Soil Vegetation Research Articles

Spatiotemporal Variability of Soil Erosion in the Pisha Sandstone Region: Influences of Precipitation and Vegetation

The Pisha sandstone area, situated in the upper and middle reaches of the Yellow River in China, is characterized by severe soil and water erosion, making it one of the most critical regions on the Loess Plateau. The rugged terrain and exposed bedrock complicate management efforts for this area, posing challenges for accurate forecasting using soil erosion models. Through an analysis of terrain, vegetation, and precipitation impacts on soil erosion, this study offers theoretical support for predicting soil erosion within the exposed Pisha sandstone area of the Loess Plateau. This has substantial implications for guiding water and soil conservation measures in this region. Focusing on China’s exposed sandstone area within the Geqiugou watershed, temporal and spatial changes in vegetation cover and land use from 1990 to 2020 were analyzed. The result shows that, from 1990 to 2020, the grassland area has exhibited a consistent downward trend, with successive reductions of 64.86% to 59.46%. The area of low vegetation cover witnessed a significant decline of 59.29% in 2020 compared to that in 1990. The moderate erosion area decreased from 84.52 to 57.17 km2. The significant reduction in soil and water loss can be attributed to the expansion of forest and grassland areas, with the implementation of the Grain for Green project serving as a key policy driver for facilitating this expansion. This study provided a good example of combining rainfall with vegetation coverage to fast estimation soil erosion. A mathematical relationship between the vegetation rainfall coupling index (RV) and soil erosion was established with strong fitting effects, enabling estimation of the soil erosion volume under varying slope conditions within Pisha sandstone areas. The main focus of future soil and water conservation in the Pisha sandstone area should be on effectively managing the channel slope and minimizing exposed bedrock areas through a combination of slope cutting, the application of anticorrosive materials, and the implementation of artificial vegetation planting.

Developing Site-Specific Prescription Maps for Sugarcane Weed Control Using High-Spatial-Resolution Images and Light Detection and Ranging (LiDAR)

Sugarcane is a perennial grass species mainly for sugar production and one of the significant crops in Costa Rica, where ideal growing conditions support its cultivation. Weed control is a critical aspect of sugarcane farming, traditionally managed through preventive or corrective mechanical and chemical methods. However, these methods can be time-consuming and costly. This study aimed to develop site-specific, variable rate prescription maps for weed control using remote sensing. High-spatial-resolution images (5 cm) and Light Detection And Ranging (LiDAR) were acquired using a Micasense Rededge-P camera and a DJI L1 sensor mounted on a drone. Precise locations of weeds were collected for calibration and validation. Normalized Difference Vegetation Index derived from multispectral images separated vegetation coverage and soil. A deep learning (DL) algorithm further classified vegetation coverage into sugarcane and weeds. The DL model performed well without overfitting. The classification accuracy was 87% compared to validation samples. The density and average heights of weed patches were extracted from the canopy height model (LiDAR). They were used to derive site-specific prescription maps for weed control. This efficient and precise alternative to traditional methods could optimize weed control, reduce herbicide usage and provide more profitable yield.

Impacts of long-term different fertilization regimes on microbial utilization of straw-derived carbon in greenhouse vegetable soils: insights from its ecophysiological roles and temperature responses

As the largest organic carbon input in the agroecosystems, crop residues can increase soil carbon sequestration and crop production in greenhouse vegetable fields (GVFs). However, the soil microbiological mechanisms driving straw decomposition in GVFs under different incubation temperatures and fertilization treatments are not clear. Thus, soil samples were collected from a long-term field experiment included chemical fertilizer application alone (CF), 2/4 fertilizer N+2/4 organic fertilizer N (CM), 2/4 fertilizer N+1/4 organic fertilizer N+1/4 straw N (CMS), 2/4 fertilizer N+2/4 straw N (CS), and incubated with 13C-labeled straw at different temperatures (15, 25, and 35°C) for 60 days. Organic-amended treatments (CM, CMS, and CS), especially CMS treatment, increased soil bacterial Alpha diversity before and after straw addition. Straw decomposition process was dominated by soil Proteobacteria, Actinobacteria, and Firmicutes for each treatments. The effect of incubation temperature on soil microbial community composition was higher than that of fertilization treatments. Soil Alphaproteobacteria and Actinomycetia were the most predominant class involved in straw decomposition. Gammaproteobacteria (Pseudomonas, Steroidobacter, Acidibacter, and Arenimonas) were the unique and predominant class involved in straw decomposition at medium and high temperatures as well as in the straw-amended treatments. Organic-amended treatments, especially straw-amended treatments, increased the relative abundance of glycosyl transferases (GT) and auxiliary activities (AA). Alphaproteobacteria, Actinomycetia, and Gammaproteobacteria had higher relative contribution to carbohydrase genes. In summary, the long-term organic-amended treatments altered the structure of soil microbial communities and increased soil bacterial diversity, with the CMS having a greater potential to enhance resistance to external environmental changes. Soil Alphaproteobacteria and Actinomycetia were responsible for the dominance of straw decomposition, and Gammaproteobacteria may be responsible for the acceleration of straw decomposition. Fertilization treatments promote straw decomposition by increasing the abundance of indicator bacterial groups involved in straw decomposition, which is important for isolating key microbial species involved in straw decomposition under global warming.

