Farm Site Research Articles

Preventing illegal seafood trade using machine-learning assisted microbiome analysis

BackgroundSeafood is increasingly traded worldwide, but its supply chain is particularly prone to frauds. To increase consumer confidence, prevent illegal trade, and provide independent validation for eco-labelling, accurate tools for seafood traceability are needed. Here we show that the use of microbiome profiling (MP) coupled with machine learning (ML) allows precise tracing the origin of Manila clams harvested in areas separated by small geographic distances. The study was designed to represent a real-world scenario. Clams were collected in different seasons across the most important production area in Europe (lagoons along the northern Adriatic coast) to cover the known seasonal variation in microbiome composition for the species. DNA extracted from samples underwent the same depuration process as commercial products (i.e. at least 12 h in open flow systems).ResultsMachine learning-based analysis of microbiome profiles was carried out using two completely independent sets of data (collected at the same locations but in different years), one for training the algorithm, and the other for testing its accuracy and assessing the temporal stability signal. Briefly, gills (GI) and digestive gland (DG) of clams were collected in summer and winter over two different years (i.e. from 2018 to 2020) in one banned area and four farming sites. 16S DNA metabarcoding was performed on clam tissues and the obtained amplicon sequence variants (ASVs) table was used as input for ML MP. The best-predicting performances were obtained using the combined information of GI and DG (consensus analysis), showing a Cohen K-score > 0.95 when the target was the classification of samples collected from the banned area and those harvested at farming sites. Classification of the four different farming areas showed slightly lower accuracy with a 0.76 score.ConclusionsWe show here that MP coupled with ML is an effective tool to trace the origin of shellfish products. The tool is extremely robust against seasonal and inter-annual variability, as well as product depuration, and is ready for implementation in routine assessment to prevent the trade of illegally harvested or mislabeled shellfish.

GIS-Based Optimal Siting of Offshore Wind Farms to Support Zero-Emission Ferry Routes

To achieve net zero emissions from ships by 2050 and align with the IMO 2023 GHG strategy, the maritime industry must significantly increase zero-emission vessels by 2030. Transitioning to fully electric ferry lines requires enhanced energy supply through renewable energy sources (RES) for complete GHG mitigation and net-zero emissions. This study presents a GIS-based framework for optimally selecting offshore wind farm locations to meet the energy demands of electric ferry operations along coastal routes. The framework involves two stages: designing feasible zero-emission ferry routes between islands or to the mainland and identifying optimal offshore wind farm sites by evaluating technical, spatial, economic, social, and environmental criteria based on national legislation and the academic literature. The aim is to create a flexible framework to support decision making for establishing sustainable electric ferry operations at a regional level, backed by strategically located offshore wind farms. The study applies this framework to the Greek Coastal Shipping Network, focusing on areas with potential for future electrification. The findings can aid policymakers in utilizing spatial decision support systems (SDSS) to enhance efficient transportation and develop sustainable island communities.

Photovoltaic Solar Farms Site Selection through “Policy Constraints–Construction Suitability”: A Case Study of Qilian County, Qinghai

The scientific selection of photovoltaic (PV) sites is essential for achieving sustainable development of renewable energy and ensuring regional ecological security. In western China, extensive land resources coexist with a fragile ecological environment. To this end, we propose a PV siting framework based on policy restrictions and construction suitability. This paper evaluated the PV construction suitability index (CSI) from four dimensions of topography, climate, location, and ecology and proposed typical “PV+” models. Then, Qilian County was selected as a case study. The results showed the following: (1) In Qilian, 59.97% (8333.18 km2) of the area is unsuitable for development due to policy restrictions, leaving 40.03% (5563.02 km2) available for PV construction. (2) The most suitable areas are approximately in the western and southern areas, where there is a lot in common with the reported PV sites under construction. (3) Three distinct PV development models are proposed according to policy guidelines and local circumstances, including the PV + pastoralism model, PV + mine rehabilitation model, and PV + hydropower model. The results can be used to determine the suitable areas for solar PV farms and the appropriate development model, as well as promote the sustainable development of renewable energy.

