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Background: Anthrax is a zoonotic disease that is still regarded as a public health issue in developing nations. This paper aims to discuss the epidemiology of anthrax in Africa, the current outbreaks in Ghana and Nigeria, clinical presentations, diagnosis, and treatment of anthrax, challenges associated with the transmission of the disease to both countries and recommendations to reduce this current outbreak and curb future outbreaks in Africa. Online databases (PubMed, and Google Scholar) and Nigeria Ministry of Agriculture report were used to provide detailed information on the paper. On June 1, 2023, two suspected human cases of anthrax were reported, via a letter sent to all stakeholders in the country, with one death in Binduri District, Upper East region of Ghana. The cases were due to the consumption of dead cattle. Four cattle were reported dead at the time, and eleven suspected human cases were identified through contact tracing. Afterward, on July 17, 2023, the Federal Ministry of Agriculture and Rural Development of Nigeria announced the first case of anthrax disease in Nigeria. The National Veterinary Research Institute confirmed the case from samples collected from a suspected livestock farm in Niger State, Nigeria. No human case has been reported. Short conclusion: Anthrax poses significant challenges to public health and requires cooperation between nations, especially in regions like Ghana and Nigeria, where animal movement and ecological changes can impact disease transmission. Challenges attributed to the spread of anthrax in both countries were discussed, focusing on the role of government and the general public in addressing this public health concern. Given the endemicity of certain transboundary animal diseases such as anthrax in sub-Saharan Africa, the control of animal movement across intra- and international borders in the region needs to be tightened. Regulations governing the transboundary movement of animals should be based on the World Organisation of Animal Health Terrestrial Code and should be strictly enforced to prevent ongoing and future outbreaks in Africa. [ABSTRACT FROM AUTHOR]

A new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper. The dataset includes five cow behaviors: standing, lying down, foraging,rumination and drinking. The dataset comprises 107 cows from the entire barn, maintaining an 80% stocking density. Monitoring occurred over 96 h for these 20-month-old cows, considering varying light conditions and nighttime data to ensure standardization and inclusivity.The dataset consists of ranch monitoring footage collected by seven cameras, including 687 video segment samples and 206,100 image samples, covering five daily behaviors of cows. The data collection process entailed the deployment of cameras, hard drives, software, and servers for storage. Data annotation was conducted using the VIA web tool, leveraging the video expertise of pertinent professionals. The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model. The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28% on the test set. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.The CBVD-5 dataset significantly influences dairy cow behavior recognition, advancing research, enriching data resources, standardizing datasets, enhancing dairy cow health and welfare monitoring, and fostering agricultural intelligence development. Additionally, it serves educational and training needs, supporting research and practical applications in related fields. The dataset will be made freely available to researchers world-wide. [ABSTRACT FROM AUTHOR]

Sustainable agricultural progress is one of the world's greatest challenges in the twenty-first century as the global population is estimated to rise to over nine billion by 2050. Over the years, the Food and Agricultural Organization (FAO) and the African Union (AU) have sought prosperous African Policies based on sustainable agriculture and inclusive growth. Additionally, the AU has adopted the Comprehensive African Agricultural Development Programme (CAADP) policy framework. Given the growing need for innovative policies and studies to reduce the negative environmental effects of agricultural development in Africa, this paper investigates the significance of green finance and digital technologies on green agricultural growth in sub-Saharan Africa (SSA) from 2003 to 2018. Analysis of panel co-integration estimates indicates all variables are integrated. Using the panel-corrected standard errors estimator for long-run equilibrium co-integration assessment, the outcomes indicate mitigated green finance (MGF), internet and mobile phone use (IMU), as well as sustainable energy utilization (RE), individually and collectively exert a positive effect on agriculture, forestry and fishing value added (AVA). Additionally, panel causality estimates indicate (i) a bi-directional causality between MGF and AVA. (ii) A uni-directional causality running from IMU towards AVA without any rebound effect. For policy insights, the AU could urge member states to implement macro-policies to increase agricultural green credit to sustain food production and employment generation. Similarly, the FAO and AU could provide technical support in digital agricultural research and value chains towards ensuring sustainable agriculture development in SSA. [ABSTRACT FROM AUTHOR]