Patterns of foliar fungal diseases and the effects on aboveground biomass in alpine meadow under simulated climate change

1.Global warming and changes in precipitation patterns significantly affect plant fungal diseases, especially plant foliar fungal diseases. Research surrounding the effects of climate change on plants are mostly concentrated on aboveground vegetation and belowground soil microorganisms, with limited attention given to foliar fungal disease. Additionally, little is known whether climate change experiments can simulate the impact of variations on foliar diseases within real natural communities.2.We conducted a long-term experiment to investigate the effect of warming and altered precipitation on plant disease in an alpine grassland on the north-eastern Tibetan Plateau. Our study tracked foliar disease across 26 species of plants including non-legume forbs, legumes, grasses and sedges from 2019 to 2021. Each species was included in a two-factor full factorial experiment manipulating both temperature and precipitation.3.In our study the non-legume forb functional group carried the primary pathogen load, sedges maintained a near zero pathogen load across all investigated scenarios. Warming significantly elevated the pathogen load in legumes and non-legume forbs, while it reduced the pathogen load of grasses. Conversely, decreased precipitation significantly increased the pathogen load of non-legume forbs and increased the pathogen load of grasses. Notably, we found that pathogen load was primarily influenced by the direct effects of warming and precipitation, rather than indirectly through changes in plant community structure. Meanwhile, interannual climate variability exhibited a strong correlation with plant community pathogen loads. Areas experiencing increased temperature and precipitation showed lower fungal disease pressure, whereas regions with elevated temperatures combined with decreased precipitation faced a heightened risk of disease in alpine meadows on the Qinghai-Tibet Plateau.4.Our findings reveal that warming and decreased precipitation led to a reduction in above-ground biomass associated with increased the pathogen load of legumes. This underscores the importance of pathogen effects in both climate change prediction and ecological management.

Winter Grazing, Not Fencing or Unicast, Promotes Stability of Microbial Community and Function in the Qilian Mountains of Qinghai‐Xizang Plateau

ABSTRACTIn alpine meadows, microorganisms are essential to sustain the stability of terrestrial geochemical processes and vegetation–soil–microbial systems. The present study in order investigate how various management measures impact the microbial communities' composition and functionality, we utilize metagenomic sequencing techniques to examinate the composition and function of soil microbial communities in the southern Qilian Mountains of the Qinghai‐Xizang Plateau in response to the management practices of fencing enclose (FE), winter grazing (WG), transition zone between natural and artificial grasslands (TZ), and artificial unicast oats (AU). Vegetation diversity and soil physicochemical characteristics were dramatically altered by the management measures. The prokaryotic community structure was considerably similar in FE and WG, as well as in TZ and AU. Near‐natural (FE) and artificial establishment (AU) disturbances changed the fungal community structure. Enzymes related to carbon metabolism did not respond significantly to the management measures, whereas those related to nitrogen metabolism did not respond significantly in TZ and AU. The relative abundance of enzymes participating in nitrogen metabolism was higher under TZ and AU than under FE and WG. We concluded that grassland management measures altered the structure of aboveground graminoid and leguminous vegetation communities and belowground biomass allocation, resulting in changes in K uptake, causing striking changes in the structure of fungal communities and nitrogen‐metabolizing enzymes; moderate disturbance (WG) was beneficial for maintaining the stability of microbial communities in alpine grasslands.

