Foray search: An effective systematic dispersal strategy in fragmented landscapes

In the absence of evidence to the contrary, population models generally assume that the dispersal trajectories of animals are random, but systematic dispersal could be more efficient at detecting new habitat and may therefore constitute a more realistic assumption. Here, we investigate, by means of simulations, the properties of a potentially widespread systematic dispersal strategy termed "foray search." Foray search was more efficient in detecting suitable habitat than was random dispersal in most landscapes and was less subject to energetic constraints. However, it also resulted in considerably shorter net dispersed distances and higher mortality per net dispersed distance than did random dispersal, and it would therefore be likely to lead to lower dispersal rates toward the margins of population networks. Consequently, the use of foray search by dispersers could crucially affect the extinction-colonization balance of metapopulations and the evolution of dispersal rates. We conclude that population models need to take the dispersal trajectories of individuals into account in order to make reliable predictions

Landing together: how flocks arrive at a coherent action in time and space in the presence of perturbations

Collective motion is abundant in nature, producing a vast amount of phenomena which have been studied in recent years, including the landing of flocks of birds. We investigate the collective decision making scenario where a flock of birds decides the optimal time of landing in the absence of a global leader. We introduce a simple phenomenological model in the spirit of the statistical mechanics-based self-propelled particles (SPP-s) approach to interpret this process. We expect that our model is applicable to a larger class of spatiotemporal decision making situations than just the landing of flocks (which process is used as a paradigmatic case). In the model birds are only influenced by observable variables, like position and velocity. Heterogeneity is introduced in the flock in terms of a depletion time after which a bird feels increasing bias to move towards the ground. Our model demonstrates a possible mechanism by which animals in a large group can arrive at an egalitarian decision about the time of switching from one activity to another in the absence of a leader. In particular, we show the existence of a paradoxical effect where noise enhances the coherence of the landing process.Comment: 15 pages, 7 figure

Non-random dispersal in the butterfly Maniola jurtina: implications for metapopulation models

The dispersal patterns of animals are important in metapopulation ecology because they affect the dynamics and survival of populations. Theoretical models assume random dispersal but little is known in practice about the dispersal behaviour of individual animals or the strategy by which dispersers locate distant habitat patches. In the present study, we released individual meadow brown butterflies (Maniola jurtina) in a non-habitat and investigated their ability to return to a suitable habitat. The results provided three reasons for supposing that meadow brown butterflies do not seek habitat by means of random flight. First, when released within the range of their normal dispersal distances, the butterflies orientated towards suitable habitat at a higher rate than expected at random. Second, when released at larger distances from their habitat, they used a non-random, systematic, search strategy in which they flew in loops around the release point and returned periodically to it. Third, butterflies returned to a familiar habitat patch rather than a non-familiar one when given a choice. If dispersers actively orientate towards or search systematically for distant habitat, this may be problematic for existing metapopulation models, including models of the evolution of dispersal rates in metapopulations

Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances

A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km2) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash–Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling

Impacts of global change on water-related sectors and society in a trans-boundary central European river basin – Part 2: From eco-hydrology to water demand management

This second part of the paper presents the details of the eco-hydrological model SWIM simulating the natural water supply and its coupling to WBalMo, a water management model. Based on the climate scenarios of the STAR model, SWIM simulates the natural water and matter fluxes for the entire Elbe River area. All relevant processes are modelled for hydrotopes and the resulting discharges are accumulated in subbasins. The output data are input for the water management model WBalMo and the quality models Moneris and QSim. WBalMo takes storage management, inputs and withdrawals into account and analyses how demands by industry, power plants and households will be met at changing natural supply conditions. Some of the first results shall be presented here

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

Social density processes regulate the functioning and performance of foraging human teams

Social density processes impact the activity and order of collective behaviours in a variety of biological systems. Much effort has been devoted to understanding how density of people affects collective human motion in the context of pedestrian flows. However, there is a distinct lack of empirical data investigating the effects of social density on human behaviour in cooperative contexts. Here, we examine the functioning and performance of human teams in a central-place foraging arena using high-resolution GPS data. We show that team functioning (level of coordination) is greatest at intermediate social densities, but contrary to our expectations, increased coordination at intermediate densities did not translate into improved collective foraging performance, and foraging accuracy was equivalent across our density treatments. We suggest that this is likely a consequence of foragers relying upon visual channels (local information) to achieve coordination but relying upon auditory channels (global information) to maximise foraging returns. These findings provide new insights for the development of more sophisticated models of human collective behaviour that consider different networks for communication (e.g. visual and vocal) that have the potential to operate simultaneously in cooperative contexts

Impacts of global change on water-related sectors and society in a trans-boundary central European river basin – Part 1: Project framework and impacts on agriculture

Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model set-up for simulating water supply and demand linking eco-hydrological and water management tools for the entire basin including the Czech part

Between-group competition elicits within-group cooperation in children

Aggressive interactions between groups are frequent in human societies and can bear significant fitness costs and benefits (e.g. death or access to resources). During between-group competitive interactions, more cohesive groups (i.e. groups formed by individuals who cooperate in group defence) should out-perform less cohesive groups, other factors being equal (e.g. group size). The cost/benefit of between-group competition are thought to have driven correlated evolution of traits that favour between-group aggression and within-group cooperation (e.g. parochial altruism). Our aim was to analyse whether the proximate relationship between between-group competition and within-group cooperation is found in 3–10 years old children and the developmental trajectory of such a relationship. We used a large cohort of children (n = 120) and tested whether simulated between-group competition increased within-group cooperation (i.e. how much of a resource children were giving to their group companions) in two experiments. We found greater within-group cooperation when groups of four children were competing with other groups then in the control condition (no between-group competition). Within-group cooperation increased with age. Our study suggests that parochial altruism and in-group/out-group biases emerge early during the course of human development