Intensive Agricultural Management Research Articles

Ecosystem multifunctionality is more related to the indirect effects than to the direct effects of human management in China's drylands

Drylands provide a wide range of important ecosystem functions but are sensitive to environmental changes, especially human management. Two major land use types of drylands are grasslands and croplands, which are influenced by intensive grazing activities and agricultural management, respectively. However, little is known about whether the ecosystem functioning of these two land use types is predominated affected by human management, or environmental factors (intrinsic environmental factors and factors modified by human management). This limits our understanding of the ecosystem functions under intensive human management in drylands. Here we reported a study where we collected data from 40 grassland and 30 cropland sites along an extensive aridity gradient in China's drylands to quantify the effects of human management intensity, intrinsic environmental factors (i.e., aridity), and environmental factors modified by human management (i.e., soil bulk density and plant density) on specific ecosystem functions (ecosystem multifunctionality, productivity, carbon storage, soil water, and soil nutrients). We found that the relative importance of each function differed between croplands and grasslands. Ecosystem functions varied with human management intensity, with lower productivity and plant carbon storage in grasslands under high grazing intensity than un-grazed, while multifunctionality and carbon storage increased with greater fertilization only in arid croplands. Furthermore, among environmental factors, soil bulk density had the greatest negative effects, which directly reduced multifunctionality in grasslands and indirectly reduced multifunctionality in croplands via suppressing crop density. Crop density was the major environmental factor that positively related to multifunctionality in croplands. However, these effects would be exacerbated with increasing aridity. Our study demonstrated that compared with the direct impacts of human management, environmental factors modified by human management (e.g., soil bulk density) are the major drivers of ecosystem functions, indicating that improving soil structure by alleviating human interferences (e.g., reducing livestock trampling) would be an effective way to restore ecosystem functions in drylands under global warming and drying.

EUROPEAN APPROACHES AND REGULATORY MECHANISMS OF ECOLOGICAL AND HYGIENIC MONITORING FROM THE PERSPECTIVE OF POTENTIAL HARMONIZATION AND IMPLEMENTATION INTO DOMESTIC LEGISLATION

Background. The usage of pesticides against pests is also accompanied by potential negative effects on non-target organisms. The risk of harm to biodiversity is quite significant. Implementation of ecological and hygienic monitoring strategies, which is quite effectively applied in the countries of the European Union, will allow to reduce potential threats, financial costs and unforeseen consequences for beneficial insects, birds, aquatic organisms, etc. Aim: analysis of European approaches and regulatory mechanisms of ecological and hygienic monitoring from the standpoint of potential harmonization and implementation in Ukrainian legislation field. Materials and methods. Data from the literature and regulatory documents of the European Union in the field of environmental assessment and ecological and hygienic monitoring were used for the analysis. An array of literary sources was analyzed, which included the most relevant, up-to-date articles over the past 5 years and valid regulatory documents that have the greatest potential for implementation into the national regulatory framework. Results. In the EU and the US, a strict risk assessment process is in place to obtain permission to use pesticides, taking into account the potential impact on non-target organisms. Risk assessment of the use of chemical plant protection on the ecosystem and monitoring of the condition of non-target kinds of objects in the territories of intensive agricultural management is carried out at the stage of pre-registration tests. State regulatory agencies primarily require data on average lethal doses and concentrations for some bird kinds (Colinus virginianus, Anas platrynchos, Perdix perdix, Coturnix japonica). However, there are studies that describe the effects on smaller songbirds that are more sensitive to acute poisoning, therefore, to consider the established standards only for large birds is rather imperfect and needs to be refined in Ukrainian practice in the future. The European rules of environmental risk assessment (ERA) have undergone significant changes in recent decades, which have caused many scientists to worry about insufficient plant protection, slow implementation of scientific developments, simplification of environmental relevance and priority. Also, in many normative documents on pesticides, a political trail is traced, which is sometimes difficult to define and measure. Conclusion. The adoption and implementation of new laws in the field of chemical plant protection in the EU countries are the basis for improving the legislation of Ukraine in this field and ensuring state regulation in the handling of pesticides and agrochemicals.