Studying the impact of urbanization on agricultural development in shrinking areas is important for maintaining food security and promoted agricultural development in China. Based on the measurement results of the shrinking cities in the three provinces of Northeast China, this paper selects 15 shrinking cities as the research object, and constructs a multi-dimensional index system to explore the impact of the urbanization level of the shrinking areas on the agricultural development in the region since 2007–2019, analyzes the influencing factors and their differences by using the geographically-weighted regression model and Geodetector, and proposes a targeted regulation strategy. The results show that: 1) overall, there is a negative correlation between the urbanization level and the agricultural development level in the contracted areas of the three northeastern provinces. The urbanization level in these areas has a certain negative impact on the overall level of agricultural development; 2) regarding the time dimension, the impact of urbanization level on the agricultural development level in the contracted areas of the three northeastern provinces gradually increases over time; 3) regarding the spatial pattern, the overall impact of shrinking urbanization levels in the three provinces of Northeast China on the agricultural development shows a significant distribution pattern of high in the east and low in the west; 4) the total population and natural population growth rate at the end of the year were the main factors influencing a certain level of urbanization on agricultural development in the shrinking cities while population density and the urban fixed asset investment rate were the secondary factors; and 5) the main reasons why the level of agricultural development in different cities was affected by the level of urbanization were different. However, they can be categorized into areas of population loss and spatial construction, which can be further divided into area of population loss in the northeast, areas of negative population growth in the west, and areas of urban spatial change in the south. According to the causes of the impact, this paper adopted targeted regulation strategies and formulated relevant policies and solutions that cater to local conditions. [ABSTRACT FROM AUTHOR]

The estimation of agricultural output is an important issue in the digital development of modern agriculture. Using embedded technology, this paper designs a multimedia platform for digital estimation of agricultural output. The terminal design of the multimedia platform selects the Intel Xscale series PXA255 processor as the core processor, uses multiple sensors to collect agricultural output-related environmental parameters and selects the digital media processing chip TMS320DM642 for multimedia processing. The software used selects the grey relational Support Vector Machine (SVM) algorithm to estimate agricultural output. First, the collected agricultural sown area, labor force, mechanical power, irrigated area, agricultural production environment and other parameters are collected as input to grey relational SVM. Second, the estimated results are outputted. Finally, the results of agricultural output estimation are digitally displayed by a display interface on the embedded multimedia terminal. The experimental results show that the prediction error is less than 1%, and the prediction accuracy is higher than 99%, which validates that the method can accurately predict agricultural output with an abundance of applications. [ABSTRACT FROM AUTHOR]

Agricultural green development is an essential direction for global sustainable agriculture. The academic literature, however, needs to place greater emphasis on studying the factors influencing agricultural green development performance and how such performance can be improved. A theoretical framework for agricultural green development performance was constructed in this paper using the Super-SBM model, which considers undesirable outputs, to measure the agricultural green development performance of 330 cities at or above the prefecture level in China (excluding Tibet Autonomous Region, Hong Kong, Macao and Taiwan of China) from 2007 to 2018. Furthermore, the influencing mechanism of agricultural green development performance was then analyzed using a spatial econometric model. The results show that: 1) from 2007 to 2018, China's agricultural green development performance experienced three stages of evolution: 'rise, decline and rise'. 2) The regions with high performance agricultural green development are mainly distributed in eastern China, northeastern China, and southern Qinghai Province. 3) The agricultural economic level, industrialization process, and labor quality play significant roles in promoting local agricultural green development performance, while such performance is obviously inhibited by the openness level and the government's environmental regulations. Local agricultural green development performance is significant inhibited by the agricultural economic level and accelerated industrialization process in neighboring cities, while significantly promoted by the agricultural industrial structure in neighboring cities. Some suggestions for improving agricultural green development performance are proposed based on these research results, which can provide scientific references for promoting sustainable agriculture. [ABSTRACT FROM AUTHOR]

Sustainable development of agriculture is the basis for achieving social sustainable development. As the basic industry of national economy, green development of agriculture has become an important support for building an environment-friendly society. Agricultural fiscal expenditure is a direct channel for the government to support agriculture and promote agricultural transformation. It is important to analyze the impact of agricultural fiscal expenditure (AFE) on agricultural green total factor productivity (AGTFP) for sustainable agricultural development. Therefore, this paper employs the random effect model and spatial Durbin model to empirically analyze the direct effect and spatial spillover effect of AFE on AGTFP by using the agricultural panel data of 30 provinces in China from 2008 to 2020. Then, by taking the policy proposal as the time node, this paper also conducts a time heterogeneity analysis to measure the impact of policy enactment on AFE and AGTFP. The main conclusions are as follows: (1) AGTFP exists significant positive spatial spillover effect. The "radiation effect" of agricultural green development is significant. (2) AFE can significantly reduce the AGTFP in the local area, that is, 1% increase of AFE in the local area will reduce AGTFP by 0.037%. At present, agriculture is still yield-oriented. The improvement of AFE in the local area will lead to the expansion of local agricultural production and increase pollution emission. (3) AFE has a significant negative spatial spillover effect on AGTFP, that is, for every 1% increase in AFE, the AGTFP will decrease 0.123% in geographically similar areas, while the AGTFP will decrease by 0.116% in economically and geographically similar areas. It is obvious that AFE will promote the optimization of agricultural production conditions in the province, with the "demonstration effect" on the surrounding areas, the enthusiasm of production in the surrounding areas will increase, thus expanding the pollution emission. (4) According to the analysis of different periods, AFE has a negative impact on AGTFP mainly before the reform innovation is proposed in 2015. It indicates that reform policies have a significant impact on agricultural sustainability. [ABSTRACT FROM AUTHOR]

