Non-growing Season Research Articles

Comparison of Root Ecological Stoichiometry between Non-Growing Season and Growing Season of Grassland on the Chang Tang Plateau.

Root C: N: P stoichiometry affect the geochemical cycles of ecosystems, while a few studies were conducted on it and its relationship with soil nutrients, especially in the non-growing season. In this study, we investigated the root C:N:P stoichiometry of alpine steppe(AS), alpine meadow steppe(AMS), and alpine meadow(AM) in April (non-growing season) and August(growing season) in 2013. The results showed that: (1) There were no differences in root C, N, P, C: N, C:P, and N:P with a depth of AS in April. However, root C and C: N increased with depth, while N and N:P decreased with a depth of AS in August. In both months, the variation of root C, N, P, C: N with depth in AM was consistent with that of AS in August, and root C at deep layer decreased in August, which indicated roots of AM began to grow in April No significant difference of root C, N, C: N and N:P with depth was found, while P and C:P varied between the two months of AMS. Root P content at 20-30 cm was higher than that of other soil layers in April, which was significantly higher than that of AS, while no significant difference was found in August. (2) Grassland types had significant effects on soil nutrients (except TP) at 0-10 cm and 20-30 cm soil layers. (3) No significant correlation between soil nutrients and root C, N, P, C: N, C: P, and N: P was found in April. Soil TN and AN content had a significant positive correlation with root N: P, indicating that soil nitrogen was the primary N source of the root. Soil TP and AP were significantly negatively correlated with root C and C: N in August. This study can provide basic data and provide theoretical support for further understanding the role of grassland roots in nutrient cycling.

Characteristics of Evapotranspiration and Crop Coefficient Correction at a Permafrost Swamp Meadow in Dongkemadi Watershed, the Source of Yangtze River in Interior Qinghai–Tibet Plateau

The Qinghai–Tibet Plateau (QTP), known as the Earth’s third pole, is highly sensitive to climate change. Various environmental degradation has occurred due to the effects of climate warming such as the degradation of permafrost and the thickening of active layers. Evapotranspiration, as a key element of hydrothermal coupling, has become a key factor of the plateau environment for deciphering deterioration, and the FAO P-M model has a good physical foundation and simple model data requirements as a primary tool to study the plateau evapotranspiration. There has been a large research base, but the estimation of evapotranspiration in alpine regions is still subject to many uncertainties. This is reflected in the fact that the classification of underlying surface types has not been sufficiently detailed and the evapotranspiration characteristics of some special underlying surface types are still unclear. Therefore, in this work, we modified the FAO P-M coefficients based on the characteristics of actual evapotranspiration measured by the Eddy covariance system and the key influencing factors to better simulate the actual evapotranspiration in alpine swamp meadow. The results were as follows: (1) Both ETa measured by the Eddy covariance system and ET0 calculated by FAO P-M showed the same trend at the daily and annual scales and hysteresis was confirmed to exist, so the error caused by hysteresis should be considered in further research. (2) The annual ETa was 566.97 mm and annual ETa/P was 0.76, and about 11.19% of ETa occurred during the night. The ETa was 2.15 during the non-growing seasons, implying that a large amount of soil water was released into the air by evapotranspiration. (3) The evapotranspiration characteristics of alpine swamp meadow are formed under the following conditions: control of net radiation (Rn) affected by VPD during the growing season and affected by soil temperature and humidity during the non-growing season. Precipitation and soil water content are no longer the main controlling factors of evapotranspiration during the growing season at the alpine swamp meadow as the volume soil water content tends to saturate. (4) The basic corrected Kc was 1.14 during the initial and mid-growing season, 1.05 during the subsequent growing season, and 0–0.25 during the non-growing season, and the correction factor process can also provide ideas for correcting the Kc of other vegetation.

Abnormal Litter Induced by Typhoon Disturbances Had Higher Rates of Mass Loss and Carbon Release than Physiological Litter in Coastal Subtropical Urban Forest Ecosystems

