This study aimed to explore the structure and stability characteristics of zonal soil aggregates in cold high‐altitude regions and reveal the variation patterns of alpine soil aggregates, using the ...Three Rivers Source of the Qinghai‐Tibetan Plateau as an example. Zonal soils representing the local vegetation types (alpine meadow soil, alpine grassland soil) were collected, and soil aggregates were separated using wet and dry sieving methods. Random forest modeling was used with climate data from 2011 to 2019 as variables in order to generate multifactor digital maps of water‐stable and mechanically stable aggregates. The composition and differences of zone‐specific soil aggregates were compared and analyzed using the evaluation indices of macroaggregate content (R > 0.25), mean weight diameter (MWD), geometric mean diameter, and fractal dimensions. Their controlling factors were also explored. The study results showed that the model's explanatory power for soil aggregates was over 68%. In the random forest model, elevation and sunshine duration contributed more to soil water‐stable aggregates, whereas precipitation contributed more to soil mechanically stable aggregates. The content of large aggregates with particle size greater than 0.5 mm was higher in alpine meadow soils than in alpine grassland soils. In contrast, the content of large aggregates with particle size less than 0.5 mm was lower than that of alpine grassland soils. There are also some differences in the distribution of water‐stable aggregates and mechanically stable aggregates between alpine meadow soils and alpine grassland soils in each particle size, and these differences are most pronounced in the particle sizes >2 and <0.25 mm. In addition, the stability of alpine meadow soil aggregates is higher than that of alpine grassland soil aggregates. Finally, the mapping results show that the stability of soil aggregates in the study area has similar zonal characteristics to the zonal variation of vegetation cover and climate and other factors.
Core Idea
Using the Three‐River‐Source region as an example, this paper aimed to study the mechanical and water stability of aggregates of two different soil types.
This study aims to explore the structure and stability characteristics of zone‐specific soil aggregates.
Random forest modeling was used with climate data from 2011 to 2019 as co‐variables.
Many functions have been proposed to describe the response of root water uptake to water and/or salinity stresses. In practice, choosing a reliable stress response function is challenging, ...particularly when water and salinity stresses occur simultaneously. To explore and quantify the effects of soil water and salinity conditions, separately and combined, on root water uptake, two experiments culturing winter wheat in artificial climate chambers were conducted with various water and salinity levels. As the key index, plant water status was evaluated by: a) considering the relative position of water and salinity to roots; b) rectifying estimation of potential transpiration for stressed plants; c) excluding data during recovery periods dominated by the hysteresis process of historical stress; and d) quantifying the interaction between water and salinity stresses. Including only one fitting parameter and two water or salinity thresholds with clear physical meaning and available recommendations, concave-convex function could quantify the effects of water or salinity stress more accurately than the others, leading to more reliable estimation of relative transpiration rate (RMSE < 0.07, R2 > 0.91, MAE < 0.24). Under combined water-salinity stress conditions, neither an additive nor multiplicative approach was able to describe the interaction accurately. In addition to cumulative effect, by quantifying cross-adaptation effect with an exponential function, the multiplicative concave-convex functions significantly improved the estimation of relative transpiration rate for water- and salinity-stressed plants (RMSE < 0.08, R2 > 0.72, MAE < 0.28). Nevertheless, mechanisms underlying the interaction between water and salinity stresses are still unclear and should be further investigated. To avoid the hysteresis effect of historical stress, excluding data during recovery periods was helpful, but its quantitative characterization is also necessary for accurate simulation of root water uptake and should be further studied.
•Improved method to screen soil water and salinity stress response functions.•Concave-convex soil water and salinity stress response functions are superior.•Cross-adaptation effect between water and salinity stresses was quantified.•Multiplicative approach was improved to quantify combined water and salinity stress.
