Post on 08-Jan-2018
description
Introduction to Occupancy Models Key to in-class exercise are in
blue
Jan 8, 2016 AEC 501 Nathan J. Hostetter Occupancy Abundance often
most interesting variable whenanalyzing a population Occupancy
probability that a site is occupied Probability abundance is >0
Detection/non-detection data
Presence data rise from a two part process The species occurs in
the region of interest AND The species is discovered by an
investigator What do absence data tell us? The species does not
occur at that particular site OR The species was not detected by
the investigator Occupancy studies Introduced by MacKenzie et al
and Tyre et al Allows for collection of data that is less intensive
thanthose based on abundance estimation Use a designed survey
method like we discussedbefore simple random, stratified random,
systematic,or double Multiple site visits are required to estimate
detectionand probability of occurrence Why occupancy? Data to
estimate abundance can be difficult tocollect, require more time
and effort, might be morelimited in spatial/temporal scope
Obtaining presence/absence data is Usually less intensive Cheaper
Can cover a larger area or time frame Might be more practical for
certain objectives Why occupancy? Some common reasons and
objectives
Extensive monitoring programs Distribution (e.g., ranges shifts,
invasive species, etc.) Habitat selection Meta-population dynamics
Species interactions Species richness Occupancy studies Key design
issues: Replication Temporal replication:
repeat visits to sample units Spatial replication: randomly
selected sites or sample units within area ofinterest Model
parameters Replication allows us to separate state andobservation
processes -probability site i is occupied. pij -probability of
detecting the species in site i at time j,given species is present.
Blue grosbeak example Associated with shrub and field habitats,
medium sized trees,and edges Voluntary program to restore
high-quality early successionalhabitat in Southern Georgia (BQI
bobwhite quail initiative) Are grosbeaks more likely to use fields
enrolled in BQI program? Blue grosbeak example N = 41 sites
(spatial replication)
K = 3 sample occasions (temporal replication) Example data: Site S1
S2 S3 1 2 3 41 Model assumptions Sites are closed to changes in
occupancy state between sampling occasions Duration between surveys
The detection process is independent at each site Distance between
sites Probability of detection is constant across sites and visits
orexplained by covariates Probability of occupancy is constant
across sites or explained by covariates Enough talk, Lets work
through the blue grosbeak example Introduction to R Basics and
Occupancy modeling Intro to R: Submitting commands
Commands can be entered one at a time 2+2 [1] 4 2^4 [1] 16 The R
environment Script file (File|New script) R Console Text file
Save for later use Submit command by highlighting command at
pressing Crtl R R Console Where commands are executed R console:
Interactive calculations
#Try the following in the script file: 2+2 a < #create the
object a a #returns object a A #Nope, case sensitive b