The decomposition of abnormal litter caused by extreme weather events might play an increasingly important role in carbon and nutrient cycling in forest ecosystems under climate change scenarios, which needs to be fully investigated. In August 2020, the abnormal foliar litter of the goldenrain tree (Koelreuteria bipinnata var. Integrifoliola), the camphor tree (Cinnamomum camphora), and the weeping willow (Salix babylonica) after Typhoon Hagupit disturbance were collected and incubated on the soil surface at the Plant Ecology Research Base at Taizhou University, which is located on the eastern coast of China. Simultaneously, the physiological foliar litter of these three trees collected in the spring litter peak was incubated at the same site. The abnormal litter had higher concentrations of carbon (C), nitrogen (N), and phosphorus (P) and lower concentrations of lignin and cellulose than the physiological litter. The accumulative mass loss rates of abnormal litter in the goldenrain tree, the camphor tree, and the weeping willow during the incubation period increased by 7.72%, 29.78%, and 21.76% in comparison with physiological litter, and the corresponding carbon release increased by 9.10%, 24.15% and 19.55%, respectively. The autumn litter peak period and plum-rain season had higher rates of litter mass loss and carbon release, while the winter nongrowing season had lower rates. Accumulative mass loss, accumulative carbon release, daily mass loss and the daily carbon release of foliar litter were significantly and positively correlated with temperature and initial P concentrations, and significantly and negatively correlated with the initial C/P ratio, lignin/N ratio, and lignin/P ratio (p < 0.05). Compared with the physiological litter, abnormal litter had higher initial substrate quality, which may be the most important factor contributing to their high rates of mass loss and carbon release. The results imply that increasing tropical cyclones under climate change scenarios will facilitate carbon cycling in coastal urban forest ecosystems.

Monthly mowing frequency does not affect soil CO2 emissions of fertilized Bromus erectus‐dominated grasslands

AbstractSecondary origin grasslands are widespread habitats that provide a wide array of ecosystem services. Their conservation relies on management practices that can, in turn, alter their soil carbon cycle to result in higher soil respiration rates. In the perspective of social and climate change scenarios, there is the need to seek the best management practices for conservation of secondary origin grasslands, climate mitigation and economic sustainability for farmers. The aim of this study was to investigate whether increasing the customary practice of mowing twice a year to monthly mowing through the growing season (when herbage production was feasible; i.e., >0.5 t/ha dry matter) generates changes to the drivers and rates of soil respiration of fertilized Bromus erectus‐dominated grasslands. Soil CO2 efflux, temperature and moisture were recorded over 3 years (2016–2018) under these “customary” and “monthly” mowing frequencies (twice per year; 4–6 times per year, respectively). Soil CO2 efflux, temperature and moisture were not affected by the higher mowing frequency over the study period. Independent of mowing frequency, soil water content was the main driver of soil CO2 emissions during the growing season (April to October, inclusive), whereas soil temperature was the main driver during the nongrowing season (November to March, inclusive). Therefore, increasing the customary mowing of twice a year to the monthly mowing frequency through the growing season does not impact upon soil respiration of B. erectus‐dominated grasslands, at least over a 3‐year period.

Soil C/N ratio is the dominant control of annual N2O fluxes from organic soils of natural and semi-natural ecosystems

Globally, organic soils of natural and semi-natural ecosystems have been considered as an important source of atmospheric nitrous oxide (N2O), a powerful greenhouse gas. However, we have little understanding of how and to what extent the magnitude of N2O emissions from such soils is mediated by variation in environmental controls. This knowledge is critical for scaling up the results of measurements from local to regional or global scales. Here we report on two-year field measurements of N2O fluxes from various alpine land use/cover types at 24 sites across an altitudinal gradient in a catchment on the eastern Tibetan Plateau. We found that annual N2O emissions varied between 0.05 and 1.39 kg N ha−1 yr−1, with non-growing season contributing 11–60% to these annual budgets. Our field results, together with published data from 43 studies on organic soils globally (natural and semi-natural ecosystems) showed that across all datasets, annual N2O fluxes were more closely related to the soil C/N ratio. Weaker relationships were found to the mean water table depth (WTD) and soil total N content. In contrast to the general assumption that soil N2O emissions may consistently increase with a narrowing of the organic soil C/N ratio, we found strong indications that the relationship of annual N2O fluxes to soil C/N ratio followed an optimum Gaussian curve, with a threshold at a C/N ratio of about 18–19. Moreover, there was a tendency towards high N2O emissions for sites with a mean annual WTD > 0.15 m, indicating a potential risk for increased N2O emissions from global organic soils under water table drawdown driven by climate drying or peatland drainage. Overall, our results suggest that the soil C/N ratio could be used as an indicator to better constrain the contribution of organic soils to N2O emissions from landscape at global scales.

Drought timing and severity affect radial growth of Picea crassifolia at different elevations in the western Qilian Mountains.

