Fishing

Math Summative: Fishing Rods Fishing Rods A fishing rod requires guides for the line so that it does not tangle and so that the line casts easily and efficiently. In this task, you will develop a mathematical model for the placement of line guides on a fishing rod. The Diagram shows a fishing rod with eight guides, plus a guide at the tip of the rod. Leo has a fishing rod with overall length 230 cm. The table shown below gives the distances for each of the line guides from the tip of his fishing rod.

Define suitable variables and discuss parameters/constraints. Using Technology, pot the data points on a graph. Using matrix methods or otherwise, find a quadratic function and a cubic function which model this situation. Explain the process you used. On a new set of axes, draw these model functions and the original data points. Comment on any differences. Find a which passes through every data point. Explain you choice of function, and discuss its reasonableness. On a new set of axes, draw this model function and the original data points. Comment on any differences.

Using technology, find one other function that fits the data. On a new set of axes, draw this model function and the original data points. Comment on any differences. Which of you functions found above best models this situation? Explain your choice. Use you quadratic model to decide where you could place a ninth guide. Discuss the implications of adding a ninth guide to the rod. Mark has a fishing rod with overall length 300cm. The table shown below gives the distances for each of the line guides from the tip of Mark’s fishing rod.

Guide Number (from tip)

How well does your quadratic model fit this new data? What changes, if any, would need to be made for that model to fit this data? Discuss any limitations to your model. Introduction: Fishing rods use guides to control the line as it is being casted, to ensure an efficient cast, and to restrict the line from tangling. An efficient fishing rod will use multiple, strategically placed guides to maximize its functionality. The placement of these will depend on the number of guides as well as the length of the rod. Companies design mathematical equations to determine the optimal placement of the guides on a rod.

Poor guide placement would likely cause for poor fishing quality, dissatisfied customers and thus a less successful company. Therefore it is essential to ensure the guides are properly placed to maximize fishing efficiency. In this investigation, I will be determining a mathematical model to represent the guide placement of a given fishing rod that has a length of 230cm and given distances for each of the 8 guides from the tip (see data below). Multiple equations will be determined using the given data to provide varying degrees of accuracy. These models can then potentially be used to determine the placement of a 9th guide.

Four models will be used: quadratic function, cubic function, septic function and a quadratic regression function. To begin, suitable variables must be defined and the parameters and constraints must be discussed. Variables: Independent Variable: Let x represent the number of guides beginning from the tip Number of guides is a discrete value. Since the length of the rod is finite (230cm) then the number of guides is known to be finite. Domain = , where n is the finite value that represents the maximum number of guides that would fit on the rod.

Dependent Variable:

Let y represent the distance of each guide from the tip of the rod in centimetres. The distance of each guide is a discrete value. Range = Parameters/Constraints: There are several parameters/constraints that need to be verified before proceeding in the investigation. Naturally, since we are talking about a real life situation, there cannot be a negative number of guides (x) or a negative distance from the tip of the rod (y). All values are positive, and therefore all graphs will only be represented in the first quadrant. The other major constraint that must be identified is the maximum length of the rod, 230cm.

This restricts the y-value as well as the x-value. The variable n represents the finite number of guides that could possibly be placed on the rod. While it is physically possible to place many guides on the rod, a realistic, maximum number of guides that would still be efficient, is approximately 15 guides. Guide Number (from tip) Distance from Tip (cm) 0* 1 2 3 4 5 6 7 8 n** 0 10 23 38 55 74 96 120 149 230 *the guide at the tip of the rod is not counted **n is the finite value that represents the maximum number of guides that would fit on the rod.

Neither of the highlighted values are analyzed in this investigation, they are only here for the purpose of defining the limits of the variables. The first step in this investigation is to graph the points in the table above (excluding highlighted points) to see the shape of the trend that is created as more guides are added to the rod. From this scatter plot of the points, we can see that there is an exponential increase in the distance from the tip of the rod as each subsequent guide is added to the rod. Quadratic Function: The first function that I shall be modeling using the points of data provided is a quadratic function.