Different types of mulching film could variously influence soil properties and plant growth. Yet, surprisingly few studies have investigated the effects of mulching film upon soil microbial diversity ...and community structure. In this research, two kinds of mulching film, a traditional PE (polyethylene) mulching film and a degradable PBAT ((Poly butyleneadipate-
co
-terephthalate)) mulching film, were applied to cotton (
Gossypium
spp.) plants grown in Xinjiang Province, China. The respective influence of the two mulching films on the cotton’s soil microbial (bacteria and fungi) diversity and community were investigated. The results showed that applying the PBAT mulching film could significantly alter the diversity of non-rhizosphere soil fungi when compared to using the PE mulching film. However, neither the PE nor PBAT mulching film had any significant influence on the diversity of soil bacteria and rhizosphere soil fungi. Nevertheless, soil microbial community composition differed under the PBAT mulching film treatment vis-à-vis the PE mulching film treatment. The abundance of
Gibellulopsis
was higher under the PBAT than PE mulching film treatment. Our study’s findings provided an empirical basis for the further application of degradable PBAT mulching film for the sustainable development of cotton crops.
Key points
Degradable mulching film alter the diversity of cotton non-rhizosphere soil fungi.
Degradable mulching film alter the soil microbial composition of cotton.
Degradable mulching film dose not alter the diversity of cotton rhizosphere fungi.
Degradable mulching film dose not alter the diversity of cotton soil bacteria.
Aphis gossypii Glover is an important pest in cotton plantations. Medicago sativa L. (alfalfa) is a host plant for the aphid Aphis craccivora Koch and may prove to be an important reservoir of ...natural enemies to combat this pest. The objective of this study was to analyze the impact of different mowing frequencies of alfalfa traps on A. gossypii and their natural enemies, using both ground survey data and UAV remote sensing data. The alfalfa was mowed twice to facilitate the transfer of this primary natural enemy to the cotton fields. Ground surveys were carried out every five days to gather data, while temporal niche and niche overlap methods were used for further analysis. Findings collected over a period ranging from day 31 to day 91 indicated that compared to their counterparts with no alfalfa traps, the cotton fields containing these pest control measures demonstrated a reduction in the A. gossypii population of approximately 16%. A survey conducted 5 days after mowing the alfalfa on days 61 and 71 found that the cotton fields with alfalfa traps experienced a 24.14% and 26.09% reduction in A. gossypii numbers. In contrast, the cotton fields without alfalfa traps experienced a 76.92% and 55.08% increase in cotton aphid numbers during the same period. It is noteworthy that the cotton fields with alfalfa traps showed a delayed onset of cotton aphid damage of approximately 5 days compared to the fields without alfalfa traps. This discovery has significant implications for understanding the ecological control mechanism of A. gossypii within alfalfa traps. Planting alfalfa traps around fields in Xinjiang could be promoted as a method to prevent and control aphid damage.
Cotton harvest can be increased by having real-time information on the state of cotton aphid populations. However, traditional cotton aphid monitoring relies on ground sample methods supported by ...models such as linear regression, resulting in low forecast accuracy. Therefore, this paper purposes to enhance the precision of the remote sensing prediction model by investigating the cotton aphid prediction model construction approach. We explored the effectiveness of the XGBoost algorithm combined with the GWO algorithm and SVR method for cotton aphid prediction relying on vegetation indices derived from UAV multispectral photography. Originally, 12 indices related to cotton aphids were calculated by UAV multispectral reflectance. Additionally, the optimal index combination for pest prediction was determined utilizing analysis of correction and two-way ANOVA, combined with the XGBoost algorithm. Furthermore, a pest prevalence prediction model for cotton aphids was constructed via the SVR methodology associated with the optimal catalog combination, and the model was optimized using the GWO algorithm. Compared with the seven algorithms, experimental results demonstrate that the MSE and MAE of the XGBoost-GWO-SVR model are reduced by 90.20% and 70.36% (SVR), 90.14% and 70.26% (XGBoost-SVR), 7.47% and 0.14% (XGBoost-GA-SVR), 5.80% and 0.11% (XGBoost-PSO-SVR), 12.06% and 58.95% (LR), and 84.77% and 89.22% (BPNN), whereas the R 2 is increased by 22.5% (SVR and XGBoost-SVR), 0.3% (LR), and 12.51% (BPNN). The R 2 of the prediction model of XGBoost-SVR combined with GWO, PSO, and GA is not significantly different. Among these models, the XGBoost-GWO-SVR obtained the highest R 2 of 0.980 and the lowest MAE of 2.838.
