Soil particle accumulation in termite (Macrotermes bellicosus) mounds and the implications for soil particle dynamics in a tropical savanna Ultisol

This study investigated the influence of mound-building termites on soil particle dynamics on the land surface and in soil-forming processes by examining the amount of soil particles in mound structures of Macrotermes bellicosus in a highly weathered Ultisol of tropical savanna. Soil particle turnover via the mounds was estimated using particle stock data and soil turnover data from previous studies. A 4-ha study plot with six mounds of relatively uniform shape and size was investigated. Soil mass constituting the mounds was 6,166 ± 1,581 kg mound⁻¹ within which the mound wall and nest body accounted for 5,002 ± 1,289 and 1,164 ± 293 kg, respectively. The mound wall contained a significantly larger amount of clay (252 ± 9.97 g kg⁻¹) balanced with a lower sand content (676 ± 26.5 g kg⁻¹) than in the adjacent surface (Ap1) horizon, (46.4 ± 12.8 g clay kg⁻¹; 866 ± 83.2 g sand kg⁻¹); the nest body had much higher clay content (559 ± 51.0 g kg⁻¹) but less sand (285 ± 79.2 g kg⁻¹) than the mound wall. As a result, the mounds of M. bellicosus accumulated clay of 2,874 ± 781 kg ha⁻¹ (corresponding to 2.52% of clay stock in the Ap1 horizon) along with an estimated clay turnover rate of 169 kg ha⁻¹ year⁻¹. These findings suggest a positive feedback effect from termite mound-building activity on soil particle dynamics in tropical savanna ecosystems: M. bellicosus preferentially use subsoil material for mound construction, resulting in relocation of illuvial clay in the subsoil to the land surface where clay eluviation from the surface soil and its illuviation in the subsoil are major soil-forming processes.     

Prediction of soil carbon levels in calcareous soils of Iran by mid-infrared reflectance spectroscopy

The objective of this study was to assess the predictive performance of midDRIFTS-PLSR models in quantifying total carbon (TC), total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), hot water extractable carbon and nitrogen (C_HWE, N_HWE), pH, and the clay, silt, and sand content of soils. A total of 68 soil samples were taken across an agroecological region in southwest Iran, and analyzed in the laboratory using mid-DRIFTS-PLSR. midDRIFTS-PLSR calibration models were developed, and external validation was performed for each of the soil properties via an independent algorithm. The calibration and validation models allowed for a sufficient prediction of TC, TIC, and TOC with residual prediction deviations ≥3 and R² values >0.9. The precise prediction ofcarbon fractions, such as TC, TIC, and TOC, in a rapid and inexpensive manner confirmed that midDRIFTS analysis was a rapid-throughput and cost-effective technique for monitoring soil carbon at the regional scale.     

Quantifying the effects of switchgrass (Panicum virgatum) on deep organic C stocks using natural abundance 14C in three marginal soils

Perennial bioenergy crops have been shown to increase soil organic carbon (SOC) stocks, potentially offsetting anthropogenic C emissions. The effects of perennial bioenergy crops on SOC are typically assessed at shallow depths (<30 cm), but the deep root systems of these crops may also have substantial effects on SOC stocks at greater depths. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow‐rooted conventional crop cover. To test this, we sampled soils to between 1‐ and 3‐m depth at three sites in Oklahoma with 10‐ to 20‐year‐old switchgrass (Panicum virgatum) stands, and collected paired samples from nearby fields cultivated with shallow rooted annual crops. We measured root biomass, total organic C, ¹⁴C, ¹³C, and other soil properties in three replicate soil cores in each field and used a mixing model to estimate the proportion of recently fixed C under switchgrass based on ¹⁴C. The subsoil C stock under switchgrass (defined over 500–1500 kg/m² equivalent soil mass, approximately 30–100 cm depth) exceeded the subsoil stock in neighboring fields by 1.5 kg C/m² at a sandy loam site, 0.6 kg C/m² at a site with loam soils, and showed no significant difference at a third site with clay soils. Using the mixing model, we estimated that additional SOC introduced after switchgrass cultivation comprised 31% of the subsoil C stock at the sandy loam site, 22% at the loam site, and 0% at the clay site. These results suggest that switchgrass can contribute significantly to subsoil organic C—but also indicated that this effect varies across sites. Our analysis shows that agricultural strategies that emphasize deep‐rooted grass cultivars can increase soil C relative to conventional crops while expanding energy biomass production on marginal lands.     