The general equation of a is y = ax2 + bx + c. To do this, I will be using three points of data to create three equations that I will solve using matrices and determine the coefficients: a, b and c. The first step in this process is to choose three data points that will be used to represent a broad range of the data. This will be difficult though since there are only three out of the eight points that can be used. Therefore, to improve the accuracy of my quadratic function, I will be solving two systems of equations that use different points and finding their mean. Data Sets Selected: Data Set 1 = {(1,10), (3,38), (8,149)}

Data Set 2 = {(1,10), (6,96), (8,149)} These points were selected for two main reasons. First, by using the x-values 1 and 8 in both sets of data, we will have a broad range of all of the data that is being represented in the final equation after the values of the coefficients are averaged. Second, I used the x values of 3 (in the first set) and 6 (in the second set) to once again allow for a broad representation of the data points in the final quadratic equation. Both of these points (3 and 6) were chosen because they were equal distances apart, 3 being the third data point, and 6 being the third from last data point.

This ensured that the final averaged values for the coefficients would give the best representation of the middle data points without skewing the data. There will be two methods that will be used to solve the system of equations, seen below. Each method will be used for one of the systems being evaluated. Data Set 1 = {(1,10), (3,38), (8,149)} In the first data set, the data points will form separate equations that will be solved using a matrices equation. The first matrix equation will be in the form: Where A = a 3×3 matrix representing the three data points X = a 3×1 matrix for the variables being solved B = a 3×1 matrix for the y-value of the three equations being solved. This matrix equation will be rearranged by multiplying both sides of the equation by the inverse of A: Since A-1*A is equal to the identity matrix (I), which when multiplied by another matrix gives that same matrix (the matrix equivalent of 1), the final matrix equation is: To determine the values of X, we must first find the inverse of matrix A using technology, since it is available and finding the inverse of a 3 by 3 matrix can take an inefficient amount of time.

First let us determine what equations we will be solving and what our matrices will look like. Point: (1,10) (3, 38) (8,149) A= The equation is: ,X= ,B= = Next, by using our GDC, we can determine the inverse of matrix A, and multiply both sides by it. Therefore we have determined that the quadratic equations given the points {(1,10), (3,38), (8,149)} is . Data Set 2 = {(1,10), (6,96), (8,149)} Point: (1,10) (6, 96) (8,149) A= ,X= ,B= The second method that will be used to solve the second system of equations is known as Gauss-Jordan elimination.

This is a process by which an augmented matrix (two matrices that are placed into one divided by a line) goes through a series of simple mathematical operations to solve the equation. On the left side of this augmented matrix (seen below) is the 3×3 matrix A (the new matrix A that was made using data set 2, seen on the previous page), and on the right is matrix B. The goal of the operations is to reduce matrix A to the identity matrix, and by doing so, matrix B will yield the values of matrix X. This is otherwise known as reduced row echelon form. Step by step process of reduction: 1. We begin with the augmented matrix. . Add (-36 * row 1) to row 2 3. Add (-64 * row 1) to row 3 4. Divide row 2 by -30 5. Add (56 * row 2) to row 3 6. Divide row 3 by 7. Add ( * row 3) to row 2 8. Add (-1 * row 3) to row 1 9. Add (-1 * row 2) to row 1 After all of the row operations, matrix A has become the identity matrix and matrix B has become the values of matrix X (a, b, c). Therefore we have determined that the quadratic equations given the points {(1,10), (6,96), (8,149)} is . Averaging of the Two Equations The next step in finding our quadratic function is to average out our established a, b, and c values from the two sets data.

Therefore we have finally determined our quadratic function to be: Rounded to 4 sig figs, too maintain precision, while keeping the numbers manageable. Data points using quadratic function Guide Number (from tip) Quadratic values Distance from Tip (cm) Original – Distance from Tip (cm) 1 10 2 22 3 37 4 54 5 74 6 97 7 122 8 149 10 23 38 55 74 96 120 149 New values for the distance from tip were rounded to zero decimal places, to maintain significant figure – the original values used to find the quadratic formula had zero decimal places, so the new ones shouldn’t either.

After finding the y-values given x-values from 1-8 for the quadratic function I was able to compare the new values to the original values (highlighted in green in the table above). We can see that the two values that are the exact same in both data sets is (1,10) and (8,149) which is not surprising since those were the two values that were used in both data sets when finding the quadratic function. Another new value that was the same as the original was (5,74). All other new data sets have an error of approximately ±2cm.

This data shows us that the quadratic function can be used to represent the original data with an approximate error of ±2cm. This function is still not perfect, and a better function could be found to represent the data with a lower error and more matching data points. Cubic Function: The next step in this investigation is to model a cubic function that represents the original data points. The general equation of a cubic function is y = ax3 + bx2 + cx + d. Knowing this, we can take four data points and perform a system of equations to determine the values of the coefficients a, b, c, and d.

The first step is to choose the data points that will be used to model the cubic function. Similarly to modeling the quadratic function, we can only use a limited number of points to represent the data in the function, only in this case it is four out of the eight data points, which means that this function should be more precise than the last. Once again I plan on solving for two sets of data points and finding their mean values to represent the cubic function. This is done to allow for a more broad representation of the data within the cubic function. Data Sets Selected: Data Set 1: {(1,10), (4,55), (5,74), (8,149)}

Data Set 2: {(1,10), (3,38), (6,96), (8,149)} Both data sets use the points (1,10) and (8,149), the first and last point, so that both data sets produce cubic functions that represent a broad range of the data (from minimum to maximum). The other points selected, were selected as mid range points that would allow for the function to represent this range of the data more accurately. When modeling a cubic function or higher, it is difficult to do so without using technology to do the bulk of the calculation due to large amounts of tedious calculations that would almost guarantee a math error somewhere.

Therefore, the most accurate and fastest way to perform these calculations will be to use a GDC. In both data sets, the reduced row echelon form function on the GDC will be utilized to determine the values of the coefficients of the cubic functions. The process of determining the values of the coefficients of the cubic function using reduced row echelon form is similar to process used for the quadratic function. An x-value matrix A (this time a 4×4 matrix), a variable matrix X (4×1) and a y-value matrix B (4×1) must be determined first. The next step is to augment matrix A and matrix B, with A on the left and B on the right.

This time, instead of doing the row operation ourselves, the GDC will do them, and yield an answer where matrix A will be the identity matrix and matrix B will be the values of the coefficients (or matrix X). Data Set 1: {(1,10), (4,55), (5,74), (8,149)} (1,10) (4, 55) (5, 74) (8,149) A1 = , X1 = , B1 = We begin with the augmented matrix or matrix A1 and matrix B1. Then this matrix is inputted into a GDC and the function “rref” is selected. After pressing enter, the matrix is reduced into reduced row echelon form. Which yields the values of the coefficients. Data Set 2: {(1,10), (3,38), (6,96), (8,149)} (1,10) (3, 38) 6, 96) (8,149) A2 = , X2 = , B2 = We begin with the augmented matrix of matrix A2 and matrix B2. Then the matrix is inputted into a GDC and the function “rref” After pressing enter, the matrix is reduced into reduced row echelon form. Which yields the values of the coefficients. The next step is to find the mean of each of the values of the coefficients a, b, c, and d. Therefore we have finally determined our cubic function to be: Once again rounded to 4 significant figures. Updated Data table, including cubic function values. Guide Number (from tip) Quadratic values Distance from Tip (cm) 1 10 2 22 3 37 4 54 5 74 6 97 122 8 149 Cubic values Distance from Tip (cm) Original – Distance from Tip (cm) 10 23 38 54 74 96 121 149 10 23 38 55 74 96 120 149 New values for the distance from tip were rounded to zero decimal places, to maintain significant figure – the original values used to find the quadratic formula had zero decimal places, so the new ones shouldn’t either. The y-values of the cubic function can be compared to that original data set values to conclude whether or not it is an accurate function to use to represent the original data points. It appears as though the cubic function has 6 out of 8 data points that are the same.

Those points being, (1,10), (2,23), (3,38), (5,74), (6,96), (8,149). The three data points from the cubic function that did not match only had an error of ±1, indicating that the cubic function would be a good representation of the original data points, but still has some error. We can further analyze these points by comparing the cubic and quadratic function to the original points by graphing them. See next page. By analyzing this graph, we can see that both the quadratic function and the cubic function match the original data points quite well, although they have slight differences.

By comparing values on the data table, we find that the quadratic function only matches 3 of the 8 original data points with an error of ±2, while the cubic function matches 6 of the 8 points with an error of just ±1, which is as small an error possible for precision of the calculation done. Both functions act as adequate representations of the original points, but the major difference is how they begin to differ as the graphs continue. The cubic function is increasing at a faster rate than the quadratic function, and this difference would become quite noticeable over time.

