Non-growing Season Research Articles

Interpreting the Response of Forest Stock Volume with Dual Polarization SAR Images in Boreal Coniferous Planted Forest in the Non-Growing Season

Polarimetric Synthetic Aperture Radar (PolSAR) images with dual polarization modes have great potential to map forest stock volume (FSV) by excellent penetration capabilities and distinct microwave scattering processes. However, the response of these SAR data to FSV is still uncertain in the non-growing season. To further interpret the response of FSV to different dual polarization SAR images, three types of dual polarization SAR images (GF-3, Sentinel-1, and ALOS-2) were initially acquired in coniferous planted forest in the non-growing season. Then, sensitivity between FSV and all alternative features extracted from each type of SAR image was analyzed to express the response of FSV to dual polarization SAR images with bands and polarization modes in the non-growing season in deciduous (Larch) and evergreen (Chinese pine) forests. Finally, mapped FSV using single and combined dual polarization images were derived by optimal feature sets and four machine learning models, respectively. The combined effects were also analyzed to clarify the difference of bands and polarization modes in deciduous and evergreen forests in the non-growing season. The results demonstrated that the backscattering energy from different sensors is significantly different in Chinese pine, and the difference is gradually reduced in Larch forests. It is also implied that the polarization mode is more important than penetration capability in mapping forest FSV in deciduous forest in the non-growing season. By comparing the accuracy of mapped FSV using single and combined images, combined images have more capability to improve the accuracy and reliability of mapped FSV. Meanwhile, it is confirmed that compensation effects with bands and polarization modes not only have great potential to delay the saturation phenomenon, but also have the capability to reduce errors caused by overestimation.

Biophysical factors control the interannual variability of evapotranspiration in an alpine meadow on the eastern Tibetan Plateau

Evapotranspiration (ET) is a key parameter regulating land–atmosphere interaction processes and the water cycle. The seasonal and interannual variability of ET and its environmental controls over an alpine meadow in a subfrigid humid zone of the Tibetan Plateau (TP) are reported on. Direct measurements were made using the eddy covariance method over a 10-year period with a significant increase in growing season length (GSL). The results showed that annual ET for the alpine meadow site was 492 ± 66 mm in comparison with 635 ± 88 mm of precipitation (P), with a ratio of ET/P ranging from 0.63 (2017) to 1.04 (2010). The path analysis and Priestley–Taylor coefficient (ET/ETeq) revealed that the daily ET experienced energy-limited and water-limited seasons within the year. During the water-limited non-growing season, the daily surface conductance (Gs) and ET/ETeq increased positively with soil water content (SWC). During the energy-limited growing season, the 16-day average ET, ET/ETeq, and Gs scaled positively with the normalized difference vegetation index (NDVI). ET/ETeq increased nonlinearly with an increase in Gs, but was insensitive to increases in Gs greater than the threshold Gs*. The mean Gs and Gs* were strongly regulated by the maximum NDVI. The maximum NDVI, Gs*, and annual mean Gs explained 46%, 80%, and 68%, respectively, of interannual variation in annual ET. Thus, we concluded that biophysical factors, rather than P and GSL, mainly controlled the interannual variability in annual ET. These findings are critical for understanding the response mechanism of ET to the changing biotic and abiotic conditions in the TP.

Impacts of clumping effect on canopy reflectance using 3D radiative transfer modeling

The product of leaf area index (LAI) and clumping index (CI) quantifies the effective leaf abundance and distribution across the landscape, and therefore, governs the radiation absorption, evapotranspiration, and carbon assimilation processes in the terrestrial ecosystems. Previous studies were mainly focused on developing inversion methods applicable to large scale for retrieving LAI and CI from multi-angular satellite observations. However, a few studies focused on quantifying the sensitivity of canopy bidirectional reflectance distribution function (BRDF) to changes in CI in a forward manner, hampering an accurate understanding of the relationship between CI and BRDF. In this study, we simulated how BRDF responds to changes in CI in Qinghai spruce (Picea crassifolia) forests based on a 3D radiative transfer model LESS and ground-measured data. We found that the LESS model effectively simulated the hot-spot, roof, and bowl-edge characteristics of the canopy BRDF by changing the sun-sensor geometry. We constructed forest scenes with variable CI (ranging from 0.4 to 0.8) to investigate the clumping effect on BRDF with different solar and observation angles. The red band bidirectional reflectance factor (BRF) showed higher sensitivity to changes in CI than that in the near-infrared (NIR) band. Canopy BRFs in the red band along the principal plane and cross principal planes measured in different seasons showed consistent sensitivity to changes in CI, suggesting that the red band BRF is helpful for CI inversion for forests with different levels of foliage clumping. In the NIR band, canopy BRFs along the principal plane measured in growing seasons [with solar zenith angle (SZA) <40°] and the cross principal plane measured in non-growing seasons (with SZA >40°) were sensitive to changes in CI in highly clumped forests (with CI ranging from 0.4 to 0.6). However, canopy BRF in the NIR band showed low sensitivity to changes in CI in highly clumped forests (CI <0.6), especially along the cross principal plane when SZA was approximately 10°. The simulated BRFs in the red and NIR bands showed relatively low sensitivity to changes in SZAs at a VZA of 40° and 0°, respectively. We highly recommend including the red band BRF for CI retrievals, and using a VZA of 40° in the red band and 0° in the NIR band may help reduce the CI estimation uncertainty caused by changes in SZA. This research provides a new perspective for understanding the sensitivity of multi-angular satellite data to changes in canopy structural characteristics of vegetation in global ecosystem studies and may help improve CI estimations using the multiangular optical remote sensing data.

