Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

Earthworm distribution and abundance predicted by a process-based model

Earthworms are significant ecosystem engineers and are an important component of the diet of many vertebrates and invertebrates, so the ability to predict their distribution and abundance would have wide application in ecology, conservation and land management. Earthworm viability is known to be affected by the availability and quality of food resources, soil water conditions and temperature, but has not yet been modelled mechanistically to link effects on individuals to field population responses. Here we present a novel model capable of predicting the effects of land management and environmental conditions on the distribution and abundance of Aporrectodea caliginosa, the dominant earthworm species in agroecosystems. Our process-based approach uses individual based modelling (IBM), in which each individual has its own energy budget. Individual earthworm energy budgets follow established principles of physiological ecology and are parameterised for A. caliginosa from experimental measurements under optimal conditions. Under suboptimal conditions (e.g. food limitation, low soil temperatures and water contents) reproduction is prioritised over growth. Good model agreement to independent laboratory data on individual cocoon production and growth of body mass, under variable feeding and temperature conditions support our representation of A. caliginosa physiology through energy budgets. Our mechanistic model is able to accurately predict A. caliginosa distribution and abundance in spatially heterogeneous soil profiles representative of field study conditions. Essential here is the explicit modelling of earthworm behaviour in the soil profile. Local earthworm movement responds to a trade-off between food availability and soil water conditions, and this determines the spatiotemporal distribution of the population in the soil profile. Importantly, multiple environmental variables can be manipulated simultaneously in the model to explore earthworm population exposure and effects to combinations of stressors. Potential applications include prediction of the population-level effects of pesticides and changes in soil management e.g. conservation tillage and climate change.

The effect of model configuration on modelled hillslope–riparian interactions

The transfer of hillslope water to and through the riparian zone forms a research area of importance in hydrological investigations. Numerical modelling schemes offer a way to visualise and quantify first-order controls on catchment runoff response and mixing. We use a two-dimensional Finite Element model to assess the link between model setup decisions (e.g. zero-flux boundary definitions, soil algorithm choice) and the consequential hydrological process behaviour. A detailed understanding of the consequences of model configuration is required in order to produce reliable estimates of state variables. We demonstrate that model configuration decisions can determine effectively the presence or absence of particular hillslope flow processes and, the magnitude and direction of flux at the hillslope–riparian interface. If these consequences are not fully explored for any given scheme and application, the resulting process inference may well be misleading.

An isotope dilution model for partitioning phenylalanine and tyrosine uptake by the mammary gland of lactating dairy cows

An isotope dilution model for partitioning phenylalanine and tyrosine uptake by the mammary gland of the lactating dairy cow is constructed and solved in the steady state. The model contains four intracellular and four extracellular pools and conservation of mass principles are applied to generate the fundamental equations describing the behaviour of the system. The experimental measurements required for model solution are milk secretion and plasma flow rate across the gland in combination with phenylalanine and tyrosine concentrations and plateau isotopic enrichments in arterial and venous plasma and free and protein bound milk during a constant infusion of [1-(13)C]phenylalanine and [2,3,5,6-(2)H]tyrosine tracer. If assumptions are made, model solution enables determination of steady state flows for phenylalanine and tyrosine inflow to the gland, outflow from it and bypass, and flows representing the synthesis and degradation of constitutive protein and hydroxylation. The model is effective in providing information about the fates of phenylalanine and tyrosine in the mammary gland and could be used as part of a more complex system describing amino acid metabolism in the whole ruminant.

GM food purchase intentions: linking the theory of planned behaviour with consumer trust and stated choice

After the “European” experience of BSE and further food safety crises consumer trust is playing an increasingly important role in political and marketing decision making. This also relates to the area of consumer acceptance of GM food. This paper integrates consumer trust with the theory of planned behavior and a stated choice model to gain a more complete picture of consumer decision making. Preliminary results indicate that when GM products offer practical benefits to consumers acceptance may increase considerably. Furthermore, both trust and perceived benefits contribute significantly to explaining the level of acceptance.