Integrating classic AI and agriculture: A novel model for predicting insecticide-likeness to enhance efficiency in insecticide development

The integration of artificial intelligence (AI) into smart agriculture boosts production and management efficiency, facilitating sustainable agricultural development. In intensive agricultural management, adopting eco-friendly and effective pesticides is crucial to promote green agricultural practices. However, exploring new insecticides species is a difficult and time-consuming task that involves significant risks. Enhancing compound druggability in the lead discovery phase could considerably shorten the discovery cycle, accelerating insecticides research and development. The Insecticide Activity Prediction (IAPred) model, a novel classic artificial intelligence-based method for evaluating the potential insecticidal activity of unknown functional compounds, is introduced in this study. The IAPred model utilized 27 insecticide-likeness features from PaDEL descriptors and employed an ensemble of Support Vector Machine (SVM) and Random Forest (RF) algorithms using the hard-vote mechanism, achieving an accuracy rate of 86 %. Notably, the IAPred model outperforms current models by accurately predicting the efficacy of novel insecticides such as nicofluprole, overcoming the limitations inherent in existing insecticide structures. Our research presents a practical approach for discovering and optimizing novel insecticide lead compounds quickly and efficiently.

Changes in soil microbial diversity under present land degradation scenario

Soil biological characteristics are drastically altered by land degradation. Degradation may reduce the number of microorganisms in the soil. Multiple activities and services provided by grassland ecosystems are impacted by land use change because of the resulting shifts in plant community composition and soil characteristics. A large body of research has examined the geographical and temporal dynamics of bacterial community structure and bacterial responses to human management in grassland ecosystems. As one of the most consequential environmental shifts occurring today, land use modification can affect microbial communities through modifying soil environmental parameters, nutritional conditions, and biological interactions. Whereas, soil microbes play crucial roles in nutrient cycling, organic matter decomposition, disease suppression, and overall soil health. Land degradation practices, such as deforestation, overgrazing, intensive agriculture, and improper land management, can disrupt the balance and diversity of soil microbial communities, leading to negative consequences for ecosystem functioning. To mitigate the negative effects of land degradation on soil microbial communities, sustainable land management practices should be adopted. These practices include soil conservation, reforestation, crop rotation, reduced tillage, organic farming methods, and proper nutrient management. By promoting soil health and restoring ecosystem processes, these approaches can help rebuild and maintain diverse and functional soil microbial communities.The purpose of this review is twofold: (1) to assess the diversity and composition of soil microorganisms in response to distinct land-use scenarios; and (2) to compare the relative importance of environmental factors driving these variations.

Mapping the dynamics of intensive forage acreage during 2008–2022 in Google Earth Engine using time series Landsat images and a phenology-based algorithm

The increasing demand for livestock feed in China has led to a remarkable increase in forage acreage, particularly in forage fields under intensive agricultural management. However, there are no maps currently available to demonstrate and document the spatial and temporal patterns of the continuous expansion of intensive forage. Here we proposed a pixel- and phenology-based approach to map intensive forage by utilizing time series Landsat images and the Google Earth Engine platform. Given the challenge of accurately identifying intensive forage fields in diverse regions using fixed multi-temporal Landsat data, along with the distinct phenological characteristics of intensive forage fields that undergo multiple annual harvests, we proposed an innovative data mining approach based on dynamic monthly composite images (DMCI). This approach aims to enhance the algorithm’s efficiency and precision in identifying intensive forage. As a pilot study, we analyzed all available Landsat images (1732 scenes) from 2008 to 2022 in a county located in the farming-pastoral ecotone of northern China and tracked the historical dynamics of intensive forage expansion over five epochs at three-year intervals. The accuracy assessment of the intensive forage maps for the five epochs using validation sample points showed that the overall accuracy and Mathews correlation coefficient ranged from 97.1 % to 98.9 % and 0.93 to 0.98 respectively. The intensive forage acreage in the study area exhibited a dramatic expansion from 2008 to 2022, particularly after the 2012s. This study demonstrates the potential of our DMCI- and phenology-based algorithm and time series Landsat images for tracking the dynamics of intensive forage acreage at 30-m resolution in temperate single-cropping regions.

