Non-growing Season Research Articles

Response of Soil Water Storage to Meteorological Factors in Alpine Shrub Meadow on Northeastern Qinghai–Tibetan Plateau

The Qinghai–Tibet Plateau (QTP) has an important function in ensuring the water ecological security of China, even Asia, and the soil water storage of alpine grassland is an important part of the ecosystem water. Grassland degradation directly affects the soil water storage capacity. However, the impact of degradation on specific soil storage capacity, especially alpine shrubs, is rarely studied. Here, we chose two plots of alpine non-degraded shrub and degraded shrub, using the automatic soil moisture monitoring system to study the change process of soil moisture storage, and then adopted the boosted regression tree (BRT) model to quantitatively evaluate the relative influence of environmental variables on soil water storage. Our results show: (1) The soil water storage in the growing season (May–September) is higher than that in the non-growing season (January–April and October–December), and the soil water storage reaches its highest in mid-July. (2) During the growing season, the 100 cm soil temperature was the most important factor affecting the seasonal variation in soil water storage, accounting for 51% of the total variation. During the non-growing season, the 40 cm soil temperature was the most important factor affecting the variation in soil water storage, accounting for 80% of the total variation. (3) The soil water storage of non-degraded Potentilla fruticosa shrub meadow increased by 6–25%, compared with degraded grassland shrub meadow during growing-season. (4) Various meteorological factors have a weak impact on soil water storage.

Interannual climate variability has predominant effects on seedling survival in a temperate forest.

Mechanisms such as conspecific negative density dependence (CNDD) and niche partitioning have been proposed to explain species coexistence and community diversity. However, as a potentially important axis of niche partitioning, the role of interannual climate variability in driving local community dynamics remains largely unknown. Here we used a 15-year monitoring data set of more than 53,000 seedlings in a temperate forest to examine (1) what are the relative effects of interannual climate variability, biotic interactions, and habitat conditions on seedling survival; (2) how the effects of biotic interactions change with interannual climate variability, and habitat conditions; and (3) whether the impacts of interannual climate variability, biotic interactions, and habitat conditions differ with plant traits. Interannual climate variability accounted for the most variation in seedling survival at the community level, followed by biotic interactions, and habitat conditions. Increased snowpack and decreased minimum temperature during the non-growing season had positive effects on seedling survival. Effects of conspecific neighbor density were weakened in higher snowpack, effective accumulated temperature, elevation, and soil-resource gradient, but were intensified with increased ultraviolet radiation, maximum precipitation, minimum temperature, and soil moisture. In addition, the relative importance of interannual climate variability versus biotic interactions differed depending on species-trait groups. Specifically, biotic interactions for gravity-dispersed species had a larger effect size in affecting seedling survival than other trait groups. Also, gravity-dispersed species experienced a stronger CNDD than wind-dispersed, probably because wind-dispersed seedlings rarely had adult conspecifics nearby. We found that interannual climate variability was most strongly associated with seedling survival, but the magnitude of climatic effects varied among species-trait groups. Interannual climate variability may act as an inhibitor or accelerator to density-dependent interactions and should be accounted for in future studies, as both a potential direct and indirect factor in understanding the diversity of forest communities.

Anthropogenic warming reduces the carbon accumulation of Tibetan Plateau peatlands

Peatland carbon accumulation generally increased during past intervals of natural warming. With recent anthropogenically-dominated warming being unprecedented over the past ∼2000 years, however, it is unclear how peatland carbon dynamics may operate compared to those under historical natural warmings. Here we examine the impacts of the recent warming from 1850 CE to present (Recent Warm Period; RWP) and the historical warming during 1000–1300 CE (Medieval Warm Period; MWP) on peatland carbon accumulation of the Tibetan Plateau using two continuous peat core records. We observed major seasonal difference between the two warming periods, with growing season (summer) warming dominating the MWP, while greater non-growing season warming characterizing the RWP. Consequently, we found a high net carbon balance during the MWP, suggesting that warming increased plant production more than decomposition of organic matter. In contrast, a low net carbon balance was observed during the RWP because non-growing season warming greatly enhanced soil carbon decomposition that could have completely offset plant carbon uptake. Therefore, recent anthropogenic warming might have induced a different ecosystem response with lower net carbon balance over the past millennium than that during historical natural warmings. As other regions of the globe have similar growing season versus non-growing season warming patterns, the risk of carbon loss from global peatlands may have been underestimated, implying that there is an even greater challenge for managing ecosystem carbon sinks under future climate change.