Researching farmer behaviour in climate change adaptation and sustainable agriculture: lessons learned from five case studies

Understanding farmer behaviour is needed for local agricultural systems to produce food sustainably while facing multiple pressures. We synthesize existing literature to identify three fundamental questions that correspond to three distinct areas of knowledge necessary to understand farmer behaviour: 1) decision-making model; 2) cross-scale and cross-level pressures; and 3) temporal dynamics. We use this framework to compare five interdisciplinary case studies of agricultural systems in distinct geographical contexts across the globe. We find that these three areas of knowledge are important to understanding farmer behaviour, and can be used to guide the interdisciplinary design and interpretation of studies in the future. Most importantly, we find that these three areas need to be addressed simultaneously in order to understand farmer behaviour. We also identify three methodological challenges hindering this understanding: the suitability of theoretical frameworks, the trade-offs among methods and the limited timeframe of typical research projects. We propose that a triangulation research strategy that makes use of mixed methods, or collaborations between researchers across mixed disciplines, can be used to successfully address all three areas simultaneously and show how this has been achieved in the case studies. The framework facilitates interdisciplinary research on farmer behaviour by opening up spaces of structured dialogue on assumptions, research questions and methods employed in investigation.

A model analysis of climate and CO2 controls on tree growth in a semi-arid woodland

We used a light-use efficiency model of photosynthesis coupled with a dynamic carbon allocation and tree-growth model to simulate annual growth of the gymnosperm Callitris columellaris in the semi-arid Great Western Woodlands, Western Australia, over the past 100 years. Parameter values were derived from independent observations except for sapwood specific respiration rate, fine-root turnover time, fine-root specific respiration rate and the ratio of fine-root mass to foliage area, which were estimated by Bayesian optimization. The model reproduced the general pattern of interannual variability in radial growth (tree-ring width), including the response to the shift in precipitation regimes that occurred in the 1960s. Simulated and observed responses to climate were consistent. Both showed a significant positive response of tree-ring width to total photosynthetically active radiation received and to the ratio of modeled actual to equilibrium evapotranspiration, and a significant negative response to vapour pressure deficit. However, the simulations showed an enhancement of radial growth in response to increasing atmospheric CO2 concentration (ppm) ([CO2]) during recent decades that is not present in the observations. The discrepancy disappeared when the model was recalibrated on successive 30-year windows. Then the ratio of fine-root mass to foliage area increases by 14% (from 0.127 to 0.144 kg C m-2) as [CO2] increased while the other three estimated parameters remained constant. The absence of a signal of increasing [CO2] has been noted in many tree-ring records, despite the enhancement of photosynthetic rates and water-use efficiency resulting from increasing [CO2]. Our simulations suggest that this behaviour could be explained as a consequence of a shift towards below-ground carbon allocation.

Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1)

The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.

Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model

Operational forecasting centres are currently developing data assimilation systems for coupled atmosphere-ocean models. Strongly coupled assimilation, in which a single assimilation system is applied to a coupled model, presents significant technical and scientific challenges. Hence weakly coupled assimilation systems are being developed as a first step, in which the coupled model is used to compare the current state estimate with observations, but corrections to the atmosphere and ocean initial conditions are then calculated independently. In this paper we provide a comprehensive description of the different coupled assimilation methodologies in the context of four dimensional variational assimilation (4D-Var) and use an idealised framework to assess the expected benefits of moving towards coupled data assimilation. We implement an incremental 4D-Var system within an idealised single column atmosphere-ocean model. The system has the capability to run both strongly and weakly coupled assimilations as well as uncoupled atmosphere or ocean only assimilations, thus allowing a systematic comparison of the different strategies for treating the coupled data assimilation problem. We present results from a series of identical twin experiments devised to investigate the behaviour and sensitivities of the different approaches. Overall, our study demonstrates the potential benefits that may be expected from coupled data assimilation. When compared to uncoupled initialisation, coupled assimilation is able to produce more balanced initial analysis fields, thus reducing initialisation shock and its impact on the subsequent forecast. Single observation experiments demonstrate how coupled assimilation systems are able to pass information between the atmosphere and ocean and therefore use near-surface data to greater effect. We show that much of this benefit may also be gained from a weakly coupled assimilation system, but that this can be sensitive to the parameters used in the assimilation.

