Plant-pollinator interactions - Free Essay Example

Abstract Very little work has been done on the evolution of floral colour diversity, outside of Europe and the Middle East. In particular, we know almost nothing about the evolution of the Australian flora in the context of hymenopteran visual systems. Such a study is likely to be important due to the geologically long isolation of the Australian flora and the high proportion of endemic plant species. The aims of this study were to investigate the colour of Australian native flowers in the context of hymenopteran visual systems, the innate colour preferences of Australian native bees (Trigona carbonaria), and the interactions between native bees and a food deceptive orchid (Caladenia carnea). Firstly, I found that the discrimination thresholds of hymenopterans match up with floral colour diversity and that hymenopterans appear to have been a major contributor to flower colour evolution in Australia. Secondly, I found that Trigona carbonaria has innate preferences for wavelengths of 422, 437 and 530 nm. Thirdly, I found that bees were able to habituate to orchid flowers based on colour, thus potentially explaining the colour polymorphism of Caladenia carnea. Together, my study suggests that the evolution of the Australian flora has been influenced by hymenopterans. 1. Introduction Plant-pollinator interactions The mutual interactions between pollinators and plants have been suspected in driving angiosperm radiation and diversification in the past (Regal 1977; Crepet 1984; McPeek 1996). The obvious mutual benefit is that pollinators depend on the pollen and/or nectar of flowering plants for food and, in return, partake in the incidental transfer of pollen necessary for plant reproduction (Faegri and van der Pijl 1978; Harder, Williams et al. 2001). Worldwide, it is estimated that more than 67% of angiosperm plants rely on pollination by insects (Tepedino 1979). Hence, pollinators play a critical role in the persistence and survival of flowering plants, which are of high value to the human food chain (Kearns and Inouye 1997; Klein, Vaissiere et al. 2007). Flower colour signals and sensory exploitation Colour is the result of the visible light being absorbed or reflected off objects and then processed by the eye and brain of an animal (Le Grand 1968). Light is part of the electromagnetic spectrum, and can be quantified by the wavelength of different photons of energy (Bueche 1986). The wavelengths reflected off the object are perceived by a visual system as the objects colour. For example, light that appears blue to a human observer can be described by a dominant wavelength of 400nm, whilst light that appears red is 700nm. Ultraviolet light falls between 300-400nm and can be seen by bees, but not humans. Flower colours have been influenced by the sensory receptors of insects, including their colour vision, which is different to human vision. Humans have a red, blue and green receptor (Chittka and Wells 2004). In contrast insects have a UV, green and blue receptor (Chittka and Wells 2004). As human vision is very different to a hymenopterans colour visual system, one cannot discuss a bees colour perception according to human colour terms such as red or blue. Therefore, this thesis will discuss colours according to wavelength. Colour is one of the most important floral signals plants use to communicate information to insect pollinators (Giurfa, Vorobyev et al. 1996; Dyer, Spaethe et al. 2008). Although it is known that pollinators select flowers based on morphology, nectar availability, size, and odour (Giurfa, Nez et al. 1994; Kunze and Gumbert 2001; Spaethe, Tautz et al. 2001; Whitney and Glover 2007), colour is known to play a critical role in enabling pollinators to detect and discriminate target flowers from a biologically important distance of up to 50 cm (Giurfa, Vorobyev et al. 1996; Dyer, Spaethe et al. 2008). Our understanding of the evolution of colour vision in insects has advanced considerably in recent years. In the past, studies of colour perception were limited due to little information on the colour visual system of insects (Frisch 1914; Daumer 1956). It is now possible to evaluate how flower visual signals appear to the visual system of hymenopteran pollinators, using spectrophotometer and colorimetry techniques, which allows quantitative evaluations of how complex colour information is perceived by insect pollinators (Chittka 1992) (fig. 1). Previous research has revealed that colour discrimination in hymenopterans is phylogenetically ancient, with different hymenopterans sharing similar colour perception (Helversen 1972; Chittka and Menzel 1992). Importantly, colour discrimination in the hymenoptera is known to predate the evolution of floral colour diversity (Chittka 1996). Here, recent research has revealed remarkable convergence in the evolution and distribution of floral colours in different parts of the world. Specifically, in a seminal paper, Chittka (1996) showed that flowering plants in both Europe and the Middle East have adapted their colour signals to the visual systems of bees, with flower colours in these regions closely matched to the visual receptors of hymenopterans (Chittka 1996). However, outside of Europe and the Middle East, very little work has been done on the evolution of floral colour diversity. In particular, we know almost nothing about the evolution of the Australian flora in the context of hy menopteran visual systems. This is an important question to investigate due to the long isolation of the Australian flora and the high proportion of endemic plant species. I hypothesise that the Australian floral coloration will closely match the discrimination thresholds of hymenopterans as recent evidence suggests that insect pollinators supported the early spread of flowering plants (Hu, Dilcher et al. 2008). Innate colour preferences of bees Charles Darwin was the first to state that innate preferences could allow an inexperienced pollinator to find a food source (Darwin 1877). Pollinators may use certain traits of flowers such as morphology, scent, temperature and colour to locate food (Heinrich 1979; Menzel 1985; Dyer, Whitney et al. 2006; Raine, Ings et al. 2006). Previous studies evaluating innate colour preferences have tended to focus on two species: the European honey bee (Apis mellifera) and bumblebee (Bombus terrestris). By contrast, no studies have looked at the innate colour preferences of Australian bees and how this affects their choices for flowers. We know that European bumblebees and honeybees show strong preferences for violet and blue (400-420nm) throughout their geographic range (Chittka, Ings et al. 2004) ,which interestingly correlates with the most profitable food sources (Lunau and Maier 1995; Chittka and Raine 2006). These preferences are likely to have had an impact on the relative success of dif ferent flower colours in regions where these bees are dominant pollinators (Chittka and Wells 2004). Consequently, information on the innate preferences of Australian bees will be important to understand hymenopteran plant interactions in the Australian context. Pollinator learning and food deceptive orchids Most plants reward their pollinators with nectar or pollen. However, some species do not offer floral rewards and, instead, employ a range of deceptive techniques to trick insects into performing the task of pollination. Deceptive pollination strategies are particularly well known and widespread among orchids (Jerskov, Johnson et al. 2006). For instance, approximately 400 orchid species are known to achieve pollination through sexual deceit, luring unsuspecting male insects to the flower through olfactory, visual and tactile mimicry of potential mates. More common are food deceptive orchids which are believed to number as many as 6,000 species (one-third of orchids) (Jerskov, Johnson et al. 2009). Food mimicking orchids employ bright colours to falsely advertise the presence of a reward to attract naive pollinators (Ackerman 1986; Nilsson 1992; Jerskov, Johnson et al. 2006). The common occurrence of food deception in orchids suggests that this form of pollination by deception is an e xtremely successful evolutionary strategy (Cozzolino and Widmer 2005). Visits by pollinators to deceptive plants are influenced by pollinator learning. In the case of sexual deception, previous research shows that insects quickly learn unrewarding flower decoys and avoid them. For example, male insects learn to avoid areas containing sexually deceptive orchids (Peakall 1990; Wong and Schiestl 2002). However, whether insects can learn to avoid food deceptive orchids remains to be investigated. In addition, high levels of variability in floral traits, particularly flower colour and floral scent, may interrupt the associative learning of insects by preventing their ability to become familiar with deceptive flowers (Schiestl 2005). Indeed, variation in colour, shape and fragrance is evident in non-model food-deceptive orchids (Moya and Ackerman 1993; Aragn and Ackerman 2004; Salzmann, Nardella et al. 2007). However, previous studies have only looked at pollinator preference for colour morphs (Koivisto, Vallius et al. 2002), rather than assessing if variable flower colour slows down the ability of naive pollinators to learn unrewarding flower decoys. Furthermore, there is a need to incorporate a combination of colour vision science and behavioural ecology to understand how a bee perceives the orchid flowers, as bees have a different visual system to humans. Although humans cannot see ultra-violet light, UV