The transition to a new reference period of 1991–2020 requires updating the estimates of agroclimatic resources in agricultural regions. The paper summarizes the results of the annual monitoring of agroclimatic conditions over 1961–1990 and 1991–2020 obtained by both the statistical analysis and the Climate–Soil–Yield simulation system and provides their comparative evaluation. It has been noted that along with growing aridity of the most fertile areas of the steppe and forest-steppe zones, there is an almost universal growth of spring precipitation, which compensates to some extent the negative impact of high summer temperatures on the yield. A significant decrease in the climate-driven productivity of spring wheat from the period of 1961–1990 to the new reference period of 1991–2020 has been revealed for the main grain-producing regions. Estimates of productivity trends for major grain crops, spring and winter wheat, are given in connection with climate change and the development of agricultural technologies. Estimates of changes in the wintering indices and sown areas for winter wheat are also given. [ABSTRACT FROM AUTHOR]

Building a more resilient response system to climate change for sustainable development and reducing uncertainty in China's food markets, requires access to historical research gaps and mapping future research progress for decision making. However, the lack of quantitative and objective analyses to ensure the stability and development of agroecosystems increases the complexity of agro-climatic mechanisms, which leads to uncertainty and undesirable consequences. In this paper, we review the characteristics of climate change in China (1951–2020), reveal the mechanisms of agroecosystem structure in response to climate, and identify challenges and opportunities for future efforts in the context of research progress. The aim is to improve the scientific validity and relevance of future research by clarifying agro-climatic response mechanisms. The results show that surface temperature, precipitation, and frequency of extreme weather events have increased to varying degrees in major agricultural regions of China in 1951–2020. And they have strong geographic variation, which has resulted in droughts in the north and floods in the south. Moreover, climate change has complicated the mechanisms of soil moisture, Net Primary Productivity (NPP), soil carbon pool, and crop pest structure in agroecosystems. This lends to a reduction in soil water holding capacity, NPP, soil carbon content, and the number of natural enemies of diseases and insects, which in turn affects crop yields. However, human interventions can mitigate the deterioration of these factors. We have also realized that the methodology and theory of historical research poses a great challenge to future agroecosystem. Historical and projected climate trends identified current gaps in interdisciplinary integration and multidisciplinary research required to manage diverse spatio-temporal climate change impacts on agroecosystems. Future efforts should highlight integrated management and decision making, multidisciplinary big data coupling, and numerical simulations to ensure sustainable agricultural development, ecological security, and food security in China. [ABSTRACT FROM AUTHOR]

The development of science and technology has also led to the progress of rural digital economy. In China, the construction of new countryside has always been an important part of economic development. The application of big data technology in rural areas can not only promote the development of rural economy, but also improve the results of environmental protection. Using the matching coefficient method of agricultural water and soil environmental characteristics, it match the rural water and soil environmental characteristics and the impact of the water environment in the autonomous region. An indispensable driving force in the process, agricultural digitalization will update the rural economic development model, weaken the barriers to the dual structure of urban and rural areas, stabilize agricultural production, promote sustainable rural development, and promote rural economic development. The current government policy support, the urgent need for new development momentum for rural economic development, and the advancement of changes in the lifestyle of urban and rural residents are promoting high-quality development of the rural economy. At the same time, we are facing challenges such as the lack of local network coverage, the lack of logistics, sales systems, and the lack of talents with digital skills. Expanding rural network coverage, optimizing rural logistics and distribution, promoting the development of agricultural big data, and strengthening the development of digital human resources are important ways for agricultural digitalization to promote rural economic development. The research focus of this paper is the parallel development of rural digital economy and environmental protection under the big data economy, and its application in the current agricultural development can achieve a win–win situation between man and nature. [ABSTRACT FROM AUTHOR]

Under the background of the new development concept, compared with the absolute impacts, the relative impacts of climate change on agricultural growth deserve more attention. Based on the data from China for years 1991 and 2018, this paper uses historical fluctuations in temperature within cities to identify the heterogeneous effects on aggregate agricultural outcomes during farming and fallow periods. The results show that: first, as temperature rises reduce the economic growth rate of each agricultural sector, and the areas that are relatively vulnerable (i.e., areas where disposable income of farm households is below the sample mean) are more significantly affected by the negative impact of temperature rise; second, the impact of temperature rise on agricultural economic growth is mainly concentrated in the farming period, while the marginal damage of temperature rise is on a decreasing trend; third, the heterogeneous impact of temperature rise on agricultural economic growth during the agricultural fallow period is also not negligible. At the same time, its impact on agricultural economy is still in the primary stage, that is, its marginal damage tends to increase with the increase in temperature fluctuation. These results inform identifying the climate's role in agricultural development and provide a theoretical and operational perspective for further optimizing the adaptive policy systems. With wide coverage of adaptive technology, we should pay more attention to the even distribution of technological dividends and continuously improve the coping ability of vulnerable groups. [ABSTRACT FROM AUTHOR]