Timely and accurate estimation of Above-Ground-Biomass (AGB) in cotton is essential for precise production monitoring. The study was conducted in Shaya County, Aksu Region, Xinjiang, China. It ...employed an unmanned aerial vehicle (UAV) as a low-altitude monitoring platform to capture multispectral images of the cotton canopy. Subsequently, spectral features and textural features were extracted, and feature selection was conducted using Pearson’s correlation (P), Principal Component Analysis (PCA), Multivariate Stepwise Regression (MSR), and the ReliefF algorithm (RfF), combined with the machine learning algorithm to construct an estimation model of cotton AGB. The results indicate a high consistency between the mean (MEA) and the corresponding spectral bands in textural features with the AGB correlation. Moreover, spectral and textural feature fusion proved to be more stable than models utilizing single spectral features or textural features alone. Both the RfF algorithm and ANN model demonstrated optimization effects on features, and their combination effectively reduced the data redundancy while improving the model performance. The RfF-ANN-AGB model constructed based on the spectral and textural features fusion worked better, and using the features SIPI2, RESR, G_COR, and RE_DIS, exhibited the best performance, achieving a test sets R2 of 0.86, RMSE of 0.23 kg·m−2, MAE of 0.16 kg·m−2, and nRMSE of 0.39. The findings offer a comprehensive modeling strategy for the precise and rapid estimation of cotton AGB.
Elevated CO
2
concentration e(CO
2
) often promotes plant growth with a decrease in tissue N concentration. In this study, three experiments, two under hydroponic and one in well-watered soil, ...including various levels or patterns of CO
2
, humidity, and N supply were conducted on wheat (
Triticum aestivum
L.) to explore the mechanisms of eCO
2
-induced N deficiency (ECIND). Under hydroponic conditions, N uptake remained constant even as transpiration was limited 40% by raising air relative humidity and only was reduced about 20% by supplying N during nighttime rather than daytime with a reduction of 85% in transpiration. Compared to ambient CO
2
concentration, whether under hydroponic or well-watered soil conditions, and whether transpiration was kept stable or decreased to 12%, eCO
2
consistently led to more N uptake and higher biomass, while lower N concentration was observed in aboveground organs, especially leaves, as long as N supply was insufficient. These results show that, due to compensation caused by active uptake, N uptake can be uncoupled from water uptake under well-watered conditions, and changes in transpiration therefore do not account for ECIND. Similar or lower tissue
NO
3
-
-N concentration under eCO
2
indicated that
NO
3
-
assimilation was not limited and could therefore also be eliminated as a major cause of ECIND under our conditions. Active uptake has the potential to bridge the gap between N taken up passively and plant demand, but is limited by the energy required to drive it. Compared to ambient CO
2
concentration, the increase in N uptake under eCO
2
failed to match the increase of carbohydrates, leading to N dilution in plant tissues, the apparent dominant mechanism explaining ECIND. Lower N concentration in leaves rather than roots under eCO
2
validated that ECIND was at least partially also related to changes in resource allocation, apparently to maintain root uptake activity and prevent more serious N deficiency.
China’s double carbon initiative faces huge challenges, and understanding the carbon sequestration service of terrestrial ecosystems under future interannual regional land use change is important to ...respond to China’s carbon policy effectively. Previous studies have recognized the important impact of land use/land cover (LULC) planning on carbon sequestration in terrestrial ecosystem services (ESs). However, exploring trends in carbon sequestration under sustainable development scenarios that combine economic and ecological development, particularly the mechanisms that balance the supply and demand of carbon sequestration, still requires in-depth exploration in different geographical contexts. In this study, we present the LULC simulation framework from 2000 to 2030 for four different development scenarios in the Xinjiang region, located in an important Belt and Road region, including business as usual (BAU), rapid economic development (RED), ecological land protection (ELP), and sustainable development with both economic and ecological development (SD). Our results suggest that both the supply and demand of carbon stock in Xinjiang will increase in 2025 and 2030, with the demand exceeding the supply. However, our scenario planning mitigates the supply and demand deficit situation for carbon sequestration in the context of future cropland expansion in different scenarios. In summary, our study’s findings will enrich the study of carbon sequestration under future scenarios in the Belt and Road region. Xinjiang should pay more attention to the dynamic changes in landscape type structure and its carbon storage supply and demand caused by cultivated land expansion. Among the four scenarios, the spatial difference between carbon storage supply and demand based on the SD scenario is the smallest, which is more in line with the high-quality development of regional ecological security in Xinjiang.
