Relating the biological stability of soil organic matter to energy availability in deep tropical soil profiles

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Relating the biological stability of soil organic matter to energy availability in deep tropical soil profiles

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Madeleine M. Stone, Alain F. Plante*

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Department of Earth and Environmental Science, University of Pennsylvania, Hayden Hall, 240 South 33rd Street, Philadelphia, PA 19104-6316, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 28 January 2015 Received in revised form 9 July 2015 Accepted 11 July 2015 Available online xxx

Tropical subsoils contain large reservoirs of carbon (C), most of which is stored in soil organic matter (SOM). Subsoil OM is thought to be particularly stable against microbial decomposition due to various mechanisms and its position in the soil profile, potentially representing a long-term C sink. However, few experiments have explicitly investigated SOM stability and microbial activity across several orders of magnitude of soil C concentrations as a function of soil depth. The objective of this study was to evaluate the biological stability of SOM in the upper 1.4 m of tropical forest soil profiles. We did so by measuring CO2 evolution during a 90-day laboratory incubation experiment on a sample set that was previously characterized for C and nutrient concentrations and microbial biomass. We concurrently measured the energy content of SOM using differential scanning calorimetry (DSC) as an index of the energy available for microbial metabolism, with the hypothesis that the biological stability of SOM would be inversely related to the energy contained within it. Cumulative CO2 evolution, mean respiration rates, and the energy density of SOM (energy released during combustion normalized to soil C) all declined with soil depth (P < 0.01). Biological indices of C stability were well correlated with measures of SOM energy. There was no change in the mean respiration rate as a function of depth when normalized to soil C, and a trend toward increased respiration per-unit microbial biomass (P ¼ 0.07). While reduced microbial respiration in subsoils suggests an increase in the biological stability of SOM, we suggest this is driven principally by concurrent declines in energy availability as measured by DSC and the size of the microbial biomass pool. On a per-unit biomass basis, subsoil OM may be as prone to decomposition and destabilization as surface SOM. © 2015 Published by Elsevier Ltd.

Keywords: Soil organic matter Stability Tropical Deep soil Incubation Thermal analysis

1. Introduction Tropical forests are a large terrestrial carbon (C) sink, and their soils contain between one third and half of the total C stored in soil
gy and Jackson, 2000; IPCC, 2007). organic matter (SOM) (Jobba Tropical forests also make large contributions to subsoil SOM stocks
gy and Jackson, 2000; Veldkamp et al., 2003), that is, SOM (Jobba stored below the upper 20e30 cm of the soil profile (Rumpel and Kogel-Knabner, 2011). Deep SOM is thought to have high potential for long-term sequestration, as indicated by radiocarbon ages on the order of 1000s of years (Trumbore, 2000; Rumpel et al., 2004; Rumpel and Kogel-Knabner, 2011). However, for C to be sequestered over long time scales, it must remain stable against microbial decomposition. Although interest in SOM stability has

* Corresponding author. Fax: þ1 215 898 0964. E-mail address: [email protected] (A.F. Plante).

increased considerably in recent years (Schmidt et al., 2011), relatively few studies have explicitly investigated stability in tropical forests (Wood et al., 2012; Wieder et al., 2013). Moreover, most studies of tropical soil C cycling have focused exclusively on the upper layers of the mineral soil (but see (Trumbore, 2000; Veldkamp et al., 2003; Marin-Spiotta et al., 2011; Kang Min et al., 2013). Understanding how SOM stability changes with depth is critical to predicting the response of deep soil C to land use change or other global change drivers (Veldkamp et al., 2003; Fontaine et al., 2007). SOM stability is defined as resistance to decomposition, regardless of the mechanism. A wide range of methods are used to infer stabilization (Denef et al., 2009), including biological, chemical and thermal methods, each of which provides information on specific stabilization processes that can produce contrasting results. Generally speaking, SOM stability is thought to increase with soil depth (Rumpel and Kogel-Knabner, 2011), given the general trend of increased SOM radiocarbon age (Trumbore, 2000; Jenkinson

http://dx.doi.org/10.1016/j.soilbio.2015.07.008 0038-0717/© 2015 Published by Elsevier Ltd.

