BASC_201_-_Lecture_21_(Mar_27_-_Prof._Chapman)_-_UNEDITED

BASC_201_-_Lecture_21_(Mar_27_-_Prof._Chapman)_-_UNEDITED -...

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Thursday, March 27, 2008 (BASC 201: Lecture 21) Prof. Chapman 8 MARCH 27, 2008 – Prof. Chapman 21
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Thursday, March 27, 2008 (BASC 201: Lecture 21) Prof. Chapman *Note : THIS IS AN UNEDITED VERSION OF THE NTC. The NTC is currently under review by the editor, and so the edited version will be posted shortly . Up to now doom and gloom. Now for the positive side. I. What we can do in an academic sense (large scale) 3 tactics 1. population viability analysis - The aim is to determine the minimum species population that will guarantee specie survival, whether a population is viable or not. By viable we mean can you sustain it over the long term. You manage your budget priorities according to what effort will bring conservation results. - types 1) subjective assessment is the most common way. It is a guess based on experience in the field. 95% of conservation work is done this way. 2) rule of thumb: guide your decisions by large rules that are subject to change over accumulation of knowledge. For example, in the 1970s, Mike Sulley (one of the father of conservation biology) and Franklin wrote a paper: It said that, from a genetic perspective, if you want to stop inbreeding, etc, you would need at least 50 individuals in the short term and 500 in the long term to allow the population to be viable. In the 1990s, a new paper was written with a new understanding of population genetics acquired over the past 20 years and changed the rule by an order of magnitude. Instead of 50 need 500 for short term and 5000 instead of 500 for long term population viability. Basically, these rules of thumb can change dramatically based on what we know. 3) analytical population model : these are demographic equations to predict future population sizes using estimates such as fecundity, mortality, and carrying capacity. They are simple models that look at demography. It is criticized for its lack of measuring the ecology. For example, how do habitat changes or logging influence fecundity? It is also difficult to know specific population parameters. For example, chimpanzees female start to cycle between the ages of 7 to 9 in one population whereas they’ll start to cycle two years earlier. This would dramatically change fertility rates. 4) computer simulations : you can change all sort of parameters (for example habitat or reproduction parameters) in the previous models and see what happens to the population. You can thus increase environmental feedback loops, explore impact of environmental stochasticity (for example, for every so random period of time there is going to be a drought or food scarcity). An example was done on the Brazilian wholly spider monkey. An brazilian endangered population. Largest south American monkey.
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Thursday, March 27, 2008 (BASC 201: Lecture 21) Prof. Chapman - The graph below looks at initial population size and then change the birth sex ratio in a random fashion. Observe what happens to population size over time. (eg: if you
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BASC_201_-_Lecture_21_(Mar_27_-_Prof._Chapman)_-_UNEDITED -...

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