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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.

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Presentation on theme: "A multi-scale approach to assess sage-grouse nesting habitat Comparing nest site selection and nest success Dan Gibson Erik Blomberg Michael Atamian Jim."— Presentation transcript:

1 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

2 Overview: Sage-grouse

3 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 Why is knowledge regarding habitat use important?

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 Analyses 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

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

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 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? Summary so far…

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

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 Demographic continuity NestingEarly Brood Rearing Late Brood Rearing *Atamian et al. 2010 Establish what habitats are required during “important” life history stages Protect the commonalities Allow for connectivity between stages Probability of Use

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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