A unit of Lasting Forests
Sustained forests; sustained profits
evolving since March 30, 1999
of an Alternative Wildlife Resource Management
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The content and processes of this course are for the future. No one can know the future but some of us must risk making predictions about it and acting on those prediction. Otherwise, all education is historical; all of us become technicians working with old manuals. We must build on the strengths of the past.
Wildlife management is a part of natural resource management or wildland management. No terms are adequate; their meanings have been blurred by years of misuse. Why plants, aquatic life, and terrestrial animals should be separated and not called "wild life" needs to be discussed.
The first textbook on game management was that by Aldo Leopold (1933). There was active wildlife management work published in the U.S. in 1905 and before that. The textbook date is relevant only as a benchmark date.
Wildlife (primarily terrestrial animals (by convention)) is a resource, one among many. By analogy, it is as meaningless to discuss it separately as to discuss the liver of the human body without discussing blood, the cardiovascular system, and the digestive system.
Wildlife management in this course means:
making decision and acting
to manipulate the structure, dynamics, and relations of wild faunal populations, faunal spaces, and human populations
to achieve specific, pre-stated human objectives from the resource system.
Emphases throughout this course (watch for them):
Study Guide:
II
If wildlife management means "making decisions ..." what does this phrase include? I exclude trivial decisions such as whether to get a drink of water or not. There is wonderful philosophy behind what is a decision and whether they exist.
*Future states of a system are based on decisions.
*Decisions can only be made if there are 2 or more alternatives.
*Decisions should be influenced by measures and estimates of accuracy, precision, confidence level, acceptable accuracy, and the power of the tests.
Sample question: Decide: Which is the best project for bears, project A or B?
In what priority should we schedule mowing of wildlife clearings in the forest? (Sort then state the sequence)
Is fertilizer treatment A better than treatment B for growing warm-season grasses for quail? (Look: Which is greater? Do a t-test on the results. If the computed "t" is greater than the table value of "t" then there probably is a real difference.
Is there a real difference in the number of female fawns born due to forage changes? (Do a chi-square test; the "expected" ratio is 100:100.)
On which factors should I do more study? (correlation analyses can be useful)
Decide among who gets permits for blinds? Be fair. Use a random number generator (available in your Capper programs). Is there a global-warming effect on plant A? (Compare the variances before and after some date of interest. Use the F test.)
At what level should I stop irrigating my game bird food plant nursery? At what point should I stop sending brochures? (Use a break-even analysis)
How many more bird-watchers index units will I get if I expand the trail system? (Use a simple linear regression procedure; trail lengths on the x-axis.,)
How can I maximize the profit from 10 species on my area using forestry, rangeland and pasture management, and planned hunting trips, all over the next 50 years? (Use optimization procedures such as "linear programming.")
Unit 3 We rarely have enough time, money, skills, or other resources in wildlife work to look at all of anything. We need to take samples. There is an elaborate literature on sampling but it is important to know a few basics so that rapid progress can be made (lowering costs) with statisticians. To estimate minimum sample size we need to know how close the answer must be to "perfect truth." How accurate must our estimate of the average value be? We can agree that tons of fish for our wild raptors probably does not have to be as accurate as our measures of workers' head size for our safety-gear studies. If we say that d = proportion of the average (on either side), then it seems logical that the wider this range, the fewer samples we'd need to take. The relationship is inversely proportional to n, the sample size being estimated. We'd expect n = f (1/d). The greater the variance (s2) the more the samples needed. The greater the confidence you must have in the answer (related by your choice of the alpha level and a value for t) the more samples needed. The relationships are n = s2 t2 / d2. Where an average has been found (for a test situation) of 12 and a variance of 16, and when the wildlife manager decides that t can be about 1.7 for large samples and alpha of 0.10, and accuracy level can be plus or minus 0.05, then n = (16) (1.72) / ((12) (0.05))2 =128. In wildlife work it may not be possible to get 128 samples or to afford analyses on each one at $35 each. What is the change in n if your relaxed your accuracy requirement to 10% not 5%? The answer: n = (16) (1.72) / ((12) (0.1))2 = 32. Decisions about alpha levels and risk and accuracy can be very influential.
The manager's job is to maximize benefits and reduce costs and risks.
Poaching or Illegal Kill
Poaching is usually expressed as a (1) proportion of the annual harvest. There are other expressions such as (2) proportion of the population or (3) proportion of hunters.
The number of permits (or checked hunters past a point) can be estimated by
Permits = Number to be Harvested/Probable success
P = N/S
P = 400 / 0.20 = 2000
If poaching, K, occurs, then "number to be harvested," N, needs to be reduced Number to be Harvested = No. to be Harvested * (1.0-K) Where poaching, K, is about 0.30, then
H = N (1.0-K)
H = 400 (1.0 - 0.30) = 400 x 0.70 = 280
When H is 280, the permits are reduced as in:
P = 280 / 0.20 = 1400
Rearranging, and using other representative numbers:
Number to be Harvested = (Permits) (Success) (1 - Poaching Loss)
For example: 1000 = (3496) (0.22) (1.0 - 0.30)
Crippling also removes animals during hunting (or even research activities). These losses are estimated by "dead-deer" type surveys. Hunter reports can also be used -- those of game hit but not taken. Crippling is expressed as a proportion of the reported harvest. For example, the loss may be 0.25. Thus
Number to be Harvested = (Permits) (Success) (1.0 + Poaching Loss + Crippling Loss)
For example:
1000 = (Permits) (0.22) (1.0 + 0.3 + 0.2)
1000 = 0.341 Permits
Permits = 2933
The harvest (and permits) can be increased by reducing poaching, reducing crippling, and reducing hunter success (as by using primitive weapons). Influencing these three "hunter" rates must be part of the manager's responsibilities for decisions and actions.
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Last revision July 20, 2000.