Motion focus global–local network: Combining attention mechanism with micro action features for cow behavior recognition

The use of machine vision technology for recognizing cow behavior plays a crucial role in daily management, health monitoring, and breeding and reproduction in dairy farming, making it an essential component of modern smart agriculture. This paper presents a novel dual-stream network model, the Motion Focus Global-Local Network (MFGN), for analyzing cow video data. The dual-stream network consists of a global spatiotemporal feature stream and a fine motion feature stream. The global spatiotemporal feature stream extracts key frames to remove redundant information and utilizes a Transformer network for global spatio-temporal feature extraction, reflecting the dynamic changes in cow videos and the temporal relationships between video frames. The fine motion feature stream, based on frame differencing of cow videos, uses focal convolution to capture subtle movements of cows, enhancing the focus on minor behavioral changes. To evaluate the performance of the proposed model, video data samples were collected from eight cows marked on their bodies and heads at an Australian farm site (CSIRO Armidale), including a total of 1715 video sequences across three behavior categories. The model achieved recognition accuracies of 98.1% for drinking, 95.5% for grazing, and 49.3% for other behaviors, with an overall average recognition accuracy of 79.4%, representing a 7.4% improvement over the classic TSN model. Overall, the MFGN network effectively extracts and integrates global spatiotemporal features with fine motion features from cow video data, modeling both the overall sequence characteristics and focusing on local motion details, achieving precise behavioral recognition. This research not only enhances the accuracy of cow behavior recognition but also provides new technological means for precise management in modern smart agriculture, with broad industry application potential to improve farm efficiency, profitability, and disease control and prevention.

Impact of cultural practices on trichoderma strains in papaya rhizosphere, diamare division, Cameroon

Organic farming is a method of agricultural production that aims to respect natural systems and cycles, maintain and improve the condition of soil, water, and air, and the health of plants and animals. It is an answer to the environmental sufferings caused by chemical pesticides and synthetic fertilizers. Microscopic soil fungi in the genus Trichoderma are important in agricultural contexts as they induce soil fertility and plant resistance to pathogens. The present work assesses the presence of Trichoderma spp. in soil samples from the papaya rhizosphere in the Sudano-Sahelian area of Cameroon. Cultural practices were recorded in papaya orchards through semi-structured interviews addressed to papaya growers identified in this region. Ten papaya trees were randomly selected for soil samples in four treated plots. Three samples of soil were collected around each labelled papaya tree at 25, 50, and 75 cm from the trunk for a depth of up to 40 cm, and a composite sample consisting of the mixture of the resulting 30 soil samples performed per plot was obtained and kept for further analysis. Moreover, an additional composite soil sample from experimental papaya in the organic experimental farming site of Meskine was committed as a control plot. Microbiological studies were performed using a specific TSM at different concentration levels from 10-4 to 10-5, 10-6, 10-7, and 10-10 in Petri dishes with 6 repetitions each. The mean colonisation rate of Trichoderma spp. was compared between plots. Results showed that the common use of agrochemicals by papaya producers and the fire-prone when implementing papaya fields negatively impacted the development of useful Trichoderma strains in their farms. No Trichoderma strain was found in soil samples for each papaya farm from treated plots (0%). While, all samples analysed from the control plot were 100% productive of the soil-born microorganism sought. Farmers in the Diamare division are encouraged to use eco-friendly cultural methods for preserving Trichoderma spp. in the rhizosphere of papaya trees.

A Multi-Objective Optimization Approach for Solar Farm Site Selection: Case Study in Maputo, Mozambique

Solar energy is an important source of clean energy to combat climate change issues that motivate the establishment of solar farms. Establishing solar farms has been considered a proper alternative for energy production in countries like Mozambique, which need reliable and clean sources of energy for sustainable development. However, selecting proper sites for creating solar farms is a function of various economic, environmental, and technical criteria, which are usually conflicting with each other. This makes solar farm site selection a complex spatial problem that requires adapting proper techniques to solve it. In this study, we proposed a multi-objective optimization (MOO) approach for site selection of solar farms in Mozambique, by optimizing six objective functions using an improved NSGA-II (Non-dominated Sorting Genetic Algorithm II) algorithm. The MOO model is demonstrated by implementing a case study in KaMavota district, Maputo city, Mozambique. The improved NSGA-II algorithm displays a better performance in comparison to standard NSGA-II. The study also demonstrated how decision-makers can select optimum solutions, based on their preferences, despite trade-offs existing between all objective functions, which support the decision-making.