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et al., 2008). One proposed mechanism for the greater stability of deep SOM is increased mineral association (Kaiser et al., 2002; Eusterhues et al., 2003; Rumpel and Kogel-Knabner, 2011), which can reduce the accessibility of SOM to microbial decomposers. However, the importance of mineral stabilization will depend on soil type owing to the effects of texture and mineralogy on surface area and surface charge (Oades, 1984; Trumbore, 2009). For instance, several authors have found Fe-oxides and clay minerals to be the most important stabilizing agents in tropical Oxisols (Eusterhues et al., 2003; Dick et al., 2005; Rumpel et al., 2008), while allophanic minerals stabilize large amounts of C in volcanic soils (Marin-Spiotta et al., 2011). As the mineralogical composition of a soil changes over the course of pedogenesis, the soil's capacity to stabilize OM can also change. These changes can also be observed downward in a soil profile as the most highly weathered materials are typically found at the surface. In addition, changes in the abundance and activity of microbial decomposers can strongly influence SOM stability. Many studies have observed reduced microbial abundance and activity with soil depth (Blume et al., 2002; Fierer et al., 2003; Stone et al., 2014). Microbial activity can decline in subsoils due to substrate scarcity and nutrient limitation (Fontaine et al., 2007), changes in the spatial distribution of microbes and substrates (Lindahl et al., 2007), and the increased stability of mineral-associated SOM (Rumpel and Kogel-Knabner, 2011). However, specific metabolic activities (normalized to soil C or microbial biomass) sometimes remain high in subsoils (Blume et al., 2002; Gelsomino and Azzellino, 2011; Kramer et al., 2013; Stone et al., 2014), indicating that subsoil microbial communities can retain the metabolic capacity to cycle C in spite of their reduced population size. Subsoil C is often recycled through microbial biomass, resulting in a SOM pool that is chemically labile but old according to its 14C signature (Gleixner et al., 2002; Kaiser and Kalbitz, 2012), a finding which calls into question the notion that radiocarbon-depleted SOM is inherently more stable. In recent studies, Stone et al. (a2014, 2014) investigated changes in soil microbial biomass, community structure and extracellular enzyme activities with depth as part of the Luquillo Critical Zone observatory (LCZO), a wet tropical forest in northeastern Puerto Rico. While we found exponential declines in microbial abundance and activity with depth, specific metabolic activity typically did not vary with depth, suggesting that some fraction of the deep SOM pool is available to microbial decomposers. In this study, we investigated changes in the shortterm biological stability of SOM along the same tropical soil profiles by measuring CO2 losses during laboratory incubation to investigate possible implications for deep soil C cycling. We simultaneously used thermal analysis to inform our understanding of SOM stability from an energetic perspective. Thermal analysis by differential scanning calorimetry (DSC) quantifies energy inputs and outputs as a sample is subjected to ramped combustion (Plante et al., 2009). For soils, this technique integrates information about the chemical composition and energy content of SOM with stabilization through interactions with soil minerals. Thermal analysis quantifies the energy as heat required for combustion, as well as the energy stored in the SOM of a sample. SOM that combusts at higher temperatures is considered more thermally stable, and is presumed to have a greater energy barrier to decomposition. This energy barrier is balanced against the energy available to microorganisms upon SOM decomposition, which can be inferred by quantifying the energy released during combustion (Peltre et al., 2013). Since microbial C mineralization depends on the thermodynamic favorability of decomposition, the persistence of organic matter may relate to both the size of the energy barrier and the quantity of energy released.

Our sample set included soils formed from two distinct geologic parent materials weathering to contrasting soils (Oxisols versus Inceptisols), occurring under two climatically distinguished forest types (low-elevation Tabonuco forest versus mid-elevation Palo Colorado forest). This factorial combination of contrasting geologies and forest types allowed us to simultaneously investigate several potential drivers of SOM stability, including soil mineralogy and substrate chemistry. Because of exponential declines in bulk soil C concentrations and microbial biomass with soil depth (Stone et al., 2014), we predicted soil respiration would likewise decline exponentially with depth. We sought to investigate whether soil and forest types mediate the biological stability of SOM, with the prediction that SOM in the higher elevation forest (which has poorer litter quality, Cusack et al. 2011) might exhibit greater biological stability. We also predicted that biological stability of soil C might be greater in the clay-rich Oxisols compared to the sandy Inceptisols. However, because previous reports demonstrated that microbial biomass and soil C stocks were not substantially different across the soil and forest types (Johnson et al., submitted for publication; Stone et al., 2014), we anticipated that any small differences attributable to these landscape-scale factors would be masked by much larger differences attributable to soil depth. To tease apart changes in the biological stability of SOM from changes in the quantities of C and decomposers, we used published datasets of soil C and microbial biomass C concentrations (Stone et al., 2014) to normalize cumulative CO2 evolution and respiration rates. The overall goals of this study were to measure changes in SOM stability as a function of soil depth, and to elucidate the possible mechanisms for changes in stability. In addition to unfavorable environmental conditions attributable to position in the soil profile (e.g., lack of oxygen, etc.), and to the conventional mechanisms contributing to SOM stability (e.g., recalcitrance, physical occlusion in aggregates, mineral association through various binding mechanisms), we hypothesize that deep SOM is stable due to low energy contents that are unable to support the metabolic needs of a large microbial population. 2. Methods 2.1. Study site and sample set This study was conducted using soils collected from the Luquillo Experimental Forest in northeastern Puerto Rico (18 180 N, 65 500 W), which supports both the Luquillo Critical Zone Observatory (LCZO) and a Long Term Ecological Research Program (LTER). The area offers a natural experiment for studying changes in SOM stability with depth in the context of landscape-scale gradients in geology, vegetation and climate. The area is composed of two dominant parent materials of differing age and mineralogy: lowerCretaceous volcaniclastic (VC) sediments of andesitic composition and an early-Tertiary age quartz-diorite (QD) pluton known as the Rio Blanco stock (Seiders, 1971a,b). The VC parent material weathers to produce Oxisols, which are clay-rich soils containing <10% weatherable minerals. The QD parent material weathers to produce Inceptisols that are sandy and contain up to 40% primary minerals in surface soils, including feldspars and quartz (Scatena, 1989; Silver et al., 1994; Johnson et al., submitted for publication). Soils are moderately to strongly acidic (pH 3e7), and contain substantial kaolinite, as well as iron and aluminum oxyhydroxides in the clay fraction. The mountainous region is characterized by steep terrain and is highly dissected by slopes >30 . The mean annual temperature decreases from approximately 24  C at 300 masl to 21  C at 800 masl and precipitation increases from 3000 mm y1 to 4000 mm y1 across the same elevation gradient (Brown et al.,