In the context of continued global climate change, the intensity and frequency of droughts have increased to varying degrees in many places. Due to the complexity of drought events, the mechanisms by which trees respond to drought are not well understood. In this study, we analyzed the growth trends of Qinghai spruce (Picea crassifolia) at different elevations in the western part of Qilian Mountains and the dynamic response to climate change. We also compared the differences in radial growth of trees at different elevations in response to drought events in the growing and non-growing seasons based on resistance (Rt), recovery (Rc), and resilience (Rs). The results showed that (1) trees at all three elevations were limited by drought stress and the lower the elevation the more sensitive the trees were to drought. (2) The response of middle- and low-elevation trees to the standardized precipitation evaporation index in June of that year was stable. (3) Growing season drought limits radial growth of trees more than non-growing season drought, and Rt is smaller and Rc is larger at low elevations. With increasing drought severity, trees at all three elevations exhibited a trend of decreasing Rt and Rs and increasing Rc. (4) There were significant differences in the growth trends of trees at the three elevations. Therefore, we should continuously pay attention to the dynamics of the forest ecosystem in the western part of Qilian Mountains and take improved measures to cope with the adverse effects of drought on Qinghai spruce.

Seasonal Variation and Driving Factors of Nitrate in Rivers of Miyun Reservoir Watershed, North China

In order to identify the seasonal variations and dominant driving factors of NO3-N in rivers, investigations of five consecutive years were conducted in seven rivers of the Miyun Reservoir Watershed. Significant seasonal variation of NO3-N in rivers was separately found in the dormant season (non-growing season) and the growing season. Furtherly, the V-shaped, W-shaped, and indistinct seasonal patterns of NO3-N accounted for 53.0%, 38.7%, and 8.3%, respectively. They were remarkably affected by stream flow, and their significant quadratic function was discovered. The annual maxima and minima of NO3-N corresponded to medium flow in the dormant season and low flow or flood in the growing season, respectively. On one hand, flood mainly played a role in the diluent for the Chao River with high NO3-N, and on the other hand, it acted as a nitrogen source for the Bai River with low NO3-N. The NO3-N was closely correlated with human activities, and this correlation had obvious seasonal change trend. In the dormant season, significant and mostly extremely significant high correlation coefficient (R) values were determined, while partly non-significant with low R values were found in July, August, September, and October. Increasing seasonal variation index of NO3-N from upstream to downstream was found that was gentle for large rivers and sharp for small tributaries. The seasonality of NO3-N was more affected by natural factors, especially flood, than human factors.

Empirical analysis of the influences of meteorological factors on the interannual variations in carbon fluxes of a Quercus variabilis plantation

Influences of meteorological factors on the carbon fluxes of a forest ecosystem can vary with time scales. While many studies were made on daily to annual variations of measured carbon flux of forest ecosystems, few were conducted on the variations of observed carbon fluxes over longer (decadal or more) time scale. This study quantified the influences of meteorological variables on the measured carbon fluxes in a Quercus variabilis plantation from 2006 to 2021 using principal component analysis (PCA) and cluster analysis (CA). PCA was used to identify the most important meteorological variables. They are monthly mean daily maximum global radiation (Rg), monthly effective accumulated temperature (Tac), monthly mean daily maximum vapor pressure deficit (VPD), and monthly precipitation (PP). CA was used to group 192 observed months into four groups based on those four meteorological variables and their effects on the observed carbon fluxes. Structural equation modeling (SEM) was then used to quantify the relative importance and direct or indirect effects of those four meteorological factors on carbon fluxes at the interannual timescale in each of the four groups. The results showed that air temperature had dominant influence on net ecosystem productivity (NEP) and ecosystem respiration (Re) with its relative importance measured by standardized coefficients (SC) of 0.59 and 0.97, respectively. PP directly impacted gross primary production (GPP) with an SC of 0.40 and indirectly influenced NEP and Re. The importance of a given meteorological factor on carbon fluxes and the dominant meteorological factors varied among the four groups. Tac mainly influenced Re with a SC of 0.79 in Group 1 (the nongrowing season). The direct effects of PP on NEP and GPP and indirect effects on Re were most prominent in Group 2 (the transition stage between the nongrowing season and the growing season). Tac and PP had greater influences than other two variables in Group 3 (the transitional stage of early growth and vigorous growth and the transitional stage of steady growth and dormant period). NEP increased with Tac, while excessive rainy weather accompanied by a decrease in temperature and radiation reduced Re and GPP in Group 4 (the wet season). The short-term seasonal droughts with warm air temperatures but little precipitation (mainly in June) led to significant reductions in both GPP and NEP of the Quercus variabilis plantation ecosystem in the warm-temperate continental monsoon climate zone. Our results can be used to guide managing forest plantations in temperate region in China to maximize their carbon sequestration.