Evaluating machine learning models and identifying key factors influencing spatial maize yield predictions in data intensive farm management

Understanding the relationships between crop yields, soil properties, weather patterns and input applications is important for optimizing agricultural production. Data variation analysis using statistical and machine learning (ML) approaches can help identify and understand the practices that optimize yield. The objectives of this study were (i) to evaluate the predictive accuracy of selected ML models for estimating grain yields in on-farm maize (Zea mays L.) trials with different combinations of seeding and fertilizer rates in a commercial field, and (ii) to investigate the ability of ML models to assist in identifying yield-limiting factors in the same field. Multiple linear regression, multilayer perceptron, decision tree, and random forest (RF) ML models were trained and tested using crop management and soil from a data-intensive farm management (DIFM) trial and remotely sensed data. The dataset consisted of multiple subplot treatment observations of crop management, soil properties and normalized difference vegetation index (NDVI), linked to final grain yield for the 2019/2020 and 2020/2021 seasons. The RF had the best combination of high correlation (R2 = 0.69 and 0.80) and low error (MAPE = 5.4 and 8.4% and RMSE = 0.69 and 0.95 t ha−1) when compared to other models for both seasons. Feature importance analysis revealed that urea application was consistently the most critical variable and explained yield variations to the greatest extent, whereas soil phosphorus (P), plant population, and sodium in 2020, and soil P, soil pH, clay content, and plant population in 2021 emerged as the most influential factors for explaining yields. This study concluded that the RF model was the best for spatial yield predictions using DIFM trial datasets. There was also variability between seasons in yield limiting factors resulting from temporal variations in growing conditions. To effectively apply insights from yield prediction models, it is crucial that the variables incorporated into these models have a significant connection to yield and the findings can be translated into actionable management decisions. The DIFM trials combined with ML can play an important role in advancing the field of precision agriculture by providing valuable insights into the complex interactions between crops, soils, and management practices, and identifying new opportunities for improving crop yields and environmental sustainability.

Food Composition of the Little Owl Athene noctua in Farmland Areas of South East Poland

The feeding ecology of the Little Owl (Athene noctua) was studied in farmlands of southeast Poland, which is dominated by monocultural farms. 3065 prey dissected from pellets were collected at 13 pellet stations between 1999 and 2001 through 7 seasons in total. Mammals were found to dominate both in total number (54.3% of caught prey) and total biomass (93.0% of caught prey) while insects comprised 43.0% of the number, but only 1.1% of the prey biomass. However, the proportion of insects reached up to 62% in certain seasons. Coleopteran beetles dominated the insect fraction representing 98.3% of the number and 87.9% of the insect biomass. Our study also illustrated that in some seasons, the prey composition included taxa related to intensive agricultural management. The food composition of the Little Owls from the examined Polish sites is more similar to Eastern and Southern populations than to Northern and Western populations of Little Owls in Europe.

Land management policy shift influenced seasonal variation of erosion-induced nitrogen and phosphorus outputs from intensive agricultural catchment