Statistical characterization of marine wind structure over wind-turbine-relevant heights in tropical cyclones

Tropical cyclones (or typhoons, hurricanes) may influence the power production and structural integrity of offshore wind turbines. However, understanding of tropical cyclone wind structure over turbine-relevant heights remains limited. Based on observations from a wind lidar and a meteorological mast at a planned offshore wind farm site, this paper investigates the marine wind characteristics, e.g., wind speed shear, wind direction veer, and turbulence intensity, over turbine-relevant heights in tropical cyclones. Statistical distributions of the marine wind characteristics are analyzed, and their variations with upstream fetch conditions and hub-height wind speeds are examined. Some noteworthy features of the marine wind structure in tropical cyclones are observed, such as the median wind veer rate of 0.018°/m and veer angle of 2.2° across the turbine rotor heights, different wind shear coefficients and wind veer rates for upper and lower rotors, and levelling off or decrease of wind shear coefficient and turbulence intensity with increasing wind speed at hub-height wind speed over 25 m/s. The outcome of this study is expected to provide useful information for design and operation of offshore wind turbines, marine platforms, and other ocean structures in tropical cyclone-prone regions.

Performance of mussel Mytilus galloprovincialis under variable environmental conditions and anthropogenic pressure: A survey of two distinct farming sites in the Adriatic Sea

Changes in natural conditions and anthropogenic pollutants, alone or in combination, pose a significant challenge to coastal bivalve populations. The susceptibility of economically important bivalves to potential stressors in their farming environment has not been sufficiently investigated, despite the increase in anthropogenic pressure along the coast and the remarkable warming of seawater in recent years. Thus, the aim of this study was to evaluate the performance of mussel (Mytilus galloprovincialis) from two important farming sites in the eastern Adriatic, namely Mali Ston Bay (MSB) and Lim Bay (LB), in relation to variations of seawater parameters, reproductive cycle dynamics and tissue content of potentially harmful pollutants. The complex seasonal and site-specific patterns of chemical pollutants were determined, with tissue levels of metals, As, PAHs and PCBs largely comparable to those previously reported for the Mediterranean region. Concentrations of organochlorinated pesticides were below the level of detection. Significantly higher Cd, As and Hg concentrations were detected in the tissues of the MSB mussels. The reproductive cycle was clearly associated with the bioaccumulation of pollutants. All biochemical response parameters varied to some extent across seasons and/or between farming sites. A very pronounced seasonality was recorded for acetylcholinesterase and glutathione S-transferase activity at both sites. Metallothionein concentration and superoxide dismutase activity were generally steady throughout the study period. The most striking difference between the two sites was recorded for lipid peroxides concentrations which were predominantly significantly higher in the MSB mussels, indicating expressed pro-oxidant conditions at this site. In particular, significant correlations were found between lipid peroxides and the potentially toxic metals (Cd, As, Hg) accumulated in the mussel tissue. Data reported here are valuable as baseline information for further studies related to stress in farmed bivalves caused by oscillations of environmental factors and increasing anthropogenic pressure along the coastline.

Decarbonizing Nitrogen Fertilizer for Agriculture with Nonthermal Plasma Technology

Synthetic nitrogen fertilizer is the backbone of modern agriculture, helping to feed ~50% of the world’s population. However, the current industrial production, distribution, and use of nitrogen fertilizers are built on an unsustainable foundation of fossil resources, and are energy-intensive, environmentally polluting, and inefficient in their usage. With the rapidly declining cost of renewable electricity, such as solar and wind, it is time to develop and implement the decentralized production and application of nitrogen fertilizer with nonthermal plasma technologies. Such locally sourced production at the farm site, using only air and water as feedstock, circumvents the need for the extensive capital investment and infrastructure required for synthetic nitrogen fertilizer production and storage, as well as the complex and costly distribution networks. It will be adaptive to the intermittency of the solar/wind electricity supply, leave no carbon footprint, and also have the advantage of being easily switched on/off, immediately responding to weather changes and local conditions, such as soil, climate, crops, and farming business models, for precision agriculture.