Please cite this article in press as: Stone, M.M., Plante, A.F., Relating the biological stability of soil organic matter to energy availability in deep tropical soil profiles, Soil Biology & Biochemistry (2015), http://dx.doi.org/10.1016/j.soilbio.2015.07.008

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1983). Most of the vegetation falls into four climate-designated life zones sensu Holdridge (1967): subtropical wet forest, subtropical rainforest, lower montane wet forest, and lower montane rainforest. The area is covered primarily by mature Tabonuco (Dacroydes excesla Vahl) forest at low elevations (<600 masl) and Palo Colorado (Cyrilla racemiflora L.) forest at intermediate elevations (600e800 masl). Sierra palm forest is found across all elevations and is dominant at the highest elevations (800e1000 masl, Brown et al., 1983; Weaver, 1991). All forest types occur on both parent materials and soil types. In the present study, we used the same sample set as Stone et al. (2014), which includes samples collected from quantitative soil pits dug in each of the two soil types (Oxisols and Inceptisols), two forest types (Tabonuco and Colorado), and from six depth intervals (0, 20, 50, 80, 110 and 140 cm) in each pit, for a total of 72 samples (2  2  3  6). The Inceptisol soil pits were located in the Naguabo watershed, while the Oxisol pits were in the Luquillo and Canovanas watershed. Three soil pits within each soil  forest type combination were used as field replicates and occur at different topographic positions (ridge, slope, and valley), thus creating the largest possible natural variability in C concentrations and SOM quality to the experiment. Basic soil characteristics (C, N and extractable P concentrations) can be found in Stone et al. (2014). Overall, soil C concentrations increased from ridge (mean ¼ 2.07%) to valley (mean ¼ 3.09%) and were greater and more variable at depth in valley soils (140 cm mean ¼ 1.46 ± 1.01) compared with ridges and slopes (140 cm mean ¼ 0.22 ± 0.09). We also made use of microbial biomass C data quantified by phospholipid fatty acid analysis and reported by Stone et al. (2014). Microbial biomass C followed a very similar pattern to that of soil C concentrations. These samples comprised part of a larger collection effect, all of which was processed by initial field-moist sieving to <5 mm. Care was taken to clean the sieves with ethanol between samples to prevent microbial cross-contamination. Samples used in this experiment came from a subset of samples that were air dried following wet sieving, and further sieved to <2 mm. We acknowledge that sieving can have an effect on soil C mineralization by disrupting aggregate structure, but was necessary to ensure sample homogeneity. 2.2. Laboratory incubation Soils mixed in a 1:1 ratio with sterile quartz sand prior to incubation to maintain pore space. Mixing these soils with sand also served to prevent anoxia, which can lead to differences in organomineral associations and C availability. While redox conditions are known to influence microbial C mineralization in situ and particularly in surface soils (Hall and Silver, 2013), the focus of our study was C mineralization under the aerobic conditions that prevail in these subsoils (McDowell et al., 1992), and we thus chose to avoid introducing the additional variable of soil redox status. Ten grams of the soil þ sand mixture were re-wet to field capacity and preincubated in 50 mL conical centrifuge tubes at 25  C for 1 week prior to respiration measurements to allow the Birch effect to pass (Fierer and Schimel, 2003). CO2 concentrations in the headspace of the tubes were then measured every 1e2 days for the first two weeks after pre-incubation, and once a week for the rest of the 90day incubation. To measure CO2 concentrations, a 1 mL air sample was collected with a syringe and injected into an infrared gas analyzer (IRGA, LI-8000, LICOR, Biosciences). Immediately following a measurement, the tube was opened for 1e2 min to allow equilibration of headspace CO2 concentrations with the atmosphere. The tube was then re-sealed and a second, baseline CO2 measurement was collected. From the CO2 concentration on a given day, we subtracted the baseline CO2 concentration from the