A shift in policy to intensive agricultural production and land management often leads to excessive fertilizer application and accelerated erosion with consequent detrimental effects to water bodies. We investigated the impact of that shift by quantifying the spatial and temporal change in sediment sources and associated total nitrogen (TN) and total phosphorus (TP) pollutants output loads in an intensive agricultural catchment in North China across one year (November 2021–November 2022). We describe the implications of this work for intensive agriculture elsewhere in China and other countries. Seasonal sediment source apportionment was estimated at the catchment outlet using Berillium-7 (7Be) combined with compound-specific stable isotope (CSSI) signatures from sources and sediments. Diagnostic ‘fingerprints’ in MixSIAR were used to discriminate sediment sources between forest and crop farmland converted from forest (F + C(F)), crop farmland (C), and vegetable farmland (V). Our study identified F + C(F) as the dominant sediment source (mean 55.24 ± 2.91 %), intermediate on V (mean 30.06 ± 2.20 %), and least on C (mean 14.70 ± 2.13 %). Sedimentation ranged from 37.98 ± 3.02 to 89.60 ± 12.68 t·ha−1·event−1 and coincided with shifted land use policy and rainfall distribution. The TN and TP in sediment were both mainly derived from F + C(F) (averaged 22.27 ± 4.26 t·event−1 and 11.62 ± 2.28 t·event−1) and least from V (averaged 1.63 ± 0.29 and 2.09 ± 0.33 t·event−1). Despite being a significant sediment source, V contributed little sediment TN and TP input for eutrophication. Our findings imply that F + C(F) are diffuse sources of catchment pollution over the short term. These results describe the successful use of CSSI and 7Be to cost-effectively quantify the seasonal variation of sediment TN and TP loads from land-use-specific sources in the catchment under shifting land management policy in China with potential for use elsewhere. These findings enable soil conservation strategies and land management practices optimized for implementing targeted pollutant abatement initiatives in intensive agriculture in China and elsewhere.

Grassland extensification enhances nest densities of ground‐nesting wild bees

Abstract Ground‐nesting wild bees provide essential pollination services in agroecosystems, but they are jeopardized by intensive agricultural management. To mitigate such negative impacts, agri‐environment schemes have been implemented. While the success of enhancing floral food resources is relatively well studied, the role of agri‐environmental schemes in providing suitable nesting habitat remains underexplored. We studied the effectiveness of meadow extensification according to the Swiss agri‐environment scheme in promoting nesting of ground‐nesting bees. Using a paired design, we quantified their nests during four rounds (March–June) in pairs of nine randomly selected extensively (i.e. no fertilizer input, postponed first mowing) and nine intensively managed meadows with similar soil properties, slope, exposure and landscape context. Nest numbers and vegetation characteristics were surveyed in areas of 250 m2. Vegetation properties were also assessed in 0.5 × 0.5 m plots around nest locations and randomly selected locations without nests within each meadow to assess their role as drivers of nesting incidence (nest presence/absence) at this plot scale. We found substantially higher nest numbers of ground‐nesting bees in extensively (mean ± SE per sampling round = 46.8 ± 14.2) compared to intensively managed meadows (0.8 ± 0.3; no nests in three of nine intensively managed meadows). Extensively managed meadows harboured nests of several dominant crop pollinator species, including aggregations of, for example, Lasioglossum malachurum contributing to high nest densities in some of them. Number of nests was negatively related to grass cover and vegetation height, which were lower in extensively compared to intensively managed meadows. Plot‐level nesting incidence increased with bare ground and moss cover, and decreased with grass cover. Synthesis and applications. Our study shows that extensively managed meadows are better nesting habitats for ground‐nesting bees than intensively managed meadows, if reduced management intensity is associated with altered vegetation characteristics such as reduced grass cover and vegetation height, and small‐scale availability of bare ground, driving these effects. This highlights that maintaining and promoting extensive management of meadows can promote ground‐nesting wild bees, including dominant crop pollinators, not only by enhancing floral resources but also by improving nesting opportunities in agroecosystems.