Grazing effects on total carbon and nitrogen content of wind‐eroded soils in desert steppe

AbstractA high stocking rate can intensify wind erosion in grasslands, and strong wind can carry away soil surface particles, soil carbon (C), and nitrogen (N), which leads to soil barrenness. In this research, the dust flux, total carbon (TC) and total nitrogen (TN) contents, and fluxes of aeolian sediment were determined in the nongrowing season (mid‐October to mid‐April of the following year) and growing season (mid‐April to mid‐October) from 2017 to 2020 at a continuous grazing gradient experiment platform established in 2004 in a desert steppe in Inner Mongolia, China. The results were as follows: (1) As the stocking rate increased, fluxes of aeolian sediment at 10 cm (H10), 30 cm (H30), and 100 cm (H100) were greatly increased (p < 0.05). Aeolian sediment fluxes followed the order control (CK) < light stocking rate (LG) < moderate stocking rate (MG) < heavy stocking rate (HG). (2) The TC and TN contents of aeolian sediment decreased with an increase in stocking rate, and higher grazing intensity resulted in a difference in TC content, which decreased between the two seasons. The TC flux/aeolian sediment flux increased with an increase in stocking rate, and the ratio of TC flux increased between two seasons due to the influence of heavy grazing. Grazing disturbance had little effect on TN flux. As grazing intensity increased, wind erosion resulted in an increase in soil available carbon loss, and this loss was more severe in the nongrowing season. (3) The C/N ratio increased with increase in aeolian sediment flux. The aeolian sediment flux and C/N showed an inverse relationship with the increase in grazing intensity. Regression lines for the two seasons showed an intersecting trend, and the intersection points moved backward as height increased, indicating that higher stocking rates could reduce the influence of grassland vegetation on C/N. As height increased, the regression intercept increased, indicating that the loss of wind‐eroded soil changed from a low C/N loss to a high C/N loss. In general, high stocking rates aggravated soil wind erosion, resulting in more C pool loss than N loss in terms of soil elements and more available C loss in the nongrowing season. In the nongrowing season, vegetation characteristics are poor, coupled with grazing interference, and wind erosion in the nongrowing season is serious in general; however, the change law of C and N in wind‐eroded soil is directly related to its particle size. C and N content in fine particles is higher, and C content in soil is much higher than N, so the TC loss is relatively large; therefore, reducing the intensity of grazing can reduce the occurrence of soil wind erosion, and implementing measures to protect grassland in spring and other periods vulnerable to wind erosion would be conducive to the sustainable usage of grassland resources.

Effect of In Situ Large Soil Column Translocation on CO2 and CH4 Fluxes under Two Temperate Forests of Northeastern China