Increased annual methane uptake driven by warmer winters in an alpine meadow

Pronounced nongrowing season warming and changes in soil freeze-thaw (F-T) cycles can dramatically alter net methane (CH4 ) exchange rates between soils and the atmosphere. However, the magnitudes and drivers of warming impacts on CH4 uptake in different stages of the F-T cycle are poorly understood in cold alpine ecosystems, which have been found to be a net sink of atmospheric CH4 . Here, we reported a year-round ecosystem daily CH4 uptake in an alpine meadow on the Qinghai-Tibetan Plateau after a 5-year warming experiment that included a control, a low-level warming treatment (+2.4℃ at 5cm soil depth), and a high-level warming treatment (+4.5℃ at 5cm soil depth). We found that warming shortened the F-T cycle under the low-level warming and soils did not freeze under the high-level warming. Although both warming treatments increased the mean CH4 uptake rate, only the high-level warming significantly increased annual CH4 uptake compared to the control. The warming-induced stimulation of CH4 uptake mainly occurred in the cold season, which was mostly during spring thaw under low-level warming and during the frozen winter under high-level warming due to a longer period with thawed soil. We also found that warming significantly stimulated daily CH4 uptake mainly by reducing near-surface soil water content in the warm season, whereas both soil water content and temperature controlled daily CH4 uptake in different ways during the autumn freeze, frozen winter, and spring thaw periods of the control. Our study revealed a strong warming effect on CH4 uptake during the entire F-T cycle in the alpine meadow, especially the unfrozen winter. Our results also suggested the important roles of soil pH, available phosphorus, and methanotroph abundance in regulating annual CH4 uptake in response to warming, which should be incorporated into biogeochemical models for accurately forecasting CH4 fluxes under future climate scenarios.

Facilitating Salt Marsh Restoration: The Importance of Event-Based Bed Level Dynamics and Seasonal Trends in Bed Level Change

Intertidal salt marshes provide a range of valuable ecosystem services which typically increase with marsh width. Understanding the drivers for salt marsh expansion versus retreat is thus key to managers. Previous research highlights the influence of short-term (daily/event) bed level dynamics on germination and establishment and subsequent vegetation presence. However, more recent literature suggests the importance of medium-term seasonal bed level dynamics on viable seed availability and subsequent vegetation presence. This study aims to assess event-based and seasonal bed level dynamics for vegetation presence in natural and semi-natural salt marshes and to provide generic thresholds for vegetation presence. To gain insight into bed level dynamics, data was used from autonomous Optical and Acoustic Surface Elevation Dynamics sensors (O-SED and A-SED) around the edge of natural and semi-natural salt marshes. Sensors were installed at vegetated and unvegetated measurement station Field observations from 22 O-SEDs deployed at 4 well-established natural salt marshes in the Western Scheldt estuary and 4 O-SEDs at a well-established semi-natural salt marsh in the Wadden Sea were reanalyzed. Six novel A-SEDs were deployed at a pioneer semi-natural salt marsh in the Ems-Dollard Estuary. The measurement duration at all salt marshes was at least 1 year. The A-SED sensor was successfully validated against manual measurements. Furthermore, vegetation data and water level data were obtained. No significant difference was observed between natural and semi-natural salt marshes. However, a significant difference between vegetated and unvegetated measurement stations for short-term bed level dynamics was observed. Vegetation was found to be present at locations restricted by short-term bed level variability smaller than or equal to 12 mm, emphasizing the presence of a short-term threshold. Although trends in the non-growing season were significantly different between vegetated and unvegetated stations, seasonal thresholds for vegetation presence were not found. The findings imply that knowledge of bed level-dynamics in well-established natural marshes can be used to predict vegetation presence in constructed semi-natural marshes. The importance of local short-term dynamics for vegetation presence instead of longer-term dynamics highlights possibilities for developing favorable conditions for vegetation presence in marsh restoration projects and the construction of new salt marsh ecosystems.

