We report on a number of ongoing studies and discuss what projects are in place to further refine and test relationships

Gerhart, Karen L.

Russell, Donald E.

van de Wetering, Debbie

White, Robert G.

Rangifer

English

Donald E. Russell

Debbie van de Wetering

Robert G. White

Karen L. Gerhart

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Oil and the Porcupine Caribou Herd — Can we quantify the impacts?

Septentrio Academic Publishing

The Sixth North American Caribou Workshop, Prince George, British Columbia, Canada, 1-4 March, 1994. Brief communication O i l and the Porcupine Caribou Herd — Can we quantify the impacts? Donald E. Russell1, Debbie van de Wetering1, Robert G.White2 & Karen L. Gerhart2 1 Environment Canada, Canadian Wildlife Service, Mile 917.6 Alaska Hwy., Whitehorse, Yukon, Y 1 A 5X7. 2 Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska, 99701. Rangifer, Special I ssue N o . 9 , 2 5 5 - 2 5 8 Introduction The Porcupine caribou herd (Rangifer tarandus gran-ti) is a large international herd of migratory caribou that annually travels from their taiga wintering grounds in Alaska and Y u k o n to calving and sum-mer grounds adjacent to the Beaufort Sea. Their summer range is east of the range of the smaller Central Arctic Herd , where considerable o i l deve-lopment has occurred. In 1980 wi th the passage of the Alaska National Interest Lands Conservation Act in the U . S., a decision on the future protection of much of the concentrated calving and post-calving grounds of the herd was delayed. Studies were initiated to assess the potential for hydrocarbon development and the impacts of that development on the envi-ronment. These environmental studies, along wi th the lessons of Prudhoe Bay and the Central Arctic Herd , form the basis for environmental impact assessment. Impact Assessment In the last two decades, impact assessment was approached from two largely separate fronts; effects on the population and effects on animal energetics. Disruptions and displacements caused by development projects must be assessed at the population level. Therefore, as more is learned about specific populations, it is important to c o m -bine the two approaches and assess energetic impacts at the population level. The amount of research and monitoring that was devoted to the Porcupine Car ibou H e r d and the lessons from the Central Arctic H e r d facilitate assessment o f the potential impacts of development before develop-ment. K e y demographic variables such as parturition rate, calf survival and recruitment rate can vary sig-nificantly from year to year. For example, in the Porcupine herd, parturition rate varied from 72% to 86% and calf survival to 1 month of age varied from 66% to 91% over the last 6 years (Fancy et ai, 1994). Other factors being equal, this range can translate into i n an increasing population or a rapid-ly declining population. This variation i n key para-meters has occurred i n the absence of any signifi-cant development within the herd's range. The key, therefore, is the ability to predict these variables based on natural variation in range condition and the added potential impacts of proposed develop-ment. In other words, our ability to translate ener-getic or body condition indices to the population level is directly related to the strength o f the func-tional relationships that can be derived. Thus, i n this paper, we report o n a number o f ongoing studies to derive these relationships and discuss what projects are i n place to further refine and test these relationships. Progress to date Relation between body fat reserves and pregnancy rate In early November 1990 - 1993, 125 adult cows were captured, weighed, and an index taken of body fat (body condition score [BCS], Gerhart et ah, 1992) taken. The product of body weight and B C S was called the Body Reserve Index (BRI) . B l o o d samples were analyzed and pregnancy deter-mined (van de Wetering et ai, 1994). As outlined by Sasser et al. (1989) animals wi th a positive preg-nancy test for P S P B and a negative diagnosis for progesterone were considered to have suffered an early intra-uterine mortality. Significant logistical regressions were determined between B R I and both pregnancy rate (P o f $ = 0 , 0 0 3 Fig . la) and early intra-uterine mortality (P o f A=0.008; Fig . l b ) . Rangifer, Special Issue N o . 9 , 1 9 9 6 255 1 0 I 1 300 400 500 600 700 800 900 1,000 1,100 1,200 BODY RESERVE INDEX Fig. la. Logistic regression relating probability of parturi-tion for adult female caribou to autumn Body Reserve Index, Porcupine Caribou Herd, 1990 -1993 ((30= -3.602, pj = 0.097, P<0.001). 