sensitivity is common in some animals (Tove 1995). UV sensitivity has been found in insects, birds, fish and reptiles (Marshall, Jones et al. 1996; Neumeyer and Kitschmann 1998; Cuthill, Partridge et al. 2000; Briscoe and Chittka 2001). Studies on UV vision in an ecological context have mainly focused on species specific signalling and mate choice (Bennett, Cuthill et al. 1996; Bennett, Cuthill et al. 1997; Pearn 2001; Cummings, Garc et al. 2006). However, few studies have looked at the role of UV signals in attracting bees to orchids. Previous studies have shown that the presence of UV reflecting crab spiders attracts honeybees to daisies (Heiling, Herberstein et al. 2003). In a similar study, Australian native bees (Austroplebia australis) were attracted but did not land on flowers with UV reflecting crab spiders (Heiling and Herberstein 2004). However, the role of UV signals in orchids is not well studied. In particular, it is not known if the UV signal is important in attracting naive bees to food deceptive orchids. Thus, it will be useful to know if UV signals might also serve to lure naive pollinators to deceptive flowers to understand deceptive pollination. Aims This project will investigate Australian flower colour diversity in the context of hymenopteran visual systems, the innate colour preferences of Australian native bees (Trigona carbonaria) and their interactions with a food deceptive orchid (Caladenia carnea). This study aims to address the following questions: 1. Is there a link between hymenopteran vision and Australian floral coloration? 2. Does an Australian native bee (Trigona carbonaria) have innate colour preferences? 3. Does a food deceptive orchid (Caladenia carnea) exploit the innate colour preferences of Trigona carbonar 2. Methods Part 1. Is there a link between hymenopteran vision and Australian floral coloration? Flower collection and spectral reflectance functions of Australian native plant flowers Australian native flowers were collected from Maranoa Gardens, Balwyn (melway ref 46 F7). Maranoa Gardens was chosen due to the diverse collection of species from all over Australia. Flowers were collected once a month, from May to January. A colour photograph was taken of the flower for identification. I also took a UV photograph for all flowers, using a digital UV camera [Fuji Finepix Pro S3 UVIR modified CCD for UV imaging] with calibrated UV-vis grey scales (Dyer, Muir et al. 2004). As UV rays are invisible to the human eye (Menzel and Blakers 1976; Dyer 2001), this photo enabled any UV reflectance areas of the flower to be measured by the spectrophotometer (Indsto, Weston et al. 2006). The spectral reflection functions of flowers were calculated from 300 to 700 nm using a spectrophotometer(S2000) with a PX-2 pulsed xenon light source attached to a PC running SpectraSuite software (Ocean Optics Inc., Dunedin, FL, USA). The spectrophotometer was used to quantify the colour of the flower as wavelength. The white standard was a freshly pressed pellet of dry BaSO4, used to calibrate the spectrophotometer. A minimum of three flowers from each plant were used for each spectral analysis. I evaluated a sample of 111 spectral measurements from Australian flowering plants, encompassing a representative variety of plant families (fig. 2). Correlations between spectral reflectance functions of different plant flowers and trichomatic vision of the honeybees To understand if there is a link between hymenopteran vision and Australian native flowers, I used the methodology used by Chittka and Menzel (1992). In that study, Chittka and Menzel looked for correlations between flower spectra sharp steps of different plant flowers and trichomatic vision of the honeybees. Sharp steps are a rapid change in the spectra wavelength (Chittka and Menzel 1992) (see fig. 3 for an example of a sharp step). These steps cross over different receptors, thereby producing vivid colours that stand out from the background. Furthermore, a colour signal will be more distinguishable to a pollinator if the sharp steps match up with the overlap of receptors in a visual system. Thus, the main feature of a flower wavelength is a sharp step. For this study, I defined a sharp step as a change of greater than 20 % reflectance in less than 50 nm of the bee visual spectrum. The midpoint of the slope was determined by eyesight as described by Chittka and Menzel (1992), as th e nature of curves varied with each flower. The absolute numbers of sharp steps within each flower spectra were counted. The frequencies are shown in fig. 4b. As hybrid plants are artificially selected by humans, hybrid flowers were not included in the analyses. Generating a Hexagon colour space To evaluate how flower colours are seen by bees, I plotted the flower colour positions in a colour hexagon space. A colour space is a numerical representation of an insects colour perception that is suitable for a wide range of hymenopteran species (Chittka 1992). In a colour space, the distances between locations of a two colour objects link with the insects capacity to differentiate those colours. To make the colour space, the spectral reflectance of the colour objects were required, as well as the receptor sensitivities of the insect. For Trigona carbonaria, the exact photoreceptors are currently unknown, but hymenopteran trichromatic vision is very similar between species as the colour photoreceptors are phylogenetically ancient (Chittka 1996). Thus, it is possible to model hymenopteran vision with a vitamin A1 visual template (Stavenga, Smits et al. 1993) as described by Dyer (1999). I then predicted how the brain processed these colour signals by using the average reflectance f rom each flower, and calculating the photoreceptor excitation (E) values, according to the UV, blue and green receptor sensitivities (Briscoe and Chittka 2001) using the methods explained by Chittka (1992). The UV, blue and green E-values of flower spectra were used as coordinates and plotted in a colour space (Chittka 1992). The colour difference as perceived by a bee was calculated by the Euclidean distance between two objects locations in the colour hexagon space (Chittka 1992). Modelling the distributions of Australian flower colours according to bees perception I analysed the most frequent flower colour according to a bees colour perception using the methods of Chittka, Shmida et al. (1994). I plotted the Australian flower colours in a colour space (Fig 5a). A colour space is a graphical representation of a bees colour perception. A radial grid of 10 degree sectors was placed over the distribution of colour loci and the number of floral colour loci within each sector was counted(fig. 5b). Part 2. Does an Australian native bee (Trigona carbonaria) have innate colour preferences? Insect model and housing Trigona carbonaria is an Australian native stingless bee that lives in colonies of 4000-10000 individuals (Heard 1988). In the wild, stingless bees live in hollows inside trees (Dollin, Dollin et al. 1997). Trigona carbonaria has a similar social structure to the honeybee (Wille 1983). They are common to North Eastern Australia and are a potentially important pollinator for several major commercial crops (Heard 1999). A research colony (ca. 4000 adults and 800 foraging individuals) of T. carbonaria was propagated for the experiments by Dr Tim Heard (CSIRO Entomology, 120 Meiers Rd, Indooroopilly 4068, Australia) as described in the paper by Heard (1988). Bees were maintained in laboratory conditions so that no previous contact with flowers had been made. For this study, a colony was placed in a pine nest box (27.5 x 20 x 31 cm; LWH) and connected to the foraging arena by a 16 cm plexiglass tube, containing individual shutters to control bee movements. All laboratory experiments were conducted in a Controlled Temperature Laboratory (CTL) at Monash University, Clayton, School of Biological Sciences (CTL room G12C dimensions 3 x 5m), during the months of July 2009- January 2010. Relative humidity (RH) was set to 30%, and the temperature was set to 27 C (SPER-Scientific Hygrometer, Arizona, USA), as this set up approximately matches conditions in Queensland for insect pollinators (Heard and Hendrikz 1993). Illumination (10/14 hr day/night) was provided by four Phillips Master TLS HE slimline 28W/865 UV+ daylight fluorescent tubes (Holland) with specially fitted high frequency (1200Hz) ATEC Jupiter EGF PMD2x14-35 electronic dimmable ballasts which closely matches daylight conditions for trichromatic hymenoptera (Dyer and Chittka 2004). The flight arena (1.2 x 0.6 x 0.5m; LWH) was made of a coated steel frame with laminated white wooden side panels. The arena floor was painted foliage green, and the arena lid was covered with UV transparent plexiglass. Experiments we re conducted from 1pm-3pm to control for time of day, as this is when bees are most active (Heard and Hendrikz 1993). Pre-training Bees were habituated to the flight arena for seven days. Naive foragers (i.e. bees that had never encountered real or artificial flowers) were initially pre-trained to forage in the flight arena on three rewarding aluminium sanded disks (25 mm in diameter), with a 10-l droplet of 15% (w/w) sucrose solution placed in the centre. The disks were placed on vertical plastic cylinders (diameter = 25 mm, height = 100 mm), to raise them above the floor of the flight arena so that bees learnt to fly to the disks. Pre-training allows bees to become habituated to visiting artificial flowers for further experiments. The aluminium sanded disks were chosen as neutral stimuli because they