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Chapter 19-1 Populations A part of a pod of dolphins.

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1 Chapter 19-1 Populations A part of a pod of dolphins

2 Objectives Explain the difference between population size, density, and dispersion Describe the three main patterns of population dispersion Explain the importance of a populations age structure Contrast the three main types of survivorship curves

3 Populations Defined by place & time Size: number of individuals
How do you find size? Count everyone? U.S. census Estimation: take a small sample and extrapolate to a larger area Density: How crowded? Individuals per unit volume

4 Density by country Country Population Area (km²) Density—
World ,445,398, ,940, Singapore 4,425, United States 295,734, ,631, Australia ,090, ,686,

5 Density by city Pittsburgh: 6,019.0/mi²
BUT: We’re now America's 56th largest city, down from 10th in 1940 This is because the big cities annex their suburbs in, increasing the size and population, but lowering the density Houston went from 17 square miles in 1910 to 160 square miles at mid-century to 579 square miles at century's end. San Diego has more than tripled its land area since mid-century, as has Dallas. San Antonio is nearly six times its 1950 land area. Phoenix is more than 27 times its mid-century form. In fact, the land gained by both Phoenix and San Antonio in the 1990s alone represents an area larger than Pittsburgh. What's funny, though, is that Pittsburgh is still more densely populated than any of them. Pittsburgh has more people per square mile, even after losing half its population, than five of the top 10 cities in the country. The chart uses data from the 2000 census. Pittsburgh has managed to misplace another 12,000 people since then, and the other cities have grown some, but the point remains. The average Pittsburgh resident has twice as many neighbors per square mile as the average resident of San Antonio or Phoenix, and at least 50 percent more than Dallas, Houston and San Diego. The average Top 10 city is 340 square miles, roughly six times the size of Pittsburgh. They've adapted to the auto age by spreading out and broadening the tax base to include those who lived in the "real" Houston, or San Diego or Phoenix, and not just those within the buggy-age boundaries. How much land is that? The smallest of the cities, San Diego, would swallow about 90 of Allegheny County's 130 municipalities entirely, and take pieces of more than a dozen others. The northern line would split Hampton and McCandless, the southern line would go deep into Upper St. Clair and Bethel Park, the eastern boundary would cut through Penn Hills and Monroeville and the western one would slice Moon. More than 900,000 people live within that circle, by my guess. The largest city in the Sun Belt quintet, Houston, would stretch wide enough to touch all but about dozen communities in Allegheny County, and would get into Peters in Washington County. About 1.2 million people live within that circle. These are approximations. There's no need to be precise because cities don't grow in perfect circles anyway. The population of any of the circles, however, would make Pittsburgh the ninth largest city in the country, and only slightly less densely populated than the Sun Belt dynamos. Question: is density in a city a good thing? Is it better than having suburbs extend into forests?

6 Dispersion patterns Now dispersion depends on what size area you look at. How would you characterize the dispersion of the United states? Clumped around the Coasts? Patterned farms in the midwest farms?

7 Population dynamics Birth rate: number of births over a period of time
Also fertility rate: How many offspring each female has Developed ~ 1/2 Developing ~ 5/6 Death/mortality rate: number of births over a period of time Life expectancy: how long an individual is expected to live Girls live longer

8 Age structure Shows distribution of individuals among different groups. Explain how it is possible to conclude that the life expectancy of a person in a stable population is longer than that of a person in an expanding population. How can you tell that women have a longer life expectancy than men?

9 Predictions from survivorship curve
Which countries population has the potential for rapid growth? Bottom heavy curves indicate that many young have been added to the youngest & most reproductive age group.

10 Survivorship curves Show how many individuals survive over time
Three different trends Type I: you’ll probably live until old age Elephants: Few young, lots of care Type II: you have an even chance to survive no matter how old Type III: you’ll probably die young, but if you survive you’ll live to an old age. Insects: Many young, little care

11 Explain how populations can be the same size but have different densities
It depends on both the number of people and on space. Two populations with the same number can have different numbers depending on the space. A little house alone on the prairie

12 Explain why even distributions usually result from social interactions between individuals
Even distributions result when organisms attempt to get as far away from each other as possible. Carnivores have well defined territories that keep individuals apart. Interesting side note: Carnivores are dangerous, but they spend a lot of energy with back up plans so they don’t have to use it. Physical conflict harms everyone, if you can resolve a conflict with some posturing everyone is better off. Stay out of my territory

13 Why might natural selection favor a high reproductive rate in Type III organisms?
Though many young die the surviving young are well adapted to the environment More young also means more variation

14 Define Birth Rate Define Death Rate
Number of births over a period of time Define Death Rate AKA mortality Rate Number of deaths over a period of time There’s only 1000 pandas left

15 Flocks are too numerous, widespread and mobile.
Explain two difficulties an ecologist might have in counting a population of migratory birds. Develop & explain a method for estimating the size of such a population Flocks are too numerous, widespread and mobile. Tagging individuals is one solution Find a bottle neck Count numbers passing over a period of time Counting a herd of zebras can be tough


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