlated (r² = 0.842, P < 0.001) with the Trophic Lake Index. The SBTI was then derived for the remaining 163 lakes, providing new knowledge of the trophic state of these unmonitored lakes. This new, robust DNA-based tool provides a rapid and cost-effective method that will allow a greater number of lakes to be monitored and more effectively managed in New Zealand and globally. The SBTI could also be applied in a paleolimnological context to investigate changes in trophic status over centuries to millennia.

Original language	English (US)
Article number	152385
Journal	Science of the Total Environment
Volume	812
DOIs	https://doi.org/10.1016/j.scitotenv.2021.152385
State	Published - Mar 15 2022

Keywords

Bacteria
Biomonitoring
Environmental DNA
Metabarcoding-based index
Trophic state

ASJC Scopus subject areas

Environmental Engineering
Environmental Chemistry
Waste Management and Disposal
Pollution

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10.1016/j.scitotenv.2021.152385

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Pearman, J. K., Wood, S. A., Vandergoes, M. J., Atalah, J., Waters, S., Adamson, J., Thomson-Laing, G., Thompson, L., Howarth, J. D., Hamilton, D. P., Pochon, X., Biessy, L., Brasell, K. A., Dahl, J., Ellison, R., Fitzsimons, S. J., Gard, H., Gerrard, T., Gregersen, R., ... Tibby, J. (2022). A bacterial index to estimate lake trophic level: National scale validation. Science of the Total Environment, 812, Article 152385. https://doi.org/10.1016/j.scitotenv.2021.152385

Pearman, JK, Wood, SA, Vandergoes, MJ, Atalah, J, Waters, S, Adamson, J, Thomson-Laing, G, Thompson, L, Howarth, JD, Hamilton, DP, Pochon, X, Biessy, L, Brasell, KA, Dahl, J, Ellison, R, Fitzsimons, SJ, Gard, H, Gerrard, T, Gregersen, R, Holloway, M, Li, X, Kelly, DJ, Martin, R, McFarlane, K, McKay, NP, Moody, A, Moy, CM, Naeher, S, Newnham, R, Parai, R, Picard, M, Puddick, J, Rees, ABH, Reyes, L, Schallenberg, M, Shepherd, C, Short, J, Simon, KS, Steiner, K, Šunde, C, Terezow, M & Tibby, J 2022, 'A bacterial index to estimate lake trophic level: National scale validation', Science of the Total Environment, vol. 812, 152385. https://doi.org/10.1016/j.scitotenv.2021.152385

@article{d4add7594c36430f88a76cc4cd8e1e7d,

title = "A bacterial index to estimate lake trophic level: National scale validation",

abstract = "Lakes and their catchments have been subjected to centuries to millennia of exploitation by humans. Efficient monitoring methods are required to promote proactive protection and management. Traditional monitoring is time consuming and expensive, which limits the number of lakes monitored. Lake surface sediments provide a temporally integrated representation of environmental conditions and contain high microbial biomass. Based on these attributes, we hypothesized that bacteria associated with lake trophic states could be identified and used to develop an index that would not be confounded by non-nutrient stressor gradients. Metabarcoding (16S rRNA gene) was used to assess bacterial communities present in surface sediments from 259 non-saline lakes in New Zealand encompassing a range of trophic states from alpine microtrophic lakes to lowland hypertrophic lakes. A subset of lakes (n = 96) with monitoring data was used to identify indicator amplicon sequence variants (ASVs) associated with different trophic states. A total of 10,888 indicator taxa were identified and used to develop a Sediment Bacterial Trophic Index (SBTI), which signficantly correlated (r2 = 0.842, P < 0.001) with the Trophic Lake Index. The SBTI was then derived for the remaining 163 lakes, providing new knowledge of the trophic state of these unmonitored lakes. This new, robust DNA-based tool provides a rapid and cost-effective method that will allow a greater number of lakes to be monitored and more effectively managed in New Zealand and globally. The SBTI could also be applied in a paleolimnological context to investigate changes in trophic status over centuries to millennia.",

keywords = "Bacteria, Biomonitoring, Environmental DNA, Metabarcoding-based index, Trophic state",

author = "Pearman, {John K.} and Wood, {Susanna A.} and Vandergoes, {Marcus J.} and Javier Atalah and Sean Waters and Janet Adamson and Georgia Thomson-Laing and Lucy Thompson and Howarth, {Jamie D.} and Hamilton, {David P.} and Xavier Pochon and Laura Biessy and Brasell, {Katie A.} and Jenny Dahl and Riki Ellison and Fitzsimons, {Sean J.} and Henry Gard and Tania Gerrard and Rose Gregersen and McKayla Holloway and Xun Li and Kelly, {David J.} and Reece Martin and Kiely McFarlane and McKay, {Nicholas P.} and Adelaine Moody and Moy, {Chris M.} and Sebastian Naeher and Rewi Newnham and Russleigh Parai and Ma{\"i}lys Picard and Jonathan Puddick and Rees, {Andrew B.H.} and Lizette Reyes and Marc Schallenberg and Claire Shepherd and Julia Short and Simon, {Kevin S.} and Konstanze Steiner and Charlotte {\v S}unde and Marianna Terezow and John Tibby",

note = "Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",

year = "2022",

month = mar,

day = "15",

doi = "10.1016/j.scitotenv.2021.152385",

language = "English (US)",

volume = "812",

journal = "Science of the Total Environment",

issn = "0048-9697",

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TY - JOUR

T1 - A bacterial index to estimate lake trophic level

T2 - National scale validation

AU - Pearman, John K.

