Behavioural switching in a central place forager: patterns of diving behaviour in the macaroni penguin (Eudyptes chrysolophus)

Recording the activity of animals as they migrate or forage has proven hugely advantageous to understanding how animals use their environment. Where animals cannot be directly observed, the problem remains of how to identify distinct behaviours that represent an animal’s decision-making process. An excellent example of this problem is that of foraging penguins, which travel to sea to find prey to provision their young. Without direct sampling of the prey field, we cannot calibrate patterns of movement with prey capture, and therefore we cannot determine how different activities link to decision-making. To overcome this, we use a hidden markov model (HMM), which is a machine-learning technique that seeks to identify the underlying states of a system from observable outputs. We apply HMM to determine classes of behaviour from repetitive dives. We take dive data from 103 breeding macaroni penguins at Bird Island, South Georgia, for which we have measures of weight gain over a trip. We identify two classes of behaviour; those of short-shallow and long-deep dives. Using these two behaviours, we calculate the transition probabilities between these states and analyse these data to determine what predicts variation in the transition probabilities. We found that the stage of reproduction during a season, the sex and year of an individual influenced the probability of transition between long-deep and short-shallow sequential dives. We also found differences in the hourly transition rates between the four reproductive stages (incubation, broodguard, crèche and premoult) over a daily cycle. We conclude that this application of HMMs for behavioural switching is potentially useful for other species and other types of recorded behaviour.     

Role of soil sorption and microbial degradation on dissipation of mesotrione in plant-available soil water

Mesotrione is a carotenoid biosynthesis-inhibiting herbicide labeled for pre-emergence and postemergence weed control in corn production. Understanding the factors that influence the dissipation of mesotrione in soil and in the plant-available water (PAW) is important for the environmental fate assessment and optimal weed management practices. The present research investigated the role of soil properties and microbial activities on the interrelated sorption and degradation processes of mesotrione in four soils by direct measurements of PAW. We found that mesotrione bound to the soils time dependently, with approximately 14 d to reach equilibrium. The 24-h batch-slurry equilibrium experiments provided the sorption partition coefficient ranging from 0.26 to 3.53 L kg(-1), depending on soil organic carbon and pH. The dissipation of mesotrione in the soil-bound phase was primarily attributed to desorption to the PAW. Degradation in the PAW was rapid and primarily dependent on microbial actions, with half-degradation time (DT(50)) <3 d in all four soils tested. The rapid degradation in the PAW became rate limited by sorption as more available molecules were depleted in the soil pore water, resulting in a more slowed overall process for the total soil-water system (DT(50) <26 d). The dissipation of mesotrione in the PAW was due to microbial metabolism and time-dependent sorption to the soils. A coupled kinetics model calibrated with the data from the laboratory centrifugation technique provided an effective approach to investigate the interrelated processes of sorption and degradation in realistic soil moisture conditions.     

An Application of the Pump-to-Fill Policy for Management of Urban Stormwater

We consider the management of urban stormwater in two connected dams. Stormwater generated by local rainfall flows into a capture dam and is subsequently pumped into a similar sized holding dam. We assume random gross inflow and constant demand. If we wish to minimise overflow from the system then the optimal management policy is to pump as much water as possible each day from the capture dam to the holding dam without allowing the holding dam to overflow. We shall refer to this policy as the pump-to-fill policy. The model is based on the Parafield stormwater management system in the City of Salisbury (CoS) but assumes constant demand instead of level dependent outflow. If there is insufficient water in the holding dam to meet the desired daily demand then all water in the holding dam is used and the shortfall is obtained from other sources. CoS, in suburban Adelaide in South Australia, is recognised in local government circles as a world leader in urban stormwater management. The water is supplied to local industry to replace regular mains water and is also used to restore and maintain urban wetlands. In mathematical terms the pump-to-fill policy defines a Markov chain with a large transition matrix and a characteristic regular block structure. We use specialised Matrix Analytic Methods to decompose the event space and find simplified equations for the steady state probability vector. In this way we enable an elementary solution procedure which we illustrate by solving the modified Parafield problem. The optimal nature of the pump-to-fill policy is established in a recent paper by Pearce et al. (JIMO 3(2):313–320, 2007). The purpose of the current study is to find optimal management policies for urban stormwater systems. Work supported by the Australian Research Council.     

Generating Synthetic Rainfall on Various Timescales—Daily, Monthly and Yearly

The main objective of this paper is to present a model for generating synthetic rainfall totals on various timescales to be applicable for a variety of uses. Many large-scale ecological and water resource models require daily, monthly and yearly rainfall data as input to the model. As historical data provides only one realisation, synthetic generated rainfall totals are needed to assess the impact of rainfall variability on water resources systems (Srikanthan, In: MODSIM2005, Melbourne, Dec. 2005, pp. 1915–1921, 2005). Thus, our preferred model should simulate rainfall for yearly, monthly and daily periods. We believe that, for water supply issues, no higher resolution is needed, although higher resolution would be useful in models designed to measure the risk of local flooding. The critical factors are daily, monthly and yearly totals and daily, monthly and yearly variation. A model for generating yearly totals will be described using traditional time series methods. This model, along with a similarly constructed daily generation model by Piantadosi et al. (A New Model for Correlated Daily Rainfall, 2008), will be cascaded to start with a synthetic yearly total, then generate a synthetic sequence of monthly totals (through selection from a large number of realisations) that match the yearly total, and subsequently perform a similar operation for sequences of daily totals to match the required monthly totals. We present a new model for the generation of synthetic monthly rainfall data, which we demonstrate for Parafield in Adelaide, South Australia. The rainfall for each month of the year is modelled as a non-negative random variable from a mixed distribution with either a zero outcome or a strictly positive outcome. We use maximum likelihood to find parameters for both the probability of a zero outcome and the gamma distribution that best matches the observed probability density for the strictly positive outcomes. We describe a new model that generates correlated monthly rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. Our model preserves the marginal monthly distributions and, hence, also preserves the monthly and yearly means. We show that, for Parafield, the correlation between rainfall totals for successive months is not significant, and so, it is reasonable to assume independence. This is, however, not true for daily rainfall. We describe a new model that generates correlated daily rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. This is an extended version of a paper presented at the 17th Biennial Congress on Modelling and Simulation, Christchurch, New Zealand, December 2007.     