The definition of the non-growing season matters: a case study of net ecosystem carbon exchange from a Canadian peatland

Climate change is a threat to the 500 Gt carbon stored in northern peatlands. As the region warms, the rise in mean temperature is more pronounced during the non-growing season (NGS, i.e., winter and parts of the shoulder seasons) when net ecosystem loss of carbon dioxide (CO2) occurs. Many studies have investigated the impacts of climate warming on NGS CO2 emissions, yet there is a lack of consistency amongst researchers in how the NGS period is defined. This complicates the interpretation of NGS CO2 emissions and hinders our understanding of seasonal drivers of important terrestrial carbon exchange processes. Here, we analyze the impact of alternative definitions of the NGS for a peatland site with multiple years of CO2 flux records. Three climatic parameters were considered to define the NGS: air temperature, soil temperature, and snow cover. Our findings reveal positive correlations between estimates of the cumulative non-growing season net ecosystem CO2 exchange (NGS-NEE) and the length of the NGS for each alternative definition, with the greatest proportion of variability explained using snow cover (R 2 = 0.89, p < 0.001), followed by air temperature (R 2 = 0.79, p < 0.001) and soil temperature (R 2 = 0.54, p = 0.006). Using these correlations, we estimate average daily NGS CO2 emitted between 1.42 and 1.90 gCO2 m−2, depending on which NGS definition is used. Our results highlight the need to explicitly define the NGS based on available climatic parameters to account for regional climate and ecosystem variability.

Stability response of alpine meadow communities to temperature and precipitation changes on the Northern Tibetan Plateau.

Biomass temporal stability plays a key role in maintaining sustainable ecosystem functions and services of grasslands, and climate change has exerted a profound impact on plant biomass. However, it remains unclear how the community biomass stability in alpine meadows responds to changes in some climate factors (e.g., temperature and precipitation). Long‐term field aboveground biomass monitoring was conducted in four alpine meadows (Haiyan [HY], Henan [HN], Gande [GD], and Qumalai [QML]) on the Qinghai‐Tibet Plateau. We found that climate factors and ecological factors together affected the community biomass stability and only the stability of HY had a significant decrease over the study period. The community biomass stability at each site was positively correlated with both the stability of the dominant functional group and functional groups asynchrony. The effect of dominant functional groups on community stability decreased with the increase of the effect of functional groups asynchrony on community stability and there may be a ‘trade‐off’ relationship between the effects of these two factors on community stability. Climatic factors directly or indirectly affect community biomass stability by influencing the stability of the dominant functional group or functional groups asynchrony. Air temperature and precipitation indirectly affected the community stability of HY and HN, but air temperature in the growing season and nongrowing season had direct negative and direct positive effects on the community stability of GD and QML, respectively. The underlying mechanisms varied between community composition and local climate conditions. Our findings highlighted the role of dominant functional group and functional groups asynchrony in maintaining community biomass stability in alpine meadows and we highlighted the importance of the environmental context when exploring the stability influence mechanism. Studies of community stability in alpine meadows along with different precipitation and temperature gradients are needed to improve our comprehensive understanding of the mechanisms controlling alpine meadow stability.

Tile Drainage Flow Partitioning and Phosphorus Export in Vermont USA

Tile drainage (TD) has been identified as a potential non-point source of phosphorus (P) pollution and subsequent water quality issues. Three fields with TD in Vermont USA were monitored to characterize hydrology and P export. Fields were in corn silage and used minimal tillage and cover cropping practices. Preferential flow path (PFP) activity was explored by separating TD flow into flow pathway and source connectivity components using two hydrograph separation techniques, electrical conductivity end member unmixing, and hydrograph recession analysis. TD was the dominant P export pathway because of higher total discharge. Drought conditions during this study limited surface runoff, and possibly resulted in maximum PFP activity in the active clay soils. The non-growing season dominated annual P loading for two of the three study years. Peak P concentrations in TD occurred during events following manure injection in the fall, as well as in the spring post cover crop termination and post-planting. Intra-event analysis of rainfall pulses showed that TD flow and P concentrations were higher because of higher intensity pulses. This study highlights the impacts of current manure management, as well as the potential for climate change to increase P transport to TD.