Hysteresis in seasonal land-atmospheric interactions over India and its characteristics across croplands and forests

Abstract Satellite-derived Vegetation Optical Depth and Soil Moisture (SM) data reveal the critical role of the soil-vegetation continuum in storing rainwater during the Indian Summer Monsoon and supporting evapotranspiration (ET) during the dry non-monsoon season. During the non-monsoon drier period, the climatologically estimated spatial mean of ET exceeds precipitation input, a phenomenon known as the Soil-Vegetation Capacitor (SVC) effect, which is pivotal in maintaining ecosystem productivity. Notably, our analysis reveals significant variations in the capacitor period between croplands and forests, with croplands exhibiting a ~77 days longer due to dual crop seasons influenced by regional precipitation. The well-recognized hysteresis curves, observed in magnetization and soil-water characteristic curves (SWCC), highlight phenomena where a system's state is influenced by its historical inputs or states and are integral to our findings. We report a previously undocumented seasonal hysteresis in the relationship between the evaporative fraction (EVF) and SM for Indian croplands and forests. We further found that the croplands SM-EVF relation exhibits a reversal in hysteresis in the case of root-zone SM. The surface SM-EVF hysteresis is not present in forests with large root depths and reduced soil evaporation due to high canopy shading, and yet it is present for the root-zone SM. With its reversal for croplands, the newly found hysteresis must be addressed in redefining the critical SM threshold to demarcate the energy and water-limiting regimes. It should be incorporated in the land surface modeling parameterization. Additionally, we observed hysteresis in the soil moisture-gross primary productivity (SM-GPP) relationship across both land covers and soil profiles (surface and root-zone), underscoring the need to investigate such processes to consider their dynamics in future ecological and hydrological models.

Flooded area detection and mapping from Sentinel-1 imagery. Complementary approaches and comparative performance evaluation

ABSTRACT The current study assesses the performance of several machine learning (ML) and deep learning (DL) models for detecting and mapping floods using Sentinel-1 SAR imagery. Three distinct approaches were used: pixel classification, object-based image analysis and object instance segmentation. The ML models are Random Forest, and Support Vector Machine and the DL models are U-NET, DeepLabV3 and Mask RCNN. Five different case studies were selected to test the models’ scalability. These areas are in Romania (Prut River, at the border between Romania, the Republic of Moldova and Ukraine, Timiș River, and Râul Negru River), the United States of America (Missouri River) and Australia (Broughton Creek). For each flood, five Sentinel-1 images were used, four collected before the flood and one collected after the flood. The intensity images were stacked and scaled in the range of the intensity thresholds associated with water and non-water so that all the case studies have the same margins for intensity. Samples of water, vegetation, agricultural fields, and bare soil were collected only from the Prut River case study and used in the training process. Out of all models, the U-Net model returned the highest accuracy with a value for Intersect over Union of 0.763 for a tile size of 128x128 pixels.

Correlations between Tree/Shrub Diversity and Herbaceous Biomass with Soil Physico-chemical Properties under Acacia saligna Canopy

Acacia saligna (A. saligna) is originated from South Western Australia, and it was brought to the Tigray region of Ethiopia in 1972 with the intention of restoring the ecosystem and conserving soil and water. This study aims to evaluate the correlations between tree/shrub diversity and herbaceous biomass with some soil physico-chemical properties under Acacia saligna canopy and away from the canopy in Atsibi Wemberta district, Tigray, Ethiopia. For collecting of vegetation data, herbaceous cover and soil sample, twelve A.saligna tree stands were used as a replication.Woody species identification, herbaceous cover and biomass production were collected under the canopy of A.saligna and 50 m away from the canopy at 1 m2 for woody species, and 0.25 m2 for herbaceous cover, and biomass production. Soil samples were taken using auger at 20 cm soil depth under the canopy and in the canopy gap A.saligna. The species richness under the canopy of A.saligna was positively insignificant correlated with pH (r = 0.48, p = 0.11), availability of phosphorus (Av.P) (r = 0.16, p = 0.63), total nitrogen (TN (r = 0.12, p = 0.7) and Silt (r = 0.71, p = 0.009). However, it is also negatively correlated with soil organic carbon (SOC (r = -0.06, p = 0.85), and sand (r = -0.77, p = 0.003). The Pearson’s correlation matrix in the canopy gap of A.saligna showed that, Shannon diversity index is insignificantly positively correlated with SOC (r = 0.19, p = 0.53), Av.P (r = 0.46, p = 0.12), availability of potassium (Av.K) (r = 0.43, p = 0.16) and TN (r = 0.13, p = 0.69). However, species richness and Shannon diversity index have insignificantly negatively correlated with pH(r = -0.13, p = 0.68, r = -0.15, p = 0.63) and sand (r = -0.23, p = 0.51, r = -0.44, p = 0.14), respectively. In the canopy gap of A.saligna, the herbaceous biomass was positively correlated with Av.K (r = 0.47, p = 0.12), silt (r = 0.39, p = 0.20), and clay( r = 0.37, p = 0.24), but the Pearson’s correlation matrix between herbaceous biomass and some soil parameters in the canopy gap is observed to be insignificantly negatively correlated with pH (r = -0.24, p = 0.44), SOC (r = -0.04, p = 0.9), Av.P (r = -0.34, p = 0.28), and TN (r = -0.33, p = 0.31).The species richness, Shannon diversity indexes and herbaceous biomass were insignificantly positively correlated with pH under the canopy of A.saligna, but for similar parameters in the canopy gap was observed negatively insignificant correlated with pH. Overall, the small positive correlation found in the current study between same soil physico chemical and diversity indexes under the A. saligna canopy suggests that the presence of these large A. saligna trees may increase soil nutrient availability through litterfall. The study found clear relationships between plant density and Shannon diversity with herbaceous biomass in Acacia saligna's canopy gap and beneath its canopy. In particular, both settings showed a substantial negative connection between herbaceous biomass and plant density, suggesting that increased plant density tends to diminish herbaceous biomass. On the other hand, a strong positive association was seen between Shannon diversity and herbaceous biomass, indicating that higher species diversity is linked to higher herbaceous biomass. Therefore, it is imperative to manage and conserve A. saligna and the woody species growing beneath the canopy in order to preserve and strengthen the favorable connections that exist between diversity indexes and the physical and chemical characteristics of soil.

