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Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

Trivedi P, Delgado-Baquerizo M, Anderson IC, Singh BK - Front Plant Sci (2016)

Bottom Line: In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties.However, main effects of agriculture on soil properties and productivity were biome-dependent.This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

View Article: PubMed Central - PubMed

Affiliation: Hawkesbury Institute for the Environment, Western Sydney University, Penrith South, NSW Australia.

ABSTRACT
Agricultural intensification is placing tremendous pressure on the soil's capacity to maintain its functions leading to large-scale ecosystem degradation and loss of productivity in the long term. Therefore, there is an urgent need to find early indicators of soil health degradation in response to agricultural management. In recent years, major advances in soil meta-genomic and spatial studies on microbial communities and community-level molecular characteristics can now be exploited as 'biomarker' indicators of ecosystem processes for monitoring and managing sustainable soil health under global change. However, a continental scale, cross biome approach assessing soil microbial communities and their functional potential to identify the unifying principles governing the susceptibility of soil biodiversity to land conversion is lacking. We conducted a meta-analysis from a dataset generated from 102 peer-reviewed publications as well as unpublished data to explore how properties directly linked to soil nutritional health (total C and N; C:N ratio), primary productivity (NPP) and microbial diversity and composition (relative abundance of major bacterial phyla determined by next generation sequencing techniques) are affected in response to agricultural management across the main biomes of Earth (arid, continental, temperate and tropical). In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties. However, main effects of agriculture on soil properties and productivity were biome-dependent. Our meta-analysis provides evidence on the predictable nature of the microbial community responses to vegetation type. This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

No MeSH data available.


Related in: MedlinePlus

Locations of the soil samples included in this study. Agricultural soil samples (n = 165) and natural soil samples (n = 353) are shown as circles and squares, respectively. The sites were selected based on a meta-analysis consisting of both published and unpublished data wherein bacterial diversity and compositions is described based on next generation sequencing techniques (either 454 or Miseq) from both. From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment (See Material and Methods for more details).
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Figure 1: Locations of the soil samples included in this study. Agricultural soil samples (n = 165) and natural soil samples (n = 353) are shown as circles and squares, respectively. The sites were selected based on a meta-analysis consisting of both published and unpublished data wherein bacterial diversity and compositions is described based on next generation sequencing techniques (either 454 or Miseq) from both. From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment (See Material and Methods for more details).

Mentions: We collected data on soil bacterial diversity based on next generation sequencing techniques (either 454 or Miseq) from both published and unpublished data. We first conducted a search using SCOPUS1 (on September 2014). The following keyword combinations were used: (1) “bacterial community” AND “soil” AND “Pyrosequencing”; and (2) “bacterial community” AND “soil” AND “Illumina.” We found ~300 references. Within these references, studies were chosen for inclusion in our analyses only if they met the following criteria: (1) were carried out in the field in terrestrial ecosystems, (2) contained the spatial location where they were carried out (latitude and longitude), as well as data on soil total C and pH; (3) provided information on Shannon bacterial diversity at 97% of similarity; (4) included data on the relative abundance of soil bacterial phyla, (5) used next generation sequencing techniques (either 454 or Miseq) and (6) were located in arid, continental, temperate or tropical ecosystems (Koppen classification; Kottek et al., 2006). From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment. The dataset included geographical locations covering all continents and biomes where agriculture is in practice (Figure 1; Data Sheet S1).


Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

Trivedi P, Delgado-Baquerizo M, Anderson IC, Singh BK - Front Plant Sci (2016)

Locations of the soil samples included in this study. Agricultural soil samples (n = 165) and natural soil samples (n = 353) are shown as circles and squares, respectively. The sites were selected based on a meta-analysis consisting of both published and unpublished data wherein bacterial diversity and compositions is described based on next generation sequencing techniques (either 454 or Miseq) from both. From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment (See Material and Methods for more details).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4940416&req=5

Figure 1: Locations of the soil samples included in this study. Agricultural soil samples (n = 165) and natural soil samples (n = 353) are shown as circles and squares, respectively. The sites were selected based on a meta-analysis consisting of both published and unpublished data wherein bacterial diversity and compositions is described based on next generation sequencing techniques (either 454 or Miseq) from both. From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment (See Material and Methods for more details).
Mentions: We collected data on soil bacterial diversity based on next generation sequencing techniques (either 454 or Miseq) from both published and unpublished data. We first conducted a search using SCOPUS1 (on September 2014). The following keyword combinations were used: (1) “bacterial community” AND “soil” AND “Pyrosequencing”; and (2) “bacterial community” AND “soil” AND “Illumina.” We found ~300 references. Within these references, studies were chosen for inclusion in our analyses only if they met the following criteria: (1) were carried out in the field in terrestrial ecosystems, (2) contained the spatial location where they were carried out (latitude and longitude), as well as data on soil total C and pH; (3) provided information on Shannon bacterial diversity at 97% of similarity; (4) included data on the relative abundance of soil bacterial phyla, (5) used next generation sequencing techniques (either 454 or Miseq) and (6) were located in arid, continental, temperate or tropical ecosystems (Koppen classification; Kottek et al., 2006). From those experimental studies that manipulated environmental conditions (e.g., nutrients or climatic conditions) we only used the data from the control treatment. The dataset included geographical locations covering all continents and biomes where agriculture is in practice (Figure 1; Data Sheet S1).

Bottom Line: In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties.However, main effects of agriculture on soil properties and productivity were biome-dependent.This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

View Article: PubMed Central - PubMed

Affiliation: Hawkesbury Institute for the Environment, Western Sydney University, Penrith South, NSW Australia.

ABSTRACT
Agricultural intensification is placing tremendous pressure on the soil's capacity to maintain its functions leading to large-scale ecosystem degradation and loss of productivity in the long term. Therefore, there is an urgent need to find early indicators of soil health degradation in response to agricultural management. In recent years, major advances in soil meta-genomic and spatial studies on microbial communities and community-level molecular characteristics can now be exploited as 'biomarker' indicators of ecosystem processes for monitoring and managing sustainable soil health under global change. However, a continental scale, cross biome approach assessing soil microbial communities and their functional potential to identify the unifying principles governing the susceptibility of soil biodiversity to land conversion is lacking. We conducted a meta-analysis from a dataset generated from 102 peer-reviewed publications as well as unpublished data to explore how properties directly linked to soil nutritional health (total C and N; C:N ratio), primary productivity (NPP) and microbial diversity and composition (relative abundance of major bacterial phyla determined by next generation sequencing techniques) are affected in response to agricultural management across the main biomes of Earth (arid, continental, temperate and tropical). In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties. However, main effects of agriculture on soil properties and productivity were biome-dependent. Our meta-analysis provides evidence on the predictable nature of the microbial community responses to vegetation type. This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

No MeSH data available.


Related in: MedlinePlus