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Assessment of the Growth in Social Groups for Sustainable Agriculture and Land Management
Get PDFFor agriculture and land management to improve natural capital over whole landscapes, social cooperation has long been required. The political economy of the later 20th and early 21st centuries prioritised unfettered individual action over the collective, and many rural institutions were harmed or destroyed. Since then, a wide range of social movements, networks and federations have emerged to support transitions toward sustainability and equity. Here we focus on social capital manifested as intentionally-formed collaborative groups within specific geographic territories. These groups focus on 1) integrated pest management; 2) forests; 3) land; 4) water; 5) pastures; 6) support services; 7) innovation platforms; 8) small-scale systems. We show across 122 initiatives in 55 countries that the number of groups has grown from 0.5M (at 2000) to 8.54M (2020). The area of land transformed by the 170-255M group members is 300 Mha, mostly in less-developed countries (98% groups; 94% area). Farmers and land managers working with scientists and extensionists in these groups have improved both environmental outcomes and agricultural productivity. In some cases, changes to national or regional policy supported this growth in groups. Together with other movements, these social groups could now support further transitions towards policies and behaviours for global sustainability
Exploring the Effects of Climate Change on Net Revenue of Farmers: an Econometric Investigation using Farm-level Data in Cross River State Nigeria
Get PDFThis paper addressed the effects of climate on the net revenue of farmers in Cross River State. The specific objectives of this paper are; to examine the level of yam production in Cross River State and, to determine the factors that affect farmers' net revenue. Data was collected from 209 farmers using a well-structured questionnaire. The analysis was done using the independent sample t-test, the Chi-square test and Ordinary Least Square (OLS) regression. The findings revealed that the mean value of the respondents on the level of profit was N88,192.13, while the maximum and minimum amount were N110,000 and N50,000, respectively. The independent sample t-test showed that education produced a statistically significant difference in means. The Chi-square test showed that educational level (p-value =0.047), age (p-value=0.034), farming experience (p-value=0.061) and access to credit (p-value=0.088) have a relationship with the net revenue of farmers. The result from the OLS regression revealed that the variables that affect the net revenue of farmers are farming experience, household size, access to the weather forecast and tenure status. This research recommends that policymakers should emphasise how to improve these factors to enhance farmers' net income to increase self-sufficiency in food crop production
Responsibility-driven collective action in the context of rapid rural depopulation
Get PDFChina has witnessed unprecedented and rapid urbanization which has led to the depopulation and structural
collapse of many traditional rural village communities, and the decline of many collective functions such as the
effective management of the public realm. In seeking to address this problem it is clear from the literature that
there is considerable potential in catalyzing collective action, particularly where there is a moral imperative to
act and the availability of leaders with the ability to organize the collective. However, while there is evidence
that community-based collective action has provided effective localized solution pathways for managing collective
goods when the focus has been on the distribution of benefits, there is little evidence about its potential in
scenarios associated with the distribution of costs, or responsibilities. In addressing this asymmetry, we present a
case study of a typical village near Shanghai which has successfully established a community based environmental
management system, and describe the process, characteristics and influencing factors of its responsibility-
centered collective action. Our findings show that smart local leadership, an effective organizing strategy,
and involvement of a suitable ‘core group’ was crucial. The strategy of mobilizing this core group, of empowering
them with decision-making rights, and supporting their volunteered role as a ‘bridge and platform’ connecting
the village cadres and villagers, significantly reduced the enforcement and monitoring costs, controlled free rider
problems, and gained public support and participation, leading to a stable and sustainable solution. Our findings
illustrate specific principles that apply to many cases in China, and general principles that are likely to be
applicable more widely
Using the Rapid Alert System for Food and Feed: potential benefits and problems on data interpretation
Get PDFThe Rapid Alert System for Food and Feed (RASFF), where competent authorities in each Member State (MS) submit notifications on the withdrawal of unsafe or illegal products from the market, makes a significant contribution to food safety control in the European Union. The aim of this paper is to frame the potential challenges of interpreting and then acting upon the dataset contained within the RASFF system. As it is largest cause of RASFF notifications, the lens of enquiry used is mycotoxin contamination. The methodological approach is to firstly iteratively review existing literature to frame the problem, and then to interrogate the RASFF system and analyse the data available. Findings are that caution should be exercised in using the RASFF database both as a predictive tool and for trend analysis, because iterative changes in food law impact on the frequency of regulatory sampling associated with border and inland regulatory checks. The study highlights the variability of engagement by MSs with the RASFF database, influencing generalisability of the trends noted. As importing countries raise market standards, there are wider food safety implications for the exporting countries themselves. As this is one of the first studies articulating the complexities and opportunities of using the RASFF database, this research makes a strong contribution to literature
Laser-Scanning Shihrazad’s Baths: 1001 Tales of Zanzibar Nights
Get PDFThis paper presents the first archaeological survey of the ornate Kidichi baths on Zanzibar. The
baths were built for or by Shihrazad, a wife of Zanzibar’s nineteenth century ruler Said bin Sultan
(1806–1856). Laser-scanning the ornate plaster stucco was used to clarify two inscriptions, the
precise meaning of which had been lost. By combining archaeological survey results with historical
research, and a translation of the inscriptions, a new narrative is presented in which the main
protagonist is, unusually, female. Her story raises a host of questions relating to heritage, gender,
religion and politics in modern-day Africa and beyond.