This would mean that if these functions were to be used to determine the distance a 9th guide should be from the tip, the two functions would provide quite different answers, with the cubic functions providing the more accurate one. Polynomial Function: Since it is known that neither the quadratic, nor the cubic function fully satisfy the original data points, then we must model a higher degree polynomial function that will satisfy all of these points. The best way to find a polynomial function that will pass through all of the original points is to use all of the original points when finding it (oppose to just three or four).

If all eight of the points are used and a system of equations is performed using matrices, then a function that satisfies all points will be found. This is a septic function. To find this function, the same procedure followed for the last two functions should be followed, this time using all eight points to create an 8×8 matrix. By then following the same steps to augment the matrix with an 8×1 matrix, we can change the matrix into reduced row echelon form to and find our answer. In this method, since we are using all eight points, the entire data set is being represented in the function and no averaging of the results will be necessary.

The general formula for a septic function is . Data Set: {(1,10), (2,23), (3,38), (4,55), (5,74), (6,96), (7,120), (8,149)} (1,10) (2,23) (3,38) (4,55) (5,74) (6,96) (7,120) (8,149) A=,X= ,B= , Augment matrix A and matrix B and perform the ‘rref’ function The answers and values for the coefficients = The final septic function equation is This function that include all the original data points can be seen graphed here below along with the original points. Updated Data table, including septic function values Guide Number (from tip) Quadratic values Distance from Tip (cm) Cubic values Distance from Tip (cm)

Septic values – Distance from Tip (cm) Original – Distance from Tip (cm) 1 10 2 22 3 37 4 54 5 74 6 97 7 122 8 149 10 23 38 54 74 96 121 149 10 23 38 55 74 96 120 149 10 23 38 55 74 96 120 149 New values for the distance from tip were rounded to zero decimal places, to maintain significant figure – the original values used to find the quadratic formula had zero decimal places, so the new ones shouldn’t either. By looking at the graph, as well as the data table (both seen above), we can see that, as expected, all 8 of the septic function data points are identical to that of the original data.

There is less than 1cm of error, which is accounted for due to imprecise (zero decimal places) original measurements. Therefore we now know that the septic function that utilised all of the original data points is the best representation of said data. Other Function: The next goal in this investigation is to find another function that could be used to represent this data. The other method that I will use to find a function that fits the data is quadratic regression. Quadratic regression uses the method of least squares to find a quadratic in the form .

This method is often used in statistics when trying to determine a curve that has the minimal sum of the deviations squared from a given set of data. In simple terms, it finds a function that will disregard any unnecessary noise in collected data results by finding a value that has the smallest amount of deviation from the majority of the data. Quadratic regression is not used to perfectly fit a data set, but to find the best curve that goes through the data set with minimal deviation. This function can be found using a GDC. First you must input the data points into lists, (L1 and L2).

Then you go to the statistic math functions and choose QuadReg. It will know to use the two lists to determine he quadratic function using the method of least squares. Once the calculation has completed, the data seen below (values for the coefficients of the function) will be presented: QuadReg a = 1. 244 b = 8. 458 c = 0. 8392 With this data we can determine that the function is When graphed, this function has the shape seen below: Updated Data table, including septic function values Guide Number (from tip) Quadratic values Distance from Tip (cm) Cubic values Distance from Tip (cm)

By analyzing the graph and values of the quadratic regression function, it is evident that it is a relatively accurate form of modeling the data. Four of the eight points matched that of the original data, with an error of ±1. The most notable difference between the quadratic regression function and the quadratic function previously determined, is the placement within the data f the accurate values. The regression function matched the middle data, while the quadratic function matched the end data. It is interesting to see how two functions in the same form, found using different methods yielded opposite areas of accuracy. Best Match: The function that acts as the best model for this situation is the septic function. It is the only function that satisfies each of the original data points with its equation. Through finding the quadratic, cubic and septic functions, it was discovered that the degree of the polynomial was directly correlated to the function’s accuracy to the data.

Therefore it was no surprise that this function acts as the best fit for this data. The other cause for this septic function having the best correlation to the original data is due to the septic function being established by creating a system of equations using all of the data points. 9th Guide: Using my quadratic model, it can be determined where the optimal placement for a ninth guide would be by substituting ‘9’ in for x in the equation . Using my quadrating model, it was found that the optimal placement for a ninth guide on the rod is 179cm from the tip of the rod.