Sensitivity of soil carbon fractions and their specific stabilization mechanisms to extreme soil warming in a subarctic grassland

Terrestrial carbon cycle feedbacks to global warming are major uncertainties in climate models. For in‐depth understanding of changes in soil organic carbon (SOC) after soil warming, long‐term responses of SOC stabilization mechanisms such as aggregation, organo‐mineral interactions and chemical recalcitrance need to be addressed. This study investigated the effect of 6 years of geothermal soil warming on different SOC fractions in an unmanaged grassland in Iceland. Along an extreme warming gradient of +0 to ~+40 °C, we isolated five fractions of SOC that varied conceptually in turnover rate from active to passive in the following order: particulate organic matter (POM), dissolved organic carbon (DOC), SOC in sand and stable aggregates (SA), SOC in silt and clay (SC‐rSOC) and resistant SOC (rSOC). Soil warming of 0.6 °C increased bulk SOC by 22 ± 43% (0–10 cm soil layer) and 27 ± 54% (20–30 cm), while further warming led to exponential SOC depletion of up to 79 ± 14% (0–10 cm) and 74 ± 8% (20–30) in the most warmed plots (~+40 °C). Only the SA fraction was more sensitive than the bulk soil, with 93 ± 6% (0–10 cm) and 86 ± 13% (20–30 cm) SOC losses and the highest relative enrichment in ¹³C as an indicator for the degree of decomposition (+1.6 ± 1.5‰ in 0–10 cm and +1.3 ± 0.8‰ in 20–30 cm). The SA fraction mass also declined along the warming gradient, while the SC fraction mass increased. This was explained by deactivation of aggregate‐binding mechanisms. There was no difference between the responses of SC‐rSOC (slow‐cycling) and rSOC (passive) to warming, and ¹³C enrichment in rSOC was equal to that in bulk soil. We concluded that the sensitivity of SOC to warming was not a function of age or chemical recalcitrance, but triggered by changes in biophysical stabilization mechanisms, such as aggregation.     

Comparison of Soil VOCs measured by soil gas,heated headspace,and methanol extraction techniques

Comparisons of soil volatile organic compound (VOC) measurement techniques and soil properties expected to influence these measurements were performed at two dissimilar sites. A total of 41 soil gas, 52 heated headspace, and 51 methanol extraction/purge‐and‐trap measurements were obtained on collocated samples. Contaminants present at both sites included cis‐1,2‐dichloroethene, 1, 1, 1‐trichloroethane, trichloroethene, and tetrachloroethene. Heated headspace offered the highest sensitivity, as indicated by the greatest percentage of detections per number of analyses. The statistical regression between headspace concentrations and methanol extraction concentrations was highly significant (p < 0.001) with r² = 0.53. Headspace concentrations (range, 7 to 4250 ng/g) ran approximately 20 to 30% of the methanol extraction concentrations (range, 260 to 7300 ng/g), indicating that the methanol was able to extract significantly more of the chlorinated hydrocarbons (CHCs) than the headspace extraction, even in soils with relatively low organic carbon contents (< 0.25%). None of the soil properties (gravimetric moisture content, organic carbon content, percent sand, and percent clay) significantly improved the regression fit. The soil gas responses were unlike either headspace or methanol extraction data. CHC measurements by vapor extraction/soil gas could not be used to predict soil CHC concentrations at these sites.     

Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties

It is becoming increasingly important to improve spatial resolutions of soil maps as a fundamental information layer for studying ecological processes and to tackle land degradation. There is growing interest in the use of remote sensing technologies to assist the identification and delineation of spatial variation in soils. This paper investigates whether selected properties of extensively weathered, low fertility soils can be predicted using high-resolution reflectance spectra over the range 400–2500 nm. Clay content, carbonate concentration, organic carbon content and iron oxide content were analysed for 300 soil samples collected from the Jamestown, Belalie district, South Australia. The paper also examines the efficacy of this soil analysis methodology to supplement or replace traditional soil sampling in soil survey to increase sampling density and improve the spatial resolution of soil maps.Reflectance spectra were obtained from air-dried samples under controlled laboratory conditions using an ASD FieldSpec Pro spectroradiometer. Partial least squares regression was used to examine relationships between soil mineralogy, clay content and organic carbon and the reflectance spectra and identify the wavelengths contributing to prediction of these soil properties. Results show that it is possible to predict clay content, soil organic carbon, iron oxide content and carbonate content. Cross-validation R² values for all analyses were above 0.5 and the residual prediction difference (RPD) was acceptable for all soil properties. Carbonate and clay content were more accurately predicted than iron oxide and organic carbon. All samples were collected from the same geographical area such that they represented physical properties over a naturally occurring range and provide a prediction that could be related to subsequent image analysis or be used to carry out local scale soil survey. A rapid and reliable form of soil mapping could be developed from this methodology.     

Interactive global change factors mitigate soil aggregation and carbon change in a semi‐arid grassland

The ongoing global change is multi‐faceted, but the interactive effects of multiple drivers on the persistence of soil carbon (C) are poorly understood. We examined the effects of warming, reactive nitrogen (N) inputs (12 g N m^?2 year^?1) and altered precipitation (+ or ? 30% ambient) on soil aggregates and mineral‐associated C in a 4 year manipulation experiment with a semi‐arid grassland on China's Loess Plateau. Our results showed that in the absence of N inputs, precipitation additions significantly enhanced soil aggregation and promoted the coupling between aggregation and both soil fungal biomass and exchangeable Mg²⁺. However, N inputs negated the promotional effects of increased precipitation, mainly through suppressing fungal growth and altering soil pH and clay‐Mg²⁺‐OC bridging. Warming increased C content in the mineral‐associated fraction, likely by increasing inputs of root‐derived C, and reducing turnover of existing mineral‐associated C due to suppression of fungal growth and soil respiration. Together, our results provide new insights into the potential mechanisms through which multiple global change factors control soil C persistence in arid and semi‐arid grasslands. These findings suggest that the interactive effects among global change factors should be incorporated to predict the soil C dynamics under future global change scenarios.     

Modeling the distribution of a wide‐ranging invasive species using the sampling efforts of expert and citizen scientists

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Sampling volume in root studies: the pitfalls of under‐sampling exposed using accumulation curves

Root systems are important for global models of below‐ground carbon and nutrient cycling. Notoriously difficult sampling methods and the fractal distribution of root diameters in the soil make data being used in these models especially susceptible to error resulting from under‐sampling. We applied the concept of species accumulation curves to root data to quantify the extent of under‐sampling inherent to minirhizotron and soil coring sampling for both root uptake and carbon content studies. Based on differences in sample size alone, minirhizotron sampling missed approximately one third of the root diameters observed by soil core sampling. Sample volumes needed to encounter 90% of root diameters averaged 2481 cm³ for uptake studies and 5878 cm³ for root carbon content studies. These results show that small sample volumes encounter a non‐representative sample of the overall root pool, and provide future guidelines for determining optimal sample volumes in root studies.     

Using functional traits to predict species growth trajectories,and cross‐validation to evaluate these models for ecological prediction

Modeling plant growth using functional traits is important for understanding the mechanisms that underpin growth and for predicting new situations. We use three data sets on plant height over time and two validation methods—in‐sample model fit and leave‐one‐species‐out cross‐validation—to evaluate non‐linear growth model predictive performance based on functional traits. In‐sample measures of model fit differed substantially from out‐of‐sample model predictive performance; the best fitting models were rarely the best predictive models. Careful selection of predictor variables reduced the bias in parameter estimates, and there was no single best model across our three data sets. Testing and comparing multiple model forms is important. We developed an R package with a formula interface for straightforward fitting and validation of hierarchical, non‐linear growth models. Our intent is to encourage thorough testing of multiple growth model forms and an increased emphasis on assessing model fit relative to a model's purpose.     

Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis–NIR Spectroscopy

Assessment and monitoring of soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural soils. Visible and near-infrared (Vis–NIR) diffuse reflectance spectroscopy (350–2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of soil properties from Vis–NIR spectra, a spectral library representing the local soil diversity needs to be constructed. The study area, covering a surface of 927 km² and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different soil parent materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topsoil (0–20 cm) samples were collected for SOM analysis and scanned with a Vis–NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to parent materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23–4.69 g kg⁻¹; R² (coefficient of determination) = 0.80–0.84; RPD (ratio of standard deviation to RMSE) = 2.19–2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88–3.08). Under the local calibrations, the individual PLSR models for each parent material improved SOM predictions (RMSE = 2.55–3.49 g kg⁻¹; R² = 0.87–0.93; RPD = 2.67–3.12; RPIQ = 3.15–4.02). Among the four different parent materials, the largest R² and the smallest RMSE were observed for the shale soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis–NIR spectroscopy.     

Changes in soil organic carbon under perennial crops

This study evaluates the dynamics of soil organic carbon (SOC) under perennial crops across the globe. It quantifies the effect of change from annual to perennial crops and the subsequent temporal changes in SOC stocks during the perennial crop cycle. It also presents an empirical model to estimate changes in the SOC content under crops as a function of time, land use, and site characteristics. We used a harmonized global dataset containing paired‐comparison empirical values of SOC and different types of perennial crops (perennial grasses, palms, and woody plants) with different end uses: bioenergy, food, other bio‐products, and short rotation coppice. Salient outcomes include: a 20‐year period encompassing a change from annual to perennial crops led to an average 20% increase in SOC at 0–30 cm (6.0 ± 4.6 Mg/ha gain) and a total 10% increase over the 0–100 cm soil profile (5.7 ± 10.9 Mg/ha). A change from natural pasture to perennial crop decreased SOC stocks by 1% over 0–30 cm (?2.5 ± 4.2 Mg/ha) and 10% over 0–100 cm (?13.6 ± 8.9 Mg/ha). The effect of a land use change from forest to perennial crops did not show significant impacts, probably due to the limited number of plots; but the data indicated that while a 2% increase in SOC was observed at 0–30 cm (16.81 ± 55.1 Mg/ha), a decrease in 24% was observed at 30–100 cm (?40.1 ± 16.8 Mg/ha). Perennial crops generally accumulate SOC through time, especially woody crops; and temperature was the main driver explaining differences in SOC dynamics, followed by crop age, soil bulk density, clay content, and depth. We present empirical evidence showing that the FAO perennialization strategy is reasonable, underscoring the role of perennial crops as a useful component of climate change mitigation strategies.     

Deep soil flipping increases carbon stocks of New Zealand grasslands

Sequestration of soil organic carbon (SOC) has been recognized as an opportunity to off‐set global carbon dioxide (CO₂) emissions. Flipping (full inversion to 1–3 m) is a practice used on New Zealand's South Island West Coast to eliminate water‐logging in highly podzolized sandy soils. Flipping results in burial of SOC formed in surface soil horizons into the subsoil and the transfer of subsoil material low in SOC to the “new” topsoil. The aims of this study were to quantify changes in the storage and stability of SOC over a 20‐year period following flipping of high‐productive pasture grassland. Topsoils (0–30 cm) from sites representing a chronosequence of flipping (3–20 years old) were sampled (2005/07) and re‐sampled (2017) to assess changes in topsoil carbon stocks. Deeper samples (30–150 cm) were also collected (2017) to evaluate the changes in stocks of SOC previously buried by flipping. Density fractionation was used to determine SOC stability in recent and buried topsoils. Total SOC stocks (0–150 cm) increased significantly by 69 ± 15% (179 ± 40 Mg SOC ha^‐1) over 20 years following flipping. Topsoil burial caused a one‐time sequestration of 160 ± 14 Mg SOC ha^‐1 (30–150 cm). The top 0–30 cm accumulated 3.6 Mg SOC ha^‐1 year^‐1. The chronosequence and re‐sampling revealed SOC accumulation rates of 1.2–1.8 Mg SOC ha^‐1 year^‐1 in the new surface soil (0–15 cm) and a SOC deficit of 36 ± 5% after 20 years. Flipped subsoils contained up to 32% labile SOC (compared to <1% in un‐flipped subsoils) thus buried SOC was preserved. This study confirms that burial of SOC and the exposure of SOC depleted subsoil results in an overall increase of SOC stocks of the whole soil profile and long‐term SOC preservation.     