have an even spectral reflectance curve in the spectral visual range of the bees, fig. 6. The sucrose solution reward on these training disks was refilled using a pipette after it was consumed by foraging bees. The spatial positions of these training disks were pseudo randomised, so that bees would not learn to as sociate particular locations with reward. Bees were allowed a minimum of two hours to forage on the pre-training disks before data collection Innate colour preference testing To test the innate colour preferences of naive bees, I performed simultaneous choice experiments with flower-naive bees using artificial flowers that simulated the floral colours of natural flowers. The aluminum rewarding disks were replaced by the ten unrewarding, coloured artificial disks in the original flight arena. Artificial flower stimuli were cut in a circle (70 mm diameter) from standardized colour papers of the HKS-N-series (Hostmann-Steinberg K+E Druckfarben, H. Schmincke Co., Germany). In each experiment the same set of ten test colours (1N pale yellow, 3N saturated yellow, 21N light pink, 32N pink, 33N purple, 50N blue, 68N green, 82N brown, 92N grey, back of 92N white) were used. These colours were chosen as they have been used in innate colour experiments with other hymenopterans (Giurfa, Nez et al. 1995; Kelber 1997; Gumbert 2000), and the colours are also widely used in other bee colour experiments (Giurfa, Vorobyev et al. 1996). The coloured paper disks w ere placed on vertical plastic cylinders (diameter = 15 mm; height = 50 mm), to raise them above the floor of the flight arena. The gate was shut in the arena to ensure the bees used in each trial were separated from the next trial. The number of landings and approaches to the stimuli were recorded for one hour. Approximately 200 bees were used for each trial. The spatial positions of the artificial flowers were pseudo randomised in a counter balance fashion every 15 minutes. After each trial, the colour disks were aired and wiped with a paper tissue to remove possible scent marks, which are known to affect experiments with honeybees (Schmitt and Bertsch 1990; Giurfa and Nez 1992). I conducted each subsequent trial after removing the used bees from the system, to ensure that the bees in the next trial were replaced with naive foragers. It is known that perception of colour can be influenced by background colour (Lunau, Wacht et al. 1996). Therefore, I also tested colour choices on other background colours of grey and black. The results are qualitatively similar (fig. 8b), so only data from the biologically relevant green background was used for subsequent analysis. Analysis of colour stimuli As bees see colours differently to humans, I quantified stimuli according to five parameters: wavelength, brightness, purity (saturation), chromatic contrast to the background and green receptor contrast. Dominant wavelength was calculated by tracing a line from the centre of the colour hexagon through the stimulus location to the corresponding spectrum locus wavelength (Wyszecki and Stiles 1982). Brightness was measured as the sum of excitation values of the UV, blue and green receptors (Spaethe, Tautz et al. 2001). Spectral purity of the stimulus was calculated by the percentage distance of the stimulus in relation to the end of the spectrum locus (Chittka and Wells 2004). Chromatic contrast was calculated as the distance of a colour stimulus from the centre of the colour hexagon relative to the background. Chromatic contrast is important as perception can be affected by background colour (Lunau, Wacht et al. 1996). Green receptor contrast was measured as the green receptor excitat ion from a stimulus relative to the background (Giurfa, Nez et al. 1995). This contrast is relevant as green receptors and green contrast are known to affect motion in bees (Srinivasan, Lehrer et al. 1987). Statistical analyses The impact of wavelength on number of landings by Trigona carbonaria was investigated using a single factor analysis of variance (ANOVA) and a post hoc Tukeys HSD test (=0.05) (Quinn and Keough 2002) using the number of landings as the dependent variable and wavelength of stimuli as the independent variable. Brightness, purity (saturation), chromatic contrast to the background and green receptor contrast of stimuli were analysed using the Spearmans rank correlation test against choices. Statistical analyses were conducted using R statistical and graphical environment (R Development Core Team, 2007). Statistical significance was set to P0.05. Part 3. Does a food deceptive orchid (Caladenia carnea) exploit the innate colour preferences of Trigona carbonaria? Plant model Caladenia carnea is a widespread species, common to eastern Australia. The orchid is highly variable in colour, ranging from pink to white. It is pollinated by Australian native bees of the Trigona species (Adams and Lawson 1993).With bright colours and fragrance, this orchid achieves pollination by food mimicry (Adams and Lawson 1993). Thus, due to the colour variation of the orchid, C. carnea is an excellent model with which to examine floral exploitation of potential pollinators. Caladenia carnea flowers were supplied by private growers from the Australasian Native Orchid Society. Can Trigona carbonaria perceive a difference between pink and white flowers of Caladenia carnea? Colorimetric analysis of the pink and white Caladenia carnea flowers were used to investigate whether different colours of the orchid would be perceived as similar or different to a bees visual system. A spectrophotometer was used to take four measurements of each flower colour (pink versus white). The actual measurements used in the analysis were an average of each colour (Dyer, Whitney et al. 2007). To predict the probability with which insect pollinators would discriminate between different flowers, these spectra were plotted as loci in a hexagon colour space (Chittka 1992) (see hexagon colour space methods). Choice experiments I conducted trials testing the preferences of bees when offered a dichotomous choice between a white versus pink Caladenia carnea flower. Each trial took place inside a flight arena. Each white and pink flower used in a trial were matched for size, placed into indiviual plastic containers (diameter= 5 cm, height=5 cm) and placed in the arena with a distance of 10 cm between flower centres. Each container was covered with Glad WrapTM (The Clorox Company, Oaklands, CA, USA) to remove olfactory cues as they are known to inuence the choice behaviour of honeybees (e.g. Pelz, Gerber et al. 1997; Laska, Galizia et al. 1999). Approximately 50 bees were let into the arena for each trial. The rst contact made by a bee with the Glad WrapTM within a distance of 4 cm, was recorded as a choice of that ower (Dyer, Whitney et al. 2007). The number of landings were recorded to the flowers for five minutes. After each trial, the Glad WrapTM was changed to prevent scent marks. In addition, individual f lowers and spatial positions were randomised. Individual bees were sacrificed after each trial to avoid pseudo replication. Does the UV signal affect the attraction of bees to orchid flowers? To investigate whether the UV reectance of the dorsal sepal affected the response of bees, I offered bees the choice between two white orchids, one with a UV signal and the other without (N=16). The UV signal was removed by applying a thin layer of sunscreen (Hamilton SPF 30+, Adelaide, SA, Australia) over the dorsal sepal. Spectral reflectance measurements were taken to ensure that the sunscreen prevented any reflection of UV light (below 395 nm) from the sepals and did not change the reflectance properties of the orchid. In addition, spectral measurements of orchid sepals under Glad WrapTM confirmed that the foil was permeable to all wavelengths of light above 300 nm and did not obscure the reflectance of flowers. Do bees display preferences when choosing between pink versus white orchid flowers? To assess whether bees show a preference for pink or white variants of the orchid Caladenia carnea, I offered bees a simultaneous choice between a pink or white flower (N=16). See procedures for choice testing. Do bees habituate to non-rewarding orchids based on differences in floral coloration? I conducted a two stage experiment to investigate if bees could learn to habituate to a non-rewarding flower colour over time and whether bees adjusted their subsequent flower choice depending on the flower colour encountered previously. At stage 1 of the experiment, native bees were presented with one flower, either white or pink. Flowers were placed in a container with Glad WrapTM. Landings to the flower were recorded at the start and again at the 30 min mark. At stage 2, the flower from stage 1 was swapped with a new flower colour and the number of landings were scored for 5 minutes. Flowers were randomised and Glad WrapTM changed to prevent scent marks after each trial. Once again, bees were used only once per experiment. Statistical analyses For experiments 2, 3 4, numbers of landings by naive bees to flower pairs were compared using two tailed paired t-tests. A two factor ANOVA was used to analyse whether bees habituate to non-rewarding orchids based on differences in floral coloration. The dependent variable was the number of landings and the two independent variables were previous flower colour and new flower colour. 