Elk Nutrition & Habitat Use Models for Management Introduction to Blue Mountains Modeling Work Blue Mountains Elk Models Nutrition Model Habitat Use Model Workshop Objectives Share methods and draft results of modeling work and discuss additional work needed. Discuss management implications and uses of models when finalized. Propose a “beta-testing” process for starting model applications with managers. Obtain feedback about how best to improve draft models during final modeling work. Elk Modeling Work For additional information: • Visit PNW Research Station website: • Web search “Elk Models PNW Station” http://www.fs.fed.us/pnw/calendar/workshop/elk/ Partners (Staffing, Funding, or Data) American Forest Resource Council Boise Cascade Corporation Boone and Crockett Club Forest Capital LLC National Council for Air and Stream Improvement National Fish and Wildlife Foundation Oregon Department of Fish and Wildlife Oregon Forest Industries Council Partners (Staffing, Funding, or Data) Oregon State University Rocky Mountain Elk Foundation Sporting Conservation Council USDA Forest Service (WO, R6, PNW) USDI Bureau of Land Management (WO, OR-WA) Washington Department of Fish and Wildlife WEST, Inc Introduction Timelines for Work Background & Need for New Models Modeling Objectives Work Accomplished and Some Caveats Timelines Westside Modeling: 2009-2011 Blue Mountains Modeling: 2011-2013 Workshop held after first year of work to share draft results with managers and obtain feedback. Final workshop held after second year to share final results and demonstrate management applications. Timelines April 2012: First Blue Mountains Workshop to share draft results and obtain feedback. Summer 2012: Conduct additional analyses to identify final model and prepare for “beta-testing.” Fall 2012: Start “beta-testing” models with managers. Early 2013: Finalize models based on additional validation tests and results of beta-testing. Spring 2013: Final models shared at second Blue Mountains workshop. Background and Need R. Cook Elk Habitat Models—Who Cares? Elk compose a multimillion dollar economy in the western U.S. (hunting, viewing, agricultural damage). Elk distribution across landscapes, and thus the species’ economic impacts across land ownerships, can be directly controlled through management. Elk Habitat Models—Who Cares? Elk are a “seral-mosaic” species whose needs are compatible with active silviculture and effective travel management. Public land use plans continue to feature elk and elk management— the large majority of summer range is on public land. Background and Need Models developed in 1970s & 80s with limited empirical data. Empirical data restricted to single variable habitat relations with elk. Contributions of multiple variables to predict relative probability of elk use not empirically-based (e.g., geometric mean); resource selection modeling not yet developed. Why New Elk Habitat Models? “Old” models still in use but structure and some components outdated (e. g., thermal cover) Data from many radiotelemetry studies now available for new modeling approaches. Data on elk nutritional resources now available for modeling at landscape scales. Modeling Objectives R. Cook Modeling Work: • Summer range (elk productivity) • Large (regional) landscapes, multiple land ownerships, integrated management strategies • Local landscapes, smaller projects within large landscapes Modeling Work: • Focus on late summer (August data) • Non-hunting periods (but populations are hunted) • Female elk Objectives 1. Build a model that predicts nutritional resources for elk across all landscape conditions on summer range (Nutrition Model). 2. Identify & rank a set of plausible, competing models that predict elk habitat use on summer range, & validate “best” models with independent data (Habitat Use Model). Objectives 3. Include nutrition model predictions as a covariate in the habitat use model. 4. Include additional human disturbance, vegetation, and physical covariates that affect or account for elk use of nutritional resources. Objectives 5. Use data from different study areas & years (different environments & ownerships) to construct, select, and validate habitat use model. Objectives Two predictions of primary interest: 1. Composition (percent area) of a landscape by nutritional condition —Nutrition Model Objectives Two predictions of primary interest: 2. Level of elk use (relative probability of use) across a landscape, given all covariates that affect use —Habitat Use Model. Objectives Two management options of primary interest: 1. Degree to which management can change landscape area by nutritional condition (Nutrition Model). 2. Degree to which management can change level of elk use on a landscape, given all factors that affect use (Habitat Use Model). Modeling Objectives: • Habitat Use Model: Designed as a tool to evaluate and manage elk distributions within and across land ownerships on regional landscapes, and on smaller (local) areas within the large landscapes. • Elk management problems often are related to where elk occur rather than elk numbers per se. Work Accomplished R. Cook Nutrition Model Set of models that predict elk dietary digestible energy based on data from grazing trials conducted with tame elk across representative environments. Habitat Use Model Use available telemetry data for model development (selection) & validation. Model selection also referred to as model “training.” Two Analytical Steps Model selection of top-ranked models among many plausible, competing models. Validation of top-ranked models Radio Telemetry Data GPS or Loran-C technology. High location accuracy, relocation frequency, and no. of collared animals. 24-hour coverage. Starkey vs. Sled Springs Areas Starkey Drier More rangeland, less wet forest, few wet meadows Gentle slopes Few canyons Open canopy from spruce budworm Sled Springs Wetter Less rangeland, more wet forest, wet meadows common Steep slopes or flat Major canyons Open canopy from timber harvest Starkey vs. Sled Springs Areas Starkey Area tends to be more representative of drier forest areas that typify the southwestern portions of the Blue Mountains. Sled Springs Area is more representative of wetter forest areas common to northeastern portions of the Blue Mountains. Neither area, however, has high-elevation subalpine forest environments. Covariates Considered Human Disturbance Nutrition Dietary digestible energy (DDE) Accepted biomass (AB) Total forage biomass (FB) EVI (Enhanced Vegetation Index) Distance to: any road open road closed road class 1 road class 2 road class 3 road class 4 road class 4 or greater road class 1 or 2 road class 3 or 4 road Density of: all roads open roads and trails Vegetation Physical/ Other Proportion of vegetation classes Percent slope Overstory canopy cover (CC) Percent area in: flat to gentle slopes moderate to steep slopes very steep slopes Dominant CC class Cover/forage ratio Percent area in cover Distance to: cover-forage edge cover patch (3 patch sizes) agricultural land Dominant slope class Cosine and sine of aspect Convexity Solar radiation Soil depth Distance to: water pond stream Dominant landowner Cattle RSF Reduced Set of Covariates in Competing Models Intended Inference Space? Caveats Models are designed to evaluate summer range. Results from model applications also represent conditions for elk on fall ranges outside the hunting seasons. Models are not designed to evaluate conditions on spring or winter ranges. Caveats Potential effects of livestock grazing on elk habitat use could not be fully assessed. We implemented a cattle model from Starkey that evaluated cattle habitat use as a potential covariate affecting elk use. We also evaluated distance to water sources (distance to streams, stock ponds, springs, etc.) as surrogates for cattle use, but these types of covariates do not directly measure cattle use. Caveats Spatial data on cattle presence and absence by pasture and date, and associated stocking rates when present in a pasture, were needed but unavailable for study areas beyond Starkey. A variety of additional cattle covariates potentially affecting elk use could not be considered because of this data void. Caveats Continuous coverage spatial data on livestock grazing systems and stocking rates, mapped by grazing dates for each livestock pasture, is an essential and unmet need for evaluating elk summer and fall ranges. Lack of continuous coverage spatial data on livestock grazing systems and stocking rates is a common problem throughout western North America. Caveats Today’s presentations contain draft, preliminary material. Additional analyses are required before models are completed. Our “best” nutrition and habitat use models presented today are likely to be very similar to the final models that will be completed and “beta-tested” in late 2012 and early 2013. Feedback from attendees at this workshop about the draft models is essential. Question and Answer/Discussion Session at End of Day