Exam (elaborations)
Wildlife Techniques FINAL (1)
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Wildlife Techniques FINAL (1)
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Wildlife Techniques FINAL-Managing habitat
-Managing people
-Managing wildlife populations directly - ANS-3 legs of wildlife management
A set of human decisions and actions that affect wildlife populations
- based in math and science - ANS-Define wildlife management
1. wildlife held as a public trust
2. elimination of market hunting
3. allocation of wildlife by law
4. kill only for legitimate purposes
5. wildlife as an international resource
6. science-based wildlife policy
7. democracy of hunting - ANS-7 Pillars of the NAM
- the classic scientific method of Chamberlain 1980
- science isn't "one and done", experiments should be retested throughout time
- each time we conduct a study we learn something, and can update our theory and try again -
ANS-The Process of Science
1. problem/question
2. theory
3. hypothesis
4. predictions
5. experiment/data collection
6. evaluate outcome - ANS-6 steps of scientific method
increases natural understanding on the natural world and informs management decisions
effectively - ANS-advantages of using science of wildlife management
takes longer and is harder to make decisions because it is no longer based on 'gut' feelings -
ANS-disadvantages of using science in wildlife managment
permits conclusions about cause and effect relationships between variables - ANS-advantages
of experimental research
- easier to design
- represents what is 'really' happening in the messy world - ANS-advantages of descriptive
research
, can be costly/not necessarily what would happen in the real world - ANS-disadvantages of
experimental research
cannot conclude cause-and effect - ANS-Disadvantages of descriptive research
To record measurements on a subsample of units from a larger population - ANS-sampling
- To gather preliminary data
- To estimate parameters (abundance of animals, trees, etc)
- To answer questions (Does treatment work?) - ANS-why do we sample
1. simple random
2. systematic random
3. stratified random - ANS-3 common sampling designs
every sampling unit has the same probability of being selected
- commonly obtained using random number generator
- best when there is no spatial or temporal trends are expected, little is known about the variable
being measured
ex. quadrats in a field, point sampling across a large area - ANS-simple random
•Randomly select a sampling unit as a starting point
•Thereafter, sample at EQUAL INTERVALS
•Useful when simple random sampling is difficult (e.g., surveying visitors in a park)
•Helpful when we assume spatial/temporal autocorrelation
•values of units that are closer together are more similar than values for units farther apart
ex. habitat use of radio-collared animal - ANS-systematic random
•When your population/area is made up of distinct sub-groups that are expected to influence the
response
•Subdivide the population/area into STRATA
•Within a strata, every unit has an equal probability of being selected
-Draw a simple random sample from each strata
-Sample size could be similar or different between strata
ex. plot sampling across a forest to describe bird communities - ANS-stratified random sampling
the degree of under or over estimation relative to the true value - ANS-bias
refers to the certainty in our estimate (large standard errors = imprecise; small standard errors =
precise) - ANS-precision
Unbiased and Precise - ANS-accurate
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