Investigating the capacity of an activated sludge process to reduce volatile organic compounds and odor emissions.

The effects of hydrogen sulfide (H2S) diffusion into activated sludge (AS) on odor and volatile organic compound (VOC) concentrations in offgas were studied over an 8-week period. Most VOCs detected in the offgas of both aeration tanks were aromatic hydrocarbons. The VOC concentrations generally decreased when H2S was introduced to the AS compared with the control, indicating a negative effect of H2S on VOC removal. Two volatile organic sulfur compounds present in the test AS offgas showed an increase followed by a decrease during H2S peak loads. Six VOCs and odor concentration increased during the introduction of an H2S peak; however no correlation was observed between H2S and odor concentration. The increase in odor concentration resulted from the increase in the concentration of six aromatic VOCs, which had their removal slowed down during a 100-ppmv H2S peak. Activated sludge diffusion provides effective H2S removal with minimal affect on odor emissions.     

气候变化对波罗的海入海河流流量的影响

进入波罗的海的河流流量是在一个面积约160万km2的流域中各种不同气候状况下产生的.波罗的海流域气候的变化不仅影响入海淡水的总量,而且对这些水源的分配亦有影响.利用水文模拟,分析了未来气候变化对波罗的海入海径流的影响.使用了瑞典区域气候模拟计划(SWECLIM)中的4种不同的气候变化情景.根据这些不同的气候情景,全部入海河流总的平均年入海量的变化范围为当前入海量的-2%～+15%.波罗的海不同亚区的入海量的变化是大不相同的,其中最剧烈的年均变化范围是-30%～+40%.但是,所有评价的气候情景的共同点是总体趋势为来自波罗的海流域南部地区入海流量减少,北部地区入海量增加.     

The biogenic content of process streams from mechanical–biological treatment plants producing solid recovered fuel. Do the manual sorting and selective dissolution determination methods correlate?

The carbon emissions trading market has created a need for standard methods for the determination of biogenic content (χ_B) in solid recovered fuels (SRF). We compare the manual sorting (MSM) and selective dissolution methods (SDM), as amended by recent research, for a range of process streams from a mechanical–biological treatment (MBT) plant. The two methods provide statistically different biogenic content values, as expressed on a dry mass basis, uncorrected for ash content. However, they correlate well (r² > 0.9) and the relative difference between them was <5% for χ_B between 21% ^w/w_d and 72% ^w/w_d (uncorrected for ash content). This range includes the average SRF biogenic content of ca. 68% ^w/w_d. Methodological improvements are discussed in light of recent studies. The repeatability of the SDM is characterised by relative standard deviations on triplicates of <2.5% for the studied population.     

Detecting pigments from colourful eggshells of extinct birds

The known chemical basis of diverse avian eggshell coloration is generated by the same two classes of tetrapyrrole pigments in most living birds. We aimed to extend the evolutionary scope of these patterns by detecting pigments from extinct birds’ eggs. In our samples biliverdin was successfully extracted from subfossil shell fragments of the blue-green egg-laying upland moa Megalapteryx didinus, while protoporphyrin was extracted from the beige eggs of two other extinct moa species. Our data on pigment detection from eggshells of other extant paleognath birds, together with published information on other modern lineages, confirm tetrapyrroles as ubiquitous and conserved pigments contributing to diverse eggshell colours throughout avian evolution.     

Sizing and Costing of Electrostatic Precipitators

This is the second of a two-part article that reviews electrostatic precipitation theory, presents size estimating methods, and gives costing procedures for a variety of electrostatic precipitator (ESP) types and sizes. Part I of the article, which appeared in the April 1988 issue of JAPCA, discussed theory and sizing; this part presents costing. Information is given for estimating total capital investment including separate costs for the bare ESP (five types) and auxiliaries. Factors are given for installation and for indirect costs. Direct and indirect annual costs are discussed. An example problem is given.     

An Evaluation of Multiple Objective Decision Support Weighting Techniques in Natural Resource Management

Multiple objective decision support (MODS) is a structured framework for evaluating decision alternatives against multiple, and often conflicting, criteria. Its ability to handle complex trade-offs in a variety of quantitative and qualitative units gives it much potential in the field of natural resource management (NRM). A key component of MODS is the process used to obtain information from decision makers on the relative importance of evaluative criteria. Ranking algorithms then use this information to determine the relative value of each decision alternative. This paper explores how practising community based NRM decision makers respond to five generic methods for weighting the criteria. It presents a study in which 55 decision makers throughout five regions in Queensland, Australia, applied MODS to evaluate environmental projects seeking funding under the Australian Natural Heritage Trust. Weighting methods applied include fixed point scoring, rating, ordinal ranking, a graphical method and paired comparisons. Decision makers evaluated each weighting method in terms of ease of use and of how much it helped clarify the decision problem. Results show that decision makers felt uncomfortable applying fixed point scoring and generally preferred to express their preferences through ordinal ranking. This has implications for the types of ranking algorithms that can be applied to evaluate the decision alternatives.