3. Results Part 1. Is there a link between hymenopteran vision and Australian floral coloration? Correlations between the inflection curves of different plant flowers and trichomatic vision of hymenopterans The analysis of 111 spectral reflection curves of Australian flowers reveals that sharp steps occur at those wavelengths where hymenoterans are most sensitive to spectral differences (fig. 4b). There are three clear peaks in sharp steps (fig. 4b). It is known that hymenopteran trichomats are all sensitive to spectral differences at approximately 400 and 500 nm (Menzel and Backhaus 1991; Peitsch, Fietz et al. 1992). Hence, the peaks at 400 and 500 nm can be discriminated well by hymenopteran trichomats, as illustrated by the inverse / function (solid curve shown in fig. 4a) of the honeybee (Helversen 1972), which is an empirically determined threshold function which shows the region of the electromagnetic function that a bees visual system discriminates colours best. In summary, the spectral position of receptors of trichomatic hymenopterans are correlates with steps in the floral spectra of Australian flowers. The distributions of Australian flower colours according to bees perception The floral colour loci are strongly clustered in the colour hexagon (fig. 5a). Blue-green flowers are the most common in the perception of bees, while pure UV flowers were the rarest (fig. 5b). Part 2. Does an Australian native bee (Trigona carbonaria) have innate colour preferences? Effect of brightness, spectral purity, chromatic contrast and green receptor contrast on colour choices There was no significant effect of stimulus brightness on choice frequency (rs= 0.333, n=10, p= 0.347; fig. 7a). There was no significant effect of spectral purity on choice frequency (rs = 0.224, n=10, p= 0.533; figure 7b). There was no significant correlation effect of chromatic contrast on choice frequency (rs = 0.042, n=10, p= 0.907; figure 7c). There was no significant effect of green receptor contrast on choice frequency (rs = 0. 0.552, n=10, p= 0.098; figure 7d). Effect of wavelength on colour choices Stimuli colours are plotted in figure 8a, as they appear to a human viewer to enable readers to understand the correlation between colour choices. However, all statistical analyses were conducted with stimuli plotted as wavelength due to the different visual perception of bees and humans (Kevan, Chittka et al. 2001). There is a significant effect of wavelength on the number of landings by Trigona carbonaria (Single factor ANOVA, F9,110 = 5.60, P 0.001), figure 8a. Tukeys post hoc test revealed that the wavelength of 437 nm (a white colour to a human viewer, but strongly coloured to a bees visual system as this stimulus does not reflect UV radiation) had significantly higher landings than other wavelengths of 528 nm (brown) (P0.01), 432 nm (grey) (P 0.01), 431 nm (light pink) (P0.01), 420 nm (purple) (P0.01), 455 nm (blue) (P=0.0196) and 535 nm (green) (P=0.0266). In addition, the number of landings to wavelengths of 530 nm (pale yellow) (P=0.0321) and 422 nm (pink) (P=0.0318) disks w ere significantly higher than that of 432 nm (grey) (figure 8a). Part 3. Does a food deceptive orchid (Caladenia carnea) exploit the innate colour preferences of Trigona carbonaria? Can Trigona carbonaria perceive a difference between pink and white flowers of Caladenia carnea? Ultraviolet photographs and reflectance measurements revealed that lateral sepals were different from the dorsal sepals (fig. 9). The spectra of the pink and white lateral sepals indicated no UV reflection. In contrast, the spectra of the dorsal sepals show reflection in the UV region (320-400 nm) (fig. 9b). Figure 10 shows the loci of the respective flower spectra in a hexagon colour space. Dyer and Chittka (2004) showed that with increasing colour distance between flowers and distractor flowers, less errors were made by foraging bees (fig. 11). Colour distance between the white and pink flowers is measured in hexagon units (Euclidean colour metric); Table 1. The lateral sepals (UV-) of pink and white flowers are separated by only 0.082 colour hexagon units, while pink and white dorsal sepals (UV+) are separated by 0.039 hexagon units. Thus, pink and white lateral sepals are distinguishable to a bee. In contrast, pink and white dorsal sepals (UV+) are perceptually similar to a bee. Therefore, the white vs. pink flowers of Caladenia carnea can thus be discriminated with between 70-90% accuracy (fig. 11). This means that visits to white/pink flower colours may results in occasional pollinator perceptual errors (1-3 errors/10 visits). Does the UV signal affect the attraction of bees to orchid flowers? When bees were presented with a choice between two white orchid flowers, one with a UV signal and one without, there was a significant preference for the flower with the UV reflectance (paired t-test: t= 6.949, df= 15, p0.001, n=16; figure 12). Do bees display preferences when choosing between pink versus white orchid flowers? When test subjects were presented with a choice between two flower colours, pink and white, there was a significant preference for the white flower (paired t-test: t= -3.484, df= 15, p= 0.003, n=16; figure 13). Do bees habituate to non-rewarding orchids based on differences in floral coloration? Bees were found to habituate to non-rewarding flowers, as the mean number of landings by Trigona carbonaria to the flower at the first time stage (T1) were found to be significantly different from the second time stage (T2) for white (paired t-test: t= 8.34, df= 15, p0.001) and pink flowers (paired t-test: t= 8.11, df= 15, p0.001) (fig. 14). Habituation rates were found to differ with different flower colours, as the mean number of landings by Trigona carbonaria to the white flower were found to be significantly higher from that of the pink flower (paired t-test: t=3.59, df=15, p=0.003, figure 14). I also looked at delta, which is calculated as the rate of change between landings at the first and second time stage for pink and white flowers separately. Hence, bees were found to habituate faster to pink flowers, as the rate of change was found to be significantly different (paired t-test: t=3.94, df=15, p=0.001). The number of landings to a flower were found to be significantly affect ed by the interaction between the previous flower colour and new flower colour, (two factor ANOVA, F3,28=6.846, p=0.001, figure 15). When the second flower colour presented was the same colour as the previous flower, landings were not significantly different to the second flower (F1,14=4.332 p=0.056). In contrast, when the second flower colour was different to the previous colour, landings were found to be significantly different to the second flower (F1,14=9.168 p=0.009) (fig. 15). In addition, preferences depended on the colour that bees were exposed to previously. When the previous flower was white, landings to the second pink or white flower were not found to be significantly different (F1,14=5.332,p=0.230). In contrast, when the previous flower colour was pink, landings were found to be significantly higher to the second white flower than to new pink flower (F1,14=8.395, p=0.012, figure 15). Bees, in this regard, were adjusting their choices to the second flower depending on their previous flower experience. 4. Discussion Hymenopteran vision and Australian floral coloration. Part 1 of this project aimed to investigate a possible link between hymenopteran vision and Australian floral coloration floral colour diversity My results suggest that the discrimination thresholds of hymenopterans match up with the Australian floral colours. These results are consistent with the study of Chittka and Menzel (1992), who found a correlation between flower spectra of different flowers and trichomatic vision of hymenopterans for flowers collected in Europe and parts of the Middle East. I have found a similar pattern in Australia, so this data is highly suggestive that hymenopterans appear to have been a major contributor to flower evolution in Australia. As bee vision predates the evolution of flower colours (Chittka 1996), one possibility is that Australian native flowers may initially have evolved to exploit the vision of hymenopteran species. Another alternative is that the existence of the current floral colours is due to phylogenetic constraints on the pigments in flower colours (Menzel and Shmida 1993). The distribution of flower colours that has evolved has a remarkably similar distribution to other parts of the world, such as Europe and the Middle East, where honeybees are the dominant pollinators (fig. 4a b, 5b c). Blue-green flowers were the most common as flower colours appear to a bee, while pure UV flowers were the rarest in the flowers sampled (fig. 5b). This result is similar to previous studies that found a similar cluster of blue-green flowers in Europe and Middle East (Chittka, Shmida et al. 1994). In that study, it was suggested that this cluster may be explained by the innate colour preferences of insects for certain colours (Chittka, Shmida et al. 1994). However, other studies contradict this because naive and experienced honeybees prefer UV-blue and blue colours over blue-green colours (Menzel 1967; Giurfa, Nez et al. 1995). However, the distribution of blue-green flowers is larger than that of UV-blue and blue flowers. The refore, Chittka (1997) suggested that the distribution could be caused by evolutionary constraints on the pigments of flower colours. Another theory for why flower colours are not evenly distributed in the colour space could be due to colour constancy (where bees only visit one flower type) in complex environments (Dyer 1999; Dyer and Chittka 2004). Hence, as there is no equal spacing of colours in the Australian floral coloration and there is a