The sources and distribution of carbon (DOC,POC, DIC) in a mangrove dominated estuary (French Guiana,South America)

Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO₂ to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.     

Rare earth elements and relation between their potential bioavailability and soil properties, Nidda catchment (Central Germany)

Rare earth elements (REEs) are widely used in industry and the entry of REEs into the pedosphere is assumed. Data about REEs in soils are scarce since only a few studies discuss their ecologically relevant behavior. Hence, we investigated total contents (aqua regia digestion) and potentially bioavailable contents (EDTA extraction) of REEs in soils from the Nidda catchment in Hesse (Central Germany). The study site covers a 1,600 km² sized area and 232 soil samples from 63 soil profiles were examined. The total REE content varied considerably, ranging from 544 mg kg^?1 to 41 mg kg^?1 (mean 201.1 mg kg^?1) with a high proportion of light REEs. Highest REE contents were found in the soilscape VB, followed by LVB, WNE, T, WSW and BF with the smallest concentrations. With respect to the parent material the contents decreased in the following order: basalt > clay slate > loess > sandstone. On average 15.9% of the total REEs belong to the potentially bioavailable fraction. They range greatly by a factor of 100, between 1.3 and 171.3 mg kg^?1 (average 33.5 mg kg^?1). Remarkably, Yttrium has a maximum available proportion of 75%. In contrast, Ce showed the highest total contents with the smallest potentially bioavailable proportion of all elements. Regression analyses established relation between soil properties and the potential bioavailability of REEs. Around 53% (range from 29.9 to 76.8%) of the REE’s potential bioavailability variations could be explained by the chosen variables (pH, clay and C_org contents and the total element concentrations). Occurrence patterns and concentrations of REEs lie within the range of the results found in the available literature. Bioavailability is linked to soil properties and varies greatly according to the individual element. In comparison with the chosen soil properties the pH value shows the least impact on bioavailability.     

Multiple Environmental Controls on Cockroach Assemblage Structure in a Tropical Rain Forest

Arthropod abundance and diversity are remarkable in tropical forests, but are also spatially patchy. This has been attributed either to resources, predators, abiotic conditions or disturbances, but whether such factors may simultaneously shape arthropod assemblage structure is little known. We used cockroaches to test for multiple environmental controls on assemblage structure in 25 km² of Amazonian forest. We performed nocturnal, direct searches for cockroaches in 30 plots (250 m × 2 m) during two seasons, and gathered data on biotic and abiotic factors from previous studies. Cockroach abundance increased with dry litter mass, a measure of resource amount, while species richness increased with litter phosphorus content, a measure of resource availability. Cockroach abundance and species richness decreased with ant relative abundance. Cockroach species composition changed along the gradient of: (1) soil clay content, which correlates with a broad differentiation between flood‐prone and non‐flooded forest; (2) soil relative moisture, consistent with known interspecific variation in desiccation tolerance; and (3) according to the abundance of ants, a potential predator. Turnover in species composition was correlated with abiotic conditions—sorting species according to physiological requirements and to disturbance‐related life history traits—and to ants' selective pressure. Cockroach abundance, diversity, and composition seem to be controlled by distinct sets of environmental factors, but predators which were represented by ants, emerged as a common factor underlying cockroach distribution. Such patterns of community structure may have been previously overlooked by undue focus on single or a few factors, and may be common to tropical forest arthropods.     

