Michigan Predator-Prey Project

Authors: Tyler Petroelje, Nick Folwer, Todd Kautz, Nate Svoboda, Jared Duquette, and Jerrold Belant of Mississippi State University, Dean Beyer of Michigan Department of Natural Resources. A presentation given at the 2015 Midwest Wolf Stewards Conference

Transcript

1. Michigan Predator-Prey Project:
   Wolf-Deer Relationships in
   Michigan’s Upper Peninsula
   Tyler Petroelje, Nick Fowler, Todd Kautz, Nate
   Svoboda, Jared Duquette, Jerrold Belant-
   Mississippi State University
   Dean Beyer- Michigan Department of Natural
   Resources
   

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4.  Abundance Estimates
    Collar and monitor adult female deer
    Collar and monitor neonate deer
    Collar and monitor predators
    Monitor inter-year variation in weather
    Estimate available habitat cover and forage
   

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5.  White-tailed deer – Remote camera surveys
    Wolves – Track surveys
    Coyotes – Howl surveys
    Bobcats – Winter hair snares
    Black bear – Summer hair snares
   

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7. • ’13 – 36 (0.036/sq. km)
   • ’14 – 38 (0.038/sq. km)
   • ‘15 - 36 (0.036/sq. km)
   

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8.  Clover traps (January-
   March)
    VHF radio-collar and
   vaginal implant transmitter
   on pregnant Does
   • Survival monitored
   weekly via airplane
   • Ground locations 3
   times/day during May-
   August
   

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9.  2013
    49 females collared
    100% of adults pregnant (42)
    89% of yearlings pregnant (9)
    2014
    45 females collared
    100% of adults pregnant (44)
    67% of yearlings pregnant (6)
    2015
    45 females collared
    98% of adults pregnant (46)
    0% of yearlings pregnant (2)
    + 10 winter collared fawns
   

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10. Fawn:Doe
    Ratio
    1:1
    Fawn:Doe
    Ratio
    0.27:1
    Fawn:Doe
    Ratio
    0.47:1
    49
    27
    6
    8
    22
    7
    0
    10
    20
    30
    40
    50
    60
    Adult Fawn Yearling
    2013
    Female
    Male
    45
    6 7
    5 6 4
    0
    10
    20
    30
    40
    50
    Adult Fawn Yearling
    2014
    Female
    Male
    45
    10
    2
    4
    11
    2
    0
    10
    20
    30
    40
    50
    Adult Fawn Yearling
    2015
    Female
    Male
    

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11.  2013: 54%
     January-April: 70%
     2014: 38%
     January-April: 42%
     2015: ...
     January-17 April: 80%
    Importance of
    condition
    between years?
    Good bone marrow Poor bone marrow
    

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12. 0
    0.1
    0.2
    0.3
    0.4
    0.5
    0.6
    0.7
    0.8
    0.9
    1
    Jan Feb Mar
    Rump Fat Depth (cm)
    2015 2014
    

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13. 1.90
    2.10
    2.30
    2.50
    2.70
    2.90
    3.10
    3.30
    JAN FEB MAR
    BODY CONDITION SCORE (1-5)
    Crystal Falls (2013-2015) Escanaba (2009-2011)
    

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14. 0
    10
    20
    30
    40
    50
    60
    70
    80
    31-Dec
    7-Jan
    14-Jan
    21-Jan
    28-Jan
    4-Feb
    11-Feb
    18-Feb
    25-Feb
    4-Mar
    11-Mar
    18-Mar
    25-Mar
    1-Apr
    8-Apr
    15-Apr
    22-Apr
    29-Apr
    Snow Depth (cm)
    Date
    Snow Depth
    '12-'13
    Snow Depth
    '13-'14
    Snow Depth
    '14-'15
    

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16. 0
    2
    4
    6
    8
    10
    12
    14
    16
    18
    Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
    Number of mortalities
    2013 Mortality events
    2014 Mortality events
    2015 Mortality events
    

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17.  VIT drop site (birth
    site) searches and
    opportunistic captures
     Measurements and
    blood/hair samples
    • Expandable VHF radio-
    collar and ear-tags
    • Daily survival monitoring
    via ground telemetry
    

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18.  2013
     43 fawns (26 male, 17 female)
     2014
     25 fawns (12 male, 13 female)
    

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19.  2013
     0 of 43 fawns surviving 2013 (May 2013-May 2014)
    Apparent survival: 0% (*13 censors*)
     2014
     2 of 25 fawns surviving 2014 (May 2014 – April 2015)
    Apparent survival: 11% (*7 censors*)
    

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20.  2013 – average birth mass 3.1 kg (6.8 lbs.)
     Lower mass and lesser survival
     2014 – average birth mass 3.7 kg (8.1 lbs.)
     Greater survival when born with greater birth mass,
    same trend observed in Escanaba
     Why a greater weight following a tougher winter?
     Only the adult females in best condition made it through
    winter
     Possibly more singletons, more resources devoted to one
    fetus rather than two (hard to identify true twinning rates)
    

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22. Estimated Fawn Age (Weeks)
    Number of Predations
    

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23.  Capture with foot hold traps
     Morphometrics
     Biological Samples
     Ear tags
     GPS collar
    Capture totals
     4 wolves from 3 packs collared in 2013
     5 wolves from 3 packs collared in 2014
    

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24. Predation Investigation
     GPS locations implemented
    into GIS and “clusters” are
    determined
     Cluster is defined spatially
    as ≥8 locations within 50 m
    of each other
     Search area using
    technicians and detection
    dogs
    

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25.  Investigated 568 clusters (2014)
     Investigated 868 cluster (2013)
     Black bear – 1.6% fawns (insects/berries)
     Bobcat – 3.7% fawns (snowshoe hare/grouse/porcupine)
     Coyote – 1.6% fawns (snowshoe hare/grouse/adult deer)
     Wolf – 3.9% fawns (yearling & adult deer)
    

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26.  Harsh winters resulted in poor condition deer
     Very low survival, fewer deer producing fawns.
     Largest source of mortality ~ Predation
     Coyotes largest predator of adults and fawns, similar to Escanaba study
    area
     Wolves have greater individual predation rate on fawns but at the
    population level have a lesser impact on the deer herd
     Winter of 2014-2015 earlier melt than previous 2 years.
     Lesser predation/mortality
     Deer condition indices similar to previous years.
     Early melt increases survival and may better prepare deer for fawning?
     Importance of late winter forage and late season snow depth and
    melting date. Fawn birth mass and available cover important for
    survival
    

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