11 1 o — 1 300 400 500 600 700 800 900 1,000 1,100 1,200 BODY RESERVE INDEX Fig. lb.Logistic regression relating probability of intrau-terine mortality for adult female caribou to autumn Body Reserve Index, Porcupine Caribou Herd, 1990 - 1993 (P0= 3.9439, Pj = 0.00932, PO.01) . Relation between weather and parturition rates For the Porcupine Caribou Herd, Russell et al., (1993a) presented 5 weather-related effects on the energetics of individual caribou. Winter snow depth, spring melt, late spring phenology, early July temperatures and late July/early August temperatu-res effect activity patterns, feeding rates and move-ment rates, which in turn alter energy balance to the individual. Fall body weights of adult females in the herd were monitored since 1986 (Allaye-Chan, 1991; Smits et al, 1991; Russell, unpubl. obs.). A l l these weather factors are integrated by the animal, affecting the body condition during the rut. Table 1 summarizes weather observations taken from key locations wi th in the range of the herd for the period 256 Table 1. Weather variables within the range of the Porcupine Caribou Herd, 1987 - 1992. Year Winter Spring Spring Early Late snow1 snow2 Phenology3- July July (cm) (cm) temp4 temp5 1987 68 49 4 12.5 11.5 1988 86 34 3 13.4 10.7 1989 76 0 6 13.0 17.5 1990 95 62 1 14.2 11.7 1991 85 0 5 5.2 9.5 1992 81 63 2 10.5 12.6 1 - snow depth March 1 at Eagle Plains (Indian and Northern Affairs snow survey bulletins). 2 - snow depth May 1 at Old Crow (Indian and Northern Affairs snow survey bulletins). 3 - ranks based on stage of phenology at peak of calving, from satellite A V H R R data. 4 - mean daily temp. (°C) at Shingle Point July 1-15. 5 - mean daily temp. (°C) at Shingle Point July 16 -Aug 7. Table 2. Weather variables as ranks, sum of ranks, fall body weights and parturition rates, 1987-1992. Variable 1987 1988 1989 1990 1991 1992 Winter snow 6 2 5 1 3 4 Spring snow 3 4 5 2 5 Phenology 4 3 6 1 5 2 Early July 4 2 3 1 6 5 temperature Late July 4 5 1 3 6 2 temperature Sum of Ranks 21 16 20 8 25 14 Fall Body Weight 95 88 92 88 98 89 Parturition Rate1 84 78 82 74 86 81 1 parturition rate measured in spring of following year i.e. in the 1987 column rate refers to rate in spring 1988. 1986 - 1992. Deep snow, late melt, early phenology and high summer temperatures were ranked among years and totalled annually to provide an index of weather conditions for each year (Table 1). The sum of these ranks was highly correlated to birth rate (r2=0.88, Fig.2). Porcupine caribou model The further development of the Porcupine caribou models (combining the Energetics and Population models, Russell et al., 1993b) led to hypothetical Rangifer, Special Issue N o . 9, 1996 30 Z3 ra 5 -o1 - 1 ' 1 ' • 1 ' u 72 74 76 78 80 82 84 86 BIRTH RATE Fig. 2. Relationship between the sum of ranks of abiotic variables to the birth rate of the Porcupine Caribou Herd. 0 1 2 3 4 5 6 7 8 9 10 PERCENT REDUCTION Fig. 3a. Simulated weight loss resulting from a 2%, 5% and 10% reduction in feeding and forage digesti-bility, June 1 - July 15. 0 1 2 3 4 5 6 7 8 9 10 PERCENT REDUCTION Fig. 3b. Simulated reduced pregnancy rate resulting from a 2%, 5% and 10% reduction in feeding and fora-ge digestibility, June 1 - July 15. development scenarios. For example, simulated reduced time spent feeding or poorer habitat result-ed in lower autumn weights (Fig. 3a) and preg-nancy rates (Fig. 3b). Ongoing Work Recent research relates birth weight and growth of calves to habitat use as wel l as condition and growth of mothers. Non-lactating females are also tracked to estimate the energetic investment in raising cal-ves. These data w i l l be used to refine and validate the Porcupine caribou model. References Allaye-Chan, A . 1991. Physiological and ecological determi-nants of nutrient partitioning in caribou and reindeer. PhD thesis, Univ. Alaska, Fairbanks, A K . Gerhart, K.L., White R. G. & Cameron, R. D. 1992. Estimating body composition of caribou and reindeer using bioelectrical impedance analysis and body condition scores. - Rangifer 12(3): 185-186. Expanded abstract. Fancy, S., Whitten, K. R. & Russell, D. E. 1994. Dynamics of a barren-ground caribou population. - Can.f. Zool. in press. Russell, D.E. , Martell, A . M . & Nixon, W.A.C . 1993a. Range ecology of the Porcupine Caribou Herd in Canada. — Rangifer Special Issue No. 8. 167p. Russell, D. E. , White, R. G., Daniel, C. & van de Wetering, D. 1993b. Porcupine Caribou models: Update on linking ENERGY and POPULATION models (Abstract). Paper presented at the American association for the Advancement of Science Conference, Arctic Division. Whitehorse, Yukon September 1993. Sasser, R. G., Crock, J. & Ruder-Montgomery, C. A. 1989. Characteristcs of pregnancy-specific protein B in cattle. - J . Reprod. Vert., Suppl. 37: 109-113. Smits, C , Ward, R., Fraser, P. & Liepens, I. 1991. Body condition of the Porcupine caribou herd. Yukon Dept. of Renewable resources. Unpublished report. van de Wetering, D., Russell, D. E. , White, R. G. & Sasser, G. 1994. Pregnancy determination in caribou using progesterone and pregnancy-specific protein B (PSBP) serum assays. Abstract, this issue. Rangifer, Special Issue N o . 9, 1996 257 

Oil and the Porcupine Caribou Herd — Can we quantify the impacts?

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