The social evolution of dispersal with public goods cooperation

Selection can favour the evolution of individually costly dispersal if this alleviates competition between relatives. However, conditions that favour altruistic dispersal also mediate selection for other social behaviours, such as public goods cooperation, which in turn is likely to mediate dispersal evolution. Here, we investigate – both experimentally (using bacteria) and theoretically – how social habitat heterogeneity (i.e. the distribution of public goods cooperators and cheats) affects the evolution of dispersal. In addition to recovering the well-known theoretical result that the optimal level of dispersal increases with genetic relatedness of patch mates, we find both mathematically and experimentally that dispersal is always favoured when average patch occupancy is low, but when average patch occupancy is high, the presence of public goods cheats greatly alters selection for dispersal. Specifically, when public goods cheats are localized to the home patch, higher dispersal rates are favoured, but when cheats are present throughout available patches, lower dispersal rates are favoured. These results highlight the importance of other social traits in driving dispersal evolution.

Single versus multiple occupancy - Effects on toxicity parameters measured on Eisenia fetida in lead nitrate-treated soil

The mortality (7 and 14 d), weight change (7 and 14 d), and metal uptake of Eisenia fetida (Savigny, 1826) kept in Pb(NO3)(2)-treated Kettering loam soil in single- and multiple-occupancy (10 earthworms) test containers were determined. The number of earthworms to dry mass (g) ratio of soil was 1:50 in both sets of test containers. Lead concentrations were in the nominal range of 0 to 10,000 mg Pb/kg soil (mg/kg hereafter). Levels of mortality at a given concentration were statistically identical between the single- and multiple-occupancy tests, except at 1,800 mg/kg, at which significantly (p less than or equal to 0.05) more mortality occurred in the multiple-occupancy tests. Death of individual earthworms in the multiple-occupancy tests did not trigger death of the other earthworms in that soil. The LC50 values (concentration statistically likely to kill 50% of the population) were identical between the multiple- and single-occupancy soils: 2,662 mg/kg (2,598-2,984, 7 d) and 2,589 mg/kg (2,251-3,013, 14 d) for the multiple-occupancy soils and 2,827 mg/kg (2,443-3,168, both 7 and 14 d) for the single-occupancy soils (values in brackets represent the 95% confidence intervals). Data were insufficient to calculate the concentration statistically likely to reduce individual earthworm mass by 50% (EC50), but after 14 d, the decrease in earthworm weight in the 1,800 and 3,000 mg/kg tests was significantly greater in the multiple- than in the single-occupancy soils. At 1,000, 1,800, and 3,000 mg/kg tests, earthworm Pb tissue concentration was significantly (p less than or equal to 0.05) greater in earthworms from the multiple-occupancy soils. The presence of earthworms increased the NH3 content of the soil; earthworm mortality increased NH3 concentrations further but not to toxic levels.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

API-CALC 1.0: a computer program for calculating the average probability of identity allowing for substructure, inbreeding and the presence of close relatives

Individual identification via DNA profiling is important in molecular ecology, particularly in the case of noninvasive sampling. A key quantity in determining the number of loci required is the probability of identity (PIave), the probability of observing two copies of any profile in the population. Previously this has been calculated assuming no inbreeding or population structure. Here we introduce formulae that account for these factors, whilst also accounting for relatedness structure in the population. These formulae are implemented in API-CALC 1.0, which calculates PIave for either a specified value, or a range of values, for F-IS and F-ST.

Particulate matter mass concentration (PM10) under different ventilation methods in classrooms

Recently, studies have shown that the classroom environment is very important for students' health and performance. Thus, the evaluation of indoor air quality (IAQ) in a classroom is necessary to ensure students' well-being. In this paper the emphasis is on airborne concentration of particulate matter (PM) in adult education rooms. The mass concentration of PM10 particulates was measured in two classrooms under different ventilation methods in the University of Reading, UK, during the winter period of 2008. In another study the measurement of the concentration of particles was accompanied with measurements of CO2 concentration in these classrooms but this study is the subject of another publication. The ambient PM10, temperature, relative humidity, wind speed and direction, and rainfall events were monitored as well. In general, this study showed that outdoor particle concentrations and outdoor meteorological parameters were identified as significant factors influencing indoor particle concentration levels. Ventilation methods showed significant effects on air change rate and on indoor/outdoor (I/O) concentration ratios. Higher levels of indoor particulates were seen during occupancy periods. I/O ratios were significantly higher when classrooms were occupied than when they were unoccupied, indicating the effect of both people presence and outdoor particle concentration levels. The concentrations of PM10 indoors and outdoors did not meet the requirements of WHO standards for PM10 annual average.

Sustainable refurbishment: quantifying the impact of façade changes in multi-storey, multi-occupancy buildings

Building refurbishment is key to reducing the carbon footprint and improving comfort in the built environment. However, quantifying the real benefit of a facade change, which can bring advantages to owners (value), occupants (comfort) and the society (sustainability), is not a simple task. At a building physics level, the changes in kWh per m2 of heating / cooling load can be readily quantified. However, there are many subtle layers of operation and mainte-nance below these headline figures which determine how sustainable a building is in reality, such as for example quality of life factors. This paper considers the range of approached taken by a fa/e refurbishment consortium to assess refurbishment solutions for multi-storey, multi-occupancy buildings and how to critically evaluate them. Each of the applued tools spans one or more of the three building parameters of people, product and process. 'De-cision making' analytical network process and parametric building analysis tools are described and their potential impact on the building refurbishment process evaluated.

Post occupancy evaluation of a building employing windcatchers for summer ventilation

A combined windcatcher and light pipe (SunCatcher) was installed in the seminar room at the University of Reading, UK. Monitoring of indoor environment in real weather conditions was conducted to evaluate the application of windcatchers for natural ventilation. In addition, a subjective occupancy survey was undertaken. External weather conditions and internal indoor air quality indicators were recorded. The “tracer-gas decay” method using SF6 was used to establish air change rate for various conditions. The results indicated that the ventilation rate achieved through the windcatcher depends on the difference between internal and external air temperatures, and on wind speed and direction, in agreement with other published work in the area. The indoor air quality parameters were found to be within acceptable levels when the windcatcher was in operation. The measured air change rate was between 1.5ac/h and 6.8ac/h. Occupants’ questionnaires showed 75 per cent satisfaction with the internal conditions and welcomed the installation of the systems in UK buildings.

Evaluation of probabilistic occupancy map people detection for surveillance systems

In this paper, we evaluate the Probabilistic Occupancy Map (POM) pedestrian detection algorithm on the PETS 2009 benchmark dataset. POM is a multi-camera generative detection method, which estimates ground plane occupancy from multiple background subtraction views. Occupancy probabilities are iteratively estimated by fitting a synthetic model of the background subtraction to the binary foreground motion. Furthermore, we test the integration of this algorithm into a larger framework designed for understanding human activities in real environments. We demonstrate accurate detection and localization on the PETS dataset, despite suboptimal calibration and foreground motion segmentation input.