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2702633
Biotelemetric methods
Descripción
exam
Sin etiquetas
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Mapa Mental por
Ron Togunov
, actualizado hace más de 1 año
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Creado por
Ron Togunov
hace más de 9 años
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Resumen del Recurso
Biotelemetric methods
Acoustic telemetry
Implant
External
Wave properties
Pressure wave
Environmental effects
^ Temperature ^ speed
^ pressure ^ speed
^ Salinity ^ speed
Passive
Active
Sonar
Sizemic
Positioning
Echo-location
Sonar
Passive
Sizemic
Triangulation
Using implats
listening to sounds
GPS fastloc
aquire pseudorange
Too large to send over satellite
Euphemurus data is aquired after tag retrieval
Data Aquisition
Popup tag
Popup Satellite archival tag
SRDL
PSAD
Acoustic
Data storage Tags (DSTs)
RF Telemetry
Wave properties
electromagnetic radiation
Electric & magnetic fields at right angles
Orrentation determites polarity
Determined by electric field
Frequency
Wavelength
Period
VHF
30-300 MHz
on ground
UHF
over 300 MHz
Sattelites
Amplitude
Behaviour
Defraction
Reflection
Absorption
Cannot pass through salt water
Not absorbed by dielectrits
Scattering
Interference
Dopler effect
Antennae
emit and detect RFs
Gain: degree of directionality
Described by antennae pattern & beam width
Impedence
Resistance to current flow
impedence matching
impedence associated with wavelength must be same in antenna and Coax cable
Positioning
VHF
Radio tracking
Very laborious
Sattelite
GPS
Tag listens to GPS
Euphemurus data
Positions of the satellies relative to earth
Pseudorange
Distance between tag and satellitse
Argos
use doppler effect
More expensive
Data aquisition
VHF
UHF
Argos
Irridium
Handshaking
Satellite network
GSM
Cell phones
Datalogger
Must be retrieved
Stores info on board
SRDL
Ethics
Three Rs
Refine
Best methots
Replace
Model
non wild animls
Reduce
Smaller sample
Three issues with Biotelemetry
Intensive use of capture and handling techniques
use methods from one spp in another
Know your animal
Surgical procedures are invasive
Risk of infection
Know your technology
Test things out
Physiological impoct on animalso
mass must be less than 2%
right shape
External tags can get caught in things and change bedavior
Attachment is important
Animal's behaviour
Risk of infection
How it will be released
negative results must be reported
Animal growth
Stretchy collars
Limited potential for monitoring posts-release.
Technology
Battery
Sensors
Trasnducer
Transmitter
Transponder
emits signal after interigation
E.g fish & birds in nests
Very light/cheap
Biology
Home range
Minimum Convex polygon
samllest polygon contiaingn 95% of all points
Sensitive to small sample size and
Kernel Density estimation
Utilization distribution
Probability distribution. probabilitf of seeing an animal in a location
Smoothing the point pattern
Based on bandwidth
hRef
Not very accurate. esp when distribution is clumped
Least squares cross validation
bandwidth minimizes variation between true and estimated UD
Sensetive to sample size
Subjective choice
See intensity of area use
Brownian bridge
Calculates UD
Takes into account sequence of poins
Estimated w/ Maximum likelihood
Habitat selection/utilization
Detirmine area restricted use
Time spent in area
Convert area to grid
Time spent in each square
Must be same for all individuals
First passage time
Time to cross a circle of a given radius
Pass through areas have low FPT
Foraging areas have high FPT
Increases with radius
plot variance of log(FPT)
Highest variance = spatial scale of ARS
estimating environmental covariates
Cox-proportional hazards model
Probability of an event occuring
output is a ratio
Below 1 = less probability animal will leave
LME
Include fixed and random effects
Fixed effetcs
informative
Random effets
Uninformative
needed to avoid pseudoreplicaiton to minimize type 1 error
eg. measuring same individual or temporally correlated data.
eg. individual ID
Can be confounding
Assume normality
GAMM
When we do not have a normal distribution
And transformation is not appropriate
Model realtionship as a smoothing function
Penalized qubic regression splines
Based on knots
More knots fit data closer
Migration
Data filtering
first step of data analysis
Sources of error
Errors can occur from insufficient satellite (ARGOS)
Animal motion
Methods
Speed Filter
Removes locations greater than given speed
Speed Distance ange
Removes locations with unrealistic speed and turning angle higher than threshold
Aust filter
Based on moving filter
Speed between each point in window. W/ speed limit
Douglas Argos filter
Uses 3 methods based on distance threshold
Can include turning angle test
Multiple state-space methods
Estimate state of unobservable process from observed dataset
looking for outliers/ unlikely data points
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