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previous timestep to calculate the CO2 accumulated over that time interval. CO2 concentrations are expressed as mg CO2eC g1 dry soil. Respiration rates were determined at each time step by dividing cumulative CO2 by the number of days since the previous measurement. The basal respiration rate (mg CO2eC g1 soil day1) was determined as the average respiration rate over the last 20 days of the incubation, when respiration rates at all depth intervals had become relatively constant. The cumulative CO2 evolved during the incubation (mg g1 soil) was determined by summing the CO2 accumulated during each time interval. Basal respiration rates and cumulative CO2 evolution were normalized to soil C as indices of SOM decomposability, and to microbial biomass C as indices of specific metabolic activity (Trasar-Cepeda et al., 2008). 2.3. Analytical thermal analysis Differential scanning calorimetry and coupled CO2-evolved gas analysis (CO2-EGA) were performed as described by Peltre et al. (2013). Briefly, thermal analysis was performed using a Netzsch STA 409PC Luxx coupled to a LI-840 CO2/H2O IRGA. Samples were weighed to obtain approximately 1 mg C, with a maximum of 50 mg soil to avoid excess thermal disequilibrium. Samples were heated from ambient (~25  C) to 105  C at 10  C min1, held at 105  C for 15 min to drive off sample moisture, then heated to 850  C at 10  C min1. The furnace atmosphere consisted of CO2free air flowing at 30 mL min1 and N2 protective gas flowing at 10 mL min1. DSC thermograms were baseline corrected for the region between 120 and 850  C using the non-parametric baseline fitting function of Peakfit (Systat Software). Qualitative examination of thermograms revealed exothermic reactions occurring between 150 and 400  C (Fig. 3a). Many thermograms (particularly deep soils) were net-endothermic between the 400e600  C range. However, in many samples, the presence of a slight shoulder in the thermogram between 400 and 450  C suggests exothermic reactions were still occurring in this region (Fig. 4a). Endothermic reactions between 400 and 600  C are associated with the dehy
ndez droxylation of kaolinite (Karathanasis and Harris, 1994; Ferna et al., 2012). To better isolate and evaluate the energy associated with SOM combustion, we measured exothermic energy release (mJ g1 soil) by integrating only the positive region of the thermogram. While this approach does not entirely separate SOM combustion from other energy producing/consuming reactions, it provides us an index that is more closely associated with the energy available to microorganisms from SOM decomposition than an integration of the entire thermogram. Energy density (J mg1 C), calculated as energy content divided by the sample C concentration, was determined to assess difference in SOM quality rather than quantity, and the temperature at which half of the CO2 was evolved (CO2-T50) was calculated as an index of overall thermal SOM stability. 2.4. Statistical analyses All statistics were performed using R v. 3.0.2 (R Core Team, 2012). To meet the assumptions of normality and homoscedasticity, appropriate statistical transformations (e.g., log, square-root) were determined using the ‘powerTransform’ function in the car package (Fox and Weisberg, 2011). Respiration indices (i.e., basal respiration, cumulative CO2) and thermal indices (e.g., energy density) were transformed prior to statistical analysis. We performed analysis of variance of linear mixed-effects models using the lme4 package in R (Bates et al., 2012), to determine the effects of depth, soil type, forest type and their interactions on SOM stability. Depth, soil type and forest type were treated as fixed effects, and

Please cite this article in press as: Stone, M.M., Plante, A.F., Relating the biological stability of soil organic matter to energy availability in deep tropical soil profiles, Soil Biology & Biochemistry (2015), http://dx.doi.org/10.1016/j.soilbio.2015.07.008

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soil pit/topographical position (representing field replication) was treated as a random effect nested within soil  forest type. Results of these ANOVA models can be found in the Supplemental Information. We also used Type II standard major axis (SMA) regression to explore relationships between biological and thermal indices of stability using the lmodel2 package (Legendre, 2013).

layers than at 140 cm depth. However, when normalized by soil C, basal respiration rates did not change with depth (Fig. 3b). When normalized to microbial biomass C, the basal respiration rate increased with depth (Fig. 3c, P ¼ 0.07).

