Rural System's

Modern Wild Faunal Resource System Management
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The Basics for Estimating Population Size

Say no! Resist making an estimate. Why?

Such estimates are:

Procedures:

  1. Resist
  2. Resist, then use richness
  3. Use relative values as density estimates (probably more than on Area X)
  4. Use trends in harvests, counts, etc.
  5. Use trends and correlations with trap nights, track counts, coo-call counts, harvest trends, trapped animals, fur reports, mail-carrier counts, bird census.
  6. Adjust counts where feasible with phenologic observations
  7. Use log of trends log(x+1)
  8. Compare areas. Use similarity index(s)
  9. Pielou's s = 2j / 2ab - (a+b)j
    j is the species on both area A and B
  10. Assume animals are correlated (e.g., with deer harvests)
  11. Make adjustments in records for illegal harvests
  12. Capturing animals is a great stress to them. Some die, but that is said to be one of the risks. I would like to study similar populations with different periods (and/or styles) of handling. The effect of the "treatment" should show up in population estimates, reproduction, and even in indices of food utilization.
  13. In live trapping to do capture-recapture studies of animals to estimate their densities, trap shyness as well as addiction is encountered. Some animals seem to love the bait, trap, etc.! Alternative nights of bait and no-bait with clean traps are needed to study trap addiction.
  14. Use representative habitats (stratified work with GIS)
  15. Do total counts (time-area counts), cumulative counts
  16. Track and sign counts (pellets, etc.)
  17. Drives with track counts
  18. Roadside counts
  19. Transects (with width and without width)
  20. Trap nights
  21. Use animal weight to estimate home range, than divide area into home-ranges for animals.

    A powerful estimator is available for population abundance using estimates of animal home range. One or two animals per home-range area should approximate the total animals within an area and contribute to convergence on a useful population estimate.(These equations are based on data from many studies in many areas. The high R-square values are impressive.)

    Where H = home range in hectares and W is weight in gram:

    H = 0.002 W1.02 herbivores

    H = 0.059W0.92 omnivores

    H = 0.11W1.36 carnivores

    And taken together,

    H = 0.008W1.08 with r2 = 0.6

    H = f (1/precipitation, latitude)

    H = f(sex, age) related to

    H = f(weight)

    Food consumption/day in grams Carnivores

    Where FCc is food consumption by carnivores then:

    FCc = 1.7W0.68 ± 0.02

    approximately FCc = 1.7 W0.66 grams

    Birds

    FCb = 0.51W0.63 ± 0.11

    approximately FCb = 0.5 W0.66

    From: Harestad, A. S. and F. L. Bunnell. 1979. Home range and body weight - a reevaluation. Ecology 60(2):389-402.

  22. Use the bounded count procedure:

    Concept: If you see more on some days, how long will it take to see them all?

    Observations: 100, 98, 118, 112, 113, 62, 105

    Select largest number A = 118

    Select next largest B = 113

    N = 2A-B = (2 x 118) - 113 = 236 - 113 = 123

    NL = 118 (at least these were all seen)

    NU = A + ((1.0 - a / a) (A - B))

    NU = 118 + )(1 - 1.05)/0.05)(118 - 113)

    NU = 118 + (19)(5) = 213

  23. When an estimate is needed and funds are available, then use Lincoln-Petersen based model.

    Premise: total marked animals (M) are to the unknown number (N) of animals, as the marked animals (m) are to the total animals in a sample. Thus: N = Mn/m

    The standard error is ([M2n(n-m)] / m3)0.5

    Where M = 27, n = 23, m = 17;

    then SE = 4.5

    Since N = 36.5,

    the upper limit of the estimate is (36.5 + 2(4.5)) = 45.4

    and the lower limit (2 standard errors) is (36.5 - 9.0) = 27.5

    The population, 95 times out of 100, will lie between 27 and 46 animals.

  24. Use Bailey's unbiased estimator:

    N = (M(n+1) / (m +1)) - 1

    SE = ((M2 (n+1)(n-m)) / ((M + 1)2 (m + 2)))0.5

  25. Schnabel
  26. Schumacher-Eschmeyer
  27. Jolly-Seber
  28. Minta and Mangel, Ecology 70(6): 1738, December, 1989.
  29. Use Removal rate or the Removal Index:

    Example: Pheasants

    100 cock "crows" per hour before the hunt or in an early survey

    3 removed

    Therefore:

    70 crows heard later (30 "lost")

    X = 10

    There were 10 pheasant cocks originally. Similar analyses can be made with track counts after deer hunts.