Global warming has a significant impact on soil carbon dioxide (CO2) and methane (CH4) fluxes in temperate forests. However, due to a lack of field observations, limited information is available about the responses of soil CO2 and CH4 fluxes to changes in temperature during the non-growing season and throughout the year in temperate forests. The broadleaf and Korean pine mixed mature forest (MF) and adjacent secondary white birch forest (BF) at different succession stages in the Changbai mountain region in northeastern China were selected, to study the effect of in situ soil column translocation on CO2 and CH4 fluxes in temperate forests. On average, the air temperature and soil temperature at 5 cm depth under BF stands from October 2018 to October 2022 increased by 0.64 and 0.42 °C during the non-growing season and by 0.49 and 0.43 °C throughout the year, respectively, compared with those under MF stands. Based on multi-year measurements in field experiments, it was shown that during the non-growing season, fluxes of CO2 and CH4 from soil columns under MF and BF stands ranged from 0.004 to 1.175 and from 0.015 to 1.401 (averages of 0.321 and 0.387) μmol CO2 m−2 s−1, and from −1.003 to 0.048 and from −1.037 to −0.013 (averages of −0.179 and −0.250) nmol CH4 m−2 s−1, respectively, accounting for approximately 20.8% and 25.3%, and 48.8% and 69.1% of the corresponding average fluxes during the growing season. When undisturbed soil columns of MF were transferred to a BF stand, to simulate warming, the cumulative soil CO2 emissions and CH4 uptake increased by 23.5% and 15.3% during the non-growing season, and by 9.5% and 16.3% across the year, respectively. However, when soil columns of BF were transferred to a MF stand, to simulate cooling, the cumulative soil CO2 emissions decreased by 16.9% and 0.1% during the non-growing season and across the year, respectively. Upon cooling, the cumulative soil CH4 uptake decreased by 21.8% during the non-growing season but increased by 15.4% across the year. The soil temperature and moisture at 5 cm depth in soil columns could explain 84–86% of the variability in CO2 fluxes and 16–51% of the variability in CH4 fluxes under the two forest stands throughout the field measurement period. The results of the in situ soil column translocation experiments highlight that a small climate warming in nature can increase soil CO2 emissions and CH4 uptake in the temperate forests of northeastern China, particularly during the non-growing season, which should be considered when predicting soil C fluxes in the temperate forests of northeastern China under global warming scenarios.

Sheepfolds induce significant increase of seasonal CO2, CH4 and N2O emissions in temperate steppes of Inner Mongolia

IntroductionThe changes in grassland management and grassland types are strongly linked with dynamics in soil physico-chemical properties and vegetation attributes, with important implications for carbon/nitrogen cycling and greenhouse gas (GHG) fluxes. However, the seasonal variations of GHG emissions from sheepfolds, and the underlying biotic and abiotic drivers affecting GHG exchanges across different steppe and management types remain largely unclear.MethodsTaking the Inner Mongolian grassland as a model system, we measured the fluxes of CO2, CH4 and N2O, as well as soil and vegetation variables, in three contrasting grassland management areas (grazing, sheepfold, enclosure) and in three representative (wet typical, dry typical, desert) grassland ecosystems in July, September and November 2016.ResultsOur results showed that: (1) GHG fluxes were mostly higher in the plant growing season (July and September) than in the nongrowing season (November); sheepfold area had significantly higher GHG emissions (in July and mean over the season) than enclosed and grazing areas, with the effects being most pronounced in dry typical steppe. (2) The high GHG emissions in dry typical steppe were closely associated with the interactions among favorable soil temperature and moisture, high total organic carbon (TOC) content, and high aboveground biomass. The important predictors for CO2 emission were soil TOC and pH, whereas that for CH4 and N2O emissions were soil temperature and moisture content, in sheepfold areas. (3) Three GHG emissions were negatively affected by species richness across all steppe and management types, which might be a consequence of indirect effects through the changes in soil TOC and total nitrogen (TN).DiscussionThese results indicate that sheepfold areas are intensive hotspot sources of GHGs in the steppes, and it is of great importance to help to account GHG emissions and develop mitigation strategies for sheepfold areas for sustainable grassland management in the natural steppe based pastoral production ecosystems.

Gas storage of peat in autumn and early winter in permafrost peatland

The carbon (C) balance of permafrost peatlands in autumn and winter, which affects the annual C budget estimation, has become a hotspot of studies on peatlands C cycle. This study combined the static chamber method, in situ soil profile measurements, and incubation experiments to investigate release and storage of C during autumn and early winter in a permafrost peatland in the Da Xing'an Mountains, Northeast China. Our results showed that the peak values of CH4 fluxes (30 August 2016) lagged behind those of CO2 fluxes (24 July 2016). At the onset of soil freezing, CH4 fluxes slightly increased, while CO2 fluxes decreased. During soil freezing in autumn, gases were found to be mainly stored in the soil as dissolved CH4 and CO2 and dissolved C concentrations (CH4, CO2, and DOC (dissolved organic carbon)) increased with depth. DOC concentrations were closely related to dissolved C gases, implying that the stored dissolved C gases might be derived from DOC decomposition. The CO2: CH4 ratio decreased sharply from the freezing of the surface layer to the total freezing of the soil, indicating larger CH4 storage in totally frozen soil. The incubation experiments also showed larger CH4 storage in the frozen soils and the stored C gases could influence the assessment of C emissions during thawing. These findings have important implications for clarifying the gas storage of permafrost peatland in autumn and early winter. The results may also clarify the key link of C emissions between the growing season and the nongrowing season.