New York City greenhouse gas emissions estimated with inverse modeling of aircraft measurements

Cities are greenhouse gas emission hot spots, making them targets for emission reduction policies. Effective emission reduction policies must be supported by accurate and transparent emissions accounting. Top-down approaches to emissions estimation, based on atmospheric greenhouse gas measurements, are an important and complementary tool to assess, improve, and update the emission inventories on which policy decisions are based and assessed. In this study, we present results from 9 research flights measuring CO2 and CH4 around New York City during the nongrowing seasons of 2018–2020. We used an ensemble of dispersion model runs in a Bayesian inverse modeling framework to derive campaign-average posterior emission estimates for the New York–Newark, NJ, urban area of (125 ± 39) kmol CO2 s–1 and (0.62 ± 0.19) kmol CH4 s–1 (reported as mean ± 1σ variability across the nine flights). We also derived emission estimates of (45 ± 18) kmol CO2 s–1 and (0.20 ± 0.07) kmol CH4 s–1 for the 5 boroughs of New York City. These emission rates, among the first top-down estimates for New York City, are consistent with inventory estimates for CO2 but are 2.4 times larger than the gridded EPA CH4 inventory, consistent with previous work suggesting CH4 emissions from cities throughout the northeast United States are currently underestimated.

Aboveground and belowground contributions to ecosystem respiration in a temperate deciduous forest

In this study, we developed a three-way carbon dioxide (CO2) flux-partitioning algorithm that separates net ecosystem exchange (NEE) into aboveground plant respiration (Rabove), belowground root and soil respiration (Rbelow), and gross primary production (GPP). We applied this algorithm to a coupled dataset of continuous chamber-measured soil respiration and eddy covariance (EC)-measured NEE of CO2 in an oak-hickory (Quercus-Carya) deciduous broadleaf forest from 2006 to 2015. We found that on annual time scale, Rbelow dominated over Rabove with the former accounting for 66.9–86.4% and the latter 13.6–33.1%, of the total ecosystem respiration (Reco). The ratio of Rbelow to Rabove varied seasonally, ranging from 1.77 to 7.25 in growing season, and 1.02 to 4.57 in non-growing season. The temperature sensitivity (E0) of Rbelow was significantly higher than that of Rabove, and E0 of Reco responded differently to air and soil temperature. Over the whole study period, annual mean Rabove, Rbelow, and GPP were 243, 806, and 1170 g C m−2, respectively, with annual Reco accounting for 89.6% of GPP, of which 68.8% was lost as Rbelow and 20.8% lost as Rabove, and leaving only 10% of the carbon fixation in ecosystems. These estimates, however, did not consider potential light inhibition of leaf respiration. If we accept the presence of light inhibition, then the daytime three-way partitioning method would underestimate annual Rabove by 20.4% whereas the nighttime method would overestimate Rabove by 23.9% and GPP by 4.7%, compared with estimates accounting for light inhibition in leaves.

Environmental Controls on Multi-Scale Dynamics of Net Carbon Dioxide Exchange From an Alpine Peatland on the Eastern Qinghai-Tibet Plateau.

Peatlands are characterized by their large carbon storage capacity and play an essential role in the global carbon cycle. However, the future of the carbon stored in peatland ecosystems under a changing climate remains unclear. In this study, based on the eddy covariance technique, we investigated the net ecosystem CO2 exchange (NEE) and its controlling factors of the Hongyuan peatland, which is a part of the Ruoergai peatland on the eastern Qinghai-Tibet Plateau (QTP). Our results show that the Hongyuan alpine peatland was a CO2 sink with an annual NEE of −226.61 and −185.35 g C m–2 in 2014 and 2015, respectively. While, the non-growing season NEE was 53.35 and 75.08 g C m–2 in 2014 and 2015, suggesting that non-growing seasons carbon emissions should not be neglected. Clear diurnal variation in NEE was observed during the observation period, with the maximum CO2 uptake appearing at 12:30 (Beijing time, UTC+8). The Q10 value of the non-growing season in 2014 and 2015 was significantly higher than that in the growing season, which suggested that the CO2 flux in the non-growing season was more sensitive to warming than that in the growing season. We investigated the multi-scale temporal variations in NEE during the growing season using wavelet analysis. On daily timescales, photosynthetically active radiation was the primary driver of NEE. Seasonal variation in NEE was mainly driven by soil temperature. The amount of precipitation was more responsible for annual variation of NEE. The increasing number of precipitation event was associated with increasing annual carbon uptake. This study highlights the need for continuous eddy covariance measurements and time series analysis approaches to deepen our understanding of the temporal variability in NEE and multi-scale correlation between NEE and environmental factors.