Potential to Ensure Safe Production of Water Spinach in Heavy Metals-Contaminated Soil by Substituting Chemical Fertilizer with Organic Fertilizer

Organic fertilizers are widely used to improve soil quality. However, their potential for ensuring the safe production of vegetables in soils with varying levels of heavy metals pollution remains inadequately explored. Here, we conducted a pot experiment to investigate the effects of substituting chemical fertilizers with organic fertilizer on the HMs accumulation in water spinach by simulating soils with different levels of HMs pollution. The results showed that the organic fertilizer significantly increased the soil pH, cation exchange capacity (CEC), and organic matter (OM). Furthermore, it led to a reduction in the soil DTPA–Cd and DTPA–Pb levels by 3.3–20.6% and 22.4–47.3%, respectively, whereas the DTPA–As levels increased by 0.07–7.7 times. The organic fertilizer effectively reduced the Cd and Pb content in water spinach below the safety limits when the added Cd content in the soil was less than 2 mg/kg and the Pb content was equal to or less than 90 mg/kg. However, its efficacy in reducing As accumulation in water spinach was limited, emphasizing the need for caution when using organic fertilizers in As-contaminated soils. Our results provide valuable insights for the scientific and precise utilization of organic fertilizers, thereby contributing to the safe production of vegetables.

Biogas Residue Carbonization Rather Than Biogas Residue Promoted the Yield of Pakchoi and Reduced the N2O Production Potential in Horticultural Soil

ABSTRACTBiogas residue (BR) and biogas residue‐derived biochar (BRC) are widely used as substitute for inorganic Nitrogen (N) fertilizers in vegetable production. Yet, their comparative research on vegetable production and N2O production was still lacking. Here, the pot experiment of pakchoi (Brassica chinensis) with a gradient of BR or BRC application rates (0, 30%, 60%, 100% w/w) was carried out to simulate different N fertilizer substitution rates. The results showed that the pakchoi yield had no difference between BR or BRC and control treatments; BRC had more advantages than BR in maintaining or increasing the pakchoi yield. BR and BRC could all reduce N2O production potential in vegetable soils. But BRC had a stronger ability to inhibit denitrification while BR had a stronger ability to inhibit nitrification compared with each other. The results showed that BR and BRC had different regulatory pathways for pakchoi yield and N2O production. BR regulated the pakchoi yield majorly through nitrification, but BRC majorly through denitrification. It suggested that BR and BRC could partially or completely replace inorganic fertilizers without reducing pakchoi yield. BRC combined with chemical fertilizers was a higher intelligence strategy in vegetable systems to improve pakchoi yield and N2O production compared with BR. It provided a theoretical basis for the application of BR and BRC to nutrient cycling and microbial processes in the soil‐vegetable system.