Development of the Optimal Logistics System for Organic Recycling

Abstract Along with the socio-economic development, the generation of solid waste in Vietnam is increasing, becoming an environmental problem. The amount of domestic solid waste generated in Vietnam is currently about 25.5 million tons/year, and is expected to increase on average by 10-15% per year due to rapid population growth, combined with the process of industrialization and urbanization. However, the collection and treatment system of solid waste is still a dilemma. Domestic solid waste management is still treated in traditional ways such as incineration and landfill, causing many harms to the environment. The Optimal Logistic System for Organic Recycling study aims to develop an IoT integrated Logistics system, called LogiOT system, to promote the circular economy model in Vietnam, and proposes a plan to combine waste segregation and utilization of domestic organic wastes as food for worm farming sites to produce organic fertilizers, will reduce CO2 emissions in greenhouse gas emission, contributing to the promotion of model development Circular economy in Vietnam helps to make the environment greener and cleaner. In addition, the logistics model is proposed to solve the problem of the collection system of waste from households, as well as the distribution of organic solid waste to worm farms and distribution of organic fertilizers to the vegetable gardens appropriately, optimizing the cost of the transportation as well as balancing the amount of organic solid waste distributed and the amount required by the garden owners and the amount of solid waste discharged.

Peningkatan Kesejahteraan Masyarakat Melalui Budidaya Jangkrik Di Kota Tangerang Selatan

This activity aims to assess the benefits of cricket farming for improving community welfare in South Tangerang City. In economic and agroecological contexts, cricket farming offers an environmentally friendly solution for producing alternative food and feed. The method used in this study combines material presentations on cricket farming, direct observation, and practical discussions at the farming site. The program involves 30 farmers, workers, and local community members. The activity took place on Saturday, May 25, 2024, focusing on cricket farming management, including cage preparation, cricket maintenance until harvest, marketing, and financial management of the business. The results show that using technology in cricket farming not only increases productivity but also supports sustainability by reducing waste and optimizing resource use. Additionally, crickets have great potential as an alternative protein source that can support global food security. This study provides important insights into cricket farming, from cage preparation and maintenance to harvesting, marketing the products, and managing the business finances. The findings indicate that a more efficient and sustainable production system can enhance community welfare

The farm shop as a retroscaped place of experiential consumption

AbstractAlternative food network research has referred to farm shops but rarely examined them in detail. This article argues that farm shops are not simply places of exchange but are complex, immersive, sensory‐rich places of meaning and experience. These arguments are developed through a study that adopts an interpretive/embodied perspective on conventions and applies them through a multi‐methods approach, incorporating autoethnography, interviews, a questionnaire and website analysis. The influence of farm shop interiors and farm context were investigated through thematic analysis. It was found that consumers desired a rustic interior aesthetic, an external ambience enabling exploration and an opportunity to escape time poverty through consumption. Farm shop owners endeavoured to provide a rich multi‐sensory interactive consumption experience, encompassing both enterprise buildings and surrounding farm sites. It is argued that use of ‘farm‐site’ consumption experiences distinguishes these enterprises from each other, contributes to consumer immersion and positively contributes to the collective identity of ‘farm shops’. Furthermore, the provision of retroscaped experiential consumption promises resilience from supermarket co‐optation.

A novel high-throughput qPCR chip for solving co-infections in RAS farmed rainbow trout

Recirculating aquaculture systems (RAS) have become more attractive due to reduced water consumption and effluent discharge. However, intensification of production increases the risk of introducing pathogens at farming sites. The emergence of uncultivable pathogens and RAS pathobiome diversity shifts the traditional disease paradigm from “one pathogen, one disease” to complex multiple-pathogen disease cases. Piscine orthoreovirus genotype 3 (PRV-3) is an excellent example, as it is capable of inducing anemia and heart pathology resembling heart and skeletal muscle inflammation under experimental conditions, and is associated with increased mortality in association with other pathogens in the field. The aim of this study was to develop a method for detection of multiple pathogens and putative pathogens, as co-infections are common in aquaculture. To do this, in the pilot study, we mapped the pathobiome of RAS-farmed rainbow trout (Oncorhynchus mykiss) (commercial RAS, farm A) using both standard diagnostic methods and metabarcording (16S rRNA) to investigate the gill microbiome. During this study, we observed infections with multiple pathogens, and detected two putative gill pathogens Candidatus Branchiomonas cysticola and Candidatus Piscichlamydia salmonis, both of which have been linked with complex gill disease in Atlantic salmon (Salmo salar). Based on the pilot study, we developed and tested a high throughput qPCR (HT-qPCR) chip targeting 22 viral and bacterial pathogens and putative pathogens, followed by a surveillance of a fish cohort in a commercial RAS farm during production (farm B). Co-infection with PRV-3 and Ca. B. cysticola combined with stress inducing management practices may explain the severe disease outbreak observed (37% mortality). The time course study sets the base for a future screening scheme for disease prediction and addresses limitations of the method when testing environmental DNA/RNA.

