Evolution of Australian Flora: Hymenopteran Visual Systems

Evolution of Australian Flora: Hymenopteran Visual Systems 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 a nd 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 object’s 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, Nà ºÃƒ ±ez 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 (Jersà ¡kovà ¡, 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) (Jersà ¡kovà ¡, 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; Jersà ¡kovà ¡, Johnson et al. 2006). The common occurrence of food deception in orchids suggests that this form of pollinat ion by deception is an extremely 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; Aragà ³n 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 vari able 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 (Tovà ©e 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 insect’s 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 insect’s 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 avera ge reflectance from 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. Experimen ts were 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-ÃŽ ¼l 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 t o associate 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, Nà ºÃƒ ±ez 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 were 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 Nà ºÃƒ ±ez 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, Nà ºÃƒ ±ez 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 (ÃŽ ±=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 P≠¤0.05. 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 in ¬Ã¢â‚¬Å¡uence 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  ¬Ã‚ rst contact made by a bee with the Glad WrapTM within a distance of 4 cm, was recorded as a choice of that  ¬Ã¢â‚¬Å¡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 ma rks. In addition, individual flowers 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 re ¬Ã¢â‚¬Å¡ectance 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 Δ ÃŽ »/ÃŽ » 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

Dealing with culture Essay

It has already been mentioned earlier that for effective intelligence work there must be an ability to understand other people’s culture especially that of the enemy. But there is also another type of culture that must be addressed and understood – it is the culture that exists within the US intelligence community. It must be made clear though that no organization or community does not develop values or norms overnight. This only means that any initiator for change must be ready for the long haul because it will not away that easily. There is always organizational culture, it helps define the group and guides its members on the proper course of action. According to Amy Zegart the culture that exists within the intelligence community can be described as parochialism, risk aversion, resistance to change, and that â€Å"need to know trumps need to share† (2007, p. 64). All of these need to be transformed in order to have a much improved intelligence community. Coordination The 9/11 fiasco as seen in the nine-one-one report clearly calls for better coordination among the different counter-terror agencies of the US government. This realization leads to the recommendation that for America to be safer there is a great need for more coordination among the said groups. But as many have known this is easier said than done. According to Zegart the CIA from the onset was not really given the power to coordinate all government agencies related to intelligence gathering and as a result: The existence of so many separate agencies and the absence of formal mechanisms to integrate them became reinforced by bureaucratic procedures over time. Throughout the Cold War, different intelligence agencies developed their own budgets and set their own priorities, hired their own staffs and trained them in separate programs, communicated by separate e-mail systems and kept intelligence in incompatible databases (2007, p. 66). Jurisdiction is one of the major stumbling blocks in solving a crime or gathering data. When this term comes up immediately more barriers will shoot up immediately preventing the agency with a significant lead to pursue even further. Now, there is a good explanation for jurisdiction and it is the need for order, focus, and responsibility. But most of the time it only serves one thing and it is to be sure who to blame when there is a failure in the system. One of the painful realizations in 9/11 is the fact that terrorists do not respect jurisdiction, they come and go as they please and successfully exploited the civil liberties offered to individuals living in this country. So a member of a terror group can be living in Asia for one year and then at the end of that period decides to fly to Los Angeles and then from there move around the country in preparation for a major attack. Who then is in charge to track this guy? Sharing of Information Aside from the lack of coordination, another related problem is the strong dislike for information sharing. And again this is understandable; each group is rewarded for their effort. If one has caught a huge quantity of fish by being up all night on a