Determinants of perception of climate change and adaptation strategies of coffee-based agroforestry farmers in western Ethiopia

Background: A range of local social and environmental factors has an impact on farmers' views of climate change and choices on the use of coping mechanisms. This study examines the factors that are limiting farmers' perceptions of climate change and their coping mechanisms in Gimbi district, Western Ethiopia. Methods: A household survey and focus group discussion were employed to collect relevant data. A total of 402 randomly selected households and six focus group discussions containing 72 participants were used to gather data. Binary logit models were used to analyze the collected data. Results: Farmers noted that some of the signs of climate change included increasing temperature, erratic rainfall, late onset of rainfall, and early cessation of rainfall. We discovered that there are three distinct sets of climate adaption strategies used by farmers: crop management, soil and water conservation and intensive farm management. The primary determinants of farmers' perceptions of climate change and adaptation techniques were household head age, education, soil fertility, market access, and agricultural training. Age, education, and soil fertility level were the characteristics that significantly impacted farmers' perspectives and coping mechanisms among the primary drivers evaluated in the area. Use of agroforestry, shifting planting dates, and fertilizer application were all essential farming practices used as climate adaptation measures. Conclusions: Both socioeconomic and environmental factors have found to affect farmers' perceptions of climate change in the area. The existing socioeconomic and environmental factors, in turn, affect their choice of strategies to adapt to climate change. When implementing climate change adaption strategies, it is critical to assess farmers' level of awareness of climate change and their coping strategies, as well as the factors limiting their ability to adapt to climate change.

Determinants of perception of climate change and adaptation strategies of coffee-based agroforestry farmers in western Ethiopia

Background: A range of local social and environmental factors has an impact on farmers' views of climate change and choices on the use of coping mechanisms. This study examines the factors that are limiting farmers' perceptions of climate change and their coping mechanisms in Gimbi district, Western Ethiopia. Methods: A household survey and focus group discussion were employed to collect relevant data. A total of 402 randomly selected households and six focus group discussions containing 72 participants were used to gather data. Binary logit models were used to analyze the collected data. Results: Farmers noted that some of the signs of climate change included increasing temperature, erratic rainfall, late onset of rainfall, and early cessation of rainfall. We discovered that there are three distinct sets of climate adaption strategies used by farmers: crop management, soil and water conservation and intensive farm management. The primary determinants of farmers' perceptions of climate change and adaptation techniques were household head age, education, soil fertility, market access, and agricultural training. Age, education, and soil fertility level were the characteristics that significantly impacted farmers' perspectives and coping mechanisms among the primary drivers evaluated in the area. Use of Agroforestry, shifting planting dates, and fertilizer application were all essential farming practices used as climate adaptation measures. Conclusions: Both socioeconomic and environmental factors have found to affect farmers’ perceptions of climate change in the area. The existing socioeconomic and environmental factors, in turn, affect their choice of strategies to adapt to climate change. When implementing climate change adaption strategies, it is critical to assess farmers' level of awareness of climate change and their coping strategies, as well as the factors limiting their ability to adapt to climate change.

The ground beetle Pseudoophonus rufipes gut microbiome is influenced by the farm management system

Intensive conventional farm management, characterized by high agrochemicals input, could alter the composition of microbial communities with potential negative effects on both functional traits and the ecosystem services provided. In this study, we investigated the gut microbial composition of a high ecological relevance carabid Pseudoophonus rufipes, sampled in two fields subjected to conventional and organic management practices. Carabids’ gut microbiota was analyzed via qPCR and NGS. Profound differences between the microbial composition of organic and conventional samples were detected: the abundance of Tenericutes and Proteobacteria was significant higher in organic and conventional samples, respectively. Spiroplasmataceae and Bifidobacteriaceae families were significantly more abundant in samples from organic management, while Enterococcaceae, Morganellaceae and Yersiniaceae were more abundant in samples from conventional management. The diverse gut microbial composition of insects between the two management systems is related to the pressure of environmental stressors and it may representing an important bioindication of ecological functions and services provided by a carabid species.