The high environmental pollution load caused by the massive pollutant emissions and the accumulation of endogenous and cross-regional pollution has become an important obstacle to the current ecological civilization construction in the Yangtze River Economic Belt (YREB) in China. Taking the YREB as an example, by using four environmental pollutant emission indicators, including chemical oxygen demand (COD), ammonia nitrogen (NH3-N), sulfur dioxide (SO2), and nitrogen oxides (NOx), this paper established an environmental pollution load index (EPLI) based on the entropy-based measurement. Moreover, the Spatial Durbin Model was used to quantitatively analyze the drivers and spatial effects of environmental pollution load. Finally, specific scientific references were provided for formulating environmental regulations of pollution source control in the YREB. The results showed that: 1) During 2011–2015, the EPLI in the YREB was reduced significantly and the environmental pollution load increased from upstream to downstream. Among them, the pollution load levels in the Upper Mainstream subbasin, Taihu Lake subbasin, and Lower Mainstream subbasin were the most prominent. 2) The environmental pollution load situation in the YREB was generally stable and partially improved. High load level areas were mainly concentrated in the Yangtze River Delta Region and the provincial borders in upstream, midstream, and downstream areas. The high load level areas already formed in Chengdu and Chongqing were also the key regulatory points in the future. 3) The degree of local environmental pollution load was apparently affected by the adjacent cities. The population size, industrialization level, and the fiscal decentralization not only drove the increase of the local environmental pollution load level, but also affected the adjacent areas through the spatial spillover effects. The land development intensity mainly drove the increase in the local EPLI in the YREB. While factors such as economic development level and agricultural economic share could only act on the environmental pollution load process in adjacent cities. 4) According to the differentiation characteristics of drivers of each city, the YREB was divided into seven zones based on k-medoids cluster method, and targeted zoning control policy recommendations for alleviating environmental pollution load in the YREB were proposed. [ABSTRACT FROM AUTHOR]

With the development of park-level agricultural, agricultural production and household electricity fusion, it is of great significance to promote users to actively respond to power consumption plan based on their own habits. In this paper, a multi-objective household intelligent power consumption optimization model is proposed from two aspects of economy and comfort. Firstly, the operating constraints of interruptible loads and non-interruptible loads were established based on the working characteristics of various household appliances. Then, the expenditure model was constructed to take into account the electricity sales situation of surplus electricity generated by photovoltaic, and a three-layer index system quantifying the influence of user preference on comfort level was constructed. The preference coefficient was determined by analytic hierarchy process, which was used to construct the users' comfort level model. Finally, the multi-objective particle swarm optimization algorithm was applied to obtain optimization results. Considering the seasonal difference, the simulation showed that this model minimized the expenditure and increased the comfort level during summer and winter by 26.0% and 27.5% respectively. [ABSTRACT FROM AUTHOR]

This paper reviews the empirical literature on the determinants of farmer adoption of sustainable intensification technologies in maize agri-food systems of the Global South. The attributes of the technology and the dissemination institutions interact with farm/farmer-specific variables, leading to heterogeneous impacts, making the prediction of technology adoption challenging. However, most empirical studies oversimplify the adoption process and examine only the farm/farmer-specific variables as the determinants of adoption, thereby limiting the scope of learning on how the attributes of the technology and the dissemination system could have been altered to realize a more efficient and more inclusive technological change. We argue for a realignment of empirical adoption analysis for better implications through a conscious rejection of the assumption that the onus of technology performance rests solely with the farmer. Here we review the studies published between 2007 and 2018 on the adoption of sustainable intensification technologies in maize systems of the Global South to examine how the adoption models are currently dependent on the farm/farmer attributes vis-à-vis the attributes of technologies and disseminating institutions. The main findings from a synthesis of 137 adoption studies are threefold. (1) Limited information access and technologies not suitable for the small landholdings were the major constraints of farmer adoption of technologies. (2) The criticisms on the conventional adoption analysis concerning oversimplification and decontextualization of the decision-making process are reaffirmed. (3) The empirical adoption research needs to incorporate the attributes of technologies and the socio-institutional context to develop better research strategies toward inclusive agrarian development. We examine how the framework of the socioeconomic analysis can be reconstructed to facilitate the research and development (R&D) institutions to overcome the major hurdles of rapid and inclusive dissemination. Evaluation of the degree to which the attributes of technology favor its adoption requires increased research attention. [ABSTRACT FROM AUTHOR]

