Social learning mechanisms compared in a simple environment

Social learning can be adaptive, but little is known about the underlying mechanisms. Many researchers have focused on imitation but this may have led to simpler mechanisms being underestimated. We demonstrate in simulation that imitative learning is not always the best strategy for a group-living animal, and that the effectiveness of any such strategy will depend on details of the environment and the animal's lifestyle. We show that observations of behavioural convergence or "traditions" might suggest effective social learning, but are meaningless considered alone

Effects of the topology of social networks on information transmission

Social behaviours cannot be fully understood without considering the network structures that underlie them. Developments in network theory provide us with relevant modelling tools. The topology of social networks may be due to selection for information transmission. To investigate this, we generated network topologies with varying proportions of random connections and degrees of preferential attachment. We simulated two social tasks on these networks: a spreading innovation model and a simple market. Results indicated that non-zero levels of random connections and low levels of preferential attachment led to more efficient information transmission. Theoretical and practical implications are discussed

Pleading with the Emperor: Pax Americana and the Transformation of Environmental Governance

The combined effects of the globalisation and integration of productive networks of capital, the hegemony of neo-liberal discourse in the framing of policy toward capital markets, the unchallenged dominance of the US military, the establishment of the International Monetary Fund (IMF), World Bank (WB) and World Trade Organisation (WTO), and the more recent signing of bilateral free trade agreements(BITs) have circumscribed the ability of governments to exercise sovereignty in the creation of environmental policy. The resultant capacity to "insulate policy from the chaos of politics" (Economist 1994, 9) has prompted a number of authors to situate issues of global governance within the context of Empire. In this paper, we chart the re-emergence of Empire as concept and phenomena. In the first section, we identify three schools of thought that invoke the concept of Empire: the image of Pax Americana held by US neoconservatives for whom Empire is a reality justified by the necessities of geo-political power; the liberal-humanitarianism of European foreign policy elites who argue for a multi-polar Empire to balance American power; and the complex multi-dimensional entity of domination depicted by the global justice movement. We reveal the tensions that exist between Empire’s agents, most notably between a vision of a multi-polar Empire and that of Pax Americana. Through the work of Hardt and Negri, Harvey and Foucault, we develop an operational concept of Empire to explore how the tensions between the agents of Empire manifest as a global system of governance. Drawing on this analysis, we discuss the implications of Empire for environmental politics and policy through a case-study of the Australian-United States Free Trade Agreement (AUSFTA) to illustrate the complex, multiform strategies of power operating in the maintenance and transformation of Empire

Computations on Sofic S-gap Shifts

Let $S=\{s_{n}\}$ be an increasing finite or infinite subset of $\mathbb N \bigcup \{0\}$ and $X(S)$ the $S$-gap shift associated to $S$. Let $f_{S}(x)=1-\sum\frac{1}{x^{s_{n}+1}}$ be the entropy function which will be vanished at $2^{h(X(S))}$ where $h(X(S))$ is the entropy of the system. Suppose $X(S)$ is sofic with adjacency matrix $A$ and the characteristic polynomial $\chi_{A}$. Then for some rational function $Q_{S}$, $\chi_{A}(x)=Q_{S}(x)f_{S}(x)$. This $Q_{S}$ will be explicitly determined. We will show that $\zeta(t)=\frac{1}{f_{S}(t^{-1})}$ or $\zeta(t)=\frac{1}{(1-t)f_{S}(t^{-1})}$ when $|S|<\infty$ or $|S|=\infty$ respectively. Here $\zeta$ is the zeta function of $X(S)$. We will also compute the Bowen-Franks groups of a sofic $S$-gap shift.Comment: This paper has been withdrawn due to extending results about SFT shifts to sofic shifts (Theorem 2.3). This forces to apply some minor changes in the organization of the paper. This paper has been withdrawn due to a flaw in the description of the adjacency matrix (2.3