3. Results

In each soil profile we examined, the size of the endothermic DSC region relative to the exothermic DSC region increased with depth, resulting in a total net endothermic energy content over the temperature range of interest in many deep soil samples (Fig. 4a, b). This was especially the case for clay-rich Oxisol samples (Fig. 4a), and much less so for quartz-rich Inceptisol samples (Fig. 4b). Endothermic, or energy-absorbing, regions of the thermogram are indicative of the dehydroxylation of mineral components, particularly kaolinite, while exothermic, or energy-releasing, regions indicate the combustion of organic matter. As the size of the exothermic peak in a thermogram diminishes, so does the energy microorganisms can acquire in a given soil. While it is the exothermic regions of the thermogram that most closely relate to the energy available to microorganisms upon SOM decomposition, endothermic and exothermic reactions can occur simultaneously, and deconvoluting them is a matter of ongoing research. In most Inceptisol samples, a sharp endothermic peak was also observed at 573  C (Fig. 4b), indicating the presence of quartz
ndez et al., 2012). An minerals undergoing an aeb transition (Ferna endothermic region was also sometimes observed around 275  C, possibly indicative of gibbsite (Karathanasis and Harris, 1994). CO2EGA curves revealed the majority of SOM combustion occurred between 200 and 400  C (Fig. 4c, d). CO2 evolution typically occurred over a broader temperature range in surface layers, while peaks became sharper with depth. In surface layers, a shoulder was sometimes visible in the CO2 curve between 350 and 500  C (Fig. 4c). In deeper soil layers, CO2-EGA data provided validation that exothermic reactions were due to SOM combustion (Fig. 4d), which was useful because in many cases the exothermic DSC peaks were only slightly above baseline, and could have been the result of baseline correction errors or integration errors. Across all soil  forest types, exothermic energy release during ramped combustion declined 96% with depth, from an average of

3.1. Biological stability of soil organic matter 3.1.1. Respiration rates over time Across all soil types and forest types, respiration rates in shallower layers (0 and 20 cm) declined exponentially over the 90-day incubation. Respiration rates in shallow layers were, on average, 30% greater in Oxisols than Inceptisols, and this difference was most pronounced early in the incubation (Fig. 1a, b). However, in deeper layers respiration rates generally did not change over time. In the deepest soil layer (140 cm), respiration rates declined 75% from the beginning to end of the incubation, although there was high variability in respiration rates at depth throughout the incubation, with standard deviations representing 50e120% of the mean (Fig. 1c). 3.1.2. Cumulative respiration and basal respiration rates Cumulative respiration was similar among the four soil and forest types. Across all soil and forest types, cumulative respiration declined exponentially with depth (Fig. 2a). The fraction of soil C respired declined more than 50% from the surface (1.42 ± 0.09%) to subsoils (80e140 cm, 0.57 ± 0.13%, Fig. 2b), with the exception of several high values in deep Tabonuco Inceptisols (Table 1, P ¼ 0.02 for soil  forest interaction). Normalized to microbial biomass C, increases in cumulative respiration with depth were not statistically significant due to large variability at depth, though a positive trend with depth could be observed (Fig. 2c). Basal respiration rates exhibited similar patterns. There was no statistically significant variation in the basal respiration rate among the four soil and forest types. Basal respiration rates declined exponentially with soil depth (Fig. 3a). Averaged across all soil and forest types, the basal respiration rate was 370% greater in surface

3.2. Thermal analysis of soils

Fig. 1. Respiration rate over time by soil type for 0, 20 and 140 cm depth increments. Data points represent mean respiration rates for each soil type at each day that a measurement was taken. Note the substantial differences in scale of the y-axes among the three panels.

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Fig. 2. Changes in cumulative C mineralization as a function of depth. Data points represent means across all soil and forest type combinations at each depth interval (n ¼ 10e12), and error bars represent standard errors of the mean. Panel a) reports mineralization on a per gram soil basis, panel b) reports the data on a per mg soil C basis, and panel c) reports on a per mg of microbial biomass C basis.

1814 mJ g1 soil in surface soil layers to 81 mJ g1 soil at 140 cm (Fig. 5a, P < 0.001), a pattern that reflects SOM quantities. Energy density declined 53% with depth, from an average of 23.9 J mg1 C in surface soil layers to 11.7 J mg1 C at 140 cm (Fig. 5b, P < 0.001). CO2-T50 values were high at the surface (364 ± 5  C) compared with all other depth intervals (20e140 cm, 341 ± 3  C, Fig. 5c, P ¼ 0.02).