非生长季降水对青藏高原高寒草甸优势种生物量稳定性的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 非生长季降水对青藏高原高寒草甸优势种生物量稳定性的影响 DOI: 10.5846/stxb202103200741 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科学基金（U20A2007-01）；第二次青藏高原综合科学考察研究（2019QZKK0307）；山西省博士毕业生、博士后研究人员来晋工作奖励资金科研项目（SXBYKY2021067）；山西农业大学博士科研启动项目（2021BQ34） Non-growing season precipitation facilitated the biomass stability of dominant species in alpine meadow of the Qinghai Tibet Plateau Author: Affiliation: Fund Project: National Natural Science Foundation of China 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:受全球气候变化的影响，青藏高原在过去的几十年间整体上呈现暖湿化的趋势，相比于年际之间温度和降水的变化外，生长季和非生长季气候变化模式的差异可能会对生态系统产生更重要的影响，但相关的研究尚不充分。以青藏高原东部的高寒草甸为研究对象，基于2001年至2017年17年的野外观测数据，包括优势植物紫花针茅的高度、多度以及生物量、次优势物种洽草的生物量，结合生长季和非生长季平均温度和降水量的变化，通过线性回归以及结构方程模型，探究生长季/非生长季不对称气候变化对于青藏高原高寒草甸优势物种生物量稳定性的影响。研究结果表明：1）青藏高原东部年均温和年降水在过去的17年间显著增加，呈现暖湿化的趋势，但是非生长的降水却变化不明显；2）紫花针茅的高度、多度以及生物量在过去17年没有显著的趋势，但是洽草的生物量稳定性显著减少；3）非生长降水结合紫花针茅的高度、多度以及洽草的生物量稳定性促进了紫花针茅的生物量稳定性。研究结果可以为青藏高原高寒草甸在未来气候变化的背景下合理保护与利用提供科学依据。 Abstract:In the past few decades,the Qinghai-Tibet Plateau showed warming and humidifying with global climate change. Compared with the interannual changes of temperature and precipitation, the difference of climate change patterns between growing season and non-growing season may have a more important impact on the ecosystem, but the relevant research is still insufficient. Based on the field observation data of 17 years from 2001 to 2017, including the height, abundance and biomass of dominant plant Stipa purpurea, and biomass of Subdominant species Koeleria cristata, combined with the changes of mean temperature and precipitation in growing season and non-growing season, the growth season/non growing season was explored by linear regression and structural equation model to explore the effects of asymmetric climate change in growing season and non-growing season on biomass stability of dominant species in alpine meadow of Qinghai Tibet Plateau. The results show that:1) the annual mean temperature and annual precipitation in the eastern Tibetan Plateau have increased significantly in the past 17 years, showing a trend of warming and wetting, but the non-growing precipitation has no significant change; 2) The height, abundance and biomass of Stipa purpurea had no significant change trend in the past 17 years, but the biomass stability of Koeleria cristata decreased significantly; 3) The non-growth precipitation combined with the height and abundance of Stipa purpurea and the biomass stability of Koeleria cristata promoted the biomass stability of Stipa purpurea. The results can provide scientific basis for the reasonable protection and utilization of alpine meadow in the context of climate change in the future. 参考文献 相似文献 引证文献

Global Terrestrial Ecosystem Carbon Flux Inferred from TanSat XCO 2 Retrievals

TanSat is China’s first greenhouse gases observing satellite. In recent years, substantial progresses have been achieved on retrieving column-averaged CO 2 dry air mole fraction (XCO 2 ). However, relatively few attempts have been made to estimate terrestrial net ecosystem exchange (NEE) using TanSat XCO 2 retrievals. In this study, based on the GEOS-Chem 4D-Var data assimilation system, we infer the global NEE from April 2017 to March 2018 using TanSat XCO 2 . The inversion estimates global NEE at −3.46 PgC yr -1 , evidently higher than prior estimate and giving rise to an improved estimate of global atmospheric CO 2 growth rate. Regionally, our inversion greatly increases the carbon uptakes in northern mid-to-high latitudes and significantly enhances the carbon releases in tropical and southern lands, especially in Africa and India peninsula. The increase of posterior sinks in northern lands is mainly attributed to the decreased carbon release during the nongrowing season, and the decrease of carbon uptakes in tropical and southern lands basically occurs throughout the year. Evaluations against independent CO 2 observations and comparison with previous estimates indicate that although the land sinks in the northern middle latitudes and southern temperate regions are improved to a certain extent, they are obviously overestimated in northern high latitudes and underestimated in tropical lands (mainly northern Africa), respectively. These results suggest that TanSat XCO 2 retrievals may have systematic negative biases in northern high latitudes and large positive biases over northern Africa, and further efforts are required to remove bias in these regions for better estimates of global and regional NEE.

