Algae Interaction

Table of Contents Introduction Method Results Discussion Conclusion References Introduction Biological interactions can be defined as the effects an organism has on the others in a common ecosystem. Basically, no organism can survive as an ‘island’ lest it ceases to exist. Biological interactions are vital for the normal functioning of an ecosystem. As such, this leads us to identifying the kind of interactions that may exist.Advertising We will write a custom essay sample on Algae Interaction specifically for you for only $16.05 $11/page Learn More These relations may happen within organisms of the same species (intra-specific) or otherwise (inter-specific). These interactions may happen at a specific stage of development or; during the entire life of an organism (e.g. endosymbiosis) and, may be detrimental (herbivory, predation, cannibalism) or beneficial (mutualism). Significantly, these relations may be direct or indirect. The degree of interactions ranges â€Å"from mutual benefit through neutral to mutual harmful interactions† (Begon, Harper and Townsend, 1996). As such, the interactions can be categorized into six classes depending on gravity of harm or benefit to the interacting individuals in a niche. As a result, individuals may be deemed to be in neutralism interaction where neither party benefits nor harms the other though difficult to ascertain or, may engage in amensalism where products of the other are toxic to the other. Also, individuals can also engage in commensalism where one individual benefits from the interaction without affecting the other. Moreover, individuals may compete for a common resource as exhibited in parasitic relation that is fetal to the involving parties or otherwise, involve in mutualism as exhibited in some symbiotic relations where both parties benefit. Finally, the organism may interact antagonistically either by predation or parasitism owing to the fact that an indi vidual profits at the expense of the counterpart. In terms of graphical relationship between species density against time, a neutral interaction ought to exhibit an upward trend for both species. However, for competing individuals, the opposite should be true. Two individuals exhibiting amensalism interactions ought to display opposite trends; upward for one species and the opposite for the other. For mutualism just like neutralism, it results in a higher carrying capacity hence; an upward trend for both individuals is expected (Stachowicz, 2001). As regards this experiment, showing the interaction between green algae (Chlorophyta) – Closterium and Micrasterias species, both species utilize sunlight with the help of chlorophyll for photosynthesis. As such, in a common ecosystem, we anticipate competition for the limiting resources e.g. water and mineral salts (Fedriani, Fuller, Sauvajot and York, 2000).Advertising Looking for essay on biology? Let's see if we can help yo u! Get your first paper with 15% OFF Learn More Consequently, this leads us to our null hypothesis (Ho): there is no competition between Closterium and Micrasterias species. The alternative hypothesis (H1) contradicts HO by suggesting that there exists a competition between the species. This is tested using a two-sample t-test at 95% C.I to ascertain the findings. Method In this experiment, colonies of Closterium species were cultured in four different regions in a Petri dish (using a tip of 100 microliters). The same was done for Micrasterias species but in a different Petri dish. In one dish a fifth colony but containing the two species were cultured. The essence, was to determine the species densities (density = (average number per colony)/100) vital in obtaining the same number of individuals as a starting point in stock culture. For the stock culture, average densities different species plus that of the mixed culture were recorded once per week over a period of 4 weeks . The results were then recorded for analysis. Results Table 1: of number of individuals per Ml of Samples (to the nearest 10). Number of individuals per Ml of Samples (to the nearest 10) Day Closterium Alone Micrasterias Alone Closterium in Mix Micrasterias in Mix 0 10 10 10 10 1 3 6 1 1 2 11 0 1 0 3 10 1 5 0 4 9 2 10 1 Graph 1: of the density of Closterium species alone vs. time. Graph 2: of the density of Micrasterias species alone vs. time.Advertising We will write a custom essay sample on Algae Interaction specifically for you for only $16.05 $11/page Learn More Graph 3: of the density of Closterium and Micrasterias species in mix culture vs. time. Hypothesis testing: Is there a possibility that there exists a competition between Closterium species and Micrasterias species residing in a common niche? Null hypothesis (Ho):  µClosterium =  µMicrasterias Alternative hypothesis (H1):  µClosterium ≠   µMicrasteriasAdver tising Looking for essay on biology? Let's see if we can help you! Get your first paper with 15% OFF Learn More At 95% confidence interval t0.05 = 1.96 Calculated value of t is 0.7638 i.e. t = (á ºâ€¹1-á ºâ€¹2)/s [(n1*n2)/ (n1+n2)] ^0.5 Where; s = 6.21, n1 = 5, n2 = 5, á ºâ€¹1= 5.4 and á ºâ€¹2 = 2.4 We therefore reject the null hypothesis since the two species are not equal thus; there exists a competition between the two species residing in a common niche. Discussion The objective of this experiment was to test the null hypothesis (Ho): there exists no competition between the algae species – Closterium and Micrasterias. As per the data collected and the test analysis done, the null hypothesis (0.7638 ≠¤ 1.96) fell within the rejection region at 95% confidence interval hence we reject the null hypothesis and state that there exists a competition between the colonies in a niche. As exhibited by the graph 3 above, the trends underscore the fact that in deed there is competition. On competing interactions, the aftermath is always detrimental to both species hence the downward tre nd of the curves. As such, the principle of competitive exclusion takes its effect hence the competing species will either adapt or die. This can be seen at the height of competition when some of the common but limited resources are exhausted. As for the species above, Micrasterias species can not compete favorably hence they die after the second and third week. On the contrary, Closterium species adapt promptly (Stachowicz, 2001). By the fourth week, both species density increase significantly courtesy of natural selection. This otherwise niche partitioning is important in eliminating the inter-specific competition that exists between the species within a limited niche. As a result, the species share resources and thrive once again portraying non-existence of competition before. This blurs the line separating two competing and two non competing species thus one cannot easily prove or disapprove. Significantly, the population blossoms after the third