Topographic control of soil microbial activity: a case study of denitrifiers

Florinsky, Igor V.; McMahon, Shawna K.; Burton, David L.

doi:10.1016/s0016-7061(03)00224-6

Cited by 83 publications

(46 citation statements)

References 45 publications

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“…This has also been demonstrated for denitrification in the pioneering work of Robertson et al (41), followed by others (13,38), and was confirmed in our study. Not surprisingly, soil nitrate and dissolved organic carbon were the most important factors correlated with the activity, which is in agreement with what others have found (40).…”

Section: Discussionsupporting

confidence: 91%

Soil Resources Influence Spatial Patterns of Denitrifying Communities at Scales Compatible with Land Management

Enwall

Throbäck

Stenberg

et al. 2010

Appl Environ Microbiol

209

146

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Knowing spatial patterns of functional microbial guilds can increase our understanding of the relationships between microbial community ecology and ecosystem functions. Using geostatistical modeling to map spatial patterns, we explored the distribution of the community structure, size, and activity of one functional group in N cycling, the denitrifiers, in relation to 23 soil parameters over a 44-ha farm divided into one organic and one integrated crop production system. The denitrifiers were targeted by the nirS and nirK genes that encode the two mutually exclusive types of nitrite reductases, the cd 1 heme-type and copper reductases, respectively. The spatial pattern of the denitrification activity genes was reflected by the maps of the abundances of nir genes. For the community structure, only the maps of the nirS community were related to the activity. The activity was correlated with nitrate and dissolved organic nitrogen and carbon, whereas the gene pools for denitrification, in terms of size and composition, were influenced by the soil structure. For the nirS community, pH and soil nutrients were also important in shaping the community. The only unique parameter related to the nirK community was the soil Cu content. However, the spatial pattern of the nirK denitrifiers corresponded to the division of the farm into the two cropping systems. The different community patterns, together with the spatial distribution of the nirS/nirK abundance ratio, suggest habitat selection on the nirS-and nirK-type denitrifiers. Our findings constitute a first step in identifying niches for denitrifiers at scales relevant to land management.

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Section: Discussionsupporting

confidence: 91%

Soil Resources Influence Spatial Patterns of Denitrifying Communities at Scales Compatible with Land Management

Enwall

Throbäck

Stenberg

et al. 2010

Appl Environ Microbiol

209

146

View full text Add to dashboard Cite

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“…Although these modeling efforts have significantly advanced our understanding of GHG dynamics at landscape to regional scales, most of them do not reflect spatial patterns (or variability) in the lateral redistribution of water (Tague and Band, 2001;Groffman, 2012). The spatial patterns of soil properties (Konda et al, 2010), microbial assemblages (Florinsky et al, 2004), and resultant biogeochemistry influenced by landscape position and topography (Creed and Beall, 2009;Riveros-Iregui and McGlynn, 2009;Creed et al, 2013;Anderson et al, 2015) have been investigated and used to scale point observations to the larger landscape in a limited number of studies. Remote sensing and vegetation classification have also been suggested as empirical methods to scale CH 4 effluxes from wetlands to larger areas (Bartlett et al, 1992;Bubier et al, 1995;Sun et al, 2013), but similar remotely sensed scaling of soil CH 4 uptake is currently lacking.…”

Section: Prediction and Scaling Of Ch 4 Consumption Using Terrain Anamentioning

confidence: 99%

Landscape analysis of soil methane flux across complex terrain

2018

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Abstract. Relationships between methane (CH 4 ) fluxes and environmental conditions have been extensively explored in saturated soils, while research has been less prevalent in aerated soils because of the relatively small magnitudes of CH 4 fluxes that occur in dry soils. Our study builds on previous carbon cycle research at Tenderfoot Creek Experimental Forest, Montana, to identify how environmental conditions reflected by topographic metrics can be leveraged to estimate watershed scale CH 4 fluxes from point scale measurements. Here, we measured soil CH 4 concentrations and fluxes across a range of landscape positions (7 riparian, 25 upland), utilizing topographic and seasonal (29 May-12 September) gradients to examine the relationships between environmental variables, hydrologic dynamics, and CH 4 emission and uptake. Riparian areas emitted small fluxes of CH 4 throughout the study (median: 0.186 µg CH 4 -C m −2 h −1 ) and uplands increased in sink strength with dry-down of the watershed (median: −22.9 µg CH 4 -C m −2 h −1 ). Locations with volumetric water content (VWC) below 38 % were methane sinks, and uptake increased with decreasing VWC. Above 43 % VWC, net CH 4 efflux occurred, and at intermediate VWC net fluxes were near zero. Riparian sites had nearneutral cumulative seasonal flux, and cumulative uptake of CH 4 in the uplands was significantly related to topographic indices. These relationships were used to model the net seasonal CH 4 flux of the upper Stringer Creek watershed (−1.75 kg CH 4 -C ha −1 ). This spatially distributed estimate was 111 % larger than that obtained by simply extrapolating the mean CH 4 flux to the entire watershed area. Our results highlight the importance of quantifying the space-time variability of net CH 4 fluxes as predicted by the frequency distribution of landscape positions when assessing watershed scale greenhouse gas balances.

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“…The spatial patterns of soil properties (Konda et al, 2010), microbial assemblages (Florinsky et al, 2004), and resultant biogeochemistry influenced by landscape position and topography (Creed and Beall, 2009;Riveros-Iregui and 20 McGlynn, 2009;Creed et al, 2013;Anderson et al, 2015) have been investigated and used to scale point observations to the larger landscape in a limited number of studies. Remote sensing and vegetation classification have also been suggested as empirical methods to scale CH4 effluxes from wetlands to larger areas (Bartlett et al, 1992;Bubier et al, 1995;Sun et al, 2013), but similar remotely sensed scaling of soil CH4 uptake is currently lacking.…”

Section: Prediction and Scaling Of Ch4 Consumption Using Terrain Analmentioning

confidence: 99%