Evaluation of gap-filling methods for CH4 flux data based on eddy covariance method in the Lake Taihu, China

Eddy covariance method has become a key technique to measure CH4 flux continuously in lakes. A large number of CH4 flux data was missing due to variable reasons. In order to reconstruct a complete time series of CH4 flux, it is necessary to find an appropriate gap-filling method to insert the CH4 flux data gap. Based on the routine meteorological data and CH4 flux data measured at Bifenggang site in the eastern part of the Taihu eddy flux network during 2014 to 2017, we analyzed the control factors of CH4 flux at the half-hour scale and daily scale. With those data, we tested that whether nonlinear regression method and two machine learning methods, random forest algorithm and error back propagation algorithm, could fill the CH4 flux gap at the half-hour scale and daily scale. The results showed that CH4 flux at the half-hour scale was mainly influenced by sediment temperature, friction velocity, air temperature, relative humidity, latent heat flux and water temperature at 20 cm in the growing season, and was mainly affected by relative humidity, latent heat flux, wind speed, sensible heat flux and sediment temperature in non-growing season. The CH4 flux at the daily scale was mainly affected by latent heat flux and relative humidity. Random forest model was the best in CH4 flux data gap filling at both time scales. The random forest model with the input variables of day of year, solar elevation angle, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, and wind speed was more suitable for filling the CH4 flux data gap at the half-hour scale. The random forest model with the input variables of day of year, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, wind speed, and downward shortwave radiation was more suitable for filling CH4 flux data gap at the day scale. The interpolation models could fill the data gap better at daily scale than that at the half-hour scale.

Abrupt permafrost thaw accelerates carbon dioxide and methane release at a tussock tundra site

ABSTRACT Abrupt thaw could cause permafrost ecosystems to release more carbon than is predicted from gradual thaw alone. However, thermokarst feature mapping is limited in scope, and observed responses of carbon fluxes to abrupt thaw are variable. We developed a thermokarst detection algorithm that identifies thermokarst features from a single elevation dataset with 71.5 percent accuracy and applied it in Healy, Alaska. Additionally, we investigated the landscape-level variation in carbon dioxide and methane fluxes by extent of abrupt thaw using eddy covariance. Seven percent of the site was classified as thermokarst. Water tracks were the most extensive form of thermokarst, although small pits were much more numerous. Abrupt thaw was positively correlated with carbon uptake during the growing season, when increases in gross primary productivity outpaced increases in ecosystem respiration in vegetation-dense water tracks. However, this was outweighed by higher carbon release in thermokarst features during the nongrowing season. Additionally, abrupt thaw was positively correlated with methane production nearly year-round. Our findings support the hypothesis that abrupt thaw of permafrost carbon will contribute to the permafrost climate feedback above and beyond that associated with gradual thaw and highlights the need to map thermokarst and incorporate abrupt thaw into Earth System Models.

Effects of warming and nitrogen input on soil N2O emission from Qinghai-Tibetan Plateau: a synthesis

Significant changes in climate and perturbation from human activities have been reported over the Qinghai-Tibetan Plateau (QTP), likely altering the ecosystem nitrogen (N) cycling and thus N2O emission. So far, a number of studies have reported variabilities of N2O fluxes from background soil conditions, or conducted warming and N addition experiments to test these effects; however, a synthesized understanding of warming and N input on soil N2O emission is still lacking for the QTP. Here, based on available studies published for this region, we investigated spatiotemporal patterns of background N2O fluxes and performed a meta-analysis to examine the warming and N-addition effects on N2O emission. Annual N2O fluxes ranged from -0.33 to 2.14 kg N2O-N ha−1 yr−1 (mean =0.73), of which their spatial distributions across ecosystems were mainly reflected by mean annual precipitation. N2O fluxes during growing seasons were generally larger than those in non-growing seasons, but hot moments of N2O emission existed during freeze-thawing periods. Our meta-analysis showed that warming had a significantly negative but minor effect on N2O emission from non-permafrost soils, although the effect varied with warming magnitudes and methods. The negative response of N2O flux to warming could be explained by the associated decrease of soil moisture and enhancement of plant N uptake. In contrast, warming-induced thawing increases soil moisture in permafrost soils, which could stimulate N2O emission. N addition exhibited an overall positive impact on N2O emission over the QTP region, with a moderate emission factor (0.8%) lower than the IPCC value. Considering the moderate N2O emission from background soils (< 1 kg N2O-N ha−1 yr−1) and common N limitation across ecosystems, our findings suggest that climate change and enhanced N inputs may not turn the QTP into a globally significant N2O source in the near future.

