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Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity

Cite this dataset

Dove, Nicholas (2020). Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity [Dataset]. Dryad. https://doi.org/10.6071/M3D104

Abstract

Chemical stabilization of microbial-derived products such as extracellular enzymes (EE) onto mineral surfaces has gained attention as a possibly important mechanism leading to the persistence of soil organic carbon (SOC). While the controls on EE activities and their stabilization in the surface soil are reasonably well-understood, how these activities change with soil depth and possibly diverge from those at the soil surface due to distinct physical, chemical, and biotic conditions remains unclear. We assessed EE activity to a depth of 1 m (10 cm increments) in 19 soil profiles across the Critical Zone Observatory Network, which represents a wide range of climates, soil orders, and vegetation types. For all EEs, activities per mass soil correlated positively with microbial biomass (MB) and SOC, all of which decreased logarithmically with depth (p < 0.05). Across all sites, over half of the potential soil EE activities per mass soil consistently occurred below 20 cm for all measured EEs. Activities per unit MB or SOC were substantially higher at depth (soils below 20 cm accounted for 80% of whole-profile EE activity), suggesting an accumulation of stabilized (i.e., mineral sorbed) EEs in subsoil horizons. The pronounced enzyme stabilization in subsurface horizons was corroborated by mixed-effects models that showed a significant, positive relationship between clay concentration and MB-normalized EE activities in the subsoil. Furthermore, the negative relationships between soil C, N, and P and C-, N-, and P-acquiring EEs found in the surface soil decoupled at 20 cm, which could have also been caused by EE stabilization. This finding suggests that EEs may not reflect soil nutrient availabilities at depth. Taken together, our results suggest that deeper soil horizons hold a significant reservoir of EEs, and that the controls of subsoil EEs differ from their surface soil counterparts.

Methods

Site selection and sampling

Samples were collected from the network of 10 Critical Zone Observatories (CZOs, http://criticalzone.org) across the USA, which represents a wide range of hydrogeological provinces, soil orders, and vegetation types as described in Brewer et al. (2018). Soils were collected at peak greenness (as estimated from NASA's MODerate-resolution Imaging Spectroradiometer, or MODIS) between April 2016 and November 2016, with the exception of the Eel River CZO samples, which were collected in May 2017 (also at peak-greenness). At each CZO, we excavated two separate soil profiles (“sites”) selected to represent distinct soil types and landscape positions. Any organic horizon was first removed, and then mineral soils were sampled in 10-cm increments with a sterile hand trowel dug into the face of each soil pit to a depth of at least 100 cm or to refusal (e.g., bedrock, hardpan, coarse regolith). 

All soil samples were shipped overnight at 4 °C to the University of California, Riverside for processing. A portion of each field sample was sieved (< 2 mm), homogenized, divided into subsamples for further analyses, and frozen (−20 °C). For some soils (particularly some wet, finely textured depth intervals), sieving was impractical. These samples were homogenized and larger root and rock fragments were removed by hand. In addition, as samples from SHAL (70-100 cm depth) consisted almost entirely of medium-sized weathered bedrock (Cr material), soil was collected by manually crushing weathered bedrock with a ceramic mortar and pestle with this material then passed through a 2-mm sieve. 

Soil physiochemical measurements

Soil pH, gravimetric water content, and clay concentration were measured using modified Long-Term Ecological Research (LTER) protocols (Robertson et al. 1999). Briefly, soil pH was determined in a 1:2 (weight to volume) solution using 5 g of oven-dried soil and 10 ml of Milli-Q water (Millipore Sigma, Burlington, MA, USA). The solution was measured on a Orion DUAL STAR pH meter (Thermo Fisher Scientific, Waltham, MA, USA). For determining gravimetric water content, approximately 7 g field-moist soil was dried at 105 ºC for a minimum of 24 h. Soil texture was measured on oven-dried and sieved soil using the hydrometer method following Gee & Bauder (2018).

