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Dan Gibson Erik Blomberg Michael Atamian Jim Sedinger

A multi-scale approach to assess sage-grouse nesting habitat Comparing nest site selection and nest success. Dan Gibson Erik Blomberg Michael Atamian Jim Sedinger. Overview: Sage-grouse. Why is knowledge regarding habitat use important?.

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Dan Gibson Erik Blomberg Michael Atamian Jim Sedinger

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  1. A multi-scale approach to assess sage-grouse nesting habitatComparing nest site selection and nest success Dan Gibson Erik Blomberg Michael Atamian Jim Sedinger

  2. Overview: Sage-grouse

  3. Why is knowledge regarding habitat use important? • Habitat degradation is the primary mechanism driving sage-grouse population declines • Habitat will continue to be degraded • We need to establish what habitat is important (during various life history stages) for species persistence at multiple scales and manage it appropriately

  4. So, what is “important” habitat? • Is it being used? • Are individuals successful? • In theory, the relationship between habitat selection and success compares what habitat features improved fitness along an organism’s evolved life history, and what improves fitness in its current environment

  5. Research Objectives • Investigate which habitat characteristics sage-grouse are being selecting for as nesting habitat and how they influence nest success • Use this information to develop tools to make more informed management decisions

  6. Monitored female sage-grouse from 2003-2012 in Eureka Co. Nevada • Ground level vegetation data was collected at nest and random sites • ~410 nests

  7. Nest Site Selection (RSF models) Binomial generalized linear mixed models (GLMM) in R (lme4 package) Random effects: year and individual Two independent analyses performed (two scales: “spatial” and “local” Nest Survival Nest survival module in Program MARK Predictor variables Ground-scale vegetation Spatial-scale habitat structure Temporal Disturbance Individual heterogeneity Analyses

  8. Results • Nest Survival • Estimates of overall nest survival were low (17%) • Note: It is very difficult to achieve a lambda >1.0 at this level of success • Selection • Local: selection pressures were the greatest for various forms of cover and forb availability • Spatial: provided a mechanism to delineate nesting from available habitat using relatively coarse spatial metrics • Very few habitat features were supported to influence both nest selection and nest success

  9. Selection versus Survival 1 denotes spatial selection model 2 denotes local selection model Bold values significant

  10. Non-sagebrush shrub cover & Forb cover

  11. Sagebrush canopy cover * Guidelines to manage sage grouse populations and their habitats Connelly et al. 2000

  12. Grass cover * Residual grass height

  13. * Guidelines to manage sage grouse populations and their habitats Connelly et al. 2000

  14. Pinyon-Juniper encroachment

  15. Exotic Grasslands

  16. Summary so far… • Very few habitat features exhibited a selective pressure and influenced nest success • Current management decisions geared to improve sage-grouse populations through modifying nesting conditions may ultimately not be successful • Current guidelines for management of sage-grouse nesting habitat do not appear to be appropriate for central Nevada • So, can we develop tools to assist management?

  17. Developing a nesting habitat use model Elevation * Slope + Distance from lek * Amount of habitat classified as sagebrush (1000m)

  18. Delineation of nesting habitat • ~18% of surrounding habitat was classified as suitable which encompassed 75% of nest points • Estimate of concordance = 0.72

  19. Independently collected nest locations fit the model well … for the most part • Additionally, statewide spring telemetry locations fell within “suitable habitat” at a high rate

  20. Demographiccontinuity Early Brood Rearing Nesting Late Brood Rearing • Establish what habitats are required during “important” life history stages • Protect the commonalities • Allow for connectivity between stages Probability of Use *Atamian et al. 2010

  21. Thanks to: • Jim Sedinger, Erik Blomberg, and Mike Atamian • Shawn Espinosa, Chet Van Dellan (NDOW) and Peter Coates (USGS) • All previous graduate students, technicians, and volunteers that have worked on this project • All funding sources:

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