Spatial-Temporal Evolution Characteristics of Agricultural Intensive Management and Its Influence on Agricultural Non-Point Source Pollution in China

The influencing mechanism of agricultural non-point source pollution under intensive agricultural management is complicated. This paper adopted provincial panel data from 2008 to 2020 to estimate the level of agricultural intensive management, the agricultural chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) emissions and emission intensity of agricultural non-point source pollution in different regions of China and analyze the spatial-temporal differentiation characteristics. Moreover, the mediation effect model and spatial spillover effect model were adopted to further explore the influence mechanism of agricultural intensive management on agricultural non-point source pollution. The results show that (1) The total emissions and emission intensity of agricultural non-point source pollution both showed an increasing trend, and these areas with high levels of agricultural non-point source pollution are roughly consistent with those areas with high-level of agricultural intensive management. (2) At the overall level, there were mediating effects of natural ecology, agricultural land management, planting and rearing structure and pollution control investment between the relationship of agricultural intensive management and agricultural non-point source pollution, among which agricultural land management was the largest. Additionally, there was significant spatial heterogeneity in the influencing mechanism of agricultural intensive management on non-point source pollution. (3) There were significant spatial agglomeration characteristics in both agricultural intensive management and agricultural non-point source pollution, which showed a fluctuating trend of “rise-decline-rise-decline”. (4) Agricultural intensive management has a significant positive spatial spillover effect on COD, TN and TP emissions of agricultural non-point source pollution. However, environmental regulation could cause agricultural non-point source pollution to be transferred nearby. Scientific understanding of the spatio-temporal differentiation characteristics and influencing mechanism of agricultural non-point source pollution under the agricultural intensive management model is conducive to providing reference for policy regulation.

Evaluation of the effects of conservation practices carried out in the 1970s on soil properties in the Eastern Region of Paraguay

AbstractSoils in subtropical and tropical regions are extremely fragile to perturbations due to their sandy texture, acid nature, low soil organic carbon (SOC) and low cation exchange capacity. In Paraguay, deforestation and subsequent cultivation affect 60% of the land. Certain conservation practices were carried out in the 1970s in response to the important degree of degradation caused by the soil degradative processes. Although the management of crop soils is still very intensive, to date there is no data on how the practices are affecting the sustainability of the system. The objective of this study was to evaluate the chemical and physical properties of three subtropical soils (Ultisol, Alfisol and Oxisol) under different agricultural systems and types of management, aimed at conservation, in the Eastern Region of Paraguay. The agricultural systems differ in the main crop (soybean or maize) and rotation crop (oat, turnip, crotalaria, lupins, maize). The soil properties were compared with those in disturbed natural forests and eucalypt plantations established on former agricultural land. The physical and chemical properties of the soil were determined in the 0 to 40 cm layer. The soils in the disturbed natural forest systems were less acidic and contained more Ca, Mg and K than the cultivated soils. Relative to the seminatural forests, the cultivated soils contained 20 to 40% less SOC and had lower macronutrient reserves and higher bulk density (up to 1.45 g cm−3). The SOC was higher in the agricultural systems with oats sown as a rotation crop in winter. By contrast, the N content was higher in systems with lupins or turnips grown in winter. Even when managed using conservation practices (direct sowing, retention of harvest residues, green manure), the soils in the agricultural systems under study displayed signs of physical and chemical degradation. The findings show that these conservation practices are not sufficient to correct the impact of intensive agricultural management.

Distance to semi‐natural habitats matters for arbuscular mycorrhizal fungi in wheat roots and wheat performance in a temperate agricultural landscape

Introduction The proximity of semi-natural habitats and agricultural fields in an agricultural landscape leads to unavoidable biological, chemical, and physical interactions. Fungi can negatively influence, but also support crop growth in agricultural fields. Therefore, in this field study we investigated the colonisation of arbuscular mycorrhizal (AM) fungi and non-AM fungi in winter-wheat roots as well as winter-wheat performance in distance to semi-natural habitats. Materials and Methods We sampled in an intensively managed agricultural landscape in North-east Germany along agricultural transition zones, that is, along 50 m-transects from semi-natural habitats like hedgerows and glacially created in-field ponds—so-called kettle holes—into agricultural fields. Results To our knowledge, we show for the first time that AM fungal colonisation in winter-wheat roots decreased linearly with increasing distance to semi-natural habitats while non-AM fungal root colonisation did not change. Winter-wheat grain yield and biomass slightly increased with increasing distance to hedgerows but not to kettle holes. This clearly shows that there is a difference between different crop performance parameters. Random forest machine learning algorithms confirmed the particular importance of distance to semi-natural habitats for AM fungal root colonisation and for winter-wheat grain yield. Less intensive agricultural management close to semi-natural habitats, for example, no herbicide and pesticide applications as a result of nature protection regulations, may partly explain this pattern. However, spatial response patterns of AM but not of non-AM fungi in wheat roots also point to changed ecological interactions close to semi-natural habitats. Conclusion Semi-natural and natural habitats in agricultural landscapes are slowly recognised not only to be important for biodiversity conservation, but also for sustainable crop production. Additionally, they may also be a tool for farmers and policy makers to improve sustainable landscape management. And agricultural transition zones are spatially and temporally complex dynamic ecosystems that should be the focus of further investigations.