higher proportion of blue-green flowers, this may correspond to either pigment constraints in flowers or selective pressures by important pollinators like hymenopterans. There are two likely scenarios as to whether floral colours in Australia have evolved independently to those of Europe and the Middle East. First, angiosperms evolved after Australia separated from Gondwana. Hence, parallel evolution may have occurred where similar flower colours were being selected by hymenopteran trichomatic vision. The second possible scenario is that ang iosperms evolved before Australia separated from Gondwana and radiated out to all continents. Thus, flowering plants drifted with the moving land masses and evolved in a similar way to European and Middle Eastern flowers. Scenario 1, in this regard, seems more likely as the evolution of flowers in Australia is likely to be independent, based on work by Kevan and Backhaus (1998) who estimate that early angiosperms were most likely to be a pale yellow pollen colour and later evolved highly coloured signals to lure important pollinator vectors. It is estimated that the earliest angiosperm fossil dates at 132 million years ago (mya), around the early Cretaceous (Crane, Donoghue et al. 1989; Crane, Friis et al. 1995). Towards the end of the Cretaceous, Australia separated from Gondwana (Rich and Rich 1993). However, the time scales are too imprecise to conclusively resolve this question. Additional data is needed on biogeographical relationships and how this relates to floral reflectance data for other continents such as Africa, South America, Asia and North America to understand this question. The foraging success of a bee is dependent on the colour vision receptors being able to relialy distinguish flower species from each other (Chittka and Menzel 1992). There is a mutual benefit here as the pollinators foraging efficiency is increased if it can distinguish flowers from the surrounding background; and the plant is more likely to be pollinated if it appears distinct from its surroundings (Chittka and Menzel 1992). It is known that bees can discriminate colour stimuli best at 400 and 500 nm (Helversen 1972). So why, then, do we see a third peak at 600 nm (fig. 4b)? One reason could be that biological material (including leaves) reflect infrared radiation above 600 nm (Chittka, Shmida et al. 1994). There is also the possibility that insects with red receptors such as butterflies and beetles (Menzel and Backhaus 1991; Peitsch, Fietz et al. 1992) might also be important pollination vectors influencing the evolution of some Australian flower colours. Currently, there is very l ittle information within Australia about the vision of insects with long wavelength sensitive receptors, but this would provide an interesting avenue for future research. It was really important to not bias my data set by specifically picking species that are pollinated by only hymenopterans. Thus, I took a broad approach of including every flowering plant species available at my sampling site to best represent the colour distribution of Australian flowering plants that have evolved. This enabled me to test whether hymenopteran colour vision has been a major driving force shaping the evolution of floral colours. In spite of the fact that the dataset included a broad sample of plants (some of which would likely not even be pollinated by hymenopterans), strong patterns were detected, suggesting that hymenopterans may have been major players shaping the evolution of floral colours. Innate colour preferences of an Australian native bee In part 2 of the study, the simultaneous choices of naive bees (Trigona carbonaria) were tested for 10 different colours using articial owers. After each test, bees were sacrificed so all the data was independent, avoiding the risk of pseudo replication. In addition, the bees were not exposed to real flowers and reared on colour neutral disks prior to colour testing (fig. 6). Thus, their behaviour can be classified as innate (Giurfa, Nez et al. 1995). It was necessary to pre-train bees to land on aluminium disks because it was not possible to get bees to land on colour stimuli without previous training (Giurfa, Nez et al. 1995). I also tested whether bees preferred stimuli on the basis of brightness, spectral purity, contrast and green receptor contrast. My results showed that bees preferred stimuli irrespective of brightness, spectral purity, contrast and green receptor contrast (fig. 7). This was found to be consistent with the study by (Giurfa, Nez et al. 1995). Thus, the only sig nificant factor affecting bees choices was wavelength. The results revealed that Trigona carbonaria has innate preferences for wavelengths of 422, 437 and 530 nm (fig. 8b). These results are remarkably similar to the innate preferences of flower naive honeybees and bumblebees in Europe (Menzel 1967; Lunau 1990; Giurfa, Nez et al. 1995) that have innate preference for blue and violet. In those studies, it was suggested that the innate preference for blue correlates with blue and violet flowers having a slightly higher nectar reward than other flower colours in Europe (Giurfa, Nez et al. 1995; Chittka, Ings et al. 2004). In the same way, I hypothesise that these the innate preferences of Trigona carbonaria might correspond to Australian flowers colours that are more profitable to bees. Thus, future studies may want to look for correlations between the amounts of nectar in Australian native flowers versus different colour categories to see if nectar content may have fine-tuned the colour preferences of Australian stingless bees. Interactions between Australian stingless bees and a food deceptive orchid In part 3, the results illustrated that bees preferred flowers with a UV signal than those without (fig. 12). The results are in agreement with the study by Peter and Johnson (2008) who removed the UV component of the flower by using sunscreen, which reduced the number of pollinator visits. In a similar way, the UV signal of C. carnea is likely to be important in attracting naive bees to the flower. The UV-signal aside, I found that bees also significantly preferred the white flower colour over the pink flower colour (fig. 13). This result is consistent with part 2 of my study where I found that Trigona carbonaria showed innate preferences for certain colours over others. This could potentially result in fitness differences for the orchid depending on the colour of its flower. Here, it is possible that negative frequency-dependent selection may be important, with pollinators visiting the rarer morph and, in so doing, help retain floral colour variation (Smithson and Macnair 1997). Fo r example, negative frequency-dependent selection was found to influence flower colour variation in Dactylorhiza sambucina (Gigord, Macnair et al. 2001), where the rarer morph was visited more often. In a similar way, it is possible that negative frequency-dependent selection might be occurring in my system, but more information would be needed on the frequency of the two colours under natural field conditions. My results also reveal that bees were able to habituate to flowers on the basis of colour (fig. 14). This result in similar to the study by Simonds and Plowright (2004), who found that bumblebees habituated to colour paper disks and patterns, with a reduction in the number of landings over time. In that particular study, it was suggested that fatigue may have been responsible for bees habituating to colour disks. Another possibility is that bees were learning to habituate to the presence of unrewarding flower decoys through associative learning. Such a possibility is consistent with work carried out on the response of wasps that are exploited as pollinators by sexually deceptive orchids (Wong and Schiestl 2002; Wong, Salzmann et al. 2004). In those studies, it was found that males quickly learn the presence of unrewarding flowers and avoided flowers and locations where they had previously been deceived. Intriguingly, I found an increase in the number of landings to a newly introduced flower if it was a colour that the bee innately preferred, thus countering the habituation effect towards unrewarding orchids. It seems reasonable, therefore, that the existence of multiple flower colours in C. carnea could have fitness consequences for the orchid by making it more difficult for their pollinators to associate a particular colour with non-rewarding flowers. In nature, the number of visits a reward less orchid receives by naive pollinators also depends on ecological factors such as flowering time along with availability of other rewarding plants. Further studies might therefore like to take such factors into account. It is also important to point out that this study only examined visual cues. In nature, pollinators may obtain and assess information about their environment from a variety of visual and olfactory cues (Kunze and Gumbert 2001). The question of which cue has the greater influe nce on pollinator decisions warrants further investigation, and provides interesting avenues for future research with food-deceptive orchids. It is possible that group learning behaviour may have occurred in the habituation experiments. For example, previous studies have shown that insects can learn through transfer of social information (Worden and Papaj 2005; Leadbeater and Chittka 2007). It has been shown that bumblebee workers, for instance, can learn by observing others (Worden and Papaj 2005). However, it was not possible to control for group learning behaviour, as bees tested in isolation did not respond at all in pilot studies. To try and minimise the effects of group learning, however, bees were used only once and were removed after each trial so that each replicate was independent. Furthermore, although I controlled for floral scent in my study by using glad wrap, it was not possible to control for floral shape. Bees, in this regard, can also have preferences based on shape (Dafni, Lehrer et al. 1997; Kunze and Gumbert 2001; Galizia, Kunze et al. 2005). The orchid flower sepals in my experiments varied subtlety in shape (e.g. width). However, to control for this, flowers were completely randomised with respect to shape. In addition, evidence suggest that subtle differences in shape may not actually be perceived by bees due to their low acuity spatial vision (Land 1997; Land 1999). However, it would be interesting to test for shape preferences in the future. Conclusion and Future Directions In part 1, I found that the discrimination thresholds of hymenopterans match up with the with Australian floral coloration and that bees appear to have been a major contributor to flower evolution in Australia. In part 2, I found that Trigona carbonaria has innate preferences for wavelengths of 422, 437 and 530 nm, which might correspond to Australian flowers colours that are more profitable to bees. In part 3, I found that bees were able to habituate orchids based on colours (consistent with the data obtained in part 2). However, evidence also suggest that variation in flower colour could be an important strategy by C. carnea orchids to counter the bees capacity to learn and avoid unrewarding flower decoys. This study has highlighted a number of areas in which future research can advance our understanding of the exploitation of bee colour vision by flowers. Most work, to date, has focused on bees and flowers from Europe and it is surprising that very few studies have looked at the i nteraction between Australia bees and flowers. My study underscores the importance of further work in the Australian context for what it might reveal about general ecological, biogeographic and evolutionary patterns of plant-pollinator relationships. Acknowledgements My supervisors, Adrian Dyer and Bob Wong. Adrian thank you for the endless support, patience, sharing your knowledge about the exciting field of colour vision science and expanding my thinking beyond intellectual boundaries. Bob thank you for your exceptional levels of guidance, feedback, time and encouragement. You both inspired me to explore this topic with great enthusiasm. The culmination of two experts in their field with the right skills enabled me to do so much in this year. I hope that you both team up to supervise many honours students as this project has opened so many doors to explore. Vera Simonov, for being my field and research assistant and talking to me about things other than research. Andreas Svensson, for help with the stats. Melanie Norgate, for all the advice and encouragement. The behavioural ecology lab group, all the ideas and suggestions were invaluable. James, Ken, Lenny, Nikki, Wendy and Marianne for reading my various thesis drafts. Mani Shrestha and Dick Thomson, for putting me touch with the orchid society. The Caladenia carnea flowers were kindly supplied by Richard Austin and Russell Mawson of the Australasian Native Orchid Society (Victorian Group). Tim Heard and the CSIRO, for supplying the bees. Paul Birch and Andrea Dennis, the gardeners at Maranoa gardens, for letting me take flower samples and providing verbal information about the flora of Maranoa gardens. My fellow honours students for the sharing of ideas, stress and all the laughs, especially Emma Jensson and Kat Rajchl. I hope we stay great friends. Alanna, Kirsten, Mez, Wendy and Vera, thank you for the motivation, support and organising outings to take my mind away from research. And finally to Mum, Dad, Lenny, Harry and Lucy- for taking care of me and understanding that honours is really a hermit year, but its been a great one! Once again, thank you to you all for making the year a great success!

The Causes And Implications Of Childhood Obesity - 873 Words

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The Washington Consensus And Related Structural Adjustment...

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Job Satisfaction, Organizational Commitment, And Job...

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The White Australia Policy, The Racist Country Its...

â€Å"Australia is not, and never has been, the racist country its academic historians have condemned† Critically analyse ‘the white Australia policy’ relating it to the quote provided In 1901, Edmund Barton the prime minster at time decided to introduce the Immigration Restriction Act left Australia banning prostitutes, criminals, and anyone under a contract or agreement to perform manual labour within Australia which seems that Edmund Barton was doing his job and kept Australia safe but he was not. This is because, he did not stop there, he introduced a dictation test to exclude certain people by making them sit a written exam that they need to pass to be welcome in Australia voted by an immigration officer and majority of the non-white people was given the answer no you are not welcome here. Many of prime ministers were involved in this as it ended in 1973. The quote â€Å"Australia is not, and never has been, the racist country its academic historians have been condemned â€Å"is most certainly incorrect between the years 1901 to 1973 as the majority of people were not allowed to enter Australia if they were non- white people. The reasons proving that Austral ia was indeed a racist country include the reasons why the white Australia policy was introduced, immigration and the way other countries saw Australia. The reasons why the white Australia policy was introduced is why Australia was awfully racist. Although numerous people were gratified to be Australians and thought it was aShow MoreRelatedOne Significant Change That Has Occurred in the World Between 1900 and 2005. Explain the Impact This Change Has Made on Our Lives and Why It Is an Important Change.163893 Words   |  656 Pagescolonies after 1870 as a predictable culmination of the long nineteenth century, which was ushered in by the industrial and political revolutions of the late 1700s. But at the same time, without serious attention to the processes and misguided policies that led to decades of agrarian and industrial depression from the late 1860s to the 1890s, as well as the social tensions and political rivalries that generated and were in turn fed by imperialist expansionism, one cannot begin to comprehend the

Building Organizational Capacity in Healthcare

Question: Discuss about the Building Organizational Capacity in Healthcare. Answer: Building Organizational Capacity in Healthcare The bureaucratic structure at the Sydney Community Hospital (SCH) is the greatest impediment towards the realization of specialized healthcare among the ever increasing number of patients in the community. The advantages of the system include establishment of particular task and roles within the departments aimed at providing positive health experience. The current structure of the hospital fails to accommodate efficiency and effectiveness regarding the flow of the information required in medical and health facilities. One of the disadvantages of this kind of management structure is that it does not facilitate the efficient and effective provision of quality health care services in the hospital (Casey, Payne, Eime, 2012). One important characteristic of the system is the availability of numerical management layers. The numerous layers of management make it tough for the effective and efficient decision-making. In a hospital setting, systems that allow quick flow and effective decisi on-making need to be integrated into the management structure (Davis et al., 2011). Bureaucratic form of management creates a chain of command through which the information flows. Each department works under the specific rules and guidelines from the top management. The top directors are involved in establishing policy, and they pass them to the managers for implementation (Edwards, Stickney, Milat, Campbell, Thackway, 2016). The traditional structure at the Sydney Community Hospital lacks the needed efficiency and flexibility regarding management and decision-making. Apparently, the current system requires multidisciplinary teams capable of performing quality, wide range of services. As dictated by the bureaucracy, each department in the hospital carried out a specific task. The population in the area has increased for the last five years. The government augments the budget of this facility to encourage the establishment of a structure that can accommodate specialized care. The fewer departments in the current structures fail to accommodate patients with special needs such as cancer patients. The population of the children in the community has increased. The current structure lacks well-established pediatrics departments to cater for the needs of the children in the area. Alternative Organizational Structure The mission of the new organization structure that needs to be put in place is to facilitate the provision of high-quality specialized care in partnership with the patients, healthcare professionals as well other stakeholders in the hospital. This can be achieved through establishing a new system that allows the needed flexibility and specialization regarding the provision of the quality care (Fuller et al., 2015). The current bureaucratic system needs to be