Correlation analyses revealed strong relationships between the biological stability of SOM and its energy content (Fig. 6). Basal respiration rate was strongly correlated with exothermic energy content (R2 ¼ 0.75, P < 0.001) and energy density (R2 ¼ 0.58, P < 0.001) and weakly correlated with CO2-T50 (R2 ¼ 0.08, P ¼ 0.02). Normalized to soil C, correlations between basal respiration and thermal indices disappeared. Normalized to microbial biomass C,

Table 1 Cumulative respiration and basal respiration rates per gram soil, per mg soil C and per mg microbial biomass C. Values are reported as means of each soil  forest  depth combination ±1 standard error. Soil type

Forest type

Depth

n

Cumulative respiration

mg CO2eC g1 soil (CO2) Inceptisol

Colorado

Oxisol

Colorado

Inceptisol

Tabonuco

Oxisol

Tabonuco

0 20 50 80 110 140 0 20 50 80 110 140 0 20 50 80 110 140 0 20 50 80 110 140

2 3 3 3 3 3 2 3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 2

405.5 197.2 208.2 121.2 20.4 13.3 1290.4 716 219.2 90 20.2 3 1012.3 217.8 44.4 9.3 10.4 7.2 762.9 364.5 48.9 11.3 3.2 4.2

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

24.5 24.2 71 41.1 8.8 5.6 54.7 34.3 24.9 11.3 5.1 0.3 122 38.7 3 2.1 2.3 1.3 55.7 37 2.5 2.2 0.7 1.6

Basal respiration

mg CO2eC mg1

soil C (CO2eCsoil) 9.3 6.1 7 5.6 1.1 1.5 16.3 16.9 10 7.1 2.9 0.8 16 10.5 4 2.4 15.4 20.3 14.2 13.4 6 3.6 1.3 3.1

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

2.2 1.4 3.1 2.9 0.4 0.8 0.4 1.5 1.3 1.1 0.7 0.2 2.8 1.4 0.4 0.8 3.3 4.4 0.8 1.2 1.1 1 0.4 1.4

mg CO2eC mg1 microbial

biomass C (CO2eCmic) 7.6 8 10 6.1 12.9 17.5 11.6 9.1 11 15.5 16.1 64.1 8.3 5.6 3.5 2 16.4 26.1 10 8.7 6.5 6.5 4.9 5.8

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

1.6 0.7 4 3.2 13.8 19.4 0.6 0.6 2.4 1.8 2.9 61.1 0.9 0.7 0.7 0.9 7.2 23.4 0.9 1.2 1.6 3.1 2.5 2.8

mg g1 soil day1 2.2 1.4 1.5 1 0.4 0.1 6.7 2.6 1.3 0.9 0.5 0.1 6.4 1.5 0.4 0.1 0.2 0.1 4.8 1.8 0.5 0.1 0.1 0.1

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.19 0.05 0.44 0.23 0.18 0.04 0.32 0.26 0.13 0.17 0.15 0 0.99 0.2 0.05 0.02 0.01 0.01 0.22 0.34 0.04 0.03 0.01 0

mg mg1 soil C day1 0.05 0.05 0.05 0.04 0.02 0.03 0.09 0.06 0.06 0.08 0.08 0.02 0.1 0.08 0.04 0.03 0.25 0.29 0.09 0.07 0.07 0.04 0.04 0.05

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.01 0.01 0.02 0.02 0.01 0.03 0.01 0.01 0.01 0.02 0.02 0 0.01 0.01 0.01 0.01 0.05 0.04 0 0.01 0.01 0.02 0.01 0.01

mg mg1 Cmic day1 0.04 0.06 0.12 0.1 0.13 0.31 0.06 0.03 0.08 0.16 0.39 1.35 0.05 0.04 0.03 0.03 0.37 0.31 0.06 0.04 0.07 0.07 0.15 0.09

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.01 0.01 0.06 0.03 0.13 0.35 0.01 0.01 0.02 0.03 0.1 1.28 0.01 0 0.01 0.01 0.2 0.26 0.01 0.01 0.02 0.03 0.08 0.02

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Fig. 3. Changes in basal respiration as a function of depth. Data points represent means across all soil and forest type combinations at each depth interval (n ¼ 10e12), and error bars represent standard errors of the mean. Panel a) reports mineralization on a per gram soil basis, panel b) reports the data on a per mg soil C basis, and panel c) reports on a per mg of microbial biomass C basis.