Assessing the concept of control points for dissolved reactive phosphorus losses in subsurface drainage.

Agricultural phosphorus (P) loss, which is highly variable in space and time, has been studied using the hot spot/hot moment concept, but increasing the rigor of these assessments through a relatively newer "ecosystem control point" framework may help better target management practices that provide a disproportionate water quality benefit. Sixteen relatively large (0.85ha) subsurface drainage plots in Illinois were used as individual observational units to assess dissolved reactive P (DRP) concentrations and losses within a given field over four study years. Three plot-months were identified as DRP control points (one export and two transport control points), where each plot-month contributed>10% of the annual DRP load from the field. These control points occurred on separate plots and in both the growing and nongrowing seasons but were likely related to agronomic P applications. Elevated soil test P, especially near a historic farmstead, and soil clay content were spatial drivers of P loss across the field. The nongrowing season was hypothesized to be the most significant period of P loss, but this was only documented in two of the four study years. A cereal rye (Secale cereale L.) cover crop did not significantly reduce DRP loss in any year, but there was also no evidence of increased drainage P losses due to freezing and thawing of the cover crop biomass. This work confirmed annual subsurface drainage DRP losses were agronomically small(<3% of P application rate), although the range of DRP concentrations relative to eutrophication criteria still demonstrated a potential for negative environmental impact. The control point concept may provide a new lens to view drainage DRP losses, but this framework should be refined through additional within-field studies because mechanisms of P export at this field were more nuanced than just the presence of tile drainage (i.e., a transport control point).

Soil water and solute transport in an Andosol apple orchard including the dormancy period in a snowy cold region

Early spring corresponds to the snowmelt season in apple orchards of the northern hemisphere. This has a significant effect on the initial growth of shoots and flower buds of apple trees. Understanding the soil environment of the orchard during the non-growth period as monitored by farmers is important for managing year-round apple production. However, the details of mass transport, such as that of soil water and solute, during the non-growing season in the Andosols remain unclear. This study conducted soil environment monitoring in an Andosol apple orchard in Aomori Prefecture, Japan, during the non-growing season in winter to examine the year-round changes in the soil environment, using a field monitoring system that is necessary for understanding the soil environment. Volumetric water content, soil bulk electrical conductivity, and soil temperature were measured, and the cumulative changes in total soil moisture (ΣΔTSM) were calculated from the monitored volumetric water content. Results showed that although ΣΔTSM tended to increase (i.e., dry out) annually with periodicity, the variation was small compared to that of apple orchards with gravelly brown forest soil. These results could significantly influence fertilization management of apple orchard soil during the summer drought season and early spring when the roots of apple trees begin taking up nutrients. In particular, it was revealed that if sufficient nutrients remain in the soil pore water in early spring, the negative impact of excessive fertilization on the surrounding environment can be reduced. Therefore, this study constitutes an innovative step in the implementation of field monitoring system to understand the details of mass transport in the Andosol apple orchard soil.

Classification of forest types in Cuigang Forest Farm based on time series data of Landsat 8

To explore the practical role of enhanced vegetation index (EVI) time series data in improving the accuracy of forest type recognition could promote the deep application of optical remote sensing data in forest resources investigation and monitoring. With Cuigang Forest Farm of Xinlin Forestry Bureau in Daxing'anling as the object, we constructed six classification schemes, using random forest algorithm with spectral feature, texture feature and EVI time series feature. The data sources were 20-view Landsat 8 OLI time series data from 2014 to 2018, 56 fixed plots data from 2017-2019, and the 2016 Class II survey data. Our aims were to realize the classification of forest types in Cuigang Forest Farm and to evaluate the accuracy of different classification schemes. The results showed the EVI values of Larix gmelinii forest, Betula platyphylla forest, coniferous-broadleaved mixed forest, coniferous mixed forest and broadleaved mixed forest were significantly different in non-growing seasons (36-111 days and 287-367 days), with the EVI value of mixed conifer forest being significantly higher, and that of mixed broadleaf forest being always lower than the other four forest types. In the early growing season (111-143 days), the EVI value of B. platyphylla forest were higher than L. gmelinii forest, which could effectively distinguish the two forests. Among the six classification schemes, spectral feature, texture feature, and EVI time series feature had the highest classification accuracy, with a Kappa of 0.82 and a classification accuracy of 86.1%. The comparison results showed that the overall accuracy of adding vegetation index time series feature was improved by 14.3% compared with that of spectral feature. The random forest algorithm with combined spectral, texture and EVI time series features could effectively classify forest stand types in Cuigang Forest Farm, with good recognition accuracy and confidence.