Urban agglomerations are spatial entities that promote the development of ‘new urbanization’ processes within China. In this context, the concept of ‘multiscale urban agglomeration spaces’ encompasses three linked levels: macroscale urban agglomerations, mesoscale cities, and microscale urban centers. Applying a series of multidisciplinary integrated research methods drawn from geography, urban planning, and architecture, this paper reveals two intensive utilization laws that can be generalized to apply to multiscale urban agglomeration spaces, top-to-bottom ‘positive transmission’ linkage and inside-to-outside ‘negative transmission’ movement. This paper also proposes optimization transmission theory and policy decision technical pathways that can be applied to these three urban agglomeration spatial scales. Specific technical pathways of transmission include intensive expansion and simulated decision-making in macroscale urban agglomerations, ecology, production, and living space intensive layout and dynamic decision-making in mesoscale cities, and four cores (i.e., ‘single, ring, axis, and pole core’) progressive linkage and intensive optimization decision-making in microscale urban centers. The theory and technical pathways proposed in this paper solve the technical problem of optimization and provide intensive methods that can be applied not only at the individual level but also at multiple scales in urban agglomeration spaces. This study also advances a series of comprehensive technical solutions that can be applied to both compact and smart growth cities as well as to urban agglomerations. Solid theoretical support is provided for the optimization of Chinese land development, urbanization, agricultural development, and ecological security. [ABSTRACT FROM AUTHOR]

The sustainable development of agricultural systems where nutrients and water are recycled to a high degree is of enormous importance. Traditional aquaponics, where fish and plants are cultivated in one recirculating system, addresses these ecological challenges, but still struggles with its economical feasibility. Decoupled multi-loop aquaponics systems, in which the aquaculture and hydroponics subsystems are running autonomously, proved that they can keep up with the productivity of state-of-the-art hydroponics systems or even outscore them. Yet, a problem of such decoupled aquaponics systems was that plants require a high nutrient concentration, whereas fish prefer rather a clean water. In practice, the opposite is happening as the nutrients are added to the aquaculture units through the feed. This paper optimizes a recent approach showing that desalination technologies, such as reverse osmosis, can play an important role in reversing the concentrations within such systems without killing beneficial plant growth–promoting rhizobacteria thermally. The proposed integrated systems approach has the potential to make both periodical nutrient and water discharges and excessive fertilizer supplementation obsolete that would otherwise be necessary to maintain good water quality for the fish and an optimal nutrient solution for the plants. [ABSTRACT FROM AUTHOR]

Wisdom agriculture is a high-level development stage of modern agriculture, which is also one of the key areas of development of national Internet planning. A large number of scientific and technological innovation technology used in agricultural development, including communication technology, automation control systems, and wisdom of agricultural management, which is a complex and unpredictable time series, most of the research methods are based on the linear model, ignoring the nonlinear factors, resulting in the prediction accuracy is not high. In this study, the ARIMA model was used to linearly model the agricultural management time series, and then the nonlinear part of the agricultural management time series was modelled by SVM. Finally, the comprehensive prediction results of the two models were obtained. In addition, this paper combined with intelligent agriculture multi-information fusion technology, which is based on corn planting management empirical analysis in Jiangsu Province. The experimental results show that the combined model is more accurate than the single model, BP neural network prediction has higher precision, and the advantages of the two models are played, and the model is better Agricultural production assessment and adaptation research which need to be applied. [ABSTRACT FROM AUTHOR]

Progressive developments in industrial and agricultural activities are causing a critical stress on groundwater quality in developing countries. The objective of this paper is to assess and evaluate the contamination level of groundwater caused by leachate in 11 villages of the Gautam Budh Nagar district in Uttar Pradesh, India. We systematically sampled 22 groundwater samples and 13 leachate samples to ascertain the source of pollution on groundwater quality. The standard analytical methods given by the American Public Health Association (APHA) (Standard methods for examination of water and wastewater, 23rd edn. APHA, AWWA, WPCF, Washington, 2017) were used for quantitative estimation of hydrochemical parameters of collected samples. The results of the analysis of groundwater samples indicate that pH values range from 7.31 to 8.97. The mean magnesium concentration in groundwater samples is 58.93 ± 21.44 mg/L. Out of the groundwater samples taken, approximately 41% and 73% of samples analysis results have been found beyond the acceptable limit with respect to the parameters of turbidity and total dissolved solids, respectively, according to the Bureau of Indian Standards (Indian standard specification for drinking water (IS:10500). BIS, Manak Bhawan, New Delhi, 2012) for drinking water. Around 95.4% of groundwater samples and 92.3% of leachate samples have high nitrate concentrations above the standard limit of BIS (45 mg/L), respectively. The Piper plot shows that 50% of the samples belong to the Ca2+–Mg2+–HCO3− type. Ternary and Durov's diagrams indicate that the mean concentrations of ions are in the order of Na+ > Mg2+ > Ca2+ > K+ (for cations) and HCO3−> NO3− > Cl− > SO42− > CO32− > F− (for anions) in groundwater of the study area. The spatial variation of the hydrochemical parameters shows that groundwater is heavily contaminated with respect to nitrate. Analytical results indicate that the groundwater of villages Achheja, Bisrakh road, Dujana, Badalpur and Sadopur is not suitable for drinking. [ABSTRACT FROM AUTHOR]