Leo’s fishing rod is 230cm long, yet his eighth guide is only 149cm from the tip of the rod. That means that there is 81cm of the line that is not being guided from the reel to first guide. By adding a ninth guide, that distance will be shortened form 81cm to 51cm. By doing this, it will be less likely for the line to bunch up and become tangled in this 81cm stretch where there is no guide. Another implication of adding another guide would be that the weight distribution of a fish being reeled in would be spread over another guide, which will allow for an easier task of reeling in the fish.

There is even enough space on the rod for a 10th guide at 211cm from the tip of the rod. This guide would once again shorten the excess line further to a point where the excess line between the reel and the first guide is shorter than line between the first and second guide. This could cause problems with reeling and casting efficiency, as that extra guide would cause slowing movement of the line. The benefit would be that once again the weight distribution of fish would be spread over a larger number of guides.

Overall, it would be beneficial to include a ninth guide to Leo’s fishing rod, but anymore will likely hinder its efficiency. Mark’s Fishing Rod: Guide Number (from tip) Distance from Tip (cm) 1 10 2 22 3 34 4 48 5 64 6 81 7 102 8 124 To see how well my quadratic model fits this new data, they must be both plotted on the same graph, seen below. My quadratic model for Leo’s fishing rod correlates with Mark’s fishing rod data for the first few values and then diverges as the number of guides increases by growing at a higher exponential rate.

The difference between Leo and Mark’s eighth guide from the tip of their respective rods is 25cm, yet both men’s first guides start the same distance from the tip of their rods. The quadratic function used to model Leo’s fishing rod does not correlate well with Mark’s fishing rod data. Changes to the model must be made for it to fit this data. The best way to find a model for Mark’s data would be to go through the same steps that we went through to determine the first quadratic formula that model’s Leo’s fishing rod.

By doing so, specific values that better represent Mark’s fishing rod data could be used to establish a better fitting function. The main limitation of my model is that is was designed as a function for Leo’s data specifically. It was created by solving systems of equations that used solely Leo’s fishing rod for data. Consequentially, the quadratic model best represented Leo’s fishing rod, which had a maximum length of 230cm, with differently spaced out guides. There were many differences between Leo and Mark’s fishing rods (such as maximum length and guide spacing) that caused my original quadratic model to not well represent Mark’s data.

A fish in a pond is a prime example of an organism living in an ecosystem.  There are multiple biological and non-biological interactions occurring in a pond.

The fish may interact with its own fish variety, with other fish species, with other vertebrates, non-vertebrates, plants and microorganisms.  In addition, the fish may also interact with its environment—the water, the fish bottom, the rocks and sand.  The fish’s well-being is affected by the amount of dissolved oxygen, the water temperature, salinity and amount of sunlight.

Any imbalance or perturbation may affect the health of the fish.  The fish’s ecosystem is very similar to an individual who belongs to an organization.  That individual intermingles with other members of the group, at the same time interacts with the immediate environment of the organization, be it an office cubicle, the entire workplace or the whole building complex.

The member’s state of well-being is also influenced by the conditions of the place, such as the temperature, lighting, humidity, office furniture/amenities and space allotments.  Poor ventilation and substandard lighting in the workplace may affect the efficiency of the member of the organization.

There are both advantages and disadvantages in being a big fish in a little pond and a little fish in a big pond.  It is good to be a big fish in a little pond because the big fish will have a greater opportunity to survive in the little pond because it can eat the little fishes in the pond, as well as ingest most of the good seaweed in the area.  For a top-rank authority member of a small organization, this individual will receive most of the recognition given for the achievements the organization has made.

That member will also receive a higher salary than the rest of the regular members of the organization because he is known to have the best qualities and capabilities in the organization.  Just like a big fish in a little pond that has his own space or territory, the top-rank member of the organization has a spacious office in the building with matching fine quality furniture and other amenities in his office space.  Unfortunately, the big fish in the little is also the first fish that is usually caught by fishermen because its big size makes it very visible for capture.

The same thing happens with the top-rank member of an organization, he is the first person to be blamed once a problem or financial crisis arises in the organization.  The top-rank member is an easy sight because he represents the organization in almost every event or interaction with the rest of the business world.

Kevin Van Dam is a professional bass angler.