Modelling Tree Allometries to Understand the Impact of African Savannah Elephant Herbivory Dynamics on the Vegetation Structure and Tree Cover Change in a Protected Area

ABSTRACTIn landscapes with high elephant density, trees often exhibit more open canopies with fewer branches and foliage due to browsing pressure. This can result in altered tree morphology, with trees exhibiting stunted growth, multiple stems or unusual branching patterns in response to repeated damage from browsing. The objectives of this research were to (i) model the vegetation structure allometries, (ii) assess the impact of African savannah elephant (Loxodonta africana) herbivory on the vegetation structure and (iii) assess tree cover change and vegetation performance over time in Mana Pools National Park in Zimbabwe. We established 26 plots of 30 × 30 m size. Selection of sampling plots was done following several steps. First, a fish net grid with 30 × 30 m polygons was created and projected on the polygon of Mana Pools National Park. The polygons for exclusion zones were then clipped from the fish net grid using the clip tool in ArcGIS Pro 3.0. Then, selection of sampling plots was done initially by stratified random sampling using the Sampling Design Tool add in for ArcGIS Pro 3.0. Landsat images for the years 2003, 2013 and 2023 were used to assess land use land cover (LULC) time series and to calculate Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) for the period. A generalised linear model (GLM) was used to analyse tree allometries. Further statistical investigations were performed using Bayesian piecewise regression (BPR) and Bayesian regression modelling (BRM). Basal area, number of stems, height, long canopy, diameter and basal circumference were all significantly different (p < 0.05) across all sampled plots. The change in growing conditions occurring as a tree grows beyond the reach of the African savannah elephant browsing indicates a natural system breakpoint. The best‐fitting models were a simple linear model and a two breakpoint model for the plant population exposed to elephant herbivory. LULC, NDVI and SAVI confirm evidence of high tree regeneration over 2 decades. Understanding the dynamics in vegetation and LULC changes is critical for effective conservation and management of the habitats for African savannah elephants, as well as for maintaining the health and resilience of forest ecosystems.

Estimating Total Rice Biomass and Crop Yield at Field Scale Using PlanetScope Imagery Through Hybrid Machine Learning Models

AbstractNear real-time crop monitoring has been a challenging due to the lack of high-resolution remote sensing images suitable for agricultural applications. The PlanetScope constellation, comprising approximately 130 Dove satellites, collects images of the entire Earth daily, with a resolution of 3.7 m. The high-resolution images from the PlanetScope satellite, along with vegetation indices, geo-environmental data, and soil and crop parameters, were utilized and analysed using machine learning models to enhance the accuracy of predicting total biomass and rice crop yield at the field scale. The study area, covering nearly 214 sample rice plots, was located in the Tarekswar block of Hooghly, West Bengal, India. Alongside ten vegetation indices and three Principal Component Analysis (PCA) soil nutrient levels, approximately thirty-six factors were analyzed to predict rice total biomass and crop yield using ten machine learning (ML) models, namely Random forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machine (SVM), Bagging Tree (Treebag), Generalized Additive Models (gamSpline), Elastic Net (enet), Ordinary regression with LASSO penalty (rqlasso), Tree Models from Genetic Algorithm (evtree), Bayesian Regularized Neutral Networks (brnn), cubist models, and there hybrid of ensembles. Boruta and multi-collinearity analysis were also conducted for the selected factors to explore their influence levels. The study area exhibited robust rice yields ranging from 5 to 10 t/ha, accompanied by healthy biomass growth. Four ML models ─cubist, random forest, enet, and the hybrid model—showed promising predictions with R2 > 0.88. Most models classified less than 20 ha of the study area as falling into the “very-low suitable class”, showing the region’s suitability for rice cultivation due to its highly fertile alluvial soil. Boruta sensitive analysis revealed that nearly 24 individual factors significantly influenced the final crop yield including, organic carbon (OC), phosphorus (P), electrical conductivity (EC), mechanization level, and the majority of the vegetation indices. A critical analysis carried out through the Map query tool showed that five vegetation indices estimated via PlanetScope displayed strong correlations (exceeding 89%) in identifying areas with high to very high rice yields. The study can serve as a guideline for near-real-time crop monitoring in the near future, using high-resolution PlanetScope images.