Integrating rainfall index-based insurance with optimal crop management strategies can reduce financial risks for Australian dryland cotton farmers

Drought undermines the financial sustainability of farmers. While farmers have adopted various strategies to mitigate some drought impacts, they remain exposed to substantial drought risk. Insurance could be useful in managing climatic risks and for encouraging farmers to take sensible risks (e.g., changing their sowing date to increase yield), but it can be costly. Here, we tested whether the integration of a change in sowing date with rainfall index-based insurance could improve farmer profitability and income stability. We used the Agricultural Production Systems Simulator (APSIM)-Cotton model to simulate cotton lint yields for various sowing dates, taking into account different management strategies, across three dry-land cotton research farm sites – Dalby, Goondiwindi, and Theodore – from 1940 to 2022. We designed the index-based insurance payout when the average rainfall received during the growing season falls below a predefined level, such as the 5th, 10th, or 20th percentile of rainfall. Our study, which involved 3.9 million cotton lint simulations and 3,000 rainfall index-based insurance products, showed that combining a shift in sowing date with insurance can lead to an income improvement of up to 21.5% at some study sites. Additionally, in drought years, the income improvement for farmers who combined optimal sowing dates with rainfall index-based insurance was up to 48.0%. The framework developed in this study could aid in devising financial strategies to enhance farming resilience during climate extremes.

Gone with the Clam Multispecies Arrangements and Feral Rhythms in the Goro Lagoon (Po River Delta)

The Goro Lagoon, located at the southern edge of the Po River Delta, is considered a major European site for clam farming. Following the advent of the Manila Clam ‘revolution’ in the 1980s, the local community transitioned from traditional fishing to a mono-focalised ecological infrastructure focused on aquaculture. However, in the last decade, anthropogenic climate alterations have severely impacted the lagoon and its industrial system, triggering a series of accelerated proliferations of macroalgae and non-indigenous species – the Atlantic Blue Crab being the most prominent one. The article investigates the eco-cultural entanglement of the Goro Lagoon and critically explores the multispecies correspondences that excited its biosocial becoming. Thus, the concept of ‘arrangement’ is employed to question both local representations of clam farming and the feral disturbances endangering its feasibility. Finally, ethical and political implications are discussed in light of the cultural expectations of controllability embedded in the technocratic administration of the lagoon.

Evaluating the effects of temperature and agitation on biofilm formation of bacterial pathogens isolated from raw cow milk

ObjectivesTo study the effect of agitation and temperature on biofilm formation (cell aggregates embedded within a self-produced matrix) by pathogenic bacteria isolated from Raw cow milk (RCM).MethodsA 40 RCM samples were gathered from eight dairy farms in Riyadh, Saudi Arabia. After bacterial culturing and isolation, gram staining was performed, and all pathogenic, identified using standard criteria established by Food Standards Australia New Zealand (FSANZ), and non-pathogenic bacteria were identified using VITEK-2 and biochemical assays. To evaluate the effects of temperature and agitation on biofilm formation, isolated pathogenic bacteria were incubated for 24 h under the following conditions: 4 °C with no agitation (0 rpm), 15 °C with no agitation, 30 °C with no agitation, 30 °C with 60 rpm agitation, and 30 °C with 120 rpm agitation. Then, biofilms were measured using a crystal violet assay.ResultsOf the eight farm sites, three exhibited non-pathogenic bacterial contamination in their raw milk samples. Of the total of 40 raw milk samples, 15/40 (37.5%; from five farms) were contaminated with pathogenic bacteria. Overall, 346 bacteria were isolated from the 40 samples, with 329/346 (95.1%) considered as non-pathogenic and 17/346 (4.9%) as pathogenic. Most of the isolated pathogenic bacteria exhibited a significant (p < 0.01) increase in biofilm formation when grown at 30 °C compared to 4 °C and when grown with 120 rpm agitation compared to 0 rpm.ConclusionHerein, we highlight the practices of consumers in terms of transporting and storing (temperature and agitation) can significantly impact on the growth of pathogens and biofilm formation in RCM.

