Agricultural commodity markets : reference point for the real value of a currency

Using monthly time-series data 1999-2013, the paper shows that markets for agricultural commodities provide a yardstick for real purchasing power, and thus a reference point for the real value of fiat currencies. The daily need for each adult to consume about 2800 food calories is universal; data from FAO food balance sheets confirm that the world basket of food consumed daily is non-volatile in comparison to the volatility of currency exchange rates, and so the replacement cost of food consumed provides a consistent indicator of economic value. Food commodities are storable for short periods, but ultimately perishable, and this exerts continual pressure for markets to clear in the short term; moreover, food calories can be obtained from a very large range of foodstuffs, and so most households are able to use arbitrage to select a near optimal weighting of quantities purchased. The paper proposes an original method to enable a standard of value to be established, definable in physical units on the basis of actual worldwide consumption of food goods, with an illustration of the method.

Contribution of insect pollinators to crop yield and quality varies with agricultural intensification

Background: Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods: We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient fromsimple to heterogeneous landscapes. Results: Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries’ commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations.

Heuristic based evolution for the coordination of autonomous vehicles in the absence of speed lanes

The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.

If the British left: agricultural policy outside the CAP?

If the Conservative party wins Britain’s General Election in 2015 the incoming Government intends to negotiate a new settlement with the EU, and then hold an in-out referendum. Opinion polls suggest a narrow majority would vote to leave. To exercise an informed choice the electorate would need to know what feasible alternatives are available, so that these can be assessed and debated. Furthermore, in the event of a no vote the Government must be ready to implement its alternative strategy: Plan B. This implies that both a new EU settlement, and Plan B, need to be negotiated concurrently. There has been no serious attempt to explain what Plan B would mean for UK farm policy. Would, for example, British farmers continue to receive the level of support that they currently enjoy; would support be more focussed on environmental objectives? WTO rules on most-favoured-nation treatment and regional trade agreements would apply. Could a WTO compatible agri-food trade agreement be negotiated with its former EU partners, or would Irish and Brazilian beef face the same tariff barriers on imports into the British market? For the EU, the loss of a major net contributor to EU finances could result in a re-examination of the CAP budget.

Drivers of change in mountain farming in Slovakia: from socialist collectivisation to the Common Agricultural Policy

The transformations in Slovak agriculture from the 1950s to the present day, considering both the generic (National and EU) and site-specific (local) drivers of landscape change, were analysed in five mountain study areas in the country. An interdisciplinary approach included analysis of population trends, evaluation of land use and landscape change combined with exploration of the perceptions of local stakeholders and results of previous biodiversity studies. The generic processes active from the 1950s to 1970s were critical for all study areas with impacts lasting right up until the present day. Agricultural collectivisation, agricultural intensification and land abandonment had negative effects in all study areas. However, the precise impacts on the landscape were different in the different study areas due to site-specific attributes (e.g. population trends, geographic localisation and local attitudes and opportunities), and these played a decisive role in determining the trajectory of change. Regional contrasts in rural development between these territories have increased in the last two decades, also due to the imperfect preconditions of governmental support. The recent Common Agricultural Policy developments are focused on maintenance of intensive large-scale farming rather than direct enhancement of agro-biodiversity and rural development at the local scale. In this context, local, site-specific attributes can and must form an essential part of rural development plans, to meet the demands for management of the diversity of agricultural mountain landscapes and facilitate the multifunctional role of agriculture.

Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.

How well can we model stream phosphorus concentrations in agricultural catchments?

Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. We investigate the reasons for this for one model, INCA-P, testing model output against 18 months of daily data in a small Scottish catchment. We examine key model processes and provide recommendations for model improvement and simplification. Improvements to the particulate phosphorus simulation are especially needed. The model evaluation procedure is then generalised to provide a checklist for identifying why model performance may be poor or unreliable, incorporating calibration, data, structural and conceptual challenges. There needs to be greater recognition that current models struggle to produce positive Nash–Sutcliffe statistics in agricultural catchments when evaluated against daily data. Phosphorus modelling is difficult, but models are not as useless as this might suggest. We found a combination of correlation coefficients, bias, a comparison of distributions and a visual assessment of time series a better means of identifying realistic simulations.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

Evaluation of optical techniques for characterising soil organic matter quality in agricultural soils

Soil organic matter (SOM) is one of the main global carbon pools. It is a measure of soil quality as its presence increases carbon sequestration and improves physical and chemical soil properties. The determination and characterisation of humic substances gives essential information of the maturity and stresses of soils as well as of their health. However, the determination of the exact nature and molecular structure of these substances has been proven difficult. Several complex techniques exist to characterise SOM and mineralisation and humification processes. One of the more widely accepted for its accuracy is nuclear magnetic resonance (NMR) spectroscopy. Despite its efficacy, NMR needs significant economic resources, equipment, material and time. Proxy measures like the fluorescence index (FI), cold and hot-water extractable carbon (CWC and HWC) and SUVA-254 have the potential to characterise SOM and, in combination, provide qualitative and quantitative data of SOM and its processes. Spanish and British agricultural cambisols were used to measure SOM quality and determine whether similarities were found between optical techniques and 1H NMR results in these two regions with contrasting climatic conditions. High correlations (p < 0.001) were found between the specific aromatic fraction measured with 1H NMR and SUVA-254 (Rs = 0.95) and HWC (Rs = 0.90), which could be described using a linear model. A high correlation between FI and the aromatics fraction measured with 1H NMR (Rs = −0.976) was also observed. In view of our results, optical measures have a potential, in combination, to predict the aromatic fraction of SOM without the need of expensive and time consuming techniques.

Landscape connectivity: a key to effective habitat restoration in lowland agricultural landscapes

Landscape scale habitat restoration has the potential to reconnect habitats in fragmented landscapes. This study investigates landscape connectivity as a key to effective habitat restoration in lowland agricultural landscapes and applies these findings to transferable management recommendations. The study area is the Stonehenge World Heritage Site, UK, where landscape scale chalk grassland restoration has been implemented. Here, the ecological benefits of landscape restoration and the species, habitat and landscape characteristics that facilitate or impede the enhancement of biodiversity and landscape connectivity were investigated. Lepidoptera were used as indictors of restoration success and results showed restoration grasslands approaching the ecological conditions of the target chalk grassland habitat and increasing in biodiversity values within a decade. Restoration success is apparent for four species with a broad range of grass larval host plants (e.g. Melanargia galathea, Maniola jurtina) or with intermediate mobility (Polyommatus icarus). However, two species with specialist larval host plants and low mobility (Lysandra bellargus), are restricted to chalk grassland fragments. Studies of restoration grassland of different ages show that recent grassland restoration (1 or 2 years old) may reduce the functional isolation of chalk grassland fragments. A management experiment showed that mowing increases boundary following behaviour in two species of grassland Lepidoptera; Maniola jurtina and Zygaena filipendulae. Analysis of the landscape scale implications of the grassland restoration illustrates an increase in grassland habitat network size and in landscape connectivity, which is likely to benefit the majority of grassland associated Lepidoptera. Landscape and habitat variables can be managed to increase the success of restoration projects including the spatial targeting of receptor sites, vegetation structure and selection of seed source and management recommendations are provided that are transferrable to other species-rich grassland landscape scale restoration projects. Overall results show restoration success for some habitats and species within a decade. However, additional management is required to assist the re-colonisation of specialist species. Despite this, habitat restoration at the landscape scale can be an effective, long term approach to enhance butterfly biodiversity and landscape connectivity.