Slow post-fire carbon balance recovery despite increased net uptake rates in Alaskan tundra

Abstract Increasing wildfire occurrence and intensity have immediate effects on northern ecosystems due to combustion of aboveground vegetation and belowground soil organic matter. These immediate impacts have indirect and longer term effects, including deepening of the active layer, changes in soil decomposition rates, and shifts in plant community composition. Despite the increasing fire impacts across the tundra region, the implications of wildfire on ecosystem carbon balance are not well understood. Using paired eddy covariance towers in unburned and burned tundra, we examined the effects of a 2015 wildfire on carbon dioxide and methane fluxes in a wetland tundra ecosystem in the Yukon-Kuskokwim Delta, Alaska, from 2020 to 2022. Wildfire increased the amplitude and variability of carbon uptake and release on seasonal and annual timescales and increased the temperature sensitivity of soil respiration. Seven years post fire, there was annual net uptake in both unburned and burned tundra based on net ecosystem exchange, with the sink strength of burned tundra exceeding that of the unburned tundra by 1.18 to 1.64 times. However, when considering emissions, it would take approximately 86 years to recover the carbon lost from the wildfire itself. Soil moisture was a dominant driver of fluxes and positively associated with higher rates of carbon dioxide uptake and release and methane release. This study underscores the importance of understanding the effects of wildfire-induced shifts on tundra carbon cycling, allowing better predictions of long-term landscape-scale climate feedbacks as the climate continues to warm.

Effects of Soil Nutrient Restoration Aging and Vegetation Recovery in Open Dumps of Cold and Arid Regions in Xinjiang, China

Open-pit coal mining inevitably damages the soil and vegetation in mining areas. Currently, the restoration of cold and arid open-pit mines in Xinjiang, China, is still in the initial exploratory stage, especially the changes in soil nutrients in spoil dumps over time. Dynamic remote sensing monitoring of vegetation in mining areas and their correlation are relatively rare. Using the Heishan Open Pit in Xinjiang, China, as a case, soil samples were collected during different discharge periods to analyze the changes in soil nutrients and uncover the restoration mechanisms. Based on four Landsat images from 2018 to 2023, the remote sensing ecological index (RSEI) and fractional vegetation cover (FVC) were obtained to evaluate the effect of mine restoration. Additionally, the correlation between vegetation changes and soil nutrients was analyzed. The results indicated that (i) the contents of nitrogen (N), phosphorus (P), potassium (K), and organic matter (OM) in the soil increased with the duration of the restoration period. (ii) When the restoration time of the dump exceeds 5 years, N, P, K, and OM content is higher than that of the original surface-covered vegetation area. (iii) Notably, under the same restoration aging, the soil in the artificial mine restoration demonstration base had significantly higher contents of these nutrients compared to the soil naturally restored in the dump. (iv) Over the past five years, the RSEI and FVC in the Heishan Open Pit showed an overall upward trend. The slope remediation and mine restoration project significantly increased the RSEI and FVC values in the mining area. (v) Air humidity and surface temperature were identified as key natural factors affecting the RSEI and FVC in cold and arid open pit. The correlation coefficients between soil nutrient content and vegetation coverage were higher than 0.78, indicating a close and complementary relationship between the two. The above results can clarify the time–effect relationship between natural recovery and artificial restoration of spoil dumps in cold and arid mining areas in Xinjiang, further promoting the research and practice of mine restoration technology in cold and arid open pits.

Towards Sustainable Productivity of Greenhouse Vegetable Soils: Limiting Factors and Mitigation Strategies.

Greenhouse vegetable production has become increasingly important in meeting the increasing global food demand. Yet, it faces severe challenges in terms of how to maintain soil productivity from a long-term perspective. This review discusses the main soil productivity limiting factors for vegetables grown in greenhouses and identifies strategies that attempt to overcome these limitations. The main processes leading to soil degradation include physical (e.g., compaction), chemical (e.g., salinization, acidification, and nutrient imbalances), and biological factors (e.g., biodiversity reduction and pathogen buildup). These processes are often favored by intensive greenhouse cultivation. Mitigation strategies involve managing soil organic matter and mineral nutrients and adopting crop rotation. Future research should focus on precisely balancing soil nutrient supply with vegetable crop demands throughout their life cycle and using targeted organic amendments to manage specific soil properties. To ensure the successful adoption of recommended strategies, socioeconomic considerations are also necessary. Future empirical research is required to adapt socioeconomic frameworks, such as Science and Technology Backyard 2.0, from cereal production systems to greenhouse vegetable production systems. Addressing these issues will enable the productivity of greenhouse vegetable soils that meet growing vegetable demand to be sustained using limited soil resources.