Bricks vs clicks: entrepreneurial online banking behaviour and relationship banking

Purpose – Little research has been conducted on the effects of information technology on financing entrepreneurial businesses or small and medium sized enterprises (SMEs). The purpose of this paper is to examine the impacts of entrepreneurial online banking and relationship banking on the severity of financial problems perceived by entrepreneurs and their interactive effect. It also investigates how characteristics of individual businesses and entrepreneurial demographics influence SMEs’ financial situation. Design/methodology/approach – An ordered logistic model is used on a UK dataset to empirically test the hypotheses derived in this paper. The empirical evidence is drawn from the 2004 UK survey of SME finances, which contains a sample of 2,500 firms. Findings – This paper finds that both entrepreneurial online banking behaviour and relationship banking alleviates the severity of financial problems perceived by entrepreneurs. The relationship affect is less evident for entrepreneurs who most frequently use an online approach to communicate with their banks than for those using traditional methods. Business and entrepreneur characteristics also have a strong impact on the severity of the financial problems suffered by SMEs. Originality/value – This paper provides evidence supporting the favourable impacts of the application of information technology on entrepreneurial finance from the perspective of entrepreneur/business. It also identifies a substitute relationship between entrepreneurial online banking behaviour and relationship banking, a relationship which contradicts existing evidence.

Smug alert! Exploring self-licensing behaviour in a cheating game

We test experimentally a prediction of the ‘moral credit model’, in which committing a virtuous act creates moral credits that can license immoral behavior in a succeeding decision. We use a basic cheating experiment that was either preceded by a virtuous deed or not in a developing country context. We found that people who previously achieved a good deed cheat more. Gender and origin are also significant explicative variables for cheating.

Collective financing among Chinese entrepreneurs and department store retailing in China

Chinese entrepreneurship in department store retailing differed from that seen in other emerging economies before 1940. Rather than the leading examples of the format being owned by advanced economy firms, in China a small group of Cantonese entrepreneurs established what became known as the ‘Big Four’ department stores in Shanghai. By 1940 the ‘Big Four’ department stores were among the most famous stores in China, and among the biggest businesses in China. None of these Chinese entrepreneurs had any prior experience in department store retailing. Rather this article explains how their success in department store retailing was dependent on a business model that enabled these Chinese entrepreneurs to act as informal investment bankers (or ‘shadow’ banks) for the thousands of overseas Chinese wanting to invest surplus savings in mainland China, so creating large indigenous business groups.

A moving-point approach to model shallow ice sheets: a study case with radially symmetrical ice sheets

Predicting the evolution of ice sheets requires numerical models able to accurately track the migration of ice sheet continental margins or grounding lines. We introduce a physically based moving-point approach for the flow of ice sheets based on the conservation of local masses. This allows the ice sheet margins to be tracked explicitly. Our approach is also well suited to capture waiting-time behaviour efficiently. A finite-difference moving-point scheme is derived and applied in a simplified context (continental radially symmetrical shallow ice approximation). The scheme, which is inexpensive, is verified by comparing the results with steady states obtained from an analytic solution and with exact moving-margin transient solutions. In both cases the scheme is able to track the position of the ice sheet margin with high accuracy.

Farmer attitudes and livestock disease: exploring citizenship behaviour and peer monitoring across two BVD control schemes in the UK

The eradication of BVD in the UK is technically possible but appears to be socially untenable. The following study explored farmer attitudes to BVD control schemes in relation to advice networks and information sharing, shared aims and goals, motivation and benefits of membership, notions of BVD as a priority disease and attitudes toward regulation. Two concepts from the organisational management literature framed the study: citizenship behaviour where actions of individuals support the collective good (but are not explicitly recognised as such) and peer to peer monitoring (where individuals evaluate other’s behaviour). Farmers from two BVD control schemes in the UK participated in the study: Orkney Livestock Association BVD Eradication Scheme and Norfolk and Suffolk Cattle Breeders Association BVD Eradication Scheme. In total 162 farmers participated in the research (109 in-scheme and 53 out of scheme). The findings revealed that group helping and information sharing among scheme members was low with a positive BVD status subject to social censure. Peer monitoring in the form of gossip with regard to the animal health status of other farms was high. Interestingly, farmers across both schemes supported greater regulation with regard to animal health, largely due to the mistrust of fellow farmers following voluntary disease control measures. While group cohesiveness varied across the two schemes, without continued financial inducements, longer-term sustainability is questionable

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example they use positive sentiment more often and negative sentiment less often. Secondly we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable to those obtained from our empirical dataset.