there was a weak (R2 ¼ 0.18e0.19, P < 0.01) negative correlation of basal respiration with energy content and with energy density (Table S2). Regressions of cumulative CO2 against energy indices typically showed similar patterns, except correlations with thermal indices were still positive when normalized to soil C, and no trends were apparent when normalized to microbial C (Table S2). 4. Discussion In this study we sought to investigate how SOM stability changes with depth across two contrasting soil and forest types. We found no evidence for differences in the biological stability of SOM among the soil and forest types. The Oxisol and Inceptisol soils investigated in this study differ in terms of their texture and mineralogy; characteristics known to influence SOM stability (Wattel-Koekkoek et al., 2001; Eusterhues et al., 2003; Schmidt et al., 2011). The Fe oxide-coated clays prevalent in Oxisols are considered one of the primary stabilizing agents for tropical SOM (Kaiser and Guggenberger, 2000; Eusterhues et al., 2003; Dick et al., 2005). As expected given their larger clay contents, the Oxisols have significantly greater C concentrations (Stone and Plante, 2014). However, C stocks are similar due to the lower bulk density of the Oxisols (Johnson et al., submitted for publication), and microbial biomass and enzyme activities are also similar (Stone et al., 2014). By contrast, the Colorado forest soils have greater C concentrations and stocks than the Tabonuco forest soils, wider C:N ratios in SOM and litter (Johnson et al., submitted for publication), and greater potential activities of several C-degrading enzymes (Stone et al., 2014). While these observations might lead one to expect greater respiration rates in the Colorado forest, we found no differences. It is possible that differences in SOM quality across the two forests might act to depress decomposition in Colorado forest soils, despite larger C concentrations. Artificial laboratory conditions, including the

near-constant moisture regime and homogenization of soil prior to incubation, may limit our ability to observe differences in microbial activity (Salome et al., 2010), or the duration of our incubation experiment may not have been long enough to detect differences in biological stability of OM across the two forests (Plante et al., 2011). With consideration of these methodological limitations, our data suggest that differences in soil texture, mineralogy, and litter inputs were not significant drivers of the metabolic capacity of microorganisms in these forest soils. Rather, dramatic changes in microbial respiration with depth eclipsed any differences across the soil and forest types. 4.1. Biological stability and energetics of SOM with depth In surface mineral soils, we observed a rapid decline in respiration rates over the first 30 days of the incubation, suggesting the presence of a small pool of energy-rich C. However, this effect was not observed below 20 cm depth. It is likely the surface soil layers contain more energy-rich, plant-derived compounds, which may decline with depth in relation to microbially-derived compounds (Baldock and Skjemstad, 2000; Kramer and Gleixner, 2008; Spielvogel et al., 2008; Hassouna et al., 2010; Rumpel and KogelKnabner, 2011; Gabor et al., 2014). Microbial polysaccharides tend €gel-Knabner, 2002). to be nutrient-rich and less energy-dense (Ko Our finding that SOM energy density as estimated by DSC declines with depth is consistent with the hypothesis of a decrease in highenergy plant-derived compounds such as lignin, and a concurrent increase in microbial polysaccharides, which have a relatively high oxidation state. CO2-T50, which was high in surface layers, also supports the hypothesis of more energy-rich plant material at the surface. A larger CO2-T50 means higher temperatures are required for C-combustion, suggesting the presence of aromatic organic molecules of greater bond energies. The negative correlation between basal respiration rates per unit microbial C and energy

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Fig. 4. Differential scanning calorimetry (DSC) thermograms for depth profiles of (a) a representative Oxisol soil and (b) a representative Inceptisol soil, and comparisons of DSC thermograms (solid line) and CO2 evolved gas analysis (CO2-EGA) thermograms (dashed lines) for (c) an Oxisol sample from 110 cm soil depth, and (d) an Inceptisol sample from 20 cm soil depth.

density supports the notion that greater energy content, aromatic molecules are more thermodynamically challenging to decompose. Taken together, thermal analysis and respiration data both suggest that energy-dense plant material in surface layers contributes to rapid initial respiration rates, as has been demonstrated by other researchers (Kuzyakov et al., 2000, 2002). Conversely, the decreased energy density of deep SOM and diminished microbial respiration may be related to a lack of plant-derived C (Fontaine et al., 2007). As expected, we found that both cumulative CO2 evolution and basal respiration rates decreased exponentially with depth. Correlation analysis suggests declining energy availability is a primary driver of reduced metabolic activity with depth. To evaluate whether declines in respiration were due strictly to diminished concentrations of C and decomposer organisms, we focused our analysis on cumulative respiration and basal respiration rates normalized to both soil C concentrations and microbial biomass C. Examining specific respiration rates, we found that the metabolic potential of the microbial community remains high throughout soil profiles. Normalized to microbial biomass C, the total amount of C respired in surface layers and at 140 cm depth was similar. Other studies have found the specific metabolic capacity of subsoil microbial communities to be high (Fierer et al., 2003; Salome et al., 2010; Gelsomino and Azzellino, 2011; Kramer et al., 2013), and some authors have suggested that specific activity measurements