Topological Entropy of Braids on the Torus

A fast method is presented for computing the topological entropy of braids on the torus. This work is motivated by the need to analyze large braids when studying two-dimensional flows via the braiding of a large number of particle trajectories. Our approach is a generalization of Moussafir's technique for braids on the sphere. Previous methods for computing topological entropies include the Bestvina--Handel train-track algorithm and matrix representations of the braid group. However, the Bestvina--Handel algorithm quickly becomes computationally intractable for large braid words, and matrix methods give only lower bounds, which are often poor for large braids. Our method is computationally fast and appears to give exponential convergence towards the exact entropy. As an illustration we apply our approach to the braiding of both periodic and aperiodic trajectories in the sine flow. The efficiency of the method allows us to explore how much extra information about flow entropy is encoded in the braid as the number of trajectories becomes large.Comment: 19 pages, 44 figures. SIAM journal styl

Developing a methodology for social network sampling (abstract)

Researchers are increasingly turning to network theory to describe and understand the social nature of animal populations. To make use of the statistical tools of network theory, ecologists need to gather relational data, typically by sampling the social relations of a population of animals over a given time-period. Due to effort constraints and the practical difficulty involved in tracking animals, these sampled relational data are almost always a subset of the actual network. Measurements of the sample – such as average path length, clustering, and assortativity – are assumed to be informative as to the structure of the real-world social network. However, this assumption is problematic. Due to artefacts of the sampling process, the various network measures taken on the sample may be biased estimators of the true values. For example, just as we would get a biased estimate of mean human height by selecting for a sample those people who stood out in a crowd, we will get a biased estimate of a measure like mean connectivity if we sample individuals who are socially prominent. This problem can only be solved by developing a qualitative theory of network sampling, answering questions such as what proportion of the whole network needs to be sampled before a given level of accuracy is achieved, and what sampling procedures are least biased? To develop such a theory, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures. But currently available data on animal social networks are unsuitable as these networks were themselves sampled. The simulation methods of artificial life provide the way forward. We have developed a computational tool for generating artificial social networks that have user-defined distributions for network properties (such as the number of nodes, and the density) and for key the measures of interest to ecologists (such as the average degree, average path length, clustering, betweenness, and assortativity). This tool allows us to perform the required systematic analyses of the biases inherent in different sampling regimes (e.g., snowball sampling) applied to different network structures. We will present details of this system, and show we are using it to develop robust sampling methods for social network data. We see the system as the first in a series of works that will allow us to develop a qualitative theory of social network sampling to aid ecologists, and eventually social scientists, in their social network data collection

Spatial and temporal patterns of land surface fluxes from remotely sensed surface temperatures within an

International audienceCharacterising the development of evapotranspiration through time is a difficult task, particularly when utilising remote sensing data, because retrieved information is often spatially dense, but temporally sparse. Techniques to expand these essentially instantaneous measures are not only limited, they are restricted by the general paucity of information describing the spatial distribution and temporal evolution of evaporative patterns. In a novel approach, temporal changes in land surface temperatures, derived from NOAA-AVHRR imagery and a generalised split-window algorithm, are used as a calibration variable in a simple land surface scheme (TOPUP) and combined within the Generalised Likelihood Uncertainty Estimation (GLUE) methodology, to provide estimates of areal evapotranspiration at the pixel scale. Such an approach offers an innovative means of transcending the patch or landscape scale of SVAT type models, to spatially distributed estimates of model output. The resulting spatial and temporal patterns of land surface fluxes and surface resistance are used to more fully understand the hydro-ecological trends observed across a study catchment in eastern Australia. The modelling approach is assessed by comparing predicted cumulative evapotranspiration values with surface fluxes determined from Bowen ratio systems and using auxiliary information such as in-situ soil moisture measurements and depth to groundwater to corroborate observed responses

Spatial and temporal patterns of land surface fluxes from remotely sensed surface temperatures within an uncertainty modelling framework