Analyses of the Effectiveness of Different Media Depths and Plant Treatments on Green Roof Rainfall Retention Capability under Various Rainfall Patterns

Green roofs have been used to reduce rainfall runoff by altering hydrological processes through plant interception and retention as well as detention within the green roof system. Green roof media depth, substrate type, plant type and density, regional climatic conditions, rainfall patterns, and roof slope all impact runoff retention. To better understand the impacts of media depth (10, 15, and 20 cm), plant (planted and non-planted), and rainfall pattern (low, medium, and high) on rainfall retention, we analyzed data collected between September 2005 and June 2008 from 24 green roof models (61 cm × 61 cm) for growing and non-growing seasons. Our results showed that a planted green roof has greater rainfall retention capability than a non-planted green roof for all media depths. Interestingly, a non-planted green roof system with a 10 cm media depth retained greater rainfall than a planted green roof during both growing and non-growing periods. Retention capability decreased with increasing rainfall amounts for both planted and non-planted green roofs and seasons (growing and non-growing). The 15 cm media depth green roof retained significantly greater rainfall depth than the 20 cm models during medium (0.64 to 2.54 cm) and high (>2.54 cm) rainfall events for the growing season but not during the non-growing season. The study provides insight into the interactive effects of media depth, rainfall amount, plant presence, and seasons on green roof performance. The results will be helpful for designing economical and effective green roof systems.

Effects of tree density and herbaceous plants on tree seedling survival across the growing and non-growing season in a temperate forest

Tree seedling survival is critical for estimating forest recruitment, but it remain elusive about how neighboring tree’s density and herbaceous plants affect it. To assess the relative importance of tree density and herbaceous plants on tree seedling survival during the growing season and non-growing season, we established a two-year experiment with seedling census and removal of herbaceous plants in both secondary and old-growth temperate forest sites in the temperate forests of northeastern China. A total of 3,443 seedlings in 17 tree species were surveyed in this study. We found that both tree density and herbaceous plants significantly affected tree seedling survival, but the specific effects depended on shade tolerance, seedling growth stage and growing season. Conspecific adult neighbors had significant negative effects on the survival of shade-tolerant seedlings during the growing season, while conspecific seedling densities positively correlated with shade-intolerant seedlings. Herb removal significantly improved the survival of newly germinated and shade-intolerant seedlings during the growing season. Furthermore, we found that the survivals of both newly germinated and established seedlings differed seasonally in response to adult, seedling neighbors and herb removal. Herb removal enhances seedling survival during the non-growing season by offsetting the negative effects of conspecific adult neighbors during the growing season. Our findings provide new evidence for seedlings’ shade tolerance, growth stage and seasonal dependence of density dependence in temperate forests, and highlight the significance of herbaceous plants for seedling survival, an important factor that has been neglected in many previous studies.

Effect of Autumn Irrigation on Salt Leaching under Subsurface Drainage in an Arid Irrigation District

Non-growing season irrigation and farmland subsurface drainage play a crucial role in salt leaching and salinization control in arid irrigation areas. This study aimed to investigate the reduction of autumn irrigation quotas and drainage discharge while maintaining soil moisture retention and reducing soil salinization. Field experiments were conducted with different autumn irrigation quotas (160 mm for SD1, 180 mm for SD2, and 200 mm for SD3) combined with subsurface drainage (1.5 m drain depth and 45 m spacing). A control treatment (referred to as CK) without subsurface drainage received 200 mm of irrigation. The results showed that, after 31 days of autumn irrigation, the groundwater depth in all three subsurface drainage plots stabilized to 1.5 m, with the CK being 0.2–0.3 m shallower compared to the SD plots. The mean soil water content in the 0–150 cm soil layer of the SD1, SD2, SD3, and CK after autumn irrigation was 0.36, 0.39, 0.41, and 0.42 cm3cm−3, respectively. The combination of autumn irrigation and subsurface drainage significantly reduced the soil salt content. The mean desalination rates in the root zone (0–60 cm) soil layer were 57.5%, 53.7%, 51.9%, and 45.1% for the SD3, SD2, CK, and SD1, respectively. The mean desalination rate of 60–150 cm was not significantly different between the SD2 and SD3 (p > 0.05), and both were significantly higher than that of the SD1 and CK (p < 0.05). The drainage discharge was 31, 36, and 40 mm in the SD1, SD2 and SD3, respectively. The amount of salt discharge through the drain pipe increased with increasing irrigation quota, which was 1.22 t/ha, 1.41 t/ha, and 1.50 t/ha for the SD1, SD2, and SD3, respectively. Subsurface drainage is an effective way to prevent salt accumulation in the soil, and an autumn irrigation quota of 180 mm is recommended for leaching of salinity in the Hetao Irrigation District. These findings provide valuable insights into optimizing irrigation practices and managing soil salinization in arid regions.