Seasonal and interannual dynamics of water vapor flux at a fen in the Zoige peatlands on the Qinghai‐Tibetan Plateau: four‐year measurements

• The Riganqiao peatland was a net water source with emission (kg m −2 yr −1 ) of average 429.3 ± 51.5 from 2013 to 2017. • Impacts of interannual relative humidity (RH) and net radiation (Rn) on water vapor flux were different in each year. • Net CO 2 ecosystem exchange (NEE) was significantly negative related to water vapor flux, whatever in seasonal or interannual scale. Although carbon flux monitoring has been studied extensively in terrestrial ecosystems around the world, water vapor flux based on eddy covariance has received little attention. As a special type of terrestrial ecosystem, wetlands are transitions between land and water, material and energy, and therefore of great significance in times of global change. In wetlands, water vapor flux has a significant impact on micrometeorological environments, making it the main conduit for water vapor exchange between the wetland and the atmosphere. Using an eddy covariance tower, we measured water vapor flux (H 2 O) over four years at the Riganqiao fen in the Zoige peatlands on the eastern Qinghai‐Tibetan Plateau, China. Diurnal H 2 O peaks occurred around 14:00, and annual mean diurnal rate (mmol m −2 s −1 ) was 0.77 ± 0.02, 1.2 ± 0.02, 0.85 ± 0.02, and 0.93 ± 0.02, respectively over the 4 years. Daily H 2 O flux rate was substantially higher between June and August, with peak values of 8836 g m −2 d −1 on DOY (day of year) 161 in 2013. The Riganqiao peatland was a net water source, with an emission average of 429.3 ± 51.5 (kg m −2 yr −1 ). Hydrological and temperature were crucial to seasonal variation in water vapor fluxes in both growing and non-growing seasons, especially the latent heat flux (LE). However, interannual water vapor flux and relative humidity (RH) were significantly positively correlated to water vapor fluxes in 2016 and 2017 but not in 2013 and 2014. Net CO 2 ecosystem exchange (NEE) was significantly negatively related to water vapor flux at seasonal and interannual scales, suggesting that enhanced transpiration of alpine wetland plants will also promote CO 2 absorption over long time scales. Few previous studies have investigated these patterns based on such an interannual monitoring data with eddy covariance tower on the Qinghai‐Tibetan Plateau. Our results suggest that peatland water vapor flux affects not only the micrometeorological environment, but also NEE in wetland ecosystems over long-time scales.

Winter warming effects on soil nitrate leaching under cover crops: A field study using high-frequency weighing lysimeters

Leaching of nitrate (NO3−)—a reactive nitrogen form with impacts on ecosystem health—increases during the non-growing season (NGS) of agricultural soils under cold climates. Cover crops are effective at reducing NGS NO3− leaching, but this benefit may be altered with less snow cover inducing more soil freezing under warmer winters. Our objective was to quantify the effect of winter warming on NO3− leaching from cover crops for a loamy sand (LS) and a silt loam (SIL) soil. This research was conducted over 2 years in Ontario, Canada, using 18 high-precision weighing lysimeters designed to study ecosystem services from agricultural soils. Infra-red heaters were used to simulate warming in lysimeters under a wheat-corn-soybean rotation planted with a cover crop mixture with (+H) and without heating (-H). Nitrate leaching determination used NO3− concentration at 90 cm (discrete sampling) and high temporal resolution drainage volume measurements. Data were analyzed for fall, overwinter, spring-thaw, post-planting, and total period (i.e., November 1 to June 30 of 2017/2018 and 2018/2019). Warming significantly affected soil temperature and soil water content—an effect that was similar for both years. As expected, experimental units under + H presented warmer soils at 5 and 10 cm, along with higher soil water content in liquid form than –H lysimeters, which translated into higher drainage values for + H than –H, especially during the overwinter period. NO3− concentrations at 90 cm were only affected by winter heating for the LS soil. The drainage and NO3− concentrations exhibited high spatial variation, which likely reduced the sensitivity to detect significant differences. Thus, although absolute differences in NO3− leaching between LS vs. SIL and +H (LS) vs. –H (LS) were large, only a trend occurred for higher leaching in LS in 2018/2019. Our research demonstrated that soil heating can influence overwinter drainage (for LS and SIL soils) and NO3− concentration at 90 cm in the LS soil—important NO3− leaching controlling factors. However, contrary to our initial hypothesis, the heating regime adopted in our study did not promote colder soils during the winter. We suggest different heating regimes such as intermittent heating to simulate extreme weather freeze/thaw events as a future research topic.

