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WILD MGT TECHNIQUES

by: Miss Jayme Block

40

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30

WILD MGT TECHNIQUES RNR 4011

Miss Jayme Block
LSU
GPA 3.89

F. Rohwer

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COURSE
PROF.
F. Rohwer
TYPE
Class Notes
PAGES
30
WORDS
KARMA
25 ?

Popular in Renewable Natural Resources

This 30 page Class Notes was uploaded by Miss Jayme Block on Tuesday October 13, 2015. The Class Notes belongs to RNR 4011 at Louisiana State University taught by F. Rohwer in Fall. Since its upload, it has received 40 views. For similar materials see /class/222668/rnr-4011-louisiana-state-university in Renewable Natural Resources at Louisiana State University.

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Date Created: 10/13/15
Focus on three very distinct estimation techniques Markrecapture Line transects Change in ratio Capturerecapture models C animals caught during second sampling period 5 average capture probability estimated from capture history of individual animals Lincoln Peterson Index estimator simplest model Involves 2 samples closed population Procedure 1 Capture and mark a subsample of population 2 Release the sample and allow to intermingle 3 Capture or observe to get estimates of number of marked and unmarked individuals Example 1 catch 50 animals mark amp release 2 days later catch 25 animals of which 5 are marked What is population 250 15 of population is marked marked 50 and that is 15 of population therefore N250 Formula N population size n1 animals captured marked and released n2 animals seen at later time interval unmarked marked m marked animals seen on second survey rs m marked animals on second survey resiqhted n1 total marked at time of capture N n2 B N n2 m n1 N n2 n1 m Rememberthis one Prior example N n2 n1 m N 25 0 505 N 250 LincolnPeterson Assumptions 1 the population is closed keep interval short 2 there is no marker loss can estimate by double marking techniques 3 all animals are equally likely to be captured in each sample Best to use two differing techniques to deal with biases in capture probabilities Example capture to mark but use resighting of a visual marker for second sample capturerecapture models are very complex and sophisticated entire courses on subject measure population size measure population processes birth amp death models for multiple sampling and open populations Line transect Line Transect Is how to measur observability o o o o o o o g o m o 0 g 0 o o o o Line Transect estimate beta aftert e fact Measure distance from transect line f f u u t O 0 a Frequency of observations Assume spaced or random distribution Distance from transect line Line transect C animals seen from the transect B probability of seeing an animal estimated from distribution of rightangle distances of sighted animals doing transects Key assumptions of line transect 1All animals on line are counted 2 Animals are fixed in location where sited and not sighted twice 3 Distances measured exactly 4 Sightings are independent events flushing one animal does not cause another to flush 5 5 decreases as distance from the line increases Most of the complication of line transect is to measure relationship of B to distance Change in ratio need 2 types 0 O O O O O O O O O 0 a 0 Change in ratio need 2 types 0 C O o O O 0 g C O O 0 CIR initial sampling of x 8 It I CIR differential harvest of x e o O O O g O 0 0 II 1 1 CIRr mpling of x amp y CIR What is the population 0 O O o O O 0 g 0 O O 0 Change in ratio Don t actually measure 15 directly but measure the relative observability of two obvious groups eg male and female Procedure 1 count two population segments x amp y 2 harvest differentially amp know the numbers ofx amp y harvested 3 recount two population segments note change in ratio Example 1 Roadside count 15 bucks amp 15 does 2 Harvest 100 bucks 3 Roadside count 10 males amp 20 females Example 1 Roadside count 15 bucks amp 15 does 2 Harvest 100 bucks 3 Roadside count 10 males amp 20 females Population size before harvest Harvest of 100 males Changed the population ratio from 11 to 1 male per 2 females Population was 400 200 males amp 200 females Formula as in book N1 total population size before the removal unknown N2 total population size after the removal unknown RX number of xtypes removed known Ry number of ytypes removed known R RX Ry the total number of animals removed known X1 of xtype animals in the initial population unknown Y1 of ytype animals in the initial population unknown P1 X1N1 the proportion of xtype animals before the removal Note that X1 and N1 are both unknown So how do we estimate P1 From the initial count data of males amp females P1 S1xS1x S1y P2 X2N2 the proportion of xtype animals after the removal Estimate as above P2 82X 82X 82y Rx N 1 P1 39 P2 Note that X and N terms are not in the equation Roadside count 15 males amp 15 females Harvest 100 bucks Road count 10 males amp 20 females Define x amp y any way you want x females y males P1 S1xS1x S1y x females y males N 0 100 02030 0 1530 2030 o 100 0667 gt2 32X 32X 32y 05 0667 667 01667 Q 30 4oo Assumptions of Change in Ratio 1 xtype and ytype animals have equal observability 2 Population is closed except for removals Best to keep interval between the 2 estimates of P and removal a short as possible 3 Number of xtype and ytype removals is known 4 Proportion of xtypes in harvest differs from population Note that the bigger the change in the ratio then the better the estimate Indices ofAbundance N 03 but we cannot or do not time amp measure 5 Thus we use C as a relative measure index of N VALUABLE can compare across time or space What do we hope for 1 B is constant That way C is a constant proportion of N Index of Population Population Size Indices ofAbundance N 03 but we cannot or do not time amp measure 5 Thus we use C as a relative measure index of N What do we hope for 1 B is constant 2 B has a slope of nearly 1 3 No nasty curvilinearity Index of Population Population Size Indices ofAbundance N 03 but we cannot or do not time amp measure 5 Thus we use C as a relative measure index of N What do we hope for 1 B is constant 2 B has a slope of nearly 1 3 No nasty curvilinearity 4 Might expegt some curvilinearity Nondispla in Floaters Index of Populatio Population Size Examples of Indices Counts of animals call counts mourning dove woodcock BBS Christmas bird count roadside pheasant rabbit fox spotlight counts of alligators Counts of animal sign track counts especially predators canids fecal or pellet counts nest counts Indirect indices tracks fecal or pellet counts nests Such counts often more accurate than counts of animals Advantages not so dependent on skill of observer easy to standardize with multiple observers act of viewing does not influence viewing conditions amp timing relatively unimportant Disadvantages time lag between sign and when observed relationship to actual density more frequently nonlinear than counts of animals

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