INTRODUCTION
The nineteenth-century Kidichi baths on the Island of Zanzibar are a legally protected historic
monument, but surprisingly have never been recorded in detail beyond an unpublished tape and
plane-table survey in 19841
. The preliminary surveys conducted by the authors in June 2017, were
undertaken as part of a Global Challenges Research Fund (GCRF) workshop to explore the threats
facing tangible and intangible heritage in Africa, and the use of modern and ancient technologies to
facilitate heritage engagement. The site was selected primarily as a convenient location to
demonstrate a range of archaeological methodologies to invited workshop participants including
ground penetrating radar (GPR), terrestrial laser scanning (TLS), unmanned aerial vehicle (UAV)
and photogrammetry to promote understanding of their utility in African contexts. Given the
international scope of the meeting, a short site summary was produced in conjunction with the
Department of Antiquities to facilitate a site tour prior to the practical demonstrations and survey. In
doing this and through surveying, it swiftly became apparent that information about the baths was
disparate and limited. Numerous questions arose including, for example, the exact date of their
construction. This was surprising given their recent age in archaeological terms; their mention as a
key tourist attraction in numerous websites and popular books such as the ‘Lonely Planet’; and their
use as a key stop during the ‘spice tours’ of Zanzibar that have proliferated since the late 1980s. This
paper aims to redress this situation, provoke discussion about heritage construction, and present a
fuller narrative based on new research as a basis for future research. Following a review of the site’s
historical context, a summary of the scientific survey is presented. The materiality of the baths is
then used to present a series of new interpretations which inform the historical narratives, before
concluding with a consideration of the wider theoretical implications of this research
Bugs and drugs: A systems biology approach to characterising the effect of moxidectin on the horse’s faecal microbiome
Get PDFBackground
Anthelmintic treatment is a risk factor for intestinal disease in the horse, known as colic. However the mechanisms involved in the onset of disease post anthelmintic treatment are unknown. The interaction between anthelmintic drugs and the gut microbiota may be associated with this observed increase in risk of colic. Little is known about the interaction between gut microbiota and anthelmintics and how treatment may alter microbiome function. The objectives of this study were: To characterise (1) faecal microbiota, (2) feed fermentation kinetics in vitro and (3) metabolic profiles following moxidectin administration to horses with very low (0 epg) adult strongyle burdens. Hypothesis: Moxidectin will not alter (1) faecal microbiota, (2) feed fermentation in vitro, or, (3) host metabolome.
Results
Moxidectin increased the relative abundance of Deferribacter spp. and Spirochaetes spp. observed after 160 hours in moxidectin treated horses. Reduced in vitro fibre fermentation was observed 16 hours following moxidectin administration in vivo (P = 0.001), along with lower pH in the in vitro fermentations from the moxidectin treated group. Metabolic profiles from urine samples did not differ between the treatment groups. However metabolic profiles from in vitro fermentations differed between moxidectin and control groups 16 hours after treatment (R2 = 0.69, Q2Y = 0.48), and within the moxidectin group between 16 hours and 160 hours post moxidectin treatment (R2 = 0.79, Q2Y = 0.77). Metabolic profiles from in vitro fermentations and fermentation kinetics both indicated altered carbohydrate metabolism following in vivo treatment with moxidectin.