Kevin has always had a love for fishing, but did not start fishing professionally until 1990. Kevin Van Dam may not be a household name to most people, but anyone who enjoys bass fishing has heard of him. Bass fishing is my passion and I look up to Kevin Van Dam, as he is the best in the world in this era of bass fishing. Kevin Van Dam was born on October 14, 1967 in Kalamazoo, Michigan.Growing up in Michigan gave Kevin the chance to fish a lot of different lakes and rivers for a variety of species of fish including trout, salmon, muskies, walleyes, and northern pike. “You can learn a lot by fishing different species in the diverse variety of lakes and rivers we have in Michigan,” Kevin once said when asked about fishing in his childhood. Kevin loved to fish and was in the perfect environment to hone his skills.

Although he fished for many species of fish, bass fishing was his favorite.Kevin dominated the tournament circuits, winning the Michigan Bass Anglers Sportsman Society Angler of the Year twice before going pro. Kevin graduated from Otsege High School, and married his high school sweetheart Sherry. Kevin and Sherry settled in their home town of Kalamazoo, and continue to live there today with there twin boys, Jackson and Nicholas. Kevin is a devoted dad and enjoys taking his children fishing and deer hunting. Kevin worked various jobs until deciding to become a professional bass angler at the age of twenty three.Kevin began one of the most successful bass fishing careers ever under shadows of doubt, that he was going pro too young.

He soon proved all that doubted his abilities wrong by winning the Toyota Tundra Angler of the Year, and was the youngest ever to win this prestiges title. Kevin also won the Bass Anglers Sportsman Society Angler of the Year title at age twenty five. The Bassmaster classic is the highest regarded title in professional bass fishing, to qualify for the Bassmaster classic you must go through a series of tournaments fished by the toughest anglers in the world.Van Dam has qualified for twenty consecutive Bassmaster classics since 1991, this is the longest running qualification streak in history. He has won the Bassmaster classic three times in 2001, 2005, and 2010. Kevin has fished in two hundred and twenty one Bassmaster events, he has won nineteen, finished second eleven times and finished in the top ten ninety times. Kevin Van Dam is a serious force to be reckoned with in the professional bass fishing world, and is simply nicknamed KVD.

He has become a ambassador for the sport as it has grown in public attention, and is now featured on ESPN. Van Dam was awarded the first ever ESPN Outdoor Sportsman of the Year in 2002. KVD was grateful to receive this award, since it was not about his lifetime records which are amazing, but his promotion of the sport. Kevin Van Dam in my opinion and many others is the greatest Angler to pass threw the professional world of bass fishing some may not admit it, but statistically this is true. Kevin is a true role model for young bass anglers today.

This undertaking is given by our instructor and we were supposed to compose about the clime alterations. I decided to compose about the subject “ coral reef ” . I want to cognize more about coral reefs, non merely the general facts about how they look like or what sort of coloring material they have, but more about the interesting facts. Why are they of import today, how we as human ruin them and what we can to halt this procedure?

As it says on International Coral Reef Initiative “ For the first clip since 1998, mass coral bleaching is impacting coral reefs across a broad country of Southeast Asia and the Indian Ocean. Bleaching has been reported in Indonesia, Malaysia, Thailand, the Philippines, Maldives, and parts of E Africa.

I know it exists menaces against coral reefs, and I want to larn more about them and what are the effects of e.g. coral bleaching. In the quotation mark above it says that coral bleaching is increasing. Why?

What are coral reefs?

Coral reefs, indicated by ruddy points, are found preponderantly in tropical Waterss 30 grades north and South of the equator

Coral reefs are among the oldest ecosystems in the universe. They are located 30 grades north or South of the equator, chiefly in the Indonesia and Pacific Ocean. In the Bahamas at 32 grades at that place exists an exclusion. The coral reefs can populate at that place because of the warm H2O from the Gulf of Mexico. Today the coral reefs are the largest life construction on Earth and the Great Barrier Reef is the largest individual construction in the universe

Coral are single animate beings and a individual coral is called polyp. Largely the polyp live in groups of 100s to 1000s indistinguishable animate beings, and organize a “ settlement ” . The procedure which formed the settlement is called budding and literally the original polyp transcripts itself and the settlement grows. There exist two ways for the coral to turn either add to their limestone or reproducing. When a coral attention deficit disorder to their limestone is means that they secrete more calcium carbonate around and under their cup. The coral will so turn both upwards and outwards. The 2nd method is by reproducing either asexually or

sexually. In the nonsexual manner the coral produced indistinguishable ringers or in a sexual manner by directing out sperm or eggs. Corals are divided into three different types depending on where signifier. The first one and most common is fringing reefs. They are close to the seashore and they form a boundary line to project themselves. Barrier reefs are another type and are similar to fringing reef. These besides environment land multitudes, but form a boundary line at a distance. The 3rd group of reef are called atolls and are either egg-shaped or round. They are lying off the seashore. ( See beginning 4 + 6 )

Why are corals of import?