week owing to the fact that intr a-specific competition exceeds inter-specific completion hence favoring coexistence between the species. For the individual species as portrayed by graphs 1 and 2 above, it can be seen that Closterium species adapts to the media promptly than Micrasteria species. But, before peaking in population density, both species lose count since they need time to adapt to the new ecosystem (Charles, Nunn, Ezenwa, and Walter, 2011). Conclusion In a conclusion, the experimental results agreed with the theoretical background which supports the facts stated herein the experiment. As such, there exists a competition between Closterium and Micrasterias species in a common niche. This topic can be better understood if you comprehend how relating organisms feed, the type of products they expel and how they affect the other organism. I would suggest that future experiments observe the species beyond the stated period to ascertain whether inter-competition will creep in leading to a decrease in populati on. References Begon, M., Harper, J. L., Townsend, C. R. (1996).  Ecology: individuals, populations, and communities. Cambridge, Massachusetts: Blackwell Science Ltd. Charles, L., Nunn, O., Ezenwa, A., Walter, K. (2011). â€Å"Mutualism or parasitism? phylogentic approach to characterize the oxpecker-ungulate relationship†. Evolution, 65(5): 1297–1304. Fedriani J., Fuller K., Sauvajot M., York, C. (2000). â€Å"Competition and intraguild predation among three sympatric carnivores†. Oecologia,  125(1): 258–270. Stachowicz, J. (2001). Mutualism, facilitation, and the structure of ecological communities. Boston, MA: Addison-Wesley This essay on Algae Interaction was written and submitted by user Brycen Buchanan to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Using System Dynamics to analyse the Economic Impact of Tourism Multip

Using System Dynamics to analyse the Economic Impact of Tourism Multip Using System Dynamics to analyse the Economic Impact of Tourism Multipliers Abstract The importance of tourism for economic development is widely recognised . This is reflected in the great interest shown by governments by promoting foreign direct investment and freeing both public and private sector projects. Most tourism studies concentrate on analysing the economic and social effects of tourism. The impact of the multiplier has been studied widely using traditional econometric techniques. This paper focuses on analysing the economic impact of tourism revenue on the Egyptian economy. The economic theory and the mathematical modelling involved in such scenarios is discussed but the main thrust of the paper is the encapsulation of this situation by Causal Loop Models . A dynamic model, run in Powersim, is then described where important non-linear dynamical movements and the significance of systems thinking in this framework are considered . This model considers the dynamics of tourism in Egypt and its impact on GNP. 1. Introduction The importance of tourism for an economy is independent of whether it is developed or developing. . Inskeep showed that in 1989 tourism revenues world-wide were nearly 209 billion dollars growing at 9% yearly. This revenue then represented nearly 7% of total international trade and 30% of total international income. Tourism played a major role in modernising the Spanish economy. In the USA, tourism generated 5 million jobs and was 6.7% of GNP in the USA in 1989 (Inskeep, 1991). It is not only income effects that make tourism sectors important. These sectors include foreign investment, subsidies and taxation. Infrastructure and resources are considered the most important feature for any country in a competitive world fighting to attract market share. In developing and advanced countries, tourism is viewed as an important means to boost levels of income and employment. There has been much research on tourism and relationships with economic development. Thus Kraph argues that tourism has a crucial role in developing countries. It helps to lower deficits in the Balance of Payments, increase levels of economic growth and raise job opportunities (Pearce, 1992). Kasse concentrated on the benefits and costs of tourism. He showed that through a certain investment in the tourism sector, income could be produced that may be used in developing different sectors of the economy. Van Doorn concludes that development theories should take into consideration the direct and the indirect effect of tourism (Pearce, 1992). Egypt is considered to have a reasonable infrastructure and adequate resources for tourism.. It has the advantage of a unique history and climate that has preserved some of the most ancient artefacts in the world. It has a good geographical location situated between three continents with a long coasts on the Mediterranean and Red Sea.. Egypt also has a stable political and social system. This paper focuses on analysing the economic impact of tourism sector revenues on the Egyptian economy. It begins by reviewing some of the most important previous studies that discuss models of tourism multipliers . It then examines a simple Keynesian model and relates this to Egyptian data. The paper presents the results of a regression analysis that considers relative effects on GNP, consumption, investment and import expenditures. Causal and System Dynamic models are then introduced and compared with econometric results. The policy implications are then discussed. 2 The Tourism Multiplier Most studies on Tourism have concentrated on analysing the economic and social effects of tourism specially by what is termed the multiplier effect. This term is a derivative of the multiplier effect first introduced by Samuelson (Samuelson, 1960). It determines the benefit to the economy for every unit of currency that is spent. It is noted that most of the conversations about the effect of tourism on economic development concentrated on the multiplied effect of tourism on the National economy. 2.1 Traditional Approaches: Archer reflects on interrelationships between three kinds of expenditure: 1) Direct expenditure. 2) Indirect expenditure. 3) Stimulated expenditure. Indirect expenditure and stimulated expenditure are called the secondary effects of the multiplier and the sum of these are called the total effect of the multiplier (Archer, 1982). Lundberg used the following formula to calculate multiplier effects (Lundberg, 1995). MPS MPI TPI TIM + = 1 (1.1) where: TIM = The tourism multiplier TPI = The marginal propensity to import for tourists MPS = The marginal propensity to save MPI = The marginal propensity to import for local residence Using published data for the Bahamas Islands, Lundberg (Lundberg, ibid) estimated the value of tourism multiplier as: 0.894 0.737 0.659 0.281 0.456 1 0.231 = = + TIM = Ryan (Ryan, 1991) devised an alternative formula for tourism multipliers as follows: BC TIM