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Microsite Differentiation Drives the Abundance of Soil Ammonia Oxidizing Bacteria along Aridity Gradients.

Delgado-Baquerizo M, Maestre FT, Eldridge DJ, Singh BK - Front Microbiol (2016)

Bottom Line: Here, we evaluate the abundance of amoA genes from AOB and AOA within six microsites commonly found in drylands (open areas, biocrusts, ant nests, grasses, nitrogen-fixing shrubs, and trees) at 21 sites from eastern Australia, including arid and mesic ecosystems that are threatened by predicted increases in aridity.While the abundance of AOA sharply increased with increasing aridity in all microsites, the response of AOB abundance was microsite-dependent, with increases (nitrogen-fixing shrubs, ant nests), decreases (open areas) or no changes (grasses, biocrusts, trees) in abundance with increasing aridity.These results are linked to particular soil characteristics (e.g., total carbon and ammonium) under these microsites.

View Article: PubMed Central - PubMed

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

ABSTRACT
Soil ammonia oxidizing bacteria (AOB) and archaea (AOA) are responsible for nitrification in terrestrial ecosystems, and play important roles in ecosystem functioning by modulating the rates of N losses to ground water and the atmosphere. Vascular plants have been shown to modulate the abundance of AOA and AOB in drylands, the largest biome on Earth. Like plants, biotic and abiotic features such as insect nests and biological soil crusts (biocrusts) have unique biogeochemical attributes (e.g., nutrient availability) that may modify the local abundance of AOA and AOB. However, little is known about how these biotic and abiotic features and their interactions modulate the abundance of AOA and AOB in drylands. Here, we evaluate the abundance of amoA genes from AOB and AOA within six microsites commonly found in drylands (open areas, biocrusts, ant nests, grasses, nitrogen-fixing shrubs, and trees) at 21 sites from eastern Australia, including arid and mesic ecosystems that are threatened by predicted increases in aridity. Our results from structural equation modeling suggest that soil microsite differentiation alters the abundance of AOB (but not AOA) in both arid and mesic ecosystems. While the abundance of AOA sharply increased with increasing aridity in all microsites, the response of AOB abundance was microsite-dependent, with increases (nitrogen-fixing shrubs, ant nests), decreases (open areas) or no changes (grasses, biocrusts, trees) in abundance with increasing aridity. Microsites supporting the highest abundance of AOB were trees, nitrogen-fixing shrubs, and ant nests. These results are linked to particular soil characteristics (e.g., total carbon and ammonium) under these microsites. Our findings advance our understanding of key drivers of functionally important microbial communities and N availability in highly heterogeneous ecosystems such as drylands, which may be obscured when different soil microsites are not explicitly considered.

No MeSH data available.


Related in: MedlinePlus

Results from structural equation modeling showing the direct and indirect effects of aridity and different microsites on the abundance of AOB and AOA and on nitrate availability. Each panel represents the model used for each microsite (indicated in the upper right box of each model). Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. Double-headed arrows between AOA and AOB indicate that the abundance of AOA can influence that one from AOB and viseversa. The proportion of variance explained (R2) appears above every response variable in the model. Significance levels are as follows: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001.
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Figure 4: Results from structural equation modeling showing the direct and indirect effects of aridity and different microsites on the abundance of AOB and AOA and on nitrate availability. Each panel represents the model used for each microsite (indicated in the upper right box of each model). Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. Double-headed arrows between AOA and AOB indicate that the abundance of AOA can influence that one from AOB and viseversa. The proportion of variance explained (R2) appears above every response variable in the model. Significance levels are as follows: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001.

Mentions: Our a priori SEM model was satisfactorily fitted to our data, as suggested by non-significant χ2 values (χ2 = 0.6–4.2; P = 0.37–0.98; df = 4), non-parametric Bootstrap P-values ranging from 0.46 to 0.97 and by values of RMSEA ranging from 0.00 to 0.03 (0.53 < P < 0.98; Figure 4). Most microsite effects (i.e., open areas, ant nests, grasses, and trees) on the abundance of amoA genes from AOB were indirectly driven by variations in soil C and ammonium availability, suggesting that these predictors adequately explained the abundance of AOB beneath these microsites. Contrary to this, we found a predominant direct positive and negative effect of N-fixing shrubs (Figure 4E) and biocrusts (Figure 4B) on the abundance of AOB, respectively, indicating that other unmeasured factors may have driven the indirect effects of these microsites on the abundance of amoA genes from AOB. Open areas and biocrusts showed a negative direct effect on soil C and ammonium compared with the other microsites, promoting an indirect negative effect on the abundance of AOB and on nitrate availability (via soil C and ammonium; Figures 4A,B). Conversely, ant nest and grasses had an indirect positive effect on AOB abundance via their influence on that of ammonium (Figures 4C,D), while trees had an indirect positive effect on AOB abundance by affecting soil C, hence the availability of ammonium in soil (Figure 4F). For AOA, our SEM results revealed that aridity had the highest direct positive effect on the abundance of amoA genes from AOA (Figure 4); aridity also had an indirect positive effect on these microorganisms by reducing both the C:N ratio (negatively related to the abundance of AOA), and the amount of soil C (positively related to ammonium; Figure 4) and by enhancing soil pH (positively related to AOA abundance; Figure 4).


Microsite Differentiation Drives the Abundance of Soil Ammonia Oxidizing Bacteria along Aridity Gradients.