Long-term variability in N2O emissions and emission factors for corn and soybeans induced by weather and management at a cold climate site

Nitrous oxide (N2O) emissions are highly variable in space and time due to the complex interplay between soil, management practices and weather conditions. Micrometeorological techniques integrate emissions over large areas at high temporal resolution. This allows identification of causes of intra- and inter-annual variability of N2O emissions and development of robust emission factors (EF). Here, we investigated factors responsible for variability in N2O emissions during growing and non-growing seasons of corn and soybeans grown in an imperfectly drained silt loam soil, in Ontario, Canada. We used quasi-continuously (at half-hourly to hourly intervals) N2O fluxes measured via the flux-gradient technique over 11 years for corn and 5 years for soybeans and evaluated the uncertainty of default IPCC and Canada-specific EFs. In the growing season, emissions were controlled by soil nitrate content, soil moisture and temperature in the fertilized corn, while moisture and temperature regulated N2O emissions in the unfertilized soybeans. In the non-growing season, nitrogen (N) input from the crop residue did not affect the emissions, pointing to freeze-thaw cycles as mechanisms for enhanced N2O emissions. The non-growing season contribution to annual emissions was 38% in corn and 43% in soybeans. On average, annual emissions were 2.6-fold higher in corn than soybeans. Observed mean N2O EFs were 0.84% (0.12–2.02%) for growing season and 1.69% (0.29–7.32%) for yearly emissions. The growing season EF derived from long-term N2O emissions was 0.9 ± 0.14%. The interannual variability in N2O emissions and EFs can be attributed to management practices and annual weather variability. The default IPCC approach based on overall N input had poorer performance in predicting annual N2O emissions compared to the current Canadian methodology, which includes management and environmental factor in addition to N inputs. The observed emissions were further evaluated with a newly developed growing season N2O emission prediction approach for Canada. However, performance of the approach was poorer than IPCC or the current national Canadian approach. Additional tests of the new national methodology are recommended as well as consideration of non-growing season emissions.

Asymmetrical warming of growing/non-growing season increases soil respiration during growing season in an alpine meadow

Soil respiration (Rs) is an important carbon flux in the global carbon cycle, and understanding the influence of global warming on Rs is critical for precise prediction future climate change. Actually, global warming is expected to be seasonally asymmetric, however, it is still unclear on the response of Rs to asymmetrical warming of growing/non-growing season in alpine regions. In this study, an experiment with asymmetrical warming of growing/non-growing season (including three treatments, CK: control; GLNG: warming magnitude of growing season lower than non-growing season; GHNG: warming magnitude of growing season higher than non-growing season) was performed in an alpine meadow of the Northern Tibet since June 2015. The ‘GLNG’ and ‘GHNG’ treatments increased mean Rs by 71.22% (1.89 μmol CO2 m−2 s−1) and 34.32% (0.91 μmol CO2 m−2 s−1) during growing season in 2019, respectively. However, the ‘GLNG’ and ‘GHNG’ treatments did not significantly affect mean Rs during growing season in 2015, 2016, 2017 and 2018, respectively. The variation coefficient of growing season mean Rs was 32.95% under the CK treatment in 2015–2019. Therefore, warming may have a lagging effect on Rs. The warming scene with a greater warming during non-growing season may have a stronger effect on Rs than the warming scene with a greater warming during growing season. Inter-annual variation of Rs may be greater than the warming effect on Rs in alpine meadows.

Modeling and assessing water and nutrient balances in a tile-drained agricultural watershed in the U.S. Corn Belt

