Uncertainty in Habitat Quality Maps for Elk: Implications for Estimates of Carrying Capacity

Ronald W. Davis1, John G. Cook2, Rachel Cook2, Louis C. Bender3, Richard E. Warner4 1.Geosciences and Natural Resources,Western Carolina University, Cullowhee, NC USA
2.National Council for Air and Stream Improvement, La Grande, OR USA
3. New Mexico Cooperative Research Unit,New Mexico State University, Las Cruses, NM USA
4. Natural Resources and Environmental Sciences, University of Illinois, Urbana, IL USA
1. rdavis@wcu.edu; 2. jgcook@nacasi.gmail.com; 3. lbender@nmsu.edu; 4. dickw@uiuc.edu

Abstract: Long term declines in ungulate populations in the Pacific Northwestern U.S. have been attributed to reduced forage production within closed-canopy forests and subsequent declines in elk nutritional body condition (i.e. autumn fat levels). Remote sensing imagery has been extensively used monitor forest resources in the region, yet error and inaccuracy in habitat models produced from these layers can be high given the detailed data required to evaluate forage resources. To estimate elk habitat quality in a way directly related to their use of forage and to explore the effects of uncertainty, we used GIS to apply a relationship between the biomass of selected forages (BSF) for elk and percent overstory canopy cover (PCC) (R2 >0.68) estimate forage-based habitat quality in 3 managed forests western Oregon and Washington. We used data-splitting to develop and validate remote sensing models and applied a Tasseled Cap transformation of Landsat ETM imagery to develop maps of PCC and estimate BSF. PCC was predictable from Tasseled indices (R2 >0.64) and we calculated supportable elk densities from BSF map estimates and compared this to actual densities and autumn fat levels in wild elk at these sites. To examine potential error and uncertainty we created a random raster layer representing error calculated between actual and estimated PCC and incorporated this into BSF models. We produced 1000 iterations and calculated the proportion of iterations in which BSF estimates met or exceeded a minimum viable BSF of >400kg/ha. Minimum viable BSF occupied an estimated 6-29% of the study area producing estimates of supportable elk densities of 6-20 elk/km2. Models incorporating error predicted BSF values ranging from 2.7-6.5% in at least 700-800 of 1000 model iterations. Error based estimated supportable densities were reduced to 0.65-6.3 elk/km2 with actual densities ranging from 0.20-5.0 eik/km2. The highest autumn body fat levels (12.4%) occurred where BSF estimates where highest and elk densities were lowest, while the poorest condition (6.2%) occurred at intermediate BSF levels but with the highest wild elk density. While the actual levels of nutrition acquired by elk will ultimately determine body condition, the incorporation of error and uncertainty into these habitat quality estimates produced estimates of habitat quality more in line with actual elk performance at these sites.

Keywords: elk, habitat evaluation, GIS, remote sensing, error, uncertainty

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