Prior to soil total organic C and N analysis, soils were freeze-dried using a Savant Novalyphe-NL500 freezer dryer (Savant, Farmingdale, NY, USA) and ground to a fine powder using a roller mill. If effervescence occurred when a drop of 1 M HCl was added to a subsample of each soil sample, then inorganic C was removed from 2 g of the soil sample by twice-washing with 30 mL 0.1 N HCl (allowing the soil slurry to stand for 1 h during each wash), twice-washing with 30 mL DI, and then freeze-dried. The soil samples were analyzed for total organic C and total N by continuous-flow, direct combustion using a Vario Micro Cube elemental analyzer (Elementar, Hanau, Germany).

            Microbially available orthophosphate, referred hereafter as Olsen P, was estimated by extracting 1 g of soil with 200 ml of 0.5 M NaHCO3 at pH 8.5 (Olsen et al. 1954). Briefly, slurries were shaken for 30 min and filtered through Whatman No. 42 filters. Orthophosphate was measured colormetrically using a Lachat AE Flow Injection Auto Analyzer (Method 12-115-01-1-Q, Lachat Instruments, Inc., Milwaukee, WI, USA). 

 

Phospholipid Fatty Acid Analysis

We used phospholipid fatty acids (PLFAs) to determine differences in the microbial biomass (MB) and the ratios of fungal to bacterial biomass. Briefly, total lipids were extracted using 10 ml of methanol, 5 ml chloroform, and 4 ml of a 50 mM phosphate buffer (pH = 7.4) from 5 g of lyophilized soil (White et al. 1979; DeForest et al. 2004). To determine analytical recovery, phospholipid 19:0 (1,2-dinonadecanoyl-sn-glycero-3-phosphocholine) and 21:0 (1,2-diheneicosanoyl-sn-glycero-3-phosphocholine) standards (Avanti Polar Lipids, Inc., Alabaster, AL, USA) were added during the extraction phase (DeForest et al. 2012). Polar lipids were separated from other lipids using silicic acid solid-phase chromatography columns (500 mg 6 ml-1; Thermo Scientific, Waltham, MA, USA), and the separated polar lipids were converted to fatty acid methyl esters (FAME) through methanolysis (Guckert et al. 1985). The resulting FAMEs were separated using a HP GC-FID (HP6890 series, Agilent Technologies, Inc. Santa Clara, CA, USA) gas chromatograph, and peaks/biomarkers were identified using the Sherlock System (v. 6.1, MIDI, Inc., Newark, DE, USA). External FAME standards (K104 FAME mix, Grace, Deerfield, IL, USA) were used to determine concentrations. The sum of all detected 14–19 C-length PLFAs was used to calculate MB because longer PLFAs can be indicators of mosses and higher plants (Zelles 1999). Ratios of fungal to bacterial biomass (fungi:bacteria) were calculated by dividing the amount (mol) of the fungal biomarker 18:2ω6c by the sum of all other microbial biomarkers (i.e., mol 18:2ω6c /(mol MB – mol 18:2ω6c)).

 

Extracellular enzyme activity

We measured potential EE activity (i.e., activity not limited by substrate concentrations) of α-glucosidase (AG), β-glucosidase (BG), cellobiohydrolase (CB), β-xylosidase (BX), N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and acid phosphatase (AP) fluorometrically following Bell et al. (2013). Briefly, an 800 µl soil slurry consisting of 2.75 g of field-moist soil in 91 ml of 50 mM sodium acetate buffer (pH = 5.5) was incubated with 200 µl of each of the 100 µM 4-methylumbelliferone (MUB)-linked or 7-amido-4-methylcoumarin (AMC)-linked substrates (only LAP was AMC-linked) in 96-deep well plates. After a 3-h incubation at 20 °C, plates were centrifuged, and the supernatant was transferred to black, flat-bottom 96-well plates. Fluorescence was measured on a Tecan M200 Pro (Tecan Group Ltd., Männedorf, Switzerland) using an excitation wavelength of 365 nm and an emission wavelength of 450 nm.

Funding

NSF EarthCube program , Award: ICER-1541047

NSF Critical Zone Observatory Network, Award: EAR-1331939

United States Department of Energy, Award: DE-AC52-07NA27344

US Department of Energy Early Career Research Program Award , Award: SCW1478

National Science Foundation for RC CZO Cooperative agreement, Award: EAR-1331872