Variation in Water Uptake Dynamics of Dominant Wood Plants of Pinus taiwanensis Hayata Communities Based on Stable Isotopes

Plant community formation is determined by plant competition, while the water uptake depth of vegetation is regarded as a critical factor in maintaining species coexistence under competition. However, the source variation of montane plant water uptake remains poorly understood, especially under the condition of climate change. We introduced stable hydrogen and oxygen isotopes to investigate the water uptake pattern of the trees and shrubs in a Pinus taiwanensis Hayata community in subtropical mountains. The results showed that the main sources of water uptake in plants varied with soil water content, due to variations in annual precipitation distribution. In July and September, under extremely wet conditions, the evergreen conifer species P. taiwanensis and the shrub Eurya muricata mainly absorbed water from the deep soil layer (40–80 cm, more than 70%). By contrast, the deciduous shrub Rhododendron dilatatum largely relied on upper soil water (0–40 cm, 75.4%) in July but the same deep water source in September. In August and the non-growing season (January), when soil moisture content was low, plants preferred surface layer soil water (0–20 cm, above 50%). In October, the soil water in the middle (20–40 cm) and deep layers (40–80 cm) were the main water source of the three plants. However, the plant water sources showed great difference between P. taiwanensis and shrubs in November: P. taiwanensis absorbed more water from the soil surface layers (89.5%), while R. dilatatum mainly took up surface soil water (54.2%) and E. muricata predominantly obtained water from surface soil water (49.6%) and the deep soil layer (39.3%). These findings suggest that the water uptake of dominant woody plants in a P. taiwanensis community has great plasticity, and its water uptake depth varies with soil water content. In addition, these co-existing species generally absorbed water from similar soil layers in the P. taiwanensis community and exhibited a hydrological niche overlap, indicating a very possible competition between species in future water-limited conditions caused by climate change.

Growing season grazing promotes the shallow stratification of soil nutrients while non-growing season grazing sequesters the deep soil nutrients in a typical alpine meadow

Grazing management and climate are known to be important drivers influencing soil nutrient accumulation. The change of soil nutrients in pasture depends on the excreta return and the vegetation regeneration. Livestock activities significantly affect plant growth and soil nutrients through feeding, trampling, and excretion. At the same time, grazing time and climate change are stimulating plant growth and altering plant composition. How long-term specific grazing management will affect soil nutrient storage and movement under a warming-humid climate trend needs further study. In 20-year grazing management trial, conducted in a typical alpine meadow in the Qilian Mountains on the Qinghai-Tibet Plateau, sampled and analyzed the soil from under a non-growing season graze pasture (WP) and a growing season graze pasture (SAP) in August 1999 and August 2019 along grazing gradients (GG) at different distances from the pasture entrance (0, 300, 600, 900, 1200, and 1500 m). The experimental results of 2019 compared to 1999 show that SAP and WP increased soil available nitrogen density (SAND) and availability (SAND:soil total nitrogen density [STND] ratio) in the first 300 m along the grazing gradient soil, while SAP showed a decrease in soil available phosphorus density (SAPD) and availability (SAPD:soil total phosphorus density [STPD] ratio), and WP had no significant difference between gradients. Grazing in spring and autumn increased soil organic carbon density (SOCD), and STND in the first 300 m along the gradient soil, whereas it had the reverse effect in WP. At the same time, STPD has no obvious changing trend along the gradient. Growing and non-growing season grazing increased the SOCD:STND ratio in the first 300 m along the grazing gradient but resulted to a lower STND:STPD ratio. The comparison found that long-term grazing from 1999 to 2019 increased the SAND and SAPD. SAP improved soil total C, N, and P density in the topsoil (0–10 cm), but WP improved it throughout the profile (0–40 cm). These findings indicate that time of grazing and the grazing gradient affect the accumulation and migration of different elements under long-term grazing. Furthermore, SAP and WP had a positive effect on the accumulation of topsoil and deep soil nutrients, respectively. We suggest that periodic pasture exchange in SAP and WP should be carried out to maintain the sustainability of the ecosystem. At the same time, for different gradients, especially the first 300 m, regular soil nutrient monitoring and human intervention (such as fertilization) should be carried out to eliminate potential element restrictions and focus on the development of possible problems caused by the livestock locked in the pens at night, such as nutrient enrichment (the excreta as the organic fertilizer and soil improvement material for farmland) and loss (element footprint) in pens, which are of important guiding significance for the grazing system’s stable development of alpine meadow.