Drylands in northwest China have limited water resources, which negatively impacts economic development, ecological security, and the United Nations Sustainable Development Goals. However, few ...studies have examined water supply and demand under multiple future spatial patterns of land use, particularly under sustainable development scenarios. Further research is therefore needed to determine how affect water output services under various land use patterns. We used the GMOP-PLUS (Gray Multi-objective Optimization-Patch-generating Land Use Simulation) and the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models to investigate future land use programs and the current and future trends in water yield services supply and demand in the typical dryland region of Xinjiang, China. The GMOP-PLUS model was used to project the spatial patterns of land use/land cover (LULC) change in Xinjiang in 2025 and 2030 under programs of business-as-usual, rapid economic development, ecological land protection and sustainable development. We then used the InVEST model to project the spatiotemporal evolution of water yield services supply and demand under the four different scenarios. Our results show that Our results show that water production in Xinjiang decreases to 911.30 × 10
8
m
3
in 2020–2030 under the business-as-usual scenario, with an expansion in arable land and a reduction in forested land being the main causes of this decrease. The decline in water production under the ecological land protection scenario is 913.88 × 10
8
m
3
. The retention effect of vegetation slows the decline in water production, but the ecological land protection scenario is not effective in controlling the reduction in arable land. The rapid economic development scenario produces a significant increase in water yield of 915.09 × 10
8
m
3
, mainly due to an increase in the area of impervious surfaces caused by the expansion of built-up land; however, the rapid economic development scenario leads to a decreasing trend in ecological land. The sustainable development scenario produces 914.15 × 10
8
m
3
of water. The sustainable development scenario increases water production while balancing the development of Constructed and the protection of ecological land, and the arable land also shows a slow growth trend. Between 2025 and 2030, the water security index fluctuates between –0.0225 and –0.0400, with a continued future deficit in water supply and demand in Xinjiang and a high degree of spatial heterogeneity. Programs for advancing sustainable development narrow the supply–demand gap for services that produce water.
High-density planting is an effective technique to optimize yields of mulched cotton. On the other hand, deficit irrigation is an emerging water-saving strategy in cotton cultivation, especially ...suitable for arid and water-scarce areas. However, the relationships between deficit irrigation, high-density planting, and regulation mechanisms of canopy light radiation and light use efficiency (LUE) in cotton is not yet clear. To clarify the mechanism of light interception (LI) and the LUE of cotton canopies, three irrigation treatments 315 (50% Fc), 405 (75% Fc, farmers’ irrigation practice), and 495 mm (100% Fc), where Fc was the field capacity with three plant densities 13.5, 18.0 (farmers’ planting practice), and 22.5 plants m2 were applied. The findings of this research revealed that, under deficit irrigation, the above-ground dry matter (ADM) was reduced by 5.05% compared to the farmers’ irrigation practice. Over both years and across all plant densities, LI and LUE under deficit irrigation decreased by 8.36% and 4.79%, respectively, relative to the farmers’ irrigation practices. In contrast, LI and LUE for the highest irrigation level increased by 10.59% and 5.23%, respectively. In the case of the interaction (plant density and irrigation level), the ADM under deficit irrigation and high-density combination increased by 7.69% compared to the control (farmers’ irrigation × sowing practices interaction effects). The LI and LUE also exhibited an increase in 1.63% and 6.34%, respectively. Notably, the LI effect of the middle and upper cotton canopy under film drip irrigation reached 70%. A lower irrigation level resulted in a higher percentage of LI in the lower canopy region. The leaf area index, light interception rate, and extinction coefficient escalated with the increase in plant density. Under deficit irrigation treatment, the LI of the 0–30 cm canopy in high plant density settings increased by 8.6% compared to the control (farmers’ irrigation × sowing practices interaction effects). In conclusion, deficit irrigation and increased plant density improved the interception of LI and LUE of cotton canopy. These findings may help the farmers to optimize their agricultural management strategies in water-deficient areas.
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