PREVALENCE OF Blastocystis sp. IN CATTLE, GOAT AND SHEEP REARED BY DIFFERENT FARM MANAGEMENT SYSTEMS IN PAHANG, MALAYSIA

Blastocystis sp. is a familiar parasite in the gastrointestinal tract causing infection in humans and animals. The purpose of this study is to evaluate the Blastocystis sp. prevalence in three sorts of livestock; cattle, goats, and sheep in Pahang, Malaysia, which are reared under two management systems; intensive and semi-intensive farm management system. About 92, 96, and 65 cattle, goat, and sheep fecal samples respectively were collected from different farms around Kuantan, Bera, and Pekan. The fecal samples were cultured in Jones’ medium supplemented with 10% heat-inactivated horse serum and incubated at 37 ºC for 2 weeks, then observed under light microscopy daily. The total prevalence of Blastocystis sp. was 29.34% in cattle (27/92), 29.16% in goats (28/96), and 43.07% in sheep (28/65). Supported the results of this study, Blastocystis sp. prevalence was higher in sheep and livestock reared by a semi-intensive farm management system (44.38%). However, further study could be done for Blastocystis sp. subtypes identification to determine its genetic diversity. Notwithstanding, this study has provided additional knowledge on the prevalence of each livestock reared in farms around Pahang that serve as important information in understanding host-parasite relationships, besides determining the best farm management system to be applied by farmers.

Contribution of a Seeded Cover Crop Mixture on Biomass Production and Nutrition Status Compared to Natural Vegetation in a Mediterranean Olive Grove

Intensive agricultural management practices (i.e., the burning of pruning residues, the absence of organic amendments) lead to a reduction in organic matter and nutrients in the soil resulting in agroecosystem vulnerability. Implementing a cover crop would provide soil organic matter while increasing nutrition levels in the soil. A mixture of cover crop trial in sandy loam soils under Mediterranean climatic conditions was conducted in a rainfed olive grove in Western Crete. In this study, the dry biomass, macro- and micronutrition, and carbon status of the seeded cover crops (legume and grass) were compared to natural plants in an olive grove. Seeded cover crops were conducted in two sustainable management systems (cover crops solely, and a combination of compost, pruning residues, and cover crops); natural plants were in a conventional system involving soil tillage. In combination with conservation tillage practices, the addition of carbon inputs may improve soil fertility. Results indicate that the dry biomass production and C content of cover crops under sustainable management systems was significantly higher than that of the control. The higher dry biomass production and C content found in cover crops compared to the natural vegetation indicates not only that this type of management provides enhanced carbon storage, but can also potentially lead to a future increase in soil organic matter through decomposition. Higher dry biomass is important in the context of carbon sequestration, and cover crops facilitated carbon storage in this study. In addition, this study suggests that sustainable agricultural management practices would provide significant benefits in terms of nutrient retention and CO2 fixation, thus improving ecosystems in Mediterranean countries.

