01_introduction.lyx

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\begin_layout Section
Introduction
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Background
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In the famous fantasy drama television series
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Game of Thrones
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and its original novel series
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 A Song of Ice and Fire, Daenerys Targaryen
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is one of the most popular characters.

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The New York Times
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 cites her as one of the author's finest creatures, named as
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Mother of Dragons
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, for she has three dragons:
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Drogon, Rhaegal,
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and
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 Viserion.

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We appreciate
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Daenerys Stormborn
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 and are willing to see her conquering the Westeros with her dragons.
 But there is another question catching our eyesight now.
 What if these three fictional dragons are alive today?
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Dragons are the creatures standing on the top of the food chain.
 Their existence will have a great impact on the ecological environment.
 It will consume quantities of resources to secure their survival.
 In order to make the existence of the dragon more possible, we need to
 figure out these circumstances around the dragons.
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Restatement of the Problem
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To find out how the dragon will live in in a real world, we need to analyze
 the following questions:
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How will the dragon grow?
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How will the dragon interact with the ecological environment?
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Will the dragon perform differently in different environments? If true,
 what is the discrepancy?
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In order to answer these questions, we take some of the scientific researches
 in the field of biology today into consideration.
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Literature Review
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The growth curve model is a model for studying the laws of a certain biological
 indicator's changes varying with time.
 So far, scientists have used nonlinear curves to fit the growth trajectory
 related to animals.
 In 1838,
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Verhulst
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 proposed the Logistic growth curve equation
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.
 In 1938,
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Von Bertalanffy
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 corrected the Logistic growth curve to accommodate the metabolic laws of
 the organism
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, and he applied this in the field of fish weight studies successfully.
 In 1959,
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F.J.
 Richards
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 extended the Bertalanffy growth curve and proposed the Richards growth
 curve
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.
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Two general approaches have been in use to determine the distance to a specified
 level of heat flux hazard from fires
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.
 These are the so-called Solid Flame Model and the Point Source Model
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.
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Species Distribution Models (SDMs) mainly use species distribution data
 and environmental data to estimate the niche of a species according to
 a specific algorithm.
 And project it into the landscape to indicate the species' preference for
 habitat in probabilistic.
 The results can be interpreted as the probability of occurrence of species,
 habitat suitability or species richness, etc..
 In the 1970s, Nix et al first used SDMs to predict the spatial distribution
 of species
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.
 After the 1990s, as the rapid developments of GIS technology and easy refining
 of remote sensing data related to climate, sea surface, land surface take
 place, it greatly enhanced the application of SDMs, together with a large
 number of species distribution models and software emerged.
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