In Spring 2015, a series of earthquakes and aftershocks struck Nepal. The earthquakes caused significant changes in labor and land availability, cash income needs, and land quality. We examine how these post-earthquake impacts converged with ongoing agricultural shifts. Earthquake-related socio-economic and landscape changes specifically motivate the adoption of cardamom, Amomum subulatum, a high-value ecologically beneficial, and low labor commercial crop. We investigate reasons for the increased interest in cardamom post-earthquake, and challenges associated with it. We find that adopting cardamom serves as an important post-disaster adaptation. However, more broadly, unevenly distributed interventions coupled with the high capital costs of agricultural transition exacerbate social differentiation in communities after the disaster. Adoption is often limited to economically better off smallholder farmers. This paper extends previous research on disasters and smallholder farming by highlighting the specific potential of disasters to accelerate agricultural transitions and resulting inequality from the changes. [ABSTRACT FROM AUTHOR]

This paper presents new data regarding agricultural developments in the Balearic Islands between the end of the third millennium bc and the arrival of the Romans in the 2nd century bc. Data available so far reveals that agriculture, together with raising livestock, were the population’s source of livelihood. Agriculture in the third and second millennium consisted essentially of growing cereals and legumes. The available data point to an agricultural development similar to that of the continent, in the region stretching between the south of France and the south of the Iberian Peninsula. The similarities, in fact, possibly reflect contacts. Arboriculture was first introduced in the island of Ibiza in the first millennium in contexts linked to Phoenician colonisation. Olive oil and wine production developed remarkably on this island and were oriented toward export. Although the chronology of this process is still unclear, it seems that in Mallorca and Menorca it took place at a later period. [ABSTRACT FROM AUTHOR]

It is well established that hedgerows provide habitats, which cannot be found in otherwise coherent agricultural landscape. However, different organisms vary in their response to various environmental variables of hedgerows. The aim of this paper is to study how are the myriapod species richness and community composition related to biological and morphological parameters of farmland hedgerows. We expected diversity to be related to size of hedgerows and community composition to be primarily affected by their biological attributes. We studied myriapod communities in 20 hedgerows located in close vicinity of Žibritov village (the Carpathians, Slovakia) in Central European upland farmland. Characteristics of the hedgerows were either measured in the field or derived from GIS layers. We used univariate and multivariate correlation methods to investigate the effect of hedgerow characteristics on diversity and composition of myriapod communities. Surprisingly high taxa numbers of myriapods were found within small area. Richness of millipedes showed negative relationship with hedgerow plant community diversity, hedgerow length and soil depth and weak positive relationships with a degree of shrub layer defoliation. Centipede richness was mainly related to diversity of hedgerow tree layer. We did not find any significant relationship between centipede communities' composition and environment. Length of hedgerows was the only variable showing significant relationship with millipede communities' composition. Despite small area, hedgerows represent important habitats for several species of centipedes and millipedes and show specific composition of their taxocoenoses determined by hedgerows attributes. Farmland hedgerows appear to be important habitats for soil organisms, which may be further beneficial for surrounding landscape. [ABSTRACT FROM AUTHOR]

There is an ongoing debate on what constitutes sustainable intensification of agriculture ( SIA). In this paper, we propose that a paradigm for sustainable intensification can be defined and translated into an operational framework for agricultural development. We argue that this paradigm must now be defined-at all scales-in the context of rapidly rising global environmental changes in the Anthropocene, while focusing on eradicating poverty and hunger and contributing to human wellbeing. The criteria and approach we propose, for a paradigm shift towards sustainable intensification of agriculture, integrates the dual and interdependent goals of using sustainable practices to meet rising human needs while contributing to resilience and sustainability of landscapes, the biosphere, and the Earth system. Both of these, in turn, are required to sustain the future viability of agriculture. This paradigm shift aims at repositioning world agriculture from its current role as the world's single largest driver of global environmental change, to becoming a key contributor of a global transition to a sustainable world within a safe operating space on Earth. [ABSTRACT FROM AUTHOR]

