A multi-scale approach to assess sage-grouse nesting habitat
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Dan Gibson Erik Blomberg Michael Atamian Jim Sedinger PowerPoint PPT Presentation

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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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A multi-scale approach to assess sage-grouse nesting habitatComparing nest site selection and nest success

Dan Gibson

Erik Blomberg

Michael Atamian

Jim Sedinger

Overview: Sage-grouse

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

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

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

  • Monitored female sage-grouse from 2003-2012 in Eureka Co. Nevada

  • Ground level vegetation data was collected at nest and random sites

  • ~410 nests

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



Individual heterogeneity



  • 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

  • Selection versus Survival

    1 denotes spatial selection model

    2 denotes local selection model

    Bold values significant

    Non-sagebrush shrub cover & Forb cover

    Sagebrush canopy cover

    * Guidelines to manage sage grouse populations and their habitats

    Connelly et al. 2000

    Grass cover * Residual grass height

    * Guidelines to manage sage grouse populations and their habitats

    Connelly et al. 2000

    Pinyon-Juniper encroachment

    Exotic Grasslands

    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?

    Developing a nesting habitat use model

    Elevation * Slope + Distance from lek * Amount of habitat classified as sagebrush (1000m)

    Delineation of nesting habitat

    • ~18% of surrounding habitat was classified as suitable which encompassed 75% of nest points

      • Estimate of concordance = 0.72

    • 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


    Early Brood Rearing


    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

    • 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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