  30. Use Indicators:
    1. feces
    2. burrows
    3. cavities
    4. lodges
    5. grouse drumming
    6. turkeys gobbling

  31. Use Moran plot of density indicators over time to gain insights about stability of the population.

Resisting the desire or pressure to estimate populations is counterintuitive for the person who gets into the field of faunal resource management because of their love of animals or desire to "work with" animals. Estimating abundance needs to be resisted. Failing that, converge on an estimate.

See uses of estimates within Managing Populations

"Estimating Numbers of Terrestrial Birds," edited by C. John Ralph and J. Michael Scott, has just been brought back (2003) into print by The Blackburn Press, making it available to libraries, scholars, researchers, ecologists and field ornithologists who would like to own or replace a copy of an invaluable reference.

See Ken Burnham and David Anderson's comments on AIC Myths and Misunderstandings.

References

(Davis, Part 2, Techniques Manual)

Abramson, N. and J. Tolladay. 1959. The use of probability sampling for estimating annual number of Angler Days. Calif. Fish and Game 45(4): 303-312.

Bergerud, A. T., and W. E. Mercer. 1966. Census of the willow ptarmigan in Newfoundland. J. Wildl Manage 30(1):101-113.

Brotzman, _ L._and _ H. Giles, Jr. 1966. Electronic data processing of capture-recapture and related ecological data. J. Wildl. Mgmt. 30(2): 286-292.

Chapman, D. G. and W. S. Overton. 1966. Estimating and testing differences between population levels by the Schnabel estimation method. J. Wildl.Manage. 30(1):173-l80.

Chapman, D.G. and G. I. Murphy. 1965. Estimates of mortality and population from survey-removal records. Biometric Soc. 2l(4):921-935.

Davis, J. 1965. The "singing male" method of censusing birds: a warning. Condor 67(1):86-87.

Hayne, D.W. and D. Q. Thompson. 1965. Methods for estimating microtine abundance. N. Amer.Wildl. and Nat. Res. Conf. 30:393-400.

Hein, D. Dale. 1966. Float counts vs flight counts as indices to abundance of nesting wood ducks. J. Wildl. Mgmt. 30(1):13-l6.

Jolly, G. M. 1965. Explicit estimates from capture-recapture data with low death and immigration--stochastic model. Biometrika 52:J3l5-337.

Lovaas, A. L., J. L. Egan, and R.R. Knight. 1966. Aerial counting of two Montana elk herds. J. Wildl. Mgmt. 30(2):364-369.

Martinson, R. K. 1966. Proportion of recovered duck bands that are reported. J. Wild1. Mgmt. 30(2):264-268.

Overton, W. S. 1965. A modification of the Sshnabel estimator to account for removal of animals from the population. Wildl. Mgmt. 29(2):392- 395.

Pe1ikan, J., J. Zejda)and V. Holisova. 1964. On the question of investigating small mammal populations by the quadrat method. Acta Theriologica 9(1):24 pp.

Reid, V. H., R. M. Hansen, and A. L. Ward. 1966. Counting mounds and earth plugs to census mountain pocket gophers. J. Wildl. Mgmt. 30(2):v327-334.

Rupp, R. S. 1966. Generalized equation for the ratio method of estimating population abundance. J. Wildl. Manage. 30(3):523-526.

S ittler, O. D. 1965. Theoretical basis for estimating deer population from automatically collected data. J. Wildl. Mgmt. 29(2):38l-387.

Stirling, I., and J. F. Bendell. 1966. Census of blue grouse with recorded calls of a female. J. Wi1d1. Mgmt. 30(1):184-187.

Swinebroad, J.. 1964. Net-shyness and wood thrush populations. Bird Banding 35(3):196-202.

Talbot, L.M. and D. R. M. Stewart. 1964. First wildlife census of the entire Serengeti-Mara region, East Africa. J. Wi1d1. Mgmt. 28(4):815-827.

Yates, F.1965. Appendix on net shyness. Proc. Royal Soc. Zool. 144(1):22-23.

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Last revision January 17, 2004.