This paper discusses an emerging role for Philippine NGOs—building and maintaining intersectoral cooperation among various sectors of society to tackle key issues like agricultural development, HIV/AIDS, and agrarian reform. The three case studies elaborated in the paper show that Philippine NGOs play important intermediary and bridging functions crucial for the success of multistakeholder partnerships. NGOs are well equipped for this because of their middle-class and professional nature and because of various characteristics like autonomy, flexibility, and the ability to mobilize resources. [ABSTRACT FROM AUTHOR]

Dutch society is changing, and so is its attitude towards animal welfare. Meat retailers respond by laying down minimum-quality criteria for farmers who wish to supply to supermarkets-forcing them to either aim for higher quality or lose their market. Policy-wise this is a top-down measure that leads to a redistribution of markets. From farmer perspective, a transition with more individual freedom to adapt seems more sustainable. By means of an existing agent-based model, this paper investigates two policies for such a market switch: immediate transition-'sudden death' (SD)-versus gradual change-'graceful degradation' (GD). Both farmers and available markets are modelled as agents. Each farmer has a collection of multi-dimensional information items, under certain conditions exchangeable with other farmers in his network, representing his knowledge and skills. Information items are a farmer's key to the market, as market criteria are expressed in terms of information requirements. We tested the effect of SD and GD policies on market redistribution, varying markets sets, available information, and network size. Results show that policy does not matter for final market redistribution, but that GD policy indeed allows more farmers to keep away from poverty, especially in information-poor situations. With GD, we see a temporarily higher inequality of income distribution over individuals (Gini) worth exploring. Studying transitions with respect to both individuals and the system as a whole may be promising for other domains as well. The model is applicable to any situation that implies aligning heterogeneous suppliers with a multi-dimensional demand spectrum. [ABSTRACT FROM AUTHOR]

In the paper we develop a two stage scenario-based stochastic programming model for water management in the Indus Basin Irrigation System (IBIS). We present a comparison between the deterministic and scenario-based stochastic programming model. Our model takes stochastic inputs on hydrologic data i.e. inflow and rainfall. We divide the basin into three rainfall zones which overlap on 44 canal commands. Data on crop characteristics are taken on canal command levels. We then use ten-daily and monthly time intervals to analyze the policies. This system has two major reservoirs and a complex network of rivers, canal head works, canals, sub canals and distributaries. All the decisions on hydrologic aspects are governed by irrigation and agricultural development policies. Storage levels are maintained within the minimum and maximum bounds for every time interval according to a power generation policy. The objective function is to maximize the expected revenue from crops production. We discuss the flexibility of two stochastic optimization models with varying time horizon. [ABSTRACT FROM AUTHOR]

Currently, there is a major concern about the future of nutrient loads discharged into the Baltic Sea from Polish rivers because they are main contributors to its eutrophication. To date, no watershed-scale studies have properly addressed this issue. This paper fills this gap by using a scenario-modeling framework applied in the Reda watershed, a small (482 km) agricultural coastal area in northern Poland. We used the SWAT model to quantify the effects of future climate, land cover, and management changes under multiple scenarios up to the 2050s. The combined effect of climate and land use change on N-NO and P-PO loads is an increase by 20-60 and 24-31 %, respectively, depending on the intensity of future agricultural usage. Using a scenario that assumes a major shift toward a more intensive agriculture following the Danish model would bring significantly higher crop yields but cause a great deterioration of water quality. Using vegetative cover in winter and spring (VC) would be a very efficient way to reduce future P-PO loads so that they are lower than levels observed at present. However, even the best combination of measures (VC, buffer zones, reduced fertilization, and constructed wetlands) would not help to remediate heavily increased N-NO loads due to climate change and agricultural intensification. [ABSTRACT FROM AUTHOR]

Recent debate in the literature on population, environment, and land use questions the applicability of theory that patterns of farm extensification and intensification correspond to the life course of farmers and to the life cycle of farm families. This paper extends the debate to the agricultural development of the United States Great Plains region, using unique data from 1875 to 1930 that link families to farms over time in 25 environmentally diverse Kansas townships. Results of multilevel statistical modeling indicate that farmer's age, household size, and household structure are simultaneously related to both the extent of farm operations and the intensity of land use, taking into account local environmental conditions and time trends as Kansas was settled and developed. These findings validate farm- and life cycle theories and offer support for intergenerational motivations for farm development that include both daughters and sons. Environmental variation in aridity was a key driver of farm structure. [ABSTRACT FROM AUTHOR]