Characterising the development of evapotranspiration through time is a difficult task, particularly when utilising remote sensing data, because retrieved information is often spatially dense, but temporally sparse. Techniques to expand these essentially instantaneous measures are not only limited, they are restricted by the general paucity of information describing the spatial distribution and temporal evolution of evaporative patterns. In a novel approach, temporal changes in land surface temperatures, derived from NOAA-AVHRR imagery and a generalised split-window algorithm, are used as a calibration variable in a simple land surface scheme (TOPUP) and combined within the Generalised Likelihood Uncertainty Estimation (GLUE) methodology to provide estimates of areal evapotranspiration at the pixel scale. Such an approach offers an innovative means of transcending the patch or landscape scale of SVAT type models, to spatially distributed estimates of model output. The resulting spatial and temporal patterns of land surface fluxes and surface resistance are used to more fully understand the hydro-ecological trends observed across a study catchment in eastern Australia. The modelling approach is assessed by comparing predicted cumulative evapotranspiration values with surface fluxes determined from Bowen ratio systems and using auxiliary information such as in-situ soil moisture measurements and depth to groundwater to corroborate observed responses

Comparison of Summer Forages and the Effect of Nitrogen Fertilizers on \u3ci\u3eBrassica\u3c/i\u3e Forages in Tasmania

Summer forage crops, and in particular Brassica spp., have become increasingly popular in dairy production systems in Tasmania. Field experiments were conducted for 3 years in northwestern Tasmania, in the spring/summers beginning in 1995. The study aimed to compare yield and quality of Brassica and Poaceae forages and the response of Brassica species to nitrogen (N) (50, 100 and 200 kg N/ha) and irrigation. The average total yields of dryland (rainfed) crops in 1995 to 1997 experiments, were turnip (Brassica rapa) 9.3 t/ha, rape (B. napus) 5.9 t/ha, oats (Aevena sativa) 5.2 t/ha, kale (B. oleracea) 5.1 t/ha, short-lived ryegrass (Lolium multiflorum) 5.1 t/ha, pasja (B. campestris × B. napus) 4.3 t/ha, perennial ryegrass (L. perenne) 4.2 t/ha, millet (Echinochloa utilis) 3.8 t/ha, and maize. (Zea mays) 2.9 t/ha. Irrigation increased the yield of turnips by 4.8 t/ha (mainly bulbs) and millet yields by 1.4 t/ha and reduced maize yield by 1.2 t/ha. Brassica species were higher in ME and lower in CP than the Poaceae forages. Nitrogen fertilizer increased the DM yield of tops of all Brassica crops in the 1997/98 experiments under irrigation, but it decreased the yield of turnips bulbs. The total yields with 50, 100 and 200 kg N/ha were 14, 15.2 and 15 t DM/ha for turnips, 7.5, 8.5 and 10 t for pasja and 10, 12 and 12.2 t DM/ha for rape, respectively. With 100 kg N/ha the average concentration of quality attributes of turnips, pasja and rape were CP 14, 22 and 19%, ME 12, 14.6 and 12.6 MJ/kg DM respectively. Nitrogen increased the CP, but had no effect on ME of any Brassica crops. Brassica forage are superior to Poaceae forages for summer feed production and as a part of pasture renovation process. They are higher in their yields, quality and water use efficiency and respond well to N fertilizer

Patient medication knowledge and adherence to asthma pharmacotherapy: a pilot study in rural Australia

Asthma is a chronic disease with both inflammatory and bronchoconstrictive elements and often requires multiple medications. Most asthma regimens include medications with different therapeutic modes of action and a number of different medication delivery devices. To effectively participate in their asthma management, patients need to recognize each of their medication types, understand their purpose, adhere to their treatment regimen, and be proficient in using the required delivery devices. This study evaluated patient knowledge of asthma pharmacotherapy and adherence. An interview study was undertaken in two rural locations, in Australia, to elicit participants' knowledge, use, and inhalation device technique. Of participants, 75.9% used preventer medication and the remaining 24.1% used reliever medication only. Of those using preventer medication, 82.5% could distinguish their preventer from a range of asthma medicines. Metered dose inhalers (MDIs) were used by 80% of participants; 23% used a Turbuhaler®; 24% used an Accuhaler®; and 5% used an MDI with a spacer device. The study established poor medication knowledge, suboptimal device technique, and disturbing levels of adherence with management recommendations. Asthma education strategies need to be modified to engage patients with low asthma knowledge to achieve improved patient outcomes. Further, strategies need to motivate patients to use preventer medication during times when they feel well