Environmental and Plant-Derived Controls on the Seasonality and Partitioning of Soil Respiration in an American Sycamore (Platanus occidentalis) Bioenergy Plantation Grown at Different Planting Densities

Bioenergy is one of the most considered alternatives to fossil fuels. Short-rotation woody crops (SRWCs) as bioenergy sources are capable of alleviating energy constraints and sequestering atmospheric CO2. However, studies investigating soil carbon (C) dynamics at SWRC plantations are scarce. We studied American sycamore (Platanus occidentalis) as a model tree species for SRWC at different planting densities ((1) 0.5 × 2.0 m (10,000 trees·ha−1 or tph), (2) 1.0 × 2.0 m (5000 tph), and (3) 2.0 × 2.0 m (2500 tph)) to examine seasonal variation in total soil respiration (Rtotal), partitioned into heterotrophic (Rh) and autotrophic (Ra) respiration, and we evaluated climatic and biological controls on soil respiration. Rtotal and Rh exhibited larger seasonal variation than Ra (p &lt; 0.05). During the nongrowing seasons, the average Rtotal was 0.60 ± 0.21 g·C·m−2·day−1 in winter and 1.41 ± 0.73 g·C·m−2·day−1 in fall. During the growing season, Rtotal was 2–7 times higher in spring (3.49 ± 1.44 g·C·m−2·day−1) and summer (4.01 ± 1.17 g·C·m−2·day−1) than winter. Average Rtotal was 2.30 ± 0.63 g·C·m−2·day−1 in 2500 tph, 2.43 ± 0.64 g·C·m−2·day−1 in 5000 tph, and 2.41 ± 0.75 g·C·m−2·day−1 in 10,000 tph treatments. Average Rh was 1.72 ± 0.40 g·C·m−2·day−1 in 2500 tph, 1.57 ± 0.39 g·C·m−2·day−1 in 5000 tph, and 1.93 ± 0.64 g·C·m−2·day−1 in 10,000 tph, whereas Ra had the lowest rates, with 0.59 ± 0.53 g·C·m−2·day−1 in 2500 tph, 0.86 ± 0.51 g·C·m−2·d−1 in 5000 tph, and 0.48 ± 0.34 g·C·m−2·day−1 in 10,000 tph treatments. Rh had a greater contribution to Rtotal (63%–80%) compared to Ra (20%–37%). Soil temperature was highly correlated to Rtotal (R2 = 0.92) and Rh (R2 = 0.77), while the correlation to Ra was weak (R2 = 0.21). Rtotal, Rh, and Ra significantly declined with soil water content extremes (e.g., &lt;20% or &gt;50%). Total root biomass in winter (469 ± 127 g·C·m−2) was smaller than in summer (616 ± 161 g·C·m−2), and the relationship of total root biomass to Rtotal, Rh, and Ra was only significant during the growing seasons (R2 = 0.12 to 0.50). The litterfall in 5000 tph (121 ± 16 g DW·m−2) did not differ (p &gt; 0.05) from the 2500 tph (108 ± 16 g DW·m−2) or 10,000 tph (132 ± 16 g DW·m−2) treatments. In no circumstances were Rtotal, Rh, and Ra significantly correlated with litterfall amount across planting densities and seasons (p &gt; 0.05). Overall, our results show that Rtotal in American sycamore SRWC is dominated by the heterotrophic component (Rh), is strongly correlated to soil environmental conditions, and can be minimized by planting at a certain tree density (5000 tph).

Rhizosphere priming effect of four non-woody perennials after leaf senescence and before shoot regrowth

Living roots and its rhizodeposition can stimulate or retard soil organic matter (SOM) decomposition via the rhizosphere priming effect (RPE). However, little is known about the RPE during non-growing seasons. In this study, we measured the RPEs of two perennial grasses (Elymus dahuricus, Stipa grandis) and two legumes (Medicago sativa, Melissilus ruthenicus) after leaf senescence and before shoot regrowth using a 13C natural tracer method. All four species produced positive RPEs at each sampling time, with the magnitude ranging from 40% to 238% compared to unplanted soil. Further, the inter-specific variation in the RPE during the non-growing season was partly explained by the root:shoot ratio, average root diameter and root tissue density. Overall, these results demonstrate that live roots of non-woody perennials could accelerate SOM decomposition even during the non-growing season.