Today coral reefs are of import and necessary in the universe. Great Barrier Reef, which is the universe largest reef, stretches along the nor’-east cost of Australia. The reef consist of over 3A 000 single reef and has a length of 30A 000 kilometers. It is really possible to see it from the outer infinite.

A satellite exposure of the Great Barrier Reef

The reef includes 400 coral species, 2A 000 fish species and six of seven species of sea polo-necks. There are many different types of coral which have assorted colorss. ( See beginning 3 )

Why are the corals deceasing?

There are many menaces to coral reefs. Some menaces are natural happening such as marauders and hurricanes. These are made of course, but because of planetary warming the menaces harmonizing to the coral reefs addition. Others menaces are made by human among them overfishing and pollutions.

Consequence of coral bleaching

Marauders and hurricanes are natural happening and it is difficult to make something about these happening because they happen of course, still increasing of rainfall over a long period lessening coral growing. The coral reefs need sunlight, clear H2O, seawater with a specific salt and warm H2O ( 23 – 29 grades Celsius ) to populate. However, addition in the temperature degree and altered salt affects the coral reefs severely. Merely one grade rise in temperature influences the coral. The harm is called coral bleaching and involves that the coral expels the algae which gives the coral its coloring material. Alternatively of being colorful the coral takes on a blunt white visual aspect. The algae do n’t return if the emphasis is prolonged and as a consequence the coral dies. “ The bleaching is really strong throughout Southeast Asia and the cardinal Indian Ocean. The studies are that it is the worst since 1997/1998. This is a truly immense event and we are traveling to see a batch of corals deceasing ” says Dr Mark Eakin

Overfishing is a menace made by human. Today many people are dependent on fish as an income and nutrient, still overfishing is a job. It affects the coral by “ taking cardinal species from the marine nutrient concatenation ” . Furthermore the methods used to catch fish can besides be harmful to the coral. For case 15 states use nitrile fishing which involves dumping toxicant onto reefs to stupefy fish for easier assemblage. The toxicant does n’t merely impact the fish, but besides the reefs. Another sensational method is called blast fishing, utilizing explosives to stupefy fish, and the method is used by more than 40 states. As a consequence of the detonation the coral are ripped apart and destroyed. On the other manus, addition of the H2O degree increases the thriving for harmful algae and other rivals. More rivals and harmful algae mean less infinite for the coral to growing. Likewise out of use sunlight lessening the growing for a coral and the coral can decease. ( See beginning 5 )

Decision

“ Seventy per centum of coral reefs may be gone in less than 40 old ages if the present rate of devastation continues ” . This destructing procedure has to be stopped, and it needs to be shortly. Coral reefs are place to over 1 million different species and protect the coastal metropoliss. In add-on to this, coral reefs create 1000000s of occupation and unafraid income for many people in more than 100 states in the universe. However coral reefs are a nutrient beginning for the people who live near the reefs, particularly the people on little islands. Another interesting fact is that without the being of coral reefs, parts of Florida would be under H2O. ( See beginning 7 )

Beginnings

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Limitations: Article 116 – there are 3 ways in which people who whose to fish on high seas are limited. What’s the limitation of fishing on high seas. – answer Isn’t 87, BUT article 116 treaty obligations must be complied with, rights and duties of coastal states must be respected. Articles 116-120 – relate to conservation and management of living sources on the high seas. Article 118 – says that countries should cooperate, subrogation fisheries and organizations so government agencies can assess what’s being exploited so as to negotiate resources.

Article 119 – when Investigating exploitation and resources, must use best scientific evidence that gives maximum sustainable yields. Consider dependent species – IPPP Can’t be discriminatory and can’t be against fisherman of particular state. Backwards from high seas what’s the next zone – economic zone – distances are important – 24 to 200 nautical miles Then next zone is contiguous zone – stretches from territorial zone out to economic zone. If you know these you can flick through the book what Is the contiguous zone and what does It do? What article relates to contiguous zone – article 33 – slide number 12.