abolished. The cross-functional team needs to be established across the organization. The organizational team will facilitate the improvement of the clinical outcome required in the Sydney Community Hospital (SCH) (Golenko, Pager, Holden, 2012). The cross-functional team will facilitate the removal or organizational or communication barriers that may exist between healthcare professionals (Hanney Gonzlez-Block, 2016). The traditional system didnt provide healthcare professionals with the mandate and responsibility of making maj or decisions. Everything had to follow a particular chain of command. In this new system, the cross-functional teams will have the responsibility of making the needed decisions to ensure the effective and efficient provision of specialized medical and healthcare services to the patient (Judd Keleher, 2013). The team will have the ability to priories what is needed within each functional department. Additionally, the teams will be composed of healthcare professionals and medical professionals with specialized training in each and every department(Stephens et al., 2017). For example, the cross-functional team in pediatric departments will be composed of pediatric doctors and nurses as well as managers in charge of the management of the health welfare of the children. In addition to that, the new supportive system of management constitutes a cross-functional team will facilitate the provision of the needed leadership at all levels of management for goals achievements and effective ser vices delivery. The diagram above shows the recommended health care structure for SCH. The new organization structure will facilitate the implementation and passing of the information among the healthcare professionals. The hospitals will establish a wing with four extra departments Oncology department- the department will be responsible for the provision of quality care to patients with different types of cancer (Fuller et al., 2015). The departments will be equipped with a cancer diagnosis and treatment equipment. Oncologist will be in charge of these departments Pediatrics Department These are departments will be in charge of all children related treatments Nursing home for senior citizens with chronic illness such as diabetes (Kong, Fang, Lou, 2017). Mental health department for patient with mental depression among others The key authority lines of authority The concept and analytic team- The team will be composed of the outcome analyst and data architects. The team will be responsible for implementation of the Electronic record keeping within SCH. The management of the data using Electronic Health Record system is the key to ensuring easy storage, retrieval and access of health records within the hospitals. Additionally, the team will be responsible for ensuring the free flow of the information in all the departments within the hospital (Wenke Mickan, 2016). The team will also be responsible for ensuring that only healthcare professionals who have access to that kind of opportunity access the sensitive data. The work group- the members include clinical staffs from different departments with the aim of executing a given clinical tasks that include hip surgery among others. The team will be composed of members who understand the patient's workflow (Webster, Thomas, Ong, Cutler, 2011). Additionally, they will be responsible for making decisions involving the appropriate medical interventions for patients suffering from sensitive illness such as cancer among others (Golenko, Pager, Holden, 2012). The team will also be involved in the analysis of the available data with the aim of identifying areas that need improvements. Clinical implementation team-The members of the team will be practicing clinicians who established and owns various types of clinical processes. The function of the team will involve evaluation of how medical processes are implemented and how they can be improved. In addition to that, the team will combine and recommend changes in their daily lives. In addition to that, the team will be responsible for outlining the workflow and what is expected of the teams. The support team will ensure that everything in the hospital operates effectively and efficiently. The processes and the protocol approved by the unit will be aimed at improving the specialized care provided to the patients. Guidance team-The mandate of this guidance team will be to monitor and evaluate the implementation of the protocols in the hospital. (Judd Keleher, 2013) The team will also provide guidance where appropriate to ensure effective and efficient utilization of quality care in the hospital. The members of the team will include specialist from different areas in the hospital. Senior Executive leadership team -The team will be involved in ensuring that the operations in the hospitals are carried out effectively (Green, Bell, Mays, 2017). They will be involved in evaluation and passing of the policy and processes in the hospitals. Members of the team will involve health administration experts who are experienced in hospital operations. The current bureaucratic system involved the following patterns or chain of command The limitation of these systems as mentioned in the first part makes it difficult to provide quality medical and healthcare services in the hospital. The decision must pass through a specific chain of command. This hinders effective and efficient quality services to the patients. Additionally, the older system does not accommodate the flexibility required regarding healthcare delivery in the hospital. The Advantage and the Limitation of the New Organization Structure The suggested organizational structure in part two above is an example of a supportive structure in which cross-functional teams are involved in the implementation of the procedures and processes within the organization. At any given organization, cross-functional teams carry out complex tasks that cannot be accomplished by a single entity (Green, Bell, Mays, 2017). The members of such team come from different departments with different skills. What makes cross-functional teams successful is the elements of diversified experience working together to complete a given task (Mills, Rosenberg, McInerney, 2014). In SCH the cross-functional teams as described above will facilitate the implementation of daily activities within the hospital. The teams will also ensure that quality and affordable care is provided to the patients in an effective and efficient manner. Each team will carry out specific roles and duties. The teams will also be involved in carry out major decision to provide hig hest quality care to the patients. The cross-functional team will facilitate the overcoming of the barriers hindering the provision of quality care in the hospital (Hanney Gonzlez-Block, 2016). Additionally, it will enable the transition from the bureaucratic system of organization. The cross-functional teams are important in healthcare because they allow provision of needed flexibility regarding decision making in the hospital. Limitation of the cross-functional team is that; they originate from different areas, it may take time for them to develop the needed chemistry. Proper association and interaction among employee are very crucial (Judd Keleher, 2013). It aids in the provision of quality services. Apparently, cross-functional teams may be faced with communication barriers as a result of different specialization (Chan, Bowers, Barton-Burke, 2017).. The interaction may also be hindered because of the lack of needed hierarchy. Doctors and nurses are required to work together as a team. This may affect the operation because the doctors may feel as if this is undermining the authorities they have over nurses. References Casey,M.M., Payne,W.R., Eime,R.M. (2012). Organisational readiness and capacity building strategies of sporting organisations to promote health.Sport Management Review,15(1), 109-124. doi:10.1016/j.smr.2011.01.001 Chan,R.J., Bowers,A., Barton-Burke,M. (2017). Organizational strategies for building capacity in evidence-based oncology nursing practice.Nursing Clinics of North America,52(1), 149-158. doi:10.1016/j.cnur.2016.10.001 Davis,E., Williamson,L., Mackinnon,A., Cook,K., Waters,E., Herrman,H., Marshall,B. (2011). Building the capacity of family day care educators to promote children's social and emotional wellbeing: an exploratory cluster randomised controlled trial.BMC Public Health,11(1). doi:10.1186/1471-2458-11-842 Edwards,B., Stickney,B., Milat,A., Campbell,D., Thackway,S. (2016). Building research and evaluation capacity in population health: the NSW Health approach.Health Promotion Journal of Australia,27(3), 264. doi:10.1071/he16045 Fuller,J., Koehne,K., Verrall,C.C., Szabo,N., Bollen,C., Parker,S. (2015). Building chronic disease management capacity in General Practice: The South Australian GP Plus Practice Nurse Initiative.Collegian,22(2), 191-197. doi:10.1016/j.colegn.2014.02.002 Golenko,X., Pager,S., Holden,L. (2012). A thematic analysis of the role of the organisation in building allied health research capacity: a senior managers perspective.BMC Health Services Research,12(1). doi:10.1186/1472-6963-12-276 Green,S.A., Bell,D., Mays,N. (2017). Identification of factors that support successful implementation of care bundles in the acute medical setting: a qualitative study.BMC Health Services Research,17(1). doi:10.1186/s12913-017-2070-1 Hanney,S.R., Gonzlez-Block,M.A. (2016). Building health research systems: WHO is generating global perspectives, and whos celebrating national successes?Health Research Policy and Systems,14(1). doi:10.1186/s12961-016-0160-x Judd,J., Keleher,H. (2013). Building health promotion capacity in a primary health care workforce in the Northern Territory: some lessons from practice.Health Promotion Journal of Australia,24(3), 163. doi:10.1071/he13082 Kong,S., Fang,C.M., Lou,V.W. (2017). Organizational capacities for residential care homes for the elderly to provide culturally appropriate end-of-life care for Chinese elders and their families.Journal of Aging Studies,40, 1-7. doi:10.1016/j.jaging.2016.12.001 Mills,J., Rosenberg,J.P., McInerney,F. (2014). Building community capacity for end of life: an investigation of community capacity and its implications for health-promoting palliative care in the Australian Capital Territory.Critical Public Health,25(2), 218-230. doi:10.1080/09581596.2014.945396 Organisational Capacity Building in Health Systems. (2012). doi:10.4324/9780203097823 Stephens,T., De Silva,A.P., Beane,A., Welch,J., Sigera,C., De Alwis,S., Haniffa,R. (2017). capacity building for critical care training delivery: development and evaluation of the network for improving critical care skills training (nicst) programme in Sri Lanka.Intensive and Critical Care Nursing,39, 28-36. doi:10.1016/j.iccn.2016.08.008