AU - Wood, Susanna A.

AU - Vandergoes, Marcus J.

AU - Atalah, Javier

AU - Waters, Sean

AU - Adamson, Janet

AU - Thomson-Laing, Georgia

AU - Thompson, Lucy

AU - Howarth, Jamie D.

AU - Hamilton, David P.

AU - Pochon, Xavier

AU - Biessy, Laura

AU - Brasell, Katie A.

AU - Dahl, Jenny

AU - Ellison, Riki

AU - Fitzsimons, Sean J.

AU - Gard, Henry

AU - Gerrard, Tania

AU - Gregersen, Rose

AU - Holloway, McKayla

AU - Li, Xun

AU - Kelly, David J.

AU - Martin, Reece

AU - McFarlane, Kiely

AU - McKay, Nicholas P.

AU - Moody, Adelaine

AU - Moy, Chris M.

AU - Naeher, Sebastian

AU - Newnham, Rewi

AU - Parai, Russleigh

AU - Picard, Maïlys

AU - Puddick, Jonathan

AU - Rees, Andrew B.H.

AU - Reyes, Lizette

AU - Schallenberg, Marc

AU - Shepherd, Claire

AU - Short, Julia

AU - Simon, Kevin S.

AU - Steiner, Konstanze

AU - Šunde, Charlotte

AU - Terezow, Marianna

AU - Tibby, John

PY - 2022/3/15

Y1 - 2022/3/15

N2 - Lakes and their catchments have been subjected to centuries to millennia of exploitation by humans. Efficient monitoring methods are required to promote proactive protection and management. Traditional monitoring is time consuming and expensive, which limits the number of lakes monitored. Lake surface sediments provide a temporally integrated representation of environmental conditions and contain high microbial biomass. Based on these attributes, we hypothesized that bacteria associated with lake trophic states could be identified and used to develop an index that would not be confounded by non-nutrient stressor gradients. Metabarcoding (16S rRNA gene) was used to assess bacterial communities present in surface sediments from 259 non-saline lakes in New Zealand encompassing a range of trophic states from alpine microtrophic lakes to lowland hypertrophic lakes. A subset of lakes (n = 96) with monitoring data was used to identify indicator amplicon sequence variants (ASVs) associated with different trophic states. A total of 10,888 indicator taxa were identified and used to develop a Sediment Bacterial Trophic Index (SBTI), which signficantly correlated (r2 = 0.842, P < 0.001) with the Trophic Lake Index. The SBTI was then derived for the remaining 163 lakes, providing new knowledge of the trophic state of these unmonitored lakes. This new, robust DNA-based tool provides a rapid and cost-effective method that will allow a greater number of lakes to be monitored and more effectively managed in New Zealand and globally. The SBTI could also be applied in a paleolimnological context to investigate changes in trophic status over centuries to millennia.

AB - Lakes and their catchments have been subjected to centuries to millennia of exploitation by humans. Efficient monitoring methods are required to promote proactive protection and management. Traditional monitoring is time consuming and expensive, which limits the number of lakes monitored. Lake surface sediments provide a temporally integrated representation of environmental conditions and contain high microbial biomass. Based on these attributes, we hypothesized that bacteria associated with lake trophic states could be identified and used to develop an index that would not be confounded by non-nutrient stressor gradients. Metabarcoding (16S rRNA gene) was used to assess bacterial communities present in surface sediments from 259 non-saline lakes in New Zealand encompassing a range of trophic states from alpine microtrophic lakes to lowland hypertrophic lakes. A subset of lakes (n = 96) with monitoring data was used to identify indicator amplicon sequence variants (ASVs) associated with different trophic states. A total of 10,888 indicator taxa were identified and used to develop a Sediment Bacterial Trophic Index (SBTI), which signficantly correlated (r2 = 0.842, P < 0.001) with the Trophic Lake Index. The SBTI was then derived for the remaining 163 lakes, providing new knowledge of the trophic state of these unmonitored lakes. This new, robust DNA-based tool provides a rapid and cost-effective method that will allow a greater number of lakes to be monitored and more effectively managed in New Zealand and globally. The SBTI could also be applied in a paleolimnological context to investigate changes in trophic status over centuries to millennia.

KW - Bacteria

KW - Biomonitoring

KW - Environmental DNA

KW - Metabarcoding-based index

KW - Trophic state

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U2 - 10.1016/j.scitotenv.2021.152385

DO - 10.1016/j.scitotenv.2021.152385

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AN - SCOPUS:85121660542

SN - 0048-9697

VL - 812

JO - Science of the Total Environment

JF - Science of the Total Environment

M1 - 152385

ER -

A bacterial index to estimate lake trophic level: National scale validation

Abstract

Keywords

ASJC Scopus subject areas

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