Effect of freeze-thaw cycles and biochar coupling on the soil water-soil environment, nitrogen adsorption and N2O emissions in seasonally frozen regions

Freeze-thaw cycles (FTCs) usually occur in the nongrowing season of crops, and the temporal mismatch between soil nitrogen (N) supply and crop N utilization increases the risk of N loss. Crop straw burning is a seasonal air pollution source, and biochar provides new alternatives for waste biomass recycling and soil pollution remediation. To investigate the effect of biochar on N loss and N2O emissions under frequent FTCs, different biochar content treatments (0 %, 1 %, 2 %) were set, and laboratory simulated soil column FTC tests were conducted. Based on the Langmuir and Freundlich models, the surface microstructure evolution and N adsorption mechanism of biochar before and after FTCs were analyzed, and the change characteristics of the soil water-soil environment, available N and N2O emissions under the interactive effect of FTCs and biochar were studied. The results showed that FTCs increased the oxygen (O) content by 19.69 % and the N content by 17.75 % and decreased the carbon (C) content by 12.39 % of biochar. The increase in the N adsorption capacity of biochar after FTCs was related to changes in surface structure and chemical properties. Biochar can improve the soil water-soil environment, adsorb available nutrients, and reduce N2O emissions by 35.89 %–46.31 %. The water-filled pore space (WFPS) and urease activity (S-UE) were the main environmental factors determining N2O emissions. Ammonium nitrogen (NH4+-N) and microbial biomass nitrogen (MBN), as substrates of N biochemical reactions, significantly affected N2O emissions. The interaction of biochar content and FTCs in different treatments had significant effects on available N (p < 0.05). The application of biochar is an effective way to reduce N loss and N2O emissions under the action of frequent FTCs. These research results can provide a reference for the rational application of biochar and efficient utilization of soil hydrothermal resources in seasonally frozen soil areas.

Post-Fire Evolution of Soil Nitrogen in a Dahurian Larch (Larix gmelinii) Forest, Northeast China

This study investigates the evolution of soil nitrogen (N) contents and forms along a 17-year wildfire chronosequence in the Daxing’an Mountains. Surface soil and subsoil samples were collected during different recovery periods after wildfires. Then, the mineral N (i.e., NH4+-N and NO3−-N) and amino acid-N (AAN) contents in the soil extracts were measured and used to calculate the different ratios as indicators of the N forms. The results showed that the NH4+-N, NO3−-N, and AAN contents increased immediately after the wildfire. With vegetation restoration, the NH4+-N and NO3−-N contents became similar to those of unburned forests nine years and two months after the wildfire, respectively. The AAN content was mostly recovered one year post-fire. The wildfire did not lead to substantial changes in the mineral N form, but the ratio significantly increased and recovered after nine years. The soil available N form was altered by wildfires. After the wildfire, the dominant available N form changed from equivalent AAN and mineral N to a predominance of AAN in the growing season, and the predominance of AAN decreased to varying degrees in the non-growing season. With the recovery of the white birch and Dahurian larch, AAN again became the dominant N form, but the predominance of AAN was low before the freeze-up. Our study demonstrates that wildfires directly affect the soil N contents and forms, and such effects could be diminished by the restoration of the soil environment and vegetation over time.

