Validation Tests of a Spatially Explicit Habitat Effectiveness Model for Rocky Mountain Elk

• Published in: The Journal of wildlife management Vol. 65; no. 4; pp. 899 - 914
• Main Authors: Roloff, Gary J., Millspaugh, Joshua J., Gitzen, Robert A., Brundige, Gary C.
• Format: Journal Article
• Language: English
• Published: Bethesda, MD The Wildlife Society 01-10-2001; Wildlife Society; Blackwell Publishing Ltd
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Animals; Autoecology; Biological and medical sciences; Cervus elaphus nelsoni; Elk; Elks; Forage; Forage quality; Forest habitats; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Habitats; Mammalia; Methods and techniques (sampling, tagging, trapping, modelling...); Summer; Vegetation; Vertebrata; Wildlife; Wildlife habitats; Wildlife management; Winter; South Dakota; Black Hills; United States; North America; America; Rocky Mountains; Radiotelemetry; Trophic factor; Environmental factor; Habitat suitability; Habitat selection; Animal active movement; Modeling; Test validation; Population survey; Vertebrata; Mammalia; Spatial distribution; Seasonal variation; Cervus elaphus; Cervidae; Habitat; Artiodactyla; Food supply; Ungulata
• ISSN: 0022-541X; 1937-2817
• DOI: 10.2307/3803039

We tested the validity of a spatially explicit habitat effectiveness model for Rocky Mountain elk (Cervus elaphus nelsoni). The model scored habitat effectiveness based on seasonal changes in the quality, quantity, and availability of forage. Seasonal forage potential scores were derived by integrating information on existing vegetation, site potential, historic disturbances, topography, and roads. The model generated maps of seasonal habitat effectiveness that were used to create utilization distributions (UD; i.e., 3-dimensional density estimates). We tested the elk habitat model using telemetry data collected on 5 cow elk sub-herds from 1993 to 1997 in Custer State Park (CSP), South Dakota, USA. We computed fixed kernel UD from elk telemetry data and simulated random UD within the confines of each sub-herd boundary. The degree of fit between elk UD and model predicted UD (elk-model UD) and random UD and model predicted UD (random-model UD) was represented by sub-herd, season, and year using the Volume of Intersection test statistic (V.I. Index). There were no differences in V.I. Indices by year for elk-model (1993 = 0.59, 1994 = 0.54, 1995 = 0.60, 1996 = 0.57, 1997 = 0.57;$F_{4,70}$= 0.93, P = 0.45) or random-model (1993 = 0.59, 1994 = 0.55, 1995 = 0.59, 1996 = 0.58, 1997 = 0.59;$F_{4,70}$= 1.49, P = 0.21) UD; thus, V.I. Indices were pooled across years. Two-way analysis of variance indicated that elk-model V.I. Indices did not differ by sub-herd (B = 0.50, Y = 0.58, A = 0.56, S = 0.58, R = 0.63;$F_{4,12}$= 2.68, P = 0.08), season (Spring = 0.55, Summer = 0.55, Fall = 0.60, Winter = 0.58;$F_{3,12}$= 0.80, P = 0.52), or the interaction terms (B Spring = 0.48, B Summer = 0.52, B Fall = 0.52, B Winter = 0.49, Y Spring = 0.60, Y Summer = 0.52, Y Fall = 0.58, Y Winter = 0.62, A Spring = 0.47, A Summer = 0.58, A Fall = 0.64, A Winter = 0.54, S Spring = 0.54, S Summer = 0.49, S Fall = 0.64, S Winter = 0.65, R Spring = 0.70, R Summer 0.64, R Fall = 0.60, R Winter = 0.59;$F_{12,55}$= 1.68, P = 0.10). V.I. Indices for random-model UD did not differ by season (Spring = 0.58, Summer = 0.57, Fall = 0.58, Winter = 0.59;$F_{3,12}$= 0.56, P = 0.65) or interaction term (B Spring = 0.55, B Summer = 0.58, B Fall = 0.56, B Winter = 0.54, Y Spring = 0.57, Y Summer = 0.53, Y Fall = 0.53, Y Winter = 0.57, A Spring = 0.61, A Summer = 0.63, A Fall = 0.63, A Winter = 0.64, S Spring = 0.60, S Summer = 0.49, S Fall = 0.57, S Winter = 0.59, R Spring = 0.59, R Summer 0.60, R Fall = 0.60, R Winter = 0.59;$F_{12,55}$= 1.44, P = 0.17); however, differences were noted among sub-herds (B = 0.56, Y = 0.55, A = 0.63, S = 0.56, R = 0.60;$F_{4,12}$= 4.48, P = 0.02). V.I. Indices for elk-model UD differed from random-model UD ($F_{4,12}$= 4.71, P = 0.02); model performance was worse than random (i.e., lower V.I. Indices) for 2 sub-herds (elk-model sub-herd B = 0.50 vs. random-model sub-herd B = 0.56 and elk-model sub-herd A = 0.56 vs. random-model sub-herd A = 0.63). Lower V.I. Indices were observed for 2 sub-herds that occupied areas recently subjected to large-scale wildfires. For sub-herds not subjected to fire effects (i.e., greater loss of vegetation security cover), the model portrayed elk habitat use less consistently, as represented by greater variability (27-42% larger standard errors) in V.I. Indices, during summer. Conversely, the model portrayed elk habitat use most consistent for the same 3 sub-herds during fall. These results suggest that the elk model performed more consistently during fall than any other season for sub-herds not affected by fire. We theorize that these seasonal trends in model performance were caused by elk use of vegetative security cover during fall, which was modeled, and use of topographic barriers for security cover during summer, which was not modeled. Conversely, poor and less consistent model performance was observed for the 2 sub-herds affected by fire, suggesting that topographic security cover was more important. The elk habitat effectiveness model offers the flexibility to incorporate a multitude of habitat factors and, with further refinement, may be a useful alternative to elk models that do not incorporate forage dynamics, topography, or variable road effects.