Wind resource assessment for turbine class identification in Bayanzhaganxiang, China

Abstract The wind resource assessment has been used effectively to identify the classification of wind turbines at a particular wind farm site. The current study used WAsP software and various statistical methods such as graphical, energy pattern factor, standard deviation, and Rayleigh distribution methods to find the Weibull parameters by evaluating the raw data collected from August 2005 until July 2006 at four (4) different heights of the meteorological mast station in Bayanzhaganxiang, China. The Weibull parameters were utilized to find the annual mean wind speed, probability density, and cumulative distribution functions of wind conditions at the reference heights of 70 m, 50 m, 30 m, and 10 m. The wind shear coefficient was 0.130 with an overall roughness factor of 0.0385 m, suggesting the site vicinity is an open country with no significant structures and vegetation. The results also showed that the post-processed output from WAsP and standard deviation method at the sensor’s height of 70 m have a correlation coefficient and confidence level of 0.99977 and above 95%, respectively. Based on the turbine classification from GL Wind 2003 and IEC 61400-1 Ed.2, it was found that the turbine class ideal for the site is class III wind turbines with an annual mean wind speed of 7.439 m/s at a hub height of 99 m. The measured wind power density at hub height was calculated according to IEC 61400-12-1, which yields 464.36 W/m2. The characteristic wind turbulence at 70 m high is IEC subclass B. Among the selected wind turbines, the net annual energy production with efficiency is 8,059.57 MWh/year using Avantis AV1010, with the highest capacity factor of 40.05%. It has been found that the lowest energy generation cost is US$ 0.0292/kWh for a period of 20 years.

Protective Measures from the Interference of Confining Animals to Farm Site

Protective Measures from the Interference of Confining Animals to Farm Site

Red and melanized focal changes in the white skeletal muscle of farmed rainbow trout Oncorhynchus mykiss.

Fillet discoloration by red and melanized focal changes (RFCs and MFCs) is common in farmed Atlantic salmon Salmo salar. In farmed rainbow trout Oncorhynchus mykiss, similar changes have been noted, but their prevalence and histological characteristics have not been investigated. Thus, we conducted a study encompassing 1293 rainbow trout from 3 different farm sites in Norway, all examined at the time of slaughter. Both macroscopic and histological assessments of the changes were performed. Reverse transcription (RT)-qPCR analyses and in situ hybridization (ISH) were used to detect the presence and location, respectively, of potential viruses. Only 1 RFC was detected in a single fillet, while the prevalence of MFCs ranged from 1.46 to 6.47% between populations. The changes were predominantly localized in the cranioventral region of the fillet. Histological examinations unveiled necrotic myocytes, fibrosis, and regeneration of myocytes. Melano-macrophages were found in the affected areas and in myoseptal adipose tissue. Organized granulomas were observed in only 1 fish. Notably, the presence of inflammatory cells, including melano-macrophages, appeared lower compared to what has been previously documented in Atlantic salmon MFCs. Instead, fibrosis and regeneration dominated. RT-qPCR and ISH revealed the presence of piscine orthoreovirus 1 (PRV-1) and salmonid alphavirus (SAV) in skeletal muscle. However, these viruses were not consistently associated with lesioned areas, contrasting previous findings in Atlantic salmon. In conclusion, rainbow trout develop MFCs of a different character than farmed Atlantic salmon, and we speculate whether the observed pathological differences are contributing to their reduced occurrence in farmed rainbow trout.

Using a multi-scale approach to examine the effects of field margins and landscape features on predatory carabid communities in crop fields

Carabid beetles are major predators in agro-ecosystems. The composition of their communities within crop environments governs the pest control services they provide. Field margins and landscape features are known to affect carabid community composition, yet evidence is currently lacking that can be used to support land management decisions targeted at optimising predation services at the farm scale. We used experimental margins across a farm site to test carabid communities in crop areas, margins, and adjacent habitats sampled in the summer. We used novel subterranean trapping with standard pitfall trapping, to distinguish above ground and below ground activity of adults and larvae in different farm habitats. Crop type was the major influence on carabid communities in crop areas. This was followed by landscape influences in terms of adjacent habitat and boundary features, and whilst significant, margin type explained relatively little variance in summer carabid communities in-field. Trap type revealed differential activity by species. Responses to crop type, landscape factors, and margin type also varied by species. Overall, abundances were less in association with margins than control of no margin. Particularly, abundances were lower in the spillover zone adjacent to grass margins, and in the wildflower margins themselves. Carabid larvae showed notably higher abundances in association with an absence of field margins. Measures to boost key carabid species in crop areas should be considered at a farm scale, taking into account potential barrier effects, and potential buffer effects.