Opposite response of N2O emissions in different seasons to warming and precipitation addition on a temperate steppe

AbstractClimate change is an important issue that affects both global warming and precipitation, and the main cause is increased N2O emissions. Temperature and moisture are key factors in grassland ecosystem's response to climate change, and they can affect N2O fluxes. To clarify the impacts of warming and precipitation changes on N2O fluxes, an experiment was conducted in a semiarid steppe in Inner Mongolia, China over a nine‐year period (2011–2019). Plant productivity and soil nutrient dynamics were examined concurrently from 2017 to 2019, and N2O fluxes were monitored in response to different treatment conditions: control (C), warming (W), precipitation addition (P), and warming and precipitation addition (WP). The results showed that N2O emissions in the growing season were higher than those in the nongrowing season. Warming and precipitation addition had no significant effect on N2O fluxes compared with ambient conditions. Compared with P treatment, warming increased N2O flux in nongrowing season and decreased it in growing season. N2O flux was positively correlated with soil temperature and moisture (p &lt; 0.05). Warming had a significant positive effect on soil NH4+‐N, whereas additional precipitation had a large positive effect on soil total nitrogen and soil nitrate nitrogen. With the WP treatment, soil microbial biomass nitrogen (MBN) and soil microbial biomass carbon (MBC) increased by 53.8% and 41.9%, respectively. The decrease in N2O emissions during the growing season in the W treatment compared with the P treatment may be largely attributed to the greater dominance of Leymus chinensis. The results highlight that changes in species dominance play an important role in regulating N2O emissions, and that the N2O fluxes in the nongrowing season account for a large proportion of the changes in N2O fluxes. Therefore, The warming effects on N2O emissions during nongrowing seasons should be further investigated.

Characteristics of net ecosystem exchange and source distribution of Xilinhot grassland, China.

To understand carbon sequestration capacity of grasslands, the changes of CO2 flux in Xilinhot grasslands and the influence of environmental factors were analyzed by using the eddy data of Xilinhot National Climate Observatory in 2018-2021, and the distribution of flux source areas was analyzed. The results showed that the southwest wind prevailed in the study area throughout the year, the source area in the growing season was larger than that in the non-growing season, and the source area under stable atmospheric conditions was larger than that under unstable conditions. The maximum length of source region with a contribution rate of 90% was close to 400 m, which was consistent with the length estimated by the classical law. The net ecosystem exchange (NEE) of Xilinhot grasslands had obvious diurnal and seasonal dynamics, which was manifested as a carbon sink in the daytime and a carbon source at night during the growing season and weak carbon source in the non-growing season. From 2018 to 2021, the annual total NEE were -15.59, -46.28, -41.94, and -78.14 g C·m-2·a-1, respectively, with an average value of -45.49 g C·m-2·a-1, indicating that Xilinhot grassland had strong carbon sequestration capacity. Vapor pressure deficit and photosynthetically active radiation helped grasslands absorb atmospheric CO2. At night, when temperature was above 0 ℃, the increases in air and soil temperature promoted vegetation respiration to release CO2.

Human activities impact the propagation from meteorological to hydrological drought in the Yellow River Basin, China

Quantifying the role of human activities in the process of drought propagation from meteorological drought to hydrological drought is helpful in developing mitigation strategies and in prediction of hydrological drought. To quantify the role of human activities, we compared the results from using simulated natural and observed streamflow to calculate drought indices and drought propagation time. In addition, we compared different propagation detection methods for evaluating the spatiotemporal characteristics of drought propagation from meteorological to hydrological in the Yellow River Basin during the period 1962–2018. The results show: (1) The intensity of meteorological drought (characterized by the standardized precipitation evapotranspiration index) in upstream regions showed an upward trend on the short-term (1-month) scale. At the 6-month scale, human activities reduced hydrological drought events (characterized by the standardized streamflow index) at 93% of stations in the midstream and downstream reaches. (2) The proposed center of gravity method is more suitable for calculating the propagation time after the impact of human activities, while the onset method is suitable for early drought warning. (3) Human activities shortened the propagation time for the controlled area of about 58% of stations (11 out of 19) during the growing season and prolonged it for the controlled area of about 53% of stations (10 out of 19) during the nongrowing season in the Yellow River Basin.

Potassium losses in runoff from cotton production fields

AbstractPotassium (K) loss in runoff represents a potential financial concern since fertilizer‐K is routinely applied to sustain optimal crop K nutrition and yield potential. Our research objectives were to quantify and characterize the soluble‐K loss in runoff from fields used for continuous cotton (Gossypium hirsutum L.) production while determining if the time of the year (growing season vs. nongrowing season), type of hydrological event (irrigation vs. rainfall), and cover crops influence K loss in runoff. Field‐scale, edge‐of‐field monitoring of runoff water and its soluble‐K concentration was performed on 10 site years in southeastern Arkansas across three production seasons. The mean K loss in surface runoff per event was 0.98 kg ha−1 across all sites and events (n = 304). The relationship between loss of K mass to runoff volume was positive and significantly correlated (p &lt; 0.0001) when both variables were transformed by the natural logarithm. K loss during the growing season was significantly higher (p &lt; 0.001) in the cotton growing season whereas K loss resulting from runoff events generated by either irrigation or rainfall was not significant. Additionally, losses from fields with cover crops were significantly larger (p &lt; −0.05) than from fields without covers. Cumulative annual‐K loss, between annual fertilizer‐K applications, averaged 32.2 kg K ha−1 across all site years representing a significant economic loss to replace the lost K with fertilizer. This study illustrates the increased risk of K losses on poorly drained soils in the Southeastern United States. Runoff‐K loss represents a significant amount of K that requires additional research on how to mitigate these losses.