What is the limitation of the contiguous zone – a state MAY control immigration in the contiguous zone – we can stop them from gashing, Infringing customs laws, sanitary laws or any regulations within the territory or territorial sea ? If no legislation, state can do nothing. From where contiguous zone is measured – from baseline – coastline is Jagged therefore they use low watermark to do it. Need to know the article – whenever you get question, you must tell article. I OFF Territorial sea – articles 3, 17 and 18. Territorial limitation is key to security for a nation.

Ships are actually allowed from foreign nations can travel through, only limitation on them is stout in article 18-21 – got to tell what PASSAGE actually means (article 18). Can’t enter internal waters (where sea enters rivers) but allowed to traverse the sea. Must be expeditious (article 18(2)) got to keep going – expeditious (check dictionary) – relatively quickly. Always exceptions – legislation says well okay even though you have to keep going, you can anchor but only if it is part of your navigation procedures. That would mean ports authority would know (have permission).

However, it says that force measure (serious intervention in the normal course of undertaking – e. G. Wild storm) so you can port for protection – or distress call – you can render assistance from ships, aircraft. You can only travel in territorial waters if passage is innocent (look at 19 and 21 said lecturer) – article 19 – meaning of innocent passage – 19(1) not prejudicial to the peace of the state, good order or security. Under article 19(2) – shows what ship cannot do through territorial waters. Question on innocent passage. Marks taken off if you go to wrong subsection – read question carefully.

Foreigners not allowed to fish in territorial waters. Do need to know article 19. Article 21 – allows laws and regulations of coastal state in respect to the territorial sea – innocent passage. Must be inline with UNCLOGS and international law. Safety of navigation, protection of navigational aids and facilities is critical of innocent passage. Conservation of fisheries and marine ecosystem – ship cannot infringe fishing laws, can’t pollute, no marine research. Article 24 – may not be a definite answer and take two sides e. G. If this if that, may be because of this etc.

Reason through a problem. Duties imposed upon a coastal state: Mustn’t hamper passage of foreign ships. Can’t impose requirement on foreign ships which deny innocent passage. Can’t discriminate – e. G. One from France, Italy, Indonesia – can’t go to Indonesia automatically (defiance of 24 1(b)). Must warn of any likely danger – e. G. Buoys etc. (24 article) Article 25 – coastal state can do anything where they think that the passage is not innocent. Got to refer to 19 and has to have reasonable proof. Rights of coastal states Only require to know certain articles put up in learn (slides).

Don’t want you to look at other articles Section 3 of the exam (consisting of 5 questions and 12 marks will be to do with End of the line – documentary 1 billion people out of 7. 3 billion rely on fish as source of protein instead of chicken/ other meats/ the likelihood of seafood running out by 2048 is high – not long to make stance Once fisheries collapse 250 million people will have there food supplies threatened 70% of global fisheries are beyond there capacity 90% of large fish in ocean have been fished out 1% of the worlds industrial fishing fleets result in 50% of world catches – what on earth can be done?

Mediumistic – blue fin tuna – largely responsible. Also the large fishing trawlers. Global fishing fleets now are 250% larger than the oceans can sustain Only 6% of the worlds oceans are actually protected e. G. Bahamas. We have got areas around news coastline protected. Cog Clove area. 40% of worlds oceans would be natural reserves blue fin tuna is major problem – 6 billion worth of illegal blue fin tuna have been fished over last 20 years. Mediumistic is freezing them. Price of tuna fish on the market is $100,000 – imagine Mediumistic price later Enormous drop in shark species over last 20 years. 5 species have dropped by 50% Tuna catches use massive nets – killing thousands of turtles, sea birds and sharks which Just get dumped back in ocean. 22,000 tones is the legal limit for tuna – currently 60,000 tones. Illegal fishing worth 9 billion a year – 52% of fish stocks are now fully exploited. If we establish exclusion ones for fishing it is possible that the biodiversity in fish stocks will be able to come back – but will take years Suggested that you check what your eating is sustainable – if not – don’t touch it.

Lecture 13 (29/06/14) – High seas belongs to everybody, and can virtually do what you want. UNCLOGS – separates prevention reduction and control on marine pollution from the rules that conserve and manage living resources. Focused on second part – sustainability. Only other convention that protects Is there any convention in the world that controls the fishing of various stocks in the high seas and beyond the continental shelf – NO