are more appropriate for assessing differences in microbial activity in soils with very different C concentrations (Trasar-Cepeda et al., 2008). A particularly interesting finding in our study was the trend towards increased basal respiration with depth when normalized to microbial biomass. High respiration rates per unit biomass are often considered an indicator of physiological stress, as stressed microbes can have higher maintenance energy demands (Allison et al., 2010). Greater physiological stress could be the result of numerous environmental challenges, including limited energy, oxygen or moisture availability, stronger association of organic molecules with minerals, or greater spatial separation between microbes and “resource hotspots” (Eilers et al., 2012; Hoehler and Jorgensen, 2013; Stone et al., 2014). Greater respiration rates per unit biomass may relate directly to the lower energy density of subsoil organic matter in that microbes may have to metabolize more C to acquire the same amount of energy. However, the trend toward increased C mineralization with depth should be interpreted with caution, for several reasons. First, there was high variability in specific respiration rates among samples, particularly at depth. A number of studies have found microbial biomass or activity to be more variable in subsoils compared with surface soil layers (Lomander et al., 1998; Tessier et al., 1998; Nunan et al., 2002; LaMontagne et al., 2003). In our system, this could be compounded by the inclusion of three topographic positions as field replicates, as this factor is known to strongly influence C concentrations and

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Fig. 5. Changes in thermal indices as a function of soil depth. Data points represent means across all soil and forest type combinations at each depth interval (n ¼ 10e12), and error bars represent standard errors of the mean.

biogeochemical nutrient cycles in this study site (Silver et al., 1999; Johnson et al., 2011). In addition, small amounts of measurement uncertainty in surface layers can have proportionally larger effects on C and biomass measurements in subsoils. Secondly, artificial laboratory conditions including the disruption of soil structure and the maintenance of oxic conditions throughout the incubation may increase C mineralization in subsoils but not surface soils (Xiang et al., 2008; Salome et al., 2010). Finally, abiotic decarboxylation

reactions are not typically considered an important source of mineralized C, but the importance of this process could be amplified in low-biomass subsoils (Blankinship et al., 2014). The stability of deep soil C remains a matter of significant debate. The classical model of organic matter stability describes soil C as becoming more chemically refractory as it ages and is processed by the microbial community, until eventually, the thermodynamics of its decomposition become unfavorable. If this were the

Fig. 6. Relationships between long-transformed basal respiration and three thermal indices: a) exothermic energy (log mJ mg1 soil), b) energy density (J mg1 soil), c) CO2-T50 ( C). Standard major axis regression equation with R2 value is written on each graph.

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case, then subsoil C would be more stable than surface C in nearly all instances, simply by virtue of its chemical nature, except in specific soil types where organic matter is transported to depth rapidly, such as soils containing large quantities of shrink-swell clays (Marin-Spiotta et al., 2011). However, there is an emerging consensus that the long-term persistence of SOM is based on a host of biological, climactic and geologic factors, rather than its chemical composition (Schmidt et al., 2011). Thus, predicting changes in C stability as a function of depth may require a more nuanced view of the changing soil environment as a function of depth, taking into account changes in soil temperature, texture, moisture, and other physiochemical factors. Our study underscores another important consideration with regards to deep soil C stability: separating the metrics used to infer stability from changes in the quantity of decomposers and substrates. We find that the decline in microbial activity with depth reflects different abundances of microbes between surface and subsoils, and the biological stability of SOM when accounting for differences in biomass is similar throughout soil profiles. In this particular tropical soil environment, then, deep SOM, while present in low concentrations, may be as prone to microbial decomposition as surface SOM. We suggest that future researchers should always look at specific activities to determine whether an apparent increase in stability is driven by proportional declines in substrates and microorganisms. 5. Conclusions Our study presents a new framework for understanding the biological stability of soil C by relating metabolic capacity to the energy content of SOM. By coupling a physiological measurement with thermal analysis, we can make inferences about the quality of SOM as an energy source for microorganisms, and about the principal drivers of microbial C metabolism. Taken together, the patterns in total microbial activity and energy availability with soil depth point to energy starvation as the primary driver of diminished subsoil microbial activity. Energy starvation can produce stressful environments where microbes expend more energy to acquire less, leading to high specific respiration rates. From a biogeochemical perspective, high specific C mineralization in subsoils suggests that the decomposability of SOM does not change significantly soil depth. We found no evidence for greater stability of deep SOM compared with surface SOM in the fractions that were respired. Rather, we found evidence for microbial resilience and capacity to mineralize whatever C substrates exist. Acknowledgements The authors wish to thank the staff of the Sabana and El Verde field stations, the USDA Forest Service International Institute of Tropical Forestry, and the Luquillo LTER for logistical support, and Xing Hao and Sebastian Rowland for assistance with sample collection. This work was completed under the NSF-funded Luquillo Critical Zone Observatory (LCZO; EAR-0722476) research program and was also supported by an NSF Graduate Research Fellowship to MMS. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.soilbio.2015.07.008.

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