Impact of warm spells during late fall and winter on frost hardiness of short-day treated Norway spruce seedlings

Warm spells during the late fall and winter are expected to become more frequent in boreal areas due to climate change. The aims of our study were to investigate whether warm spells in the late fall and winter cause deacclimation of Norway spruce (Picea abies (L.) Karst.) seedlings, whether the seedlings are capable of reacclimating in response to a subsequent cold period, and whether a short-day (SD) treatment applied in a nursery affects seedlings’ responses to warm and cold spells during the non-growing season (hereafter off-season). During the preceding growing season, the seedlings were treated either with a SD treatment (SD1: June 29 – July 20 or SD2: July 20 – August 10) or were grown in a natural photoperiod. The seedlings were artificially exposed to a 7-day warm spell, followed by a 7-day cold spell on four occasions (late fall: October and November; winter: January and March). The frost hardiness of the needles and the probability of bud damage were determined before and after the warm spell and after the cold spell. The dormancy status of the seedlings was also determined. Warm spells reduced the frost hardiness in needles and increased the probability of bud damage in January and March, but not in October and November. Needles were able to reacclimate from November to January, and buds also in early March. Our results indicate that in boreal areas, warm spells followed by low temperatures may predispose Norway spruce seedlings to freezing damage later in the winter, but not in the late fall. The seedlings that received SD2 treatment retained an ability to reacclimate after a warm spell in March, unlike the seedlings in the other photoperiod treatments, indicating that the responses of seedlings to the fluctuating temperature conditions in winter are affected by the growth conditions during the previous growing season. Therefore, the use and timing of SD treatment may affect survival of fall-planted seedlings and seedlings that overwinter outdoors in nurseries, especially during snowless winters.

Nongrowing season soil nitrous oxide emissions as influenced by cover crops and fall tillage termination

Cropland soil is a major driver of global nitrous oxide (N2O) emissions. In cold climates, nongrowing season (NGS) emissions can be significant due to high fluxes during freeze–thaw (FT) cycles. Cover crops can alter key soil conditions that govern N2O-producing microbial processes, with multiple potential pathways to either increase or decrease N2O production during FT cycles. Cultivating cover crops in the fall to terminate may further disrupt these processes and the overall impact of cover crops on N2O emissions. Yet, few studies have touched on how termination practices of cover crops impact FT emissions over the NGS. Using the flux gradient method to continuously measure N2O emissions from a conventional corn–soybean rotation, we investigated the effects of summer-established cover crops (perennial ryegrass and crimson clover) (with cover crops, +CC; without cover crops, −CC) when terminated by fall cultivation (with fall cultivation, +FC; without fall cultivation, −FC) over a six-month NGS that was characterized by several freezing and thawing periods. Crimson clover cover crop was completely winterkilled, while the ryegrass survived on the +CC−FC field. Total NGS (Nov–Apr) emissions varied nearly 2.5-fold among treatments from 395.1 (−CC−FC) to 978.1 (+CC+FC) g N2O-N ha−1. Compared with the control treatment (−CC−FC), fall cultivation alone (−CC+FC) and cover crops alone (+CC−FC) increased total NGS N2O emissions, and fall cultivation with cover crops (+CC+FC) increased N2O fluxes even more. Careful CC species selection and management are important to avoid elevated NGS emissions.