Gothic horror novel Essay Example For Students

Gothic horror novel Essay Frankenstein is a gothic horror novel written by Mary Shelley. The novel is about death, love, ambition and prejudice. When Mary Shelley wrote Frankenstein in the 19th century she was only 18 years old. The novel came to be written because of a challenge set by Marys liturgy friends, Lord Byron and Percy Shelley. The challenge was to write the most frightening ghost story of all time. Mary Shelley revealed later on that the novel had come from a dream she had. Mary Shelleys life influenced her novel greatly. For example, her mother died shortly after giving birth to Mary and as we can see she incorporates this idea into this novel. Furthermore this novel incorporates the theory of Luigi Galvani who believed that he had discovered electricity in human limbs.  This novel is about a doctor by the name of Victor Frankenstein who is obsessed at the possibility of creating an artificial life. The monster created from discarded human limbs is later rejected for its ugliness and inhumanity. The creature, unwanted, untutored in normal human behaviour and finally driven away by rejection to a murderous revenge on Frankenstein and his family. With this happening to the monster throughout the novel, Mary Shelley created the affect on us the reader of sympathy and concern towards the monster. By examining this novel, I will try to uncover how Mary Shelley makes us, the reader, sympathise with the monster. Firstly I will look at the relationship between the monster and Victor and how that makes us sympathetic towards the creature. When Victor comes across the monster for the first time he describes the monster with the words its unearthly ugliness rendered it almost too horrible for human eyes, this instantly shows the reader that there is a lack of sympathy towards the monster. Whats more the use of unearthly is stating that the monster is unnatural, absurd and meaningless. Mary Shelley carefully chose words with evil connotations to emphasise Victors hatred, such as Victors name calling of the monster, devil, daemon and vile insect all emphasise Victors hatred towards the creature. If Mary Shelley portrayed Victor in a different light and for him to act frightened, anxious and nervous when talking to the monster then that would probably make us take pity on Victor because he is afraid of his creation. However because Mary Shelley portrays Victors reaction to the monster to be completely the opposite of being scared, the reader feels they have to sympathise with the monster as it is Victor who is acting like the monster. In one example of analysis, Mary Shelley uses the metaphor of Adam and Eve to develop our sympathy with the monster. She has the monster say to Victor, on the sea of ice, Remember I am thy creature; I ought to be thy Adam, but I am rather the fallen angel, whom thou drivest from joy for no misdeed. Here the monster is stating that Victor needs to take responsibility for what he has created. Victor is supposed to be playing God, however God stood by his creations whereas Victor has just abandoned his. The monster wants to shame Victor into taking responsibility for the lives that were lost. Hence, Shelley is stating that the monster has been abandoned by Victor which increases our sympathy towards the monster. Mary Shelley creates a contrast between Victor and the monster whilst they speak for the first time. These two reactions are completely the opposite. Whilst Victor has feelings of bitter anguish, and he somewhat loathes the monster as he describes the monster with words such as wretched devil, daemon. Here Mary Shelley chose words with evil connotations to emphasise Victors detestation of the monster. This increases our sympathy towards the monster as the name calling from Victor is proving that his emotions appear more like the monsters. .u0cc926d9e15843bd2f409370d491f589 , .u0cc926d9e15843bd2f409370d491f589 .postImageUrl , .u0cc926d9e15843bd2f409370d491f589 .centered-text-area { min-height: 80px; position: relative; } .u0cc926d9e15843bd2f409370d491f589 , .u0cc926d9e15843bd2f409370d491f589:hover , .u0cc926d9e15843bd2f409370d491f589:visited , .u0cc926d9e15843bd2f409370d491f589:active { border:0!important; } .u0cc926d9e15843bd2f409370d491f589 .clearfix:after { content: ""; display: table; clear: both; } .u0cc926d9e15843bd2f409370d491f589 { display: block; transition: background-color 250ms; webkit-transition: background-color 250ms; width: 100%; opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #95A5A6; } .u0cc926d9e15843bd2f409370d491f589:active , .u0cc926d9e15843bd2f409370d491f589:hover { opacity: 1; transition: opacity 250ms; webkit-transition: opacity 250ms; background-color: #2C3E50; } .u0cc926d9e15843bd2f409370d491f589 .centered-text-area { width: 100%; position: relative ; } .u0cc926d9e15843bd2f409370d491f589 .ctaText { border-bottom: 0 solid #fff; color: #2980B9; font-size: 16px; font-weight: bold; margin: 0; padding: 0; text-decoration: underline; } .u0cc926d9e15843bd2f409370d491f589 .postTitle { color: #FFFFFF; font-size: 16px; font-weight: 600; margin: 0; padding: 0; width: 100%; } .u0cc926d9e15843bd2f409370d491f589 .ctaButton { background-color: #7F8C8D!important; color: #2980B9; border: none; border-radius: 3px; box-shadow: none; font-size: 14px; font-weight: bold; line-height: 26px; moz-border-radius: 3px; text-align: center; text-decoration: none; text-shadow: none; width: 80px; min-height: 80px; background: url(https://artscolumbia.org/wp-content/plugins/intelly-related-posts/assets/images/simple-arrow.png)no-repeat; position: absolute; right: 0; top: 0; } .u0cc926d9e15843bd2f409370d491f589:hover .ctaButton { background-color: #34495E!important; } .u0cc926d9e15843bd2f409370d491f589 .centered-text { display: table; height: 80px; padding-left : 18px; top: 0; } .u0cc926d9e15843bd2f409370d491f589 .u0cc926d9e15843bd2f409370d491f589-content { display: table-cell; margin: 0; padding: 0; padding-right: 108px; position: relative; vertical-align: middle; width: 100%; } .u0cc926d9e15843bd2f409370d491f589:after { content: ""; display: block; clear: both; } READ: Dickens presents the characters of Gradgrind EssayWhereas the monsters reaction towards Victor is completely different as the monster is calm and collective and he expected the reaction he got off Victor as his first words to Victor were I expected this reaction. This shows that the monster is intellectual as he was aware of the reaction he received from Victor. In addition to that whilst the monster is talking to Victor on the sea of ice the monster appears to be reflective and sad from the time when he says You purpose to kill me up until Do your duty towards me these words that Mary Shelley wrote increases our sympathy towards the monster because these words spoken by t he monster verify the fact that it is Victor who is acting as the monster. Mary Shelley includes the theme of nature/nurture into her novel to increase our sympathy with the monster because by nature he is naturally a sensitive, composed creature underneath his deceptive manner. Although he strives to portray himself as a well-mannered being, the evil side in him seeks to overcome this.  However as the monster hasnt been nurtured by Victor he doesnt realise the extent of his behaviour. If Victor stood by his creation and taught him right from wrong then he would know good from evil. On the other hand because Victor neglected him hes resentful of Victor and seeks to gain revenge which eventually leads to the murder of one of Victors family. Mary Shelleys intention with the affect of nature/nurture is that nature is instinctive and needs to be nurtured to bring out the better alternatives.  I feel as if I have learnt a lot from the novel Frankenstein because I think that people shouldnt act in the way in which Victor did because everybody should be treated the same no matter what they look like. Also if people get treated badly like in the way in which the monster did we dont actually realise how it will affect them.  Mary Shelley intended to make Victor look like the real monster and Shelley achieves this by making Victors emotions get the better of him. In addition to that Shelley also intended us, the reader to sympathise with the monster; she achieves this by portraying Victor as the monster and makes him treat the monster inadequately.