Identifying the key processes and primary sources of water and nutrient losses is essential for water quantity and quality management in watersheds. This is especially true in the U.S. Corn Belt, which has been recognized as the primary region contributing nutrient loads to the Great Lakes and the Gulf of Mexico. A SWAT (Soil and Water Assessment Tool) model simulation was set up in an agricultural watershed with about 50% tile drainage area in the U.S. Corn Belt to study the water and nutrient balance components for the whole watershed and the corn-soybean rotation system. The SWAT model was improved to consider additional nitrogen and phosphorus loss paths from the soil. The model was comprehensively calibrated and validated for simulating monthly stream flow, total suspended solids (TSS), nutrient loads (including total Kjeldahl nitrogen (TKN), nitrate and nitrite nitrogen (NOx-N), total phosphorus (TP) and orthophosphate phosphorus (orthoP)), actual evapotranspiration (ETa), leaf area index (LAI) and annual crop yields in the watershed from 2011 to 2019. Results showed the model performance was very good for simulating the stream flow, TSS and ETa, and acceptable for nutrient loads, LAI and crop yields. ETa, surface runoff, lateral soil flow, tile drainage and percolation respectively accounted for 65%, 15%, 2%, 8% and 9% of the precipitation. Fertilizer was the main source of nitrogen and phosphorus input to the watershed, and harvested crops were the main paths removing nutrients. Surface runoff, tile drainage and percolation each contributed about 30% of total nitrogen losses to water, with surface runoff being dominated by organic nitrogen while tile drainage and percolation were dominated by nitrate nitrogen. Phosphorus losses were mainly through surface runoff, which resulted in 66% of the total losses and was dominated by organic phosphorus and soluble phosphorus. Representing about 49% of the watershed area, the corn-soybean rotation system contributed 83% and 88% of the total nitrogen and phosphorus inputs, respectively, to the watershed, as well as 64% and 46% of the nitrogen and phosphorus losses to the water system, respectively. The non-growing season (October to the next April) was identified as the critical period resulting in water and nutrient losses due to low evapotranspiration and plant uptake. Targeted management strategies for reducing nutrient loads in key hydrological paths were suggested.

Nongrowing Season CO2 Emissions Determine the Distinct Carbon Budgets of Two Alpine Wetlands on the Northeastern Qinghai—Tibet Plateau

Alpine wetlands sequester large amounts of soil carbon, so it is vital to gain a full understanding of their land-atmospheric CO2 exchanges and how they contribute to regional carbon neutrality; such an understanding is currently lacking for the Qinghai—Tibet Plateau (QTP), which is undergoing unprecedented climate warming. We analyzed two-year (2018–2019) continuous CO2 flux data, measured by eddy covariance techniques, to quantify the carbon budgets of two alpine wetlands (Luanhaizi peatland (LHZ) and Xiaobohu swamp (XBH)) on the northeastern QTP. At an 8-day scale, boosted regression tree model-based analysis showed that variations in growing season CO2 fluxes were predominantly determined by atmospheric water vapor, having a relative contribution of more than 65%. Variations in nongrowing season CO2 fluxes were mainly controlled by site (categorical variable) and topsoil temperature (Ts), with cumulative relative contributions of 81.8%. At a monthly scale, structural equation models revealed that net ecosystem CO2 exchange (NEE) at both sites was regulated more by gross primary productivity (GPP), than by ecosystem respiration (RES), which were both in turn directly controlled by atmospheric water vapor. The general linear model showed that variations in nongrowing season CO2 fluxes were significantly (p &lt; 0.001) driven by the main effect of site and Ts. Annually, LHZ acted as a net carbon source, and NEE, GPP, and RES were 41.5 ± 17.8, 631.5 ± 19.4, and 673.0 ± 37.2 g C/(m2 year), respectively. XBH behaved as a net carbon sink, and NEE, GPP, and RES were –40.9 ± 7.5, 595.1 ± 15.4, and 554.2 ± 7.9 g C/(m2 year), respectively. These distinctly different carbon budgets were primarily caused by the nongrowing season RES being approximately twice as large at LHZ (p &lt; 0.001), rather than by other equivalent growing season CO2 fluxes (p &gt; 0.10). Overall, variations in growing season CO2 fluxes were mainly controlled by atmospheric water vapor, while those of the nongrowing season were jointly determined by site attributes and soil temperatures. Our results highlight the different carbon functions of alpine peatland and alpine swampland, and show that nongrowing season CO2 emissions should be taken into full consideration when upscaling regional carbon budgets. Current and predicted marked winter warming will directly stimulate increased CO2 emissions from alpine wetlands, which will positively feedback to climate change.