Simulating nitrogen balance in Canadian agricultural soils from 1981 to 2016

Agriculture produces food, fiber and biofuels for the world's growing population, however, agriculture can be a major contributor of nitrogen (N) losses including emissions of ammonia (NH3), nitrous oxide (N2O) and nitrate (NO3−) leaching and runoff. A Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model was developed to estimate the soil N balance in 3487 soil landscape of Canada polygons from 1981 to 2016. The CANBNr model integrates NH3 emission from fertilizers, manure from housing, storage and field, as well as direct/indirect N2O emissions from fertilizers, manures, crop residues and soil organic matter. The NO3− leaching is estimated based on the residual soil N (RSN) at harvest and drainage derived with the DeNitrification-DeComposition (DNDC) model. From 1981 to 2016, the N input from fertilizer and N fixation increased at a greater rate than N removal in harvested crops in all provinces of Canada, resulting in an increase in the RSN and N losses. In 2016, the Prairie provinces had lower N losses (11.7 kg N ha−1) from N2O, NH3 and NO3− compared with 43.2 kg N ha−1 in central Canada, and 76.5 kg N ha−1 in Atlantic Canada. However, the Prairie provinces had 84.3% of the total Canadian farmland (74.3% of the total Canadian N input), while central Canada had 12.9% of Canadian farmland (21.7% of the total Canadian N input). In the Prairie provinces, the total N2O loss from fertilizer N ranged 4.4–8.6 Gg N whereas NH3 loss ranged from 17.1 to 44.6 Gg N and these values were influenced by both emission intensity and total land area. Total N2O losses from manure were highest in Alberta, Ontario and Quebec resulting in 4.8, 4.4, and 3.4 Gg N and NH3 losses from manure were also highest in these 3 provinces at 61.1, 45.2 and 40.4 Gg N, respectively. Nitrate leaching was impacted by drainage volumes, soil type and N inputs. In the non-growing season, NO3− leaching losses (36-yr average) were 63.3 Gg in Ontario and 57.5 Gg N in Quebec compared with 20.8 Gg N for Ontario and 35.5 Gg N for Quebec in the growing season. In contrast, the Prairie provinces showed higher NO3− leaching in the growing season (23.1–37.4 Gg N) than in the non-growing season (10.4–13.7 Gg N). In summary, total fertilizer N increased the most over the 36 years in the Prairies which resulted in increased RSN and N leaching losses that will require further intervention.

Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models

Timely and cost-effective crop yield prediction is vital in crop management decision-making. This study evaluates the efficacy of Unmanned Aerial Vehicle (UAV)-based Vegetation Indices (VIs) coupled with Machine Learning (ML) models for corn (Zea mays) yield prediction at vegetative (V6) and reproductive (R5) growth stages using a limited number of training samples at the farm scale. Four agronomic treatments, namely Austrian Winter Peas (AWP) (Pisum sativum L.) cover crop, biochar, gypsum, and fallow with sixteen replications were applied during the non-growing corn season to assess their impact on the following corn yield. Thirty different variables (i.e., four spectral bands: green, red, red edge, and near-infrared and twenty-six VIs) were derived from UAV multispectral data collected at the V6 and R5 stages to assess their utility in yield prediction. Five different ML algorithms including Linear Regression (LR), k-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Regression (SVR), and Deep Neural Network (DNN) were evaluated in yield prediction. One-year experimental results of different treatments indicated a negligible impact on overall corn yield. Red edge, canopy chlorophyll content index, red edge chlorophyll index, chlorophyll absorption ratio index, green normalized difference vegetation index, green spectral band, and chlorophyll vegetation index were among the most suitable variables in predicting corn yield. The SVR predicted yield for the fallow with a Coefficient of Determination (R2) and Root Mean Square Error (RMSE) of 0.84 and 0.69 Mg/ha at V6 and 0.83 and 1.05 Mg/ha at the R5 stage, respectively. The KNN achieved a higher prediction accuracy for AWP (R2 = 0.69 and RMSE = 1.05 Mg/ha at V6 and 0.64 and 1.13 Mg/ha at R5) and gypsum treatment (R2 = 0.61 and RMSE = 1.49 Mg/ha at V6 and 0.80 and 1.35 Mg/ha at R5). The DNN achieved a higher prediction accuracy for biochar treatment (R2 = 0.71 and RMSE = 1.08 Mg/ha at V6 and 0.74 and 1.27 Mg/ha at R5). For the combined (AWP, biochar, gypsum, and fallow) treatment, the SVR produced the most accurate yield prediction with an R2 and RMSE of 0.36 and 1.48 Mg/ha at V6 and 0.41 and 1.43 Mg/ha at the R5. Overall, the treatment-specific yield prediction was more accurate than the combined treatment. Yield was most accurately predicted for fallow than other treatments regardless of the ML model used. SVR and KNN outperformed other ML models in yield prediction. Yields were predicted with similar accuracy at both growth stages. Thus, this study demonstrated that VIs coupled with ML models can be used in multi-stage corn yield prediction at the farm scale, even with a limited number of training data.