Understanding the causes of land use change is of great importance for issues of tropical deforestation, agricultural development and biodiversity conservation. Many quantitative studies, therefore, aim to link land use change to its causal ‘driving forces.’ The epistemology of virtually all these studies is inductive, searching for correlations within relatively large, sometimes spatially explicit, datasets. This can be sound science but we here aim to exemplify that there is also scope for more deductive approaches that test a pre-defined explanatory theory. The paper first introduces the principles and merits of inductive and more deductive types of land use modeling. It then presents one integrated causal model that is subsequently specified to predict land use in an area in northeastern Philippines in a deductive manner, and tested against the observed land use in that area. The same set of land use data is also used in an inductive (multinomial regression) approach. With a goodness-of-prediction of 70% of the deductive model and a goodness-of-fit of 77% of the inductive model, both perform equally well, statistically. Because the deductive model explicitly contains not only the causal factors but also the causal mechanisms that explain land use, the deductive model then provides a more truly causal, as well as more theory-connected, understanding of land use. This provides land use scholarship with an invitation to add more deductive (theory-driven and theory-building) daring to its methodological repertoire. [ABSTRACT FROM AUTHOR]

Micro-irrigation technologies are promoted for various reasons in India. Despite the reported significant economic advantages, and the concerted support of the government and NGOs, the current micro-irrigation area in India remains an insignificant proportion of its potential. This paper analyzes: (1) the economics of alternative micro-irrigation technologies, (2) the determinants of adoption, (3) the poverty outreach of the different micro-irrigation systems, and (4) the sustainability implications of micro-irrigation adoption. In line with the findings of other studies, this study indicates that micro-irrigation technologies result in a significant productivity and economic gains. The most important determinants of micro-irrigation adoption include access to groundwater, cropping pattern, availability of cash, and level of education, the social status and poverty status of the farmer. Contrary to the expectations, the majority of the current adopters of low-cost micro-irrigation systems are the better-off farmers. The study indicates that the impact of micro-irrigation systems on the sustainability of groundwater resources depends upon the magnitude of the overall productivity gain following the shift from traditional irrigation method to micro-irrigation system, the pattern of use of the saved water, and the type and potential number of adopters. [ABSTRACT FROM AUTHOR]

The production of reactive nitrogen worldwide has more than doubled in the last century because of human activities and population growth. Advances in our understanding of the nitrogen cycle and the impacts of anthropogenic activities on regional to global scales is largely hindered by the paucity of information about nitrogen inputs from human activities in fast-developing regions of the world such as the tropics. In this paper, we estimate nitrogen inputs and outputs in Brazil, which is the world’s largest tropical country. We determined that the N cycle is increasingly controlled by human activities rather than natural processes. Nitrogen inputs to Brazil from human activities practically doubled from 1995 to 2002, mostly because of nitrogen production through biological fixation in agricultural systems. This is in contrast to industrialized countries of the temperate zone, where fertilizer application and atmospheric deposition are the main sources of anthropogenic nitrogen. In Brazil, the production of soybean crops over an area of less than 20 million ha, was responsible for about 3.2 Tg N or close to one-third of the N inputs from anthropogenic sources in 2002. Moreover, cattle pastures account for almost 70% of the estimated 280×106 ha of agricultural land in Brazil and potentially fix significant amounts of N when well managed, further increasing the importance of biological nitrogen fixation in the nitrogen budget. Much of these anthropogenic inputs occur in the Brazilian savannah region ( Cerrado), while more urbanized regions such as the state of São Paulo also have high rates of nitrogenous fertilizer inputs. In the Amazon, rates of anthropogenic nitrogen inputs are relatively low, but continuing conversion of natural forests into cattle pasture or secondary forests potentially add a significant amount of new nitrogen to Brazil given the vast area of the region. Better measurements of biological fixation rates in Brazil are necessary for improving the nitrogen budgets, especially at a more refined spatial scale. [ABSTRACT FROM AUTHOR]

Since the 1970s the Brazilian Amazon has received over 1 million migrant farm households from other regions of the country, many of whom were attracted to government-sponsored frontier settlement programs that offered free tropical forest land. As a result, pressures on tropical forests have intensified along several settlement corridors throughout the region. Despite their importance as agents of landscape change, surprisingly little is known about the land use practices of these farmers. This paper briefly reviews the research literature on smallholder land use patterns in Amazonia, describes the recent history of one important agricultural land settlement program in the western Brazilian Amazon state of Rondônia, and, based on 240 household surveys conducted in three separate settlement locations in the state, highlights key differences in land use patterns among the rural population. Typologies of farming systems are presented on the basis of cluster analysis of land use data and ANOVA tests. The findings indicate considerable complexity and heterogeneity in smallholder farming systems. Spatial variations in farming system types may be due to geographic differences in soil regimes, the social histories of specific communities, and site-specific responses to exogenous variables. [ABSTRACT FROM AUTHOR]

Labor productivity is a major component of agricultural development. Boserup is the scholar most associated with the view that labor productivity declines with intensification of agriculture. This paper reviews the theoretical argument and empirical support for the decline thesis. An empirical test is conducted by means of a comparative study of traditional rice agriculture in Southeast Asia. The decline thesis is rejected. The implications for agricultural development are discussed. [ABSTRACT FROM AUTHOR]