Enhancing highland ecosystems in East Hararge, Ethiopia: evaluating intervention strategies for species diversity, soil organic carbon stock, and carbon sequestration

Forest loss and soil degradation pose significant challenges globally, particularly in developing nations like Ethiopia. Various intervention strategies have been implemented to rehabilitate degraded ecosystems. However, research gaps exist in understanding the most effective approaches, particularly in highland ecosystems. This study aimed to evaluate the effectiveness of different intervention strategies on species diversity and carbon stock in the West Hararghe zone, specifically at the Doba district Hades site. The data was collected from 5 February 2022 to 10 December 2022. The study area was characterized by systematic plots and transects to assess vegetation diversity and soil properties across four intervention categories: (physical; only soil and water conservation structures were used, enclosure; only animal and human interaction was restricted, biological; only different tree species were planted, biophysical; both soil water conservation and tree planting were used). Soil samples were collected at different depths, and biomass estimation was conducted using established formulas. Statistical analyses, including one-way ANOVA and post-hoc tests, were performed to test the level of significance. Biophysical interventions exhibited the highest species diversity index (SDI) (4.65 ± 1.21), followed by enclosure interventions (1.68 ± 0.58), while physical interventions recorded the lowest SDI (0.63 ± 0.18). Enclosure interventions led to the highest soil organic carbon (SOC) stocks at 40.13 t C ha−1, followed by biophysical interventions at 39.26 t C ha−1. Physical interventions resulted in the lowest SOC stocks at 23.9 t C ha−1, underscoring their potential for carbon sequestration. Biophysical interventions, which include both above-ground and below-ground biomass, showed significant carbon stock accumulation, totaling 173.8 t C ha−1 (39.26 t C ha−1 from SOC and 114.6 t C ha−1 from biomass), highlighting their effectiveness in enhancing ecosystem resilience. Other studies support these findings, underscoring the importance of context-specific approaches and long-term monitoring for sustainable land management. Enclosure and biophysical interventions emerge as promising strategies for enhancing species diversity and soil health, as well as promoting carbon sequestration in highland ecosystems. These findings emphasize the need for informed decision-making and community involvement in ecosystem restoration efforts to achieve meaningful and lasting impacts.

Rice husk biochar is more effective in blocking the cadmium and lead accumulation in two Brassica vegetables grown on a contaminated field than sugarcane bagasse biochar.

Heavy metal-contaminated soil has a great impact on yield reduction of vegetable crops and soil microbial community destruction. Biochar-derived waste biomass is one of the most commonly applied soil conditioners in heavy metal-contaminated soil. Different heavy metal-contaminated soil added with suitable biochars represent an intriguing way of the safe production of crops. This study investigated the effects of two types of biochar [rice husk biochar (RHB) and sugarcane bagasse biochar (SBB)] on Cd and Pb accumulation in Shanghaiqing (SHQ, a variety of Brassica campestris L.) and Fengyou 737 (FY, a variety of Brassica napus), as well as on the soil microbial community, through a field experiment. RHB and SBB were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and Brunauer-Emmet-Teller method. The results showed that RHB and SBB displayed the higher pH, cation exchange capacity and pore properties, and the addition of RHB and SBB enhanced soil pH and rhizosphere microorganisms promoting vegetables yield. RHB treatments were more effective than SBB in reducing upward transfer of Cd and Pb, blocking the accumulation of Cd and Pb in the edible parts of SHQ and FY, and decreasing soil Cd and Pb bioavailability. Additionally, RHB and SBB changed the composition of the rhizosphere soil microbial community. The application of biochar promoted the growth of ecologically beneficial bacteria (Nitrospira, Opitutus, and Gemmatimonas) and fungi (Mortierella and Holtermanniella), whereas reducing the enrichment of plant pathogenic fungi (Alternaria, Stagonosporopsis, Lectera, and Periconia) in rhizosphere soil. Our findings demonstrated that the application of RHB significantly reduces Cd and Pb accumulation in the edible parts by decreasing the soil Cd and Pb bioavailability and altering the rhizosphere microbial community composition in two Brassica vegetables grown on Cd/Pb-contaminated soils. Thus, the application of two biochar, especially RHB is a feasible strategy for the safe production of vegetable crops in Cd/Pb co-contaminated soils.

Evaluating the ability of the Wind Erosion Prediction System (WEPS) to simulate near-surface wind speeds in the Inland Pacific Northwest, USA