Conclusions
These data suggest that in horses with low parasite burdens moxidectin had a small but measurable effect on both the community structure and the function of the gut microbiome
Spotlight on UK artisan entrepreneurs’ situated collaborations - through the lens of entrepreneurial capitals and their conversion
Get PDFAbstract
Purpose - The article’s purpose is to demonstrate how UK artisan entrepreneurs organise entrepreneurial activities within the context of a creative industry organisation. The research asks how artisan entrepreneurs draw on contexts to organise entrepreneurial activities. The article investigates how these entrepreneurs organise collaborative business solutions through the lens of entrepreneurial capitals and their conversion.
Design/methodology/approach - The research employs a phenomenological approach to analyse the situated entrepreneurial activities of artisan entrepreneurs. Ethnographic methods assisted in capturing these activities.
Findings - The findings demonstrate the context dependent collaborative business solutions by artisan entrepreneurs. Such solutions emerge from the interplay of the materiality of buildings, social relations management and personal resources. This materiality facilitates creative forms of social relations management for entrepreneurial activities between artisan entrepreneurs.
Originality - The detailed discussion of how artisan entrepreneurs organise entrepreneurial activities individually and collaboratively sheds light on dynamic micro-processes in context. The lens of entrepreneurial capitals and their conversion for these micro-processes integrates the literature on capital conversions with context as the main contribution to theory. This lens allows to home in on social relations and material environment management adding more fine-grained insights into how these micro-exchange-processes work. These insights contribute to the literature on artisan entrepreneurship in the creative industries and entrepreneurship and context.
Practical implications - The discussed entrepreneurial collaborative solutions are beneficial for many entrepreneurs in fragmented working conditions
Biochar aging: Mechanisms, physico-chemical changes, assessment, and implications for field applications
Get PDFBiochar has triggered a black gold rush in environmental studies as a carbon-rich material with well-developed porous structure and tunable functionality. While much attention has been placed on its apparent ability to store carbon in the ground, immobilize soil pollutants, and improve soil fertility, its temporally evolving in situ performance in these roles must not be overlooked. After field application, various environmental factors, such as temperature variations, precipitation events and microbial activities, can lead to its fragmentation, dissolution, and oxidation, thus causing drastic changes to the physicochemical properties. Direct monitoring of biochar-amended soils can provide good evidence of its temporal evolution, but this requires long-term field trials. Various artificial aging methods, such as chemical oxidation, wet–dry cycling and mineral modification, have therefore been designed to mimic natural aging mechanisms. Here we evaluate the science of biochar aging, critically summarize aging-induced changes to biochar properties, and offer a state-of-the-art for artificial aging simulation approaches. In addition, the implications of biochar aging are also considered regarding its potential development and deployment as a soil amendment. We suggest that for improved simulation and prediction, artificial aging methods must shift from qualitative to quantitative approaches. Furthermore, artificial preaging may serve to synthesize engineered biochars for green and sustainable environmental applications
Mapping soil pollution by using drone image recognition and machine learning at an arsenic-contaminated agricultural field
Get PDFMapping soil contamination enables the delineation of areas where protection measures are needed. Traditional soil sampling on a grid pattern followed by chemical analysis and geostatistical interpolation methods (GIMs), such as Kriging interpolation, can be costly, slow and not well-suited to highly heterogeneous soil environments. Here we propose a novel method to map soil contamination by combining high-resolution aerial imaging (HRAI) with machine learning algorithms. To support model establishment and validation, 1068 soil samples were collected from an arsenic (As) contaminated area in Zhongxiang, Hubei province, China. The average arsenic concentration was 39.88 mg/kg (SD = 213.70 mg/kg), with individual sample points determined as low risk (66.9%), medium risk (29.4%), or high risk (3.7%), respectively. Then, identified features were extracted from a HRAI image of the study area. Four machine learning algorithms were developed to predict As risk levels, including (i) support vector machine (SVM), (ii) multi-layer perceptron (MLP), (iii) random forest (RF), and (iii) extreme random forest (ERF). Among these, we found that the ERF algorithm performed best overall and that its prediction performance was generally better than that of traditional Kriging interpolation. The accuracy of ERF in test area 1 reached 0.87, performing better than RF (0.81), MLP (0.78) and SVM (0.77). The F1-score of ERF for discerning high-risk points in test area 1 was as high as 0.8. The complexity of the distribution of points with different risk levels was a decisive factor in model prediction ability. Identified features in the study area associated with fertilizer factories had the most important contribution to the ERF model. This study demonstrates that HRAI combined with machine learning has good potential to predict As soil risk levels
Using animal‐mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows
Get PDFWorldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew’s correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf