13 USING SNOW URINE SAMPLES TO ASSESS THE IMPACT OF WINTER TICKS ON MOOSE CALF CONDITION AND SURVIVAL Daniel Ellingwood1, Peter J. Pekins1, and Henry Jones2 1Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, 03824, USA; 2Maine Department of Inland Fisheries and Wildlife, Bangor, ME, 04401, USA. ABSTRACT: Snow urine samples collected in northern New Hampshire, USA were used to mea- sure urea nitrogen (UN) and creatinine (C) content to develop ratios for tracking the nutritional restriction of individual moose (Alces alces) through winter (2014–2017), inclusive of the adult winter tick (Dermacentor albipictus) engorgement period. Samples (n = 215) were collected from 55 moose (38 calves, 17 cows) on a twice monthly schedule from late January through snowmelt or calf mortality (March – early April). Early winter UN:C ratios from cows, surviving calves, and calves that ultimately died from infestation of winter ticks were similar and reflected a normal win- ter diet low in protein. A heightened UN:C ratio (> 3.5 mg/dL) was measured in March which aligned with peak feeding by adult winter ticks, and presumably reflected accelerated protein deficit associated with blood loss. This increase was not observed population-wide despite shared habitat, occurring only in calves with mortal weight loss and anemia associated with heavy winter tick infestation. Measurement of UN:C ratios from snow urine samples proved an effective method to measure the temporal impact of winter tick infestation, and March samples can support other met- rics used to estimate calf mortality. ALCES VOL. 55: 13–21 (2019) Key words: creatinine, epizootic, New Hampshire, moose, nutritional restriction, snow urine, urea nitrogen, winter ticks New Hampshire has experienced at least 5 winter tick (Dermacentor albipictus) epi- zootics (> 50% calf mortality) in the last decade, an unprecedented rate of occurrence (Musante et al. 2010, Bergeron et al. 2013, Jones et al. 2019). Concurrent with this heightened frequency of epizootics, New Hampshire’s moose (Alces alces) population has declined ~45% over the past 15 years (NHFG 2015). The cause of this decline in northern New Hampshire is the negative influence of winter ticks on calf survival which can be < 30% annually, and associated lower productivity of yearling and adult cows (Musante et al. 2010, Jones et al. 2017, 2019). The fate of moose calves (8–12 months old) during an epizootic is determined by their relative condition (i.e., body weight, fat stores) and the severity of tick infestation as it relates to metabolic impacts, including blood loss, protein deficiency, and subse- quent weight loss (Samuel 2004, Musante et al. 2007, Ellingwood 2018). As such, mon- itoring the condition of calves through winter and spring should provide insight into the rel- ative and temporal influence of tick loads on metabolic imbalance, survival, and produc- tivity. Measurement of urea nitrogen from urine samples in snow serves as an informa- tive measure of individual condition, reflect- ing muscle tissue catabolism in animals with an otherwise low-protein diet (Seal et al. SNOW URINE SAMPLING – ELLINGWOOD ET AL. ALCES VOL. 55, 2019 14 1972, Kirkpatrick et al. 1975, Bahnak et al. 1979). Radio-marked calves provide for a unique opportunity to monitor and assess specific physiological parameters from indi- viduals with known fate through the peak mortality period associated with winter tick parasitism. STUDY AREA The study area (Berlin) is located within Coos County and includes sections of Wildlife Management Units (WMU) B, C1, and C2 in the towns of Berlin, Milan, Dummer, Success, Cambridge, Millsfield, Stark, and Second College Grant (Fig. 1). Fig.1. Location of the study area in Wildlife Management Units A2, B, C1, and C2 in Coos County, New Hampshire, USA. ALCES VOL. 55, 2019 SNOW URINE SAMPLING – ELLINGWOOD ET AL. 15 The landscape is bisected by the Androscoggin River and is relatively mountainous, bor- dered to the west by the Kilkenny Range and the south by the Mahoosuc Range. Landcover is predominately commercial forest in which deciduous areas are dominated by yellow (Betula alleghaniensis) and paper birch (B. papyrifera), American beech (Fagus grandifolia), and sugar maple (Acer saccha- rum), with softwood stands characterized by black spruce (Picea mariana), red spruce (P. rubens), balsam fir (Abies balsamea), and white cedar (Thuja occidentalis) (DeGraaf et al. 1992). Logging operations remove 1–3% of timber annually, and optimal moose habi- tat (4–16 year-old growth) increased 2.5X between 2001 and 2015 to equal > 17% of forest cover (Dunfey-Ball 2017). Habitat quality is considered good and not a limit- ing factor to the local moose population (Bergeron et al. 2011, Dunfey-Ball 2017). The average date of first snowfall is 14 November, with permanent snow cover typi- cally in December (Dunfey-Ball 2017). This site was the location of a comprehensive study of moose population dynamics in 2001–2005 when density was estimated as ~0.8 moose/km2 (Musante et al. 2010). The most recent population estimate is ~0.6 moose/km2, and from 2014–2018, > 200 moose were fit with radio-collars as part of a larger study. Winter tick-related calf mortality was 62%, 74%, 77%, and 30% in 2014, 2015, 2016, and 2017, respec- tively (Jones et al. 2019, P. J. Pekins, unpub- lished data). METHODS Capture and monitoring Calves (~8 months old) were captured in early January 2014 – 2017 via net-gun- ning and aerial darting techniques (Aero Tech Inc., Clovis, New Mexico, USA in 2014 and 2015; Native Range Capture Services, Elko, Nevada, USA in 2016 and 2017). Moose were fitted with either VHF (n = 76; M2610B, Advanced Telemetry Systems, Isanti, Minnesota, USA; Mod-600, Telonics, Mesa, Arizona, USA) or GPS radio-collars (n = 104; GPS Plus Vertex Survey Collar, Vectronic Aerospace GmbH, Berlin, Germany). The tick load of each moose was measured by summing the num- ber of ticks on 4, 10 cm transects on both the shoulder and rump (Sine et al. 2009, Bergeron and Pekins 2014). The sum of those 8 transects is used as an index to com- pare relative tick loads between individuals and across years. The VHF radio-collars transmitted at 55 pulses/min (ppm) while active, and switched to 110 ppm after 4 h without move- ment, signifying a mortality event. The GPS radio-collars transmitted 2 location fixes/day (00:00 and 12:00 hr EST) which were viewed and downloaded via Vectronics Aerospace software (GPS PLUS X V10.4), and also had a VHF beacon transmitting at the same pulse rates as the VHF radio-collars. These radio-collars switched to mortality mode and sent a mortality alert via email after 5 h of inactivity. All calves were necropsied in the field following standard procedures (Mason and Madden 2007, Munson 2015), including an external examination, body weight mea- surement, and collection of tissue samples for subsequent examination at the New Hampshire Veterinary Diagnostics Lab (Durham, New Hampshire) to determine cause of death (Jones et al. 2019). Urea nitrogen:creatinine sampling Snow urine samples were used to track the nutritional restriction of individual ani- mals through the winter, inclusive of the adult tick engorgement period. Samples were collected from radio-marked calves and accompanying unmarked adult cows pre- sumed to be the mothers. An effort was made to collect a sample from each individual SNOW URINE SAMPLING – ELLINGWOOD ET AL. ALCES VOL. 55, 2019 16 every 2 weeks beginning in late January and extending through snowmelt or mortality (March – early April); the goal was to collect 3–6 temporal samples per individual. Samples were collected within 24 h of urina- tion by locating the bedding site and/or tracks in the snow at coordinates transmitted by the GPS radio-collar at 00:00 hr that day; tracks were followed until a sample was identified. Moose with VHF radio-collars were located using ground telemetry techniques (Mech 1983) and back-tracked to collect urine sam- ples. In cases where an adult accompanied the calf, samples were distinguished between the pair by the size of tracks and bed nearest to the sample. Consistent with the methods used by DelGiudice et al. (1988), the most concentrated portion was collected in plastic bags using rubber gloves to avoid contamina- tion. Samples were subsequently thawed at room temperature and aliquoted into 2 mL cryovials. These aliquots were stored frozen until submission to BiovetUSA (Burnsville, Minnesota) for measurement of urea nitro- gen (UN) and urinary creatinine (C) content (mg/dL). These data were expressed as a ratio (UN:C) to correct for the dilution of each sample by snow (DelGiudice et al. 1988); C is proportional to muscle mass and remains near constant in individuals over a given day (DelGiudice