Wind speed is one of the main control factors of wind erosion and dust emissions, which are major problems in arid and semiarid regions of the world. Accurately simulating highly precise hourly wind speeds is critical and cost-efficient for land management decisions with the goal of mitigating wind erosion and land degradation. The Wind Erosion Prediction System (WEPS) is a process-based, daily time-step model that simulates changes in the soil–vegetation–atmosphere. However, to date, relatively few studies have been conducted to test the ability of the WEPS in simulating hourly wind speeds. In this study, the performance of the WEPS model was tested in the Inland Pacific Northwest (iPNW), where wind erosion is a serious problem. Hourly wind speeds were observed and simulated by the WEPS at 13 meteorological stations from 2009 to 2018 using the WEPS hourly wind speed probability histogram. Owing to increasing wind shear, the model is not as precise in reproducing high wind speeds. The WEPS inadequately simulated the hourly wind speeds at six of the 13 stations, with a low index of agreement (d < 0.5). The complex regional topography may be one of the reasons for this lack of agreement, because the WEPS’s performance of interpolation relies on spatial distances and surface complexity. Therefore, we validated the model using another wind-speed database to eliminate the impact of spatial interpolation. The performance of the WEPS was improved after removing the impact of spatial interpolation, producing d values > 0.5 at nine of the 13 stations. Our results suggest that the WEPS can accurately simulate hourly wind speeds and assess wind erosion in the absence of interpolation, whereas the model may be uncertain when invoking spatial interpolation. Some evidence also suggests that the model may have a tendency to underestimate observed hourly wind speeds. Pragmatically, this suggests that model users should consider the possibility that WEPS may underestimate wind erosion risk in the iPNW and plan implementation of conservation practices accordingly.

Influence of Acetylene Concentration on N2O and N2 Emissions from an Intensive Vegetable Soil under Anoxic and Oxic Conditions

Acetylene (C2H2) is often employed to assess soil total denitrification (N2O + N2) due to its ease of implementation. However, this technique underestimates soil denitrification in soils with low nutrient contents, particularly those supporting grain yields. To our knowledge, there are limited studies that have specifically investigated the impact of C2H2 on nutrient-rich vegetable soils, especially concerning the emissions of N2 and N2O and the nitrogenous gas product ratio (i.e., N2O/(N2O + N2)). In this study, we conducted both anoxic and oxic incubations at various C2H2 concentrations (0%, 0.01%, and 10%, v/v) and utilized a robotized sampling and analysis system to quantify soil N2, N2O, and CO2 emissions. Our findings revealed that the cumulative N2O production in soil treated with 10%C2H2 was significantly lower than that in soil treated with 0.01%C2H2 and soil without C2H2. Contrarily, high concentrations of C2H2 (10%, v/v) led to increased N2 production. Similar trends were observed under oxic conditions, where 10%C2H2 concentration did not enhance N2O production but markedly increased N2 and CO2 emissions. Moreover, the N2O/(N2O + N2) product ratio was notably higher in soils treated with 0%C2H2 compared to the 10%C2H2 treatment under anoxic conditions. These findings indicate that high concentrations of acetylene could facilitate the reduction of N2O to N2 and lead to underestimated soil total denitrification in vegetable soil, regardless of anoxic or oxic conditions. This discovery underscores the drawbacks when employing high concentrations of acetylene to evaluate actual total denitrification in intensive greenhouse vegetable soils, highlighting the necessity for further investigation into alternative methodologies.

Shallow drainage of agricultural peatlands without land-use change: have your peat and eat it too

IntroductionDrainage for agricultural purposes is one of the main drivers of peatland degradation, leading to significant greenhouse gas (GHG) emissions, biodiversity loss, and soil eutrophication. Rewetting is a potential solution to restore peatlands, but it generally requires a land-use shift to paludiculture or nature areas.MethodsThis study explored whether three different water level management techniques (subsoil irrigation, furrow irrigation, and dynamic ditch water level regulation) could be implemented on dairy grasslands to yield increases in essential ecosystem services (vegetation diversity and soil biogeochemistry) without the need to change the current land use or intensity. We investigated vegetation diversity, soil biogeochemistry, and CO2 emission reduction in fourteen agricultural livestock pastures on drained peat soils in Friesland (Netherlands).ResultsAcross all pastures, Shannon-Wiener diversity was below 1, and the species richness was below 5. The plant-available phosphorus (P) was consistently higher than 3 mmol L−1. None of the water level management (WLM) techniques enhanced vegetation diversity or changed soil biogeochemistry despite a notable increase in water table levels. The potential for CO2 emission reduction remained small or even absent. Indicators of land-use intensity (i.e., grass harvest and fertilization intensity), however, showed a strong negative correlation with vegetation diversity. Furthermore, all sites’ total and plant-available P and nitrate exceeded the upper threshold for species-rich grassland communities.DiscussionIn conclusion, our research suggests that incomplete rewetting (i.e., higher water tables while maintaining drainage) while continuing the current land use does neither effectively mitigate GHG emissions nor benefit vegetation diversity. Therefore, we conclude that combining WLM and reducing land-use intensity is essential to limit the degradation of peat soils and restore more biodiverse vegetation.