fishing expedition there is no logic to sharing it with others who did not put up the same effort. On the other hand there are cases wherein the failure of one agency is the failure of all. Take for instance 9/11, there is no use shifting blame or pointing fingers at the CIA because the destruction is close to the heart of America where everyone is affected. This leads to the argument that information should not be the standard-operating-procedure but there are cases where information sharing is a must. And one way of doing this is by classifying cases, finding out which one requires the collaboration of those working internationally, on the national level or local level. Improvements The preceding pages clearly demonstrated that there is a need for positive change in the US Intelligence community. If civilians and those who are from the outside looking in can provide key observations on areas that needed change then those who are working within the intelligence community are painfully aware of their shortcomings. The following pages will describe the improvements made by various counter-terror groups within the fold of the Federal Government. Need to Share Information One of the areas that requires overhaul is with regards to information sharing. This has not been lost to the analysts and strategists working under the U. S. Department of Homeland Security and its think tank the Homeland Security Advisory Council who proposed the Intelligence and Information Sharing Initiative: Homeland Security Intelligence and Information Fusion. The key term here is fusion and this program calls for the: †¦ managing of flow of information and intelligence across levels and sectors of government and the private sector to support the rapid identification of emerging terrorism-related threats and other circumstances requiring intervention by government and private-sector authorities. It is more than the one-time collection of law enforcement and/or terrorism-related intelligence information and it goes beyond establishing an intelligence center or creating a computer network (see Homeland Security Advisory Council). This relatively recent move by the DHS is not only audacious but shows how they have completely acknowledged the error of their ways. There is no single or central agency that can do all the work when it comes to apprehending terrorists. The lowly policeman may not be wearing fancy suits and may not even pull top dollar from his work but a police officer does the dirty work. The operatives of counter-terror groups may have the firepower and the resources apprehend a terror group but they can be far away; it will take them precious time to leave their offices in and pursue. Whereas the local police department is in close proximity to the terrorist cell and therefore there is no reason why they could not be dispatched to stop the said terror group from executing their plans. To get a better idea with regards to how serious DHS is in improving their capabilities, the anti-terror agency is not only acknowledging the need for sharing information and intelligence but they are also admitting that crucial data can come from anywhere. The DHS pointed out the sources of relevant information to be coming from: a) Federal; b) State; c) local; d) tribal; e) various government entities; f) General public; and g) Private-sector entities. Therefore, there is a great need to improve on the process of information analysis and information dissemination. The following steps are designed to jump-start the said process (see Homeland Security Advisory Council): †¢ The use of common terminology, definitions, and lexicon by all stakeholders; †¢ Identifying critical information repositories and establishing the process, protocols, procedures, and technical capabilities to extract information and/or intelligence from those repositories; †¢ Understanding and elimination of impediments to information collection and sharing (i. e. , it should be a priority for the Federal Government to provide State, local, and tribal entities unclassified terrorism-related information); †¢ Extensive and continuous interaction with the private sector and with the public at large. The FBI It was mentioned earlier that in the decades of the 70s and 80s the Federal Bureau of Investigation was forced to mellow down its tough investigative stance. The lack of aggressiveness was criticized in the aftermath of 9/11. Today new laws are giving new life to the FBI invigorating the said agency to pursue suspected terrorists. Aside from the new mandate – following 9/11 – that allow the FBI to step on the accelerator the President of the United States issued a new directive in 2005 that would forever transform the FBI. On June 28, 2005 the President directed the FBI to create the National Security Branch within the FBI that will result in, â€Å"Integrating investigative and intelligence activities against current and emerging national security threats†¦Ã¢â‚¬  (see National Security Branch Overview, 2006). This new mandate from the President allows for the creation of the following: a) the FBI’s Counterterrorism Division (CTD); b) the Counterintelligence Division (CD); c) the Directorate of Intelligence (DI); and d) the Weapons of Mass Destruction Directorate (WMDD). This simply means that the FBI is