Climate consequences of temperate forest conversion to open pasture or silvopasture

Land use change, particularly the conversion of forest to agriculture, is an important driver of climate change but is rarely considered a major factor in northern temperate regions. This study explored the climate impacts of temperate forest clearing for agriculture in the northeastern United States, hypothesizing that compared to managed cool-season pasture, forest conversion to silvopasture would moderate changes in surface temperature, soil greenhouse fluxes, and soil carbon and nutrient losses. To test this hypothesis, we conducted two land use change experiments, one in New York and the other in New Hampshire, USA. In both locations, forests have regenerated following a period of forest clearing, intensive agricultural management, and farm abandonment, such that secondary forests currently comprise ~60–80% of the land base. In both experiments, we measured microclimatic variables of air and soil temperature and soil moisture, soil greenhouse gas emissions of CO2 and N2O, and soil carbon and nitrogen content. Using a mixed-effects modeling framework, we found that near-surface air and soil temperatures were highest in converted pasture plots, lowest in reference secondary forest areas, and intermediate in the converted silvopasture treatment. Soil respiration followed a similar pattern, with elevated soil CO2 fluxes in open pastures as compared to converted silvopasture and reference secondary forest sites. Although we detected few changes in soil C among treatments, we observed higher soil N stocks and soil N2O fluxes in converted pastures but not in the converted silvopasture treatment. Our results suggest that silvopasture may offer a biogeochemical “middle ground” between intact secondary forests and managed open fields, retaining the climate benefits of forests while enabling expansion of the agricultural land base. Understanding the climate impacts of forest conversion to open pasture or silvopasture is critical to better anticipate the climate consequences of potentially re-emerging agricultural land uses, both across the northeastern US and other temperate forest regions globally.

The regulators of soil organic carbon mineralization upon lime and/or phosphate addition vary with depth

Knowledge of the key factors regulating soil organic carbon (OC) mineralization in response to fertilizers and lime application is essential to understanding the effects of agricultural land management on soil OC preservation. Microbial community composition and OC availability to microorganisms have been proposed as the two most imperative factors controlling soil OC mineralization, although their relative importance is still under debate. Here we performed a laboratory incubation in combination with high-throughput sequencing and structural equation modeling to examine the mechanisms underlying the responses of OC mineralization in the topsoil and the subsoil of a volcanic soil (an Andosol) to the additions of lime and/or phosphate. Results showed that lime and/or phosphate additions induced distinct shifts in the microbial community composition and functional profiles in the topsoil and the subsoil. We found that OC mineralization relied on microbial community composition and functionality in the topsoil but was strongly related to the quality and quantity of the water-extractable OC (indicative of the OC availability) in the subsoil. These data suggest that the key regulator controlling the response of OC mineralization to lime and/or P additions shifts from microbial community composition to OC availability as soil depth increases in the Andosol. Our findings highlight the central role of mechanisms controlling soil OC mineralization in regulating the responses of mineralization to intensive agricultural management practices.

Synergy between compost and cover crops in a Mediterranean row crop system leads to increased subsoil carbon storage

Abstract. Subsoil carbon (C) stocks are a prime target for efforts to increase soil C storage for climate change mitigation. However, subsoil C dynamics are not well understood, especially in soils under long-term intensive agricultural management. We compared subsoil C storage and soil organic matter (SOM) composition in tomato–corn rotations after 25 years of differing C and nutrient management in the California Central Valley: CONV (mineral fertilizer), CONV+WCC (mineral fertilizer and cover crops), and ORG (composted poultry manure and cover crops). The cover crop mix used in these systems is a mix of oat (Avena sativa L.), faba bean (Vicia faba L.), and hairy vetch (Vicia villosa Roth). Our results showed a ∼19 Mg ha−1 increase in soil organic C (SOC) stocks down to 1 m under ORG systems, no significant SOC increases under CONV+WCC or CONV systems, and an increased abundance of carboxyl-rich C in the subsoil (60–100 cm) horizons of ORG and CONV+WCC systems. Our results show the potential for increased subsoil C storage with compost and cover crop amendments in tilled agricultural systems and identify potential pathways for increasing C transport and storage in subsoil layers.