Delgado-Baquerizo M, Maestre FT, Eldridge DJ, Singh BK - Front Microbiol (2016)

Results from structural equation modeling showing the direct and indirect effects of aridity and different microsites on the abundance of AOB and AOA and on nitrate availability. Each panel represents the model used for each microsite (indicated in the upper right box of each model). Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. Double-headed arrows between AOA and AOB indicate that the abundance of AOA can influence that one from AOB and viseversa. The proportion of variance explained (R2) appears above every response variable in the model. Significance levels are as follows: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4834304&req=5

Figure 4: Results from structural equation modeling showing the direct and indirect effects of aridity and different microsites on the abundance of AOB and AOA and on nitrate availability. Each panel represents the model used for each microsite (indicated in the upper right box of each model). Numbers adjacent to arrows are standardized path coefficients, analogous to relative regression weights, and indicative of the effect size of the relationship. Continuous and dashed arrows indicate positive and negative relationships, respectively. The width of arrows is proportional to the strength of path coefficients. Double-headed arrows between AOA and AOB indicate that the abundance of AOA can influence that one from AOB and viseversa. The proportion of variance explained (R2) appears above every response variable in the model. Significance levels are as follows: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001.
Mentions: Our a priori SEM model was satisfactorily fitted to our data, as suggested by non-significant χ2 values (χ2 = 0.6–4.2; P = 0.37–0.98; df = 4), non-parametric Bootstrap P-values ranging from 0.46 to 0.97 and by values of RMSEA ranging from 0.00 to 0.03 (0.53 < P < 0.98; Figure 4). Most microsite effects (i.e., open areas, ant nests, grasses, and trees) on the abundance of amoA genes from AOB were indirectly driven by variations in soil C and ammonium availability, suggesting that these predictors adequately explained the abundance of AOB beneath these microsites. Contrary to this, we found a predominant direct positive and negative effect of N-fixing shrubs (Figure 4E) and biocrusts (Figure 4B) on the abundance of AOB, respectively, indicating that other unmeasured factors may have driven the indirect effects of these microsites on the abundance of amoA genes from AOB. Open areas and biocrusts showed a negative direct effect on soil C and ammonium compared with the other microsites, promoting an indirect negative effect on the abundance of AOB and on nitrate availability (via soil C and ammonium; Figures 4A,B). Conversely, ant nest and grasses had an indirect positive effect on AOB abundance via their influence on that of ammonium (Figures 4C,D), while trees had an indirect positive effect on AOB abundance by affecting soil C, hence the availability of ammonium in soil (Figure 4F). For AOA, our SEM results revealed that aridity had the highest direct positive effect on the abundance of amoA genes from AOA (Figure 4); aridity also had an indirect positive effect on these microorganisms by reducing both the C:N ratio (negatively related to the abundance of AOA), and the amount of soil C (positively related to ammonium; Figure 4) and by enhancing soil pH (positively related to AOA abundance; Figure 4).

Bottom Line: Here, we evaluate the abundance of amoA genes from AOB and AOA within six microsites commonly found in drylands (open areas, biocrusts, ant nests, grasses, nitrogen-fixing shrubs, and trees) at 21 sites from eastern Australia, including arid and mesic ecosystems that are threatened by predicted increases in aridity.While the abundance of AOA sharply increased with increasing aridity in all microsites, the response of AOB abundance was microsite-dependent, with increases (nitrogen-fixing shrubs, ant nests), decreases (open areas) or no changes (grasses, biocrusts, trees) in abundance with increasing aridity.These results are linked to particular soil characteristics (e.g., total carbon and ammonium) under these microsites.

View Article: PubMed Central - PubMed

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

ABSTRACT
Soil ammonia oxidizing bacteria (AOB) and archaea (AOA) are responsible for nitrification in terrestrial ecosystems, and play important roles in ecosystem functioning by modulating the rates of N losses to ground water and the atmosphere. Vascular plants have been shown to modulate the abundance of AOA and AOB in drylands, the largest biome on Earth. Like plants, biotic and abiotic features such as insect nests and biological soil crusts (biocrusts) have unique biogeochemical attributes (e.g., nutrient availability) that may modify the local abundance of AOA and AOB. However, little is known about how these biotic and abiotic features and their interactions modulate the abundance of AOA and AOB in drylands. Here, we evaluate the abundance of amoA genes from AOB and AOA within six microsites commonly found in drylands (open areas, biocrusts, ant nests, grasses, nitrogen-fixing shrubs, and trees) at 21 sites from eastern Australia, including arid and mesic ecosystems that are threatened by predicted increases in aridity. Our results from structural equation modeling suggest that soil microsite differentiation alters the abundance of AOB (but not AOA) in both arid and mesic ecosystems. While the abundance of AOA sharply increased with increasing aridity in all microsites, the response of AOB abundance was microsite-dependent, with increases (nitrogen-fixing shrubs, ant nests), decreases (open areas) or no changes (grasses, biocrusts, trees) in abundance with increasing aridity. Microsites supporting the highest abundance of AOB were trees, nitrogen-fixing shrubs, and ant nests. These results are linked to particular soil characteristics (e.g., total carbon and ammonium) under these microsites. Our findings advance our understanding of key drivers of functionally important microbial communities and N availability in highly heterogeneous ecosystems such as drylands, which may be obscured when different soil microsites are not explicitly considered.

No MeSH data available.


Related in: MedlinePlus