Temperature, moisture and freeze\u2013thaw controls on CO2 production in soil incubations from northern peatlands

Peat accumulation in high latitude wetlands represents a natural long-term carbon sink, resulting from the cumulative excess of growing season net ecosystem production over non-growing season (NGS) net mineralization in soils. With high latitudes experiencing warming at a faster pace than the global average, especially during the NGS, a major concern is that enhanced mineralization of soil organic carbon will steadily increase CO2 emissions from northern peatlands. In this study, we conducted laboratory incubations with soils from boreal and temperate peatlands across Canada. Peat soils were pretreated for different soil moisture levels, and CO2 production rates were measured at 12 sequential temperatures, covering a range from − 10 to + 35 °C including one freeze–thaw event. On average, the CO2 production rates in the boreal peat samples increased more sharply with temperature than in the temperate peat samples. For same temperature, optimum soil moisture levels for CO2 production were higher in the peat samples from more flooded sites. However, standard reaction kinetics (e.g., Q10 temperature coefficient and Arrhenius equation) failed to account for the apparent lack of temperature dependence of CO2 production rates measured below 0 °C, and a sudden increase after a freezing event. Thus, we caution against using the simple kinetic expressions to represent the CO2 emissions from northern peatlands, especially regarding the long NGS period with multiple soil freeze and thaw events.

Spatial soil moisture estimation in agro-pastoral transitional zone based on synergistic use of SAR and optical-thermal satellite images

Synthetic Aperture Radar (SAR) Sentinel-1 (S1) surface soil moisture (SSM) retrieval is promising but challenging in canopy areas. Additional data from optical-thermal infrared (TIR) sensors (e.g., Moderate Resolution Imaging Spectroradiometer, MODIS) have potential to compensate for SSM monitoring from single S1 product, suggesting their synergistic use for SSM retrieval in vegetated terrains. A physical, straightforward and non-calibration synergy method of SAR S1 and optical-TIR MODIS was proposed in this study to enhance SSM estimation in an agro-pastoral transitional zone. Change detection for S1 backscatter (σ°) and simplified triangle method representing land surface temperature (LST) – normalized difference vegetation index (NDVI) space (Ts-VI) for MODIS, were combined under a synergistic framework regarding vegetation conditions. The synergy method performance was evaluated against in-situ soil moisture sites for different phenological stages. Correlation analysis results indicated that S1 σ° is highly sensitive to SSM in non-growing season, whereas MODIS LST is negatively linked to root-zone soil moisture during summer crop growth as the seasonal vegetation effect that can be explained via the observed trapezoidal Ts-VI shape. For the synergy, S1 is mainly involved in during non-growing period, while major contribution in growing period was from MODIS, which accounted for 90% improvements in correlation (R, 0.29 – 0.55) and 30% for Root-Mean-Square Error (RMSE, 0.093 – 0.065 m3m−3) during a four-month crop growth as compared to single S1 product. For entire period, the synergy method outperformed single S1 over all sites, where the average R and RMSE improved 30% (0.46 – 0.60) and 14% (0.070 – 0.060 m3m−3), respectively, with highest values (R = 0.73 and RMSE = 0.039 m3m−3) observed in a maize site. This synergy suggests a suitability of integrating optical-TIR data to improve SAR SSM estimation in agricultural lands, especially over the crop growth period when water is a major limiting factor.

A 406-year non-growing-season precipitation reconstruction in the southeastern Tibetan Plateau

Abstract. Trees record climatic conditions during their growth, and tree rings serve as proxy to reveal the features of the historical climate of a region. In this study, we collected tree-ring cores of hemlock forest (Tsuga forrestii) from the northwestern Yunnan area of the southeastern Tibetan Plateau (SETP) and created a residual tree-ring width (TRW) chronology. An analysis of the relationship between tree growth and climate revealed that precipitation during the non-growing season (NGS) (from November of the previous year to February of the current year) was the most important constraining factor on the radial tree growth of hemlock forests in this region. In addition, the influence of NGS precipitation on radial tree growth was relatively uniform over time (1956–2005). Accordingly, we reconstructed the NGS precipitation over the period spanning from 1600–2005. The reconstruction accounted for 28.5 % of the actual variance during the common period of 1956–2005. Based on the reconstruction, NGS was extremely dry during the years 1656, 1694, 1703, 1736, 1897, 1907, 1943, 1982 and 1999. In contrast, the NGS was extremely wet during the years 1627, 1638, 1654, 1832, 1834–1835 and 1992. Similar variations of the NGS precipitation reconstruction series and Palmer Drought Severity Index (PDSI) reconstructions of early growing season from surrounding regions indicated the reliability of the present reconstruction. A comparison of the reconstruction with Climate Research Unit (CRU) gridded data revealed that our reconstruction was representative of the NGS precipitation variability of a large region in the SETP. Our study provides the first historical NGS precipitation reconstruction in the SETP which enriches the understanding of the long-term climate variability of this region. The NGS precipitation showed slightly increasing trend during the last decade which might accelerate regional hemlock forest growth.