Driving forces of soil organic carbon evolution at the landscape and regional scale using data from a stratified soil monitoring

Soil monitoring programmes face significant challenges as there is an important trade‐off between detecting significant changes in soil properties on the one hand (which can be achieved by minimizing variability by higher sampling density or stratification approaches), and identifying the driving forces responsible for these changes on the other hand (which requires enough variability). This study aims to reconcile these two objectives by identifying the driving forces of soil organic carbon (SOC) evolution over a long period, based on an extensive but stratified soil monitoring programme. Data at both the finest level (questionnaires to the farmers) and the large scale (agricultural census, climate and soil databases for southern Belgium) were used in a cluster analysis, multiple linear regressions and mixed odels in order to discriminate between the driving forces involved. Results indicated that the negative ‘baseline effect’ (i.e. the inversely proportional effect of the initial SOC content on the SOC evolution) was responsible for an important part of the SOC variability. Consequently, the systems are not at steady state when starting the observations, although this assumption is used by most SOC dynamic models. Moreover, the baseline effect resulted in a trend of the soils to converge towards a regional SOC stock which significantly differed according to land use (36.4 t C ha^?1 for the plough depth of cropland and 92.2 t C ha^?1 for the 0–30 cm layer of grassland). Despite this strong effect, the main driving forces of the SOC decrease of cropland (?0.2 t C ha^?1 yr^?1) and SOC increase of grassland (+0.2 t C ha^?1 yr^?1) over a period of 50 years were discriminated. The agricultural management (cropland) and the clay content (grassland), together with the change in precipitation (to a lesser degree for cropland) were highlighted as the predominant factors involved in SOC evolution, when land use change is excluded. The use of questionnaires allowed to better understanding the impact of an intensive agricultural management on the SOC content, as the lowest SOC stocks were associated to the most intensively managed fields. The mixed models partly succeeded in predicting SOC evolution as they presented still large uncertainties after validation (mean error from 3% to 25%, root mean square error of prediction from 21% to 242%). While SOC monitoring schemes are increasingly being implemented, our results will likely apply to those using a similar design. It was shown that this strategy succeeded to reconcile both the SOC change detection and the distinction of the driving forces involved at the regional scale.     

Fine root dynamics and trace gas fluxes in two lowland tropical forest soils

Fine root dynamics have the potential to contribute significantly to ecosystem‐scale biogeochemical cycling, including the production and emission of greenhouse gases. This is particularly true in tropical forests which are often characterized as having large fine root biomass and rapid rates of root production and decomposition. We examined patterns in fine root dynamics on two soil types in a lowland moist Amazonian forest, and determined the effect of root decay on rates of C and N trace gas fluxes. Root production averaged 229 (±35) and 153 (±27) g m^?2 yr^?1 for years 1 and 2 of the study, respectively, and did not vary significantly with soil texture. Root decay was sensitive to soil texture with faster rates in the clay soil (k=?0.96 year^?1) than in the sandy loam soil (k=?0.61 year^?1), leading to greater standing stocks of dead roots in the sandy loam. Rates of nitrous oxide (N₂O) emissions were significantly greater in the clay soil (13±1 ng N cm^?2 h^?1) than in the sandy loam (1.4±0.2 ng N cm^?2 h^?1). Root mortality and decay following trenching doubled rates of N₂O emissions in the clay and tripled them in sandy loam over a 1‐year period. Trenching also increased nitric oxide fluxes, which were greater in the sandy loam than in the clay. We used trenching (clay only) and a mass balance approach to estimate the root contribution to soil respiration. In clay soil root respiration was 264–380 g C m^?2 yr^?1, accounting for 24% to 35% of the total soil CO₂ efflux. Estimates were similar using both approaches. In sandy loam, root respiration rates were slightly higher and more variable (521±206 g C m² yr^?1) and contributed 35% of the total soil respiration. Our results show that soil heterotrophs strongly dominate soil respiration in this forest, regardless of soil texture. Our results also suggest that fine root mortality and decomposition associated with disturbance and land‐use change can contribute significantly to increased rates of nitrogen trace gas emissions.