no longer typecast as the main investigative body of Federal government it now also functions as counterintelligence and counterterrorism arm of the government as well as the main agency that will handle weapons of mass destruction in the domestic sphere. Conclusion The United States of America, its leaders and its citizens must come to terms with its new found status. And it is the sole superpower in the global arena. There is nothing that comes close to the US in terms of economic and military might. This is good news for those who come to enjoy the protection of a superpower – a protector who believes in democracy and the rule of law. But this is not a welcome thought for American citizens who are now perceived as enemies by those who have a sick worldview such as extremists. These fanatics are frighteningly angry at the US and their blabbering and crazed invectives show that they may not be coherent at times but are dead serious in causing harm. The US Army is capable pulverizing a small country into smithereens and even able to bring a powerful enemy nation to its knees e. g. Iraq but it does not have the moral authority to simply barge in and decimate suspected enemies. The Federal Government is therefore dependent on an effective and efficient intelligence gathering arm. It has been shown earlier that it is no longer possible to rely on one single agency to combat terrorism and therefore what is needed is coordination and information sharing. One of the major issues that was resolved was in dealing with a prevailing culture of fragmentation, parochialism, and the insistence of need to know versus sharing of information. After 9/11 it is easy to consider changing negative attitudes and adopting a new view on coordination and information sharing. Thus, after 9/11 the U. S. Department of Homeland Security was tasked to break down barriers as it has become painfully clear that the lack of coordination was the simple explanation as to why suspected terrorists were able to undergo flight training under the noses of Federal officials. Concrete steps are made to ensure information dissemination as well as the creation of structures and human resources that will be able to analyze data coming from different parts of the world. Aside from these the U. S. Intelligence community acknowledged the fact that everyone is involved including the State, local and even tribal entities. The big wigs from the Federal Government are also acknowledging the importance of local law enforcement agencies as a deterrent as well as the most effective and efficient aspect of the whole counter-terrorism apparatus of the US. A welcome development was the strengthening of the capabilities of the CIA and the FBI. Special mention is appropriate for the President’s directive to vastly improve the ability of the FBI not only as an investigative arm of the Federal Government but also as a counter-intelligence as well as counter-terrorism agency especially when it comes to weapons of mass destruction that could be potentially deployed in the homeland. All of these changes and improvements combined will greatly deter terrorist activity and would help in the speedy arrest as well as dismantling of terror cells before these groups can wreak havoc in the same magnitude as September 11, another day that will also live in infamy. References Carafano, J. & M. Sauter (2005). Homeland Security. New York: McGraw-Hill. Federal Bureau of Investigation. (2006). National Security Branch Overview. Retrieved 07 February 2008 from http://www. fbi. gov/hq/nsb/whitepaper12-06/whitepaper. pdf. Ganor, B. (2005). The Counter-Terrorism Puzzle: A Guide For Decision Makers. New Jersey: Transaction Publishers. Hulnick, A. (2004). Keeping Us Safe: Secret Intelligence and Homeland Security. Westport, CT: Praeger Publishers. Paine, T. (2005). Homeland Security: The American Tradition. In M. Sauter & J. J. Carafano (Eds. ). Homeland Security. New York: The McGraw-Hill Companies, Inc. Perl. R. (2007). Terrorism and National Security: Issues and Trends. In A. L. Fitzgerald (Ed. ). Terrorism and National Security. New York: Nova Science Publishers, Inc. Posner, R. (2006). Uncertain Shield: The U. S. Intelligence System in the Throes of Reform. Maryland: Rowman & Littlefield Publishers, Inc. Sands, A. (2005). Integrating Open Sources into Transnational Threat Assessments. In J. E. Sims & B. Gerber (Eds. ). Transforming U. S. Intelligence. Washington, D. C. : Georgetown University Press. Sims, J. & B. Gerber. (2005). Transforming U. S. Intelligence. Washington, D. C. : Georgetown University Press. The 9/11 Commission Report. Retrieved 08 February 2008 from http://www. 911commission. gov/report/911Report. pdf. Turner, M. (2005). Why Secret Intelligence Fails. Dulles, Virginia: Potomac Books, Inc. U. S. Department of Homeland Security. (2005). Intelligence and Information Sharing Initiative: Homeland Security Intelligence & Information Fusion. Retrieved 07 February 2008 from http://www. dhs. gov/xlibrary/assets/HSAC_HSIntelInfoFusion_Apr05. pdf . Warner, M. & J. K. McDonald. (2005). US Intelligence Community Reform Studies Since 1947. Washington, D. C. : Center for the Study of Intelligence. Zegart, A. (2007). Spying Blind: The CIA, the FBI, and the Origins of 9/11. New Jersey: Princeton University Press.

Return on Investment MBA Education Funding Essay

As change happens, we can take the fact that Masters of Business Administration degree is still a constant to embrace. In between the complex setting, a modern manager must still do what managers in every past era had to do in order to become successful. Recently, the once-lonely voices of demur have advanced into choruses of recrimination when the practical value of an MBA degree is in question. They say that MBA curricula are inaccessible with the real world desires, claiming that the degree is over-hyped and many programs have a culture which turns a blind eye to deceit. If businesses follow the naysayers’ advice, $100,000 tuition fee or the crucial decision to pay huge bucks to hire an MBA might start to look like less of a sound investment (CBS MoneyWatch, 2007). My decision to obtaining an MBA is not only personal, but also professional. The pursuit of an MBA degree is surrounded by many negative connotations. Questions arise regarding whether or not the pursuit will increase the Pay range of a person with an MBA versus a person without an MBA. Simmering and Wilcox identified 5 factors that largely affect the decision to pursue an MBA graduate degree. The five factors centre around the career exploration opportunities, personal prestige associated with the MBA, goals for improving and developing interpersonal skills, increasing career mobility and entrepreneurial aspirations. The Graduate Management Admission Council survey carried out by Simmering and Wilcox, discovered that that the MBA Class of 2012 had 69% into mid-level jobs, with 21% taking entry-level positions, 8% taking senior-level spots, and 1% taking the executive positions. This is considerably worse when compared to last year, where only 17 percent of the class went to entry- level spots, while 14 percent of the total went into senior-level jobs, and only 3 percent accounted the executive position (Lavelle,  2013).Housing market crash will impact on the value and positions or jobs that an individual with an MBA graduate degree will get. For instance, since 2007, the economy has played a huge part in not only downturn and fluctuations, but also landing jobs. In MBA class of 2011, the average full time salary for MBAs that were employed was $79806, a year over a year decrease of 5.4% or $4,533, not including the inflation (Brewer & Brewer, 2012). The Graduate Management Admission Council survey also calculated the return on investment and considered it ‘Stellar’. The alumni recouped a third of their B school investment within a year of graduation, 100% 4 years out, doubling the monetary value after 10 good years. On statistics, if a person obtains an MBA is not a full guarantee to getting an executive level spot after graduating. It is more of investing that has the highest probability of paying off over time. The survey as it pertains to the return on investment is simply looking at the B schools, which solely would imply the A schools return on investments is speedier and higher. Therefore, it might not be the actual degree rather the school that a person obtains his or her MBA degree which will impact on his or her potential income. For instance, I can refer to my cousin as a good example of the impact of obtaining an MBA. She studied at Princeton University for her master’s degree and after her graduat ion it took her 3 years to get employed. She found that because she was younger and the degree program which she chose, was actually intimidating to older managements. She also encountered remarks of her being â€Å"too qualified† for all jobs. It became so frustrating for her. Similarly, so many people reason that an ‘A school’ master’s degree means an automatic employment with high salaries, which is not usually the case. My investment decision will be based on the returns I get. The payback period for my accounting occupation will for instance be; payback period is obviously between 3 and 4 years as the identical initial outlay is $110,000 which is between $90,000 and $170,000. For exact period, Payback period for my desired occupation = 3years + ($110,000 – $90,000) / $79,806 = 3 years + $20,000/$50,000 = 3 years and 4.8 months. The NPV for my accounting occupational will be; Net Present Value @ 12%; Years 1 2 3 4 Net Cash flow (NCF) $000 20 30 40 50 Cost of Capital @ 12% 0.893 0.797 0.712 0.636 Present Value $000 17.86 23.91 28.48 31.8 5 70 0.567 39.69 141, 74. Net Present Value = $141,740 – $110,000 = $31,740. The IRR for my accounting occupational will be; Internal rate of return = positive rate + (positive NPV / (positive NPV + negative NPV)) x range of rates = 20% + ($2,880 / ($2,880 + $10,860)) x (25% – 20%) = 20% + ($2,880 / $13,740) x 5% = 20% + (0.21 x 5) = 20% + 1.05 = 21.05% Internal rate of return for my desired occupation= 21.05% and is a good one since it is greater than cost of capital. A main factor that most objectionable to an MBA is the monetary cost of obtaining the degree. Tuition fee can range from $30000 to $ 50000 per annum. Other expenses raises the cost to about $85,000 yearly, implying the cost of about $170000 in two years. Although the cost for an MBA may be quite high, according to a statistics by the Graduate Management Admission Council, the average package for an MBA in the last ten years was $110000, which is up from the average of $87,000 in 2007. The average salary of graduates with a Bachelor’s degree in 2011 was $48351. The difference between an MBA and Bachelor’s is an increase of 195% or $45649. The ‘return on investment’ is 171.7 %, using the cost of $170000 from and the average increase of salary over a bachelor’s degree for a ten year period (Lavelle,  2013). Different people have varying reasons as per MBA value, when it is about obtaining it. The reason I have for obtaining an MBA is personal and is something that I have always wanted in my life. It may not be of benefit to me in my current job in terms of earnings potential income, but I believe it will make me more marketable if I decide to change careers or companies. Many statics show a path of MBA negativity from a viewpoint of new graduates without careers versus those with careers, those with who are employed and are from the a-schools versus the b-schools. I believe MBA is of more benefit to those individuals who have a career and are looking for new career change or looking to moving up in their own personal companies. If a person is feeling stagnant in his or her career, then getting an MBA will be the excellent way to take himself or herself to the next level. For most people an MBA will open up more new opportunities, whether it is a career that will makes more sense for your life and skills or a career that will promote you to a better position within your company. The act of getting an MBA shows that you are serious about your potential to succeed and other people are most likely see you in a higher regard because of undertaking such an action. For most people, MBA continue to be the building block of ultimate success. References Brewer, Kristen L.; Brewer Peggy D. (2012). Influencing variables and perceptions regarding MBA degree programs. Academy of Educational Leadership Journal. Retrieved from EBSCOhost. CBS Money Watch. (2007).Five hard truths about the MBA. Retrieved from http://www.cbsnews.com/8301-505125_162-51170538/five-hard-truths-about-the-mba/ Lavelle, L.  (2013).  Bloomberg business week: the MBA’s value? Debatable.  Retrieved fromhttp://www.businessweek.com/bschools/blogs/mba_admissions/archives/2014/11/the_mbas_value_debatable.html Source document

The Art Of Paintings - 978 Words

The goal of my creative project was to create various splatter paint works that each represented a key human emotion. I settled on just three and I chose joy, anxiousness, and depression. I bought three 8 by 10 inches blank canvases to do my work on, paint, and an assortment of brushes. Before I started I looked up a video on different splatter paint techniques, and I became interested in adding some texture to my artwork, so the first painting I worked on, representing joy, I added some saltwater to it and actual grains of salt. I really wanted this artwork to stand out from the other two, because of how different this emotion is. The canvas has a yellow background, because I wanted all the bright colors I used to really pop on the†¦show more content†¦I knew this activity would be messy, but I did enjoy it and I learned that you really can’t go wrong with a splatter painting. No matter what you do, it is going to be interesting in way, because no one has done someth ing like it before. I really enjoyed splatter painting, it was an enjoyable way of just showing my creativity and letting my mind flow. I think it would be even better to do this with a friend rather than just by yourself, and next time I will mix other paint colors to create more interesting colors. The creation showed me that I’m capable of doing at least one thing that is artistic, before I would say that I couldn’t even draw a straight line correctly. These three artworks are important to me, because I have never created art that I am proud of, this is the first time that has ever happened. I am satisfied with my result, I expressed everything in the way I imagines it. I’m not sure that people could just as readily recognize what emotions each canvas represents, but that doesn’t bother me, I’d rather just get some type of reaction out of them than nothing. 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