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 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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