national marsh bird monitoring: methods, pilot study, and where we go from here 16 january 2013
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National Marsh Bird Monitoring: Methods, Pilot Study, and Where We Go From Here 16 January 2013. Mark Seamans U.S. Fish and Wildlife Service Lakewood, CO. Webinar Outline. Background History of Marsh Bird Monitoring Survey Protocol and Sampling Design Pilot Study Methods Results - PowerPoint PPT PresentationTRANSCRIPT
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National Marsh Bird Monitoring:Methods, Pilot Study, and Where We Go From Here
16 January 2013
Mark SeamansU.S. Fish and Wildlife Service
Lakewood, CO
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Webinar Outline
• Background– History of Marsh Bird Monitoring– Survey Protocol and Sampling Design
• Pilot Study– Methods– Results
• Transition from Pilot to Operational Program
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Target Species
• Rallidae: clapper rail, black rail, king rail, sora, Virginia rail, and yellow rail, common moorhen, purple gallinule, American Coot, purple swamphen
• Ardeidae: American bittern, least bittern• Aramidae: limpkin• Podicipedidae: pied-billed grebe• Scolopacidae: Wilson’s snipe
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Background
• Workshops– 1998, 2006, 2011
• King Rail Conservation Plan 2006• Waterbird Conservation for the Americas
(Waterbirds Initiative) 2006 Assessment• AFWA-Webless Funding Priorities Report 2008• Independent research
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Background Continued
• Survey Protocol– Courtney Conway– http://www.cals.arizona.edu/research/azfwru/NationalMarshBird/
– Details of Protocol• Study Design
– Johnson, D. H., J. P. Gibbs, M. Herzog, S. Lor, N. D. Niemuth, C. A. Ribic, M. Seamans, T. L. Shaffer, W. G. Shriver, S. V. Stehman, and W. L. Thompson. 2009. A sampling design framework for monitoring secretive marshbirds. Waterbirds 32:230-215.
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Example of Hexagon Selection
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Example of Point Selection in Hexes
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Pilot Study
• Wisconsin 2008• Idaho 2009 – 2010• Kentucky 2009• New York 2009• Florida 2010• Michigan 2010• Ohio 2011
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HQ
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Objectives of Pilot
• Do protocol and design work together• Sampling effort to achieve certain levels of
precision for abundance or trend estimates. This included thoughts on how to stratify
• As pilot progressed shifted focus to work under a new paradigm– How to use monitoring to address management issues– Can monitoring meet information needs for species of
greatest concern
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Methods• The Data
– repeat visits within & among years, strata– Individuals identified (counted) each survey– Distance to individual estimated– Two-stage sample (variance estimator)– Covariates related to detection and abundance
• Analysis– Binomial Mixture Model with Horvitz-Thompson Estimator
• Detection related to distance done first– Zero-inflated Poisson model with Bayesian Framework– Abundance (& Occupancy) estimated by strata & year
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RESULTS
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Pilot Results: Abundance
ID KY MI NY OH WI0
10,000
20,000
30,000
40,000
50,000
American Bittern
200920102011
Abun
danc
e
ID KY MI NY OH WI0
50,000
100,000
150,000
200,000
Sora
200920102011
Abun
danc
e
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Pilot Results: Abundance
ID KY MI NY OH WI0
50,000
100,000
Virginia Rail
200920102011
Abun
danc
e
FL0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
Clapper Rail
20102011
Abun
danc
e
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Pilot Results: OccupancyFlorida Clapper Rail
2010: φ = 0.81 (0.70-0.92) 95% CI 2011: φ = 0.90 (0.80-0.97)
Idaho Sora High Quality Stratum2009: φ = 0.76 (0.63-0.83) 2010: φ = 0.86 (0.76-0.95)
General Stratum2009: φ = 0.38 (0.18-0.76) 2010: φ = 0.21 (0.10-0.39)
Wisconsin Sora2009: φ = 0.59 (0.50-0.70) 2010: φ = 0.49 (0.38-0.64) 2011: φ = 0.35 (0.25-0.54)
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Clapper Rail Detection Probability
Survey Period
15-31 Mar 1-14 Apr 15-30 Apr 1-14 May 15-31 May
Det
ectio
n P
roba
bilit
y
0.0
0.2
0.4
0.6
0.8
1.0
20102011
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Detection Probability of American Bittern in Idaho (A) and the
Upper Midwest (B)Survey Period
15-30 April
1-14 May
15-31 May
1-14 June
15-30 June
Det
ectio
n P
roba
bilit
y
0.2
0.4
0.6
0.8
1.0
200920102011
Survey Period
15-30 April 1-14 May 15-31 May 1-15 June 16-30 June
Det
ectio
n P
roba
bilit
y
0.0
0.2
0.4
0.6
0.8
1.0
20092010
B
A
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Precision of N as Function of % PSUs Surveyed
0 10 20 30 40 50 60 700
20
40
60
80
100
120
American bittern sora
Virginia rail
Percentage of Primary Sampling Units Surveyed
Coeffi
cien
t of V
aria
tion
B
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Precision of N as Function of # PSUs Surveyed
5 10 15 20 25 30 35 40 45 500
20
40
60
80
100
120
American bittern sora
Virginia rail
Number of Primary Sampling Units Surveyed
Coeffi
cien
t of V
aria
tion
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Partitioning Variance
𝑣𝑎𝑟 (�̂� )=𝑁 (𝑁−𝑛 )𝑛 (𝑛−1 ) ∑
𝑖=1
𝑛
(𝑦 𝑖−𝑟 𝑀 𝑖)2+𝑁𝑛 ∑
𝑖=1
𝑛
𝑀𝑖 (𝑀𝑖−𝑚𝑖)𝑠𝑖2
𝑚𝑖
𝑠𝑖2= 1
𝑚𝑖−1∑𝑗=1
𝑚 𝑖
(𝑦 𝑖𝑗− 𝑦 𝑖 )2�̂�=
∑𝑖=1
𝑛
�̂� 𝑖
∑𝑖=1
𝑛
𝑀𝑖
.
�̂� 𝑖=𝑀 𝑖
𝑚𝑖∑𝑗=1
𝑚𝑖
𝑦 𝑖𝑗
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Inferences from Pilot
• There are a lot of some species on the landscape
• Rare species are an issue• Omnibus approach to monitoring and what
we did during the Pilot
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Inferences Cont.
• What can omnibus approach give us?– Inform harvest management, except for KIRA– Inform state conservation plans? Depends.– May reveal general habitat affinities
• What omnibus approach cannot give us.– An assessment of KIRA or BLRA populations– Why they are declining and what to do about it– How any species responds to habitat management
• Water levels, burning, invasive management, etc.
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Proposed Way Forward
• Mix of omnibus and “management monitoring”
• Mix of two would give us:– Experimental comparisons– Efficient way to meet needs of multi-species
survey
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King Rail Management
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Data can be used to:
• Nwrp = abundance from treatment areas
• Ngen = abundance from general whole area
• H0: Dwrp = Dgen
• Ntotal = Nwrp + Ngen (a status assessment)
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Marsh Bird Conservation Program
Steps to Conserving & Managing Marsh Birds1. Define Conservation Issues2. Develop Hypotheses or Management
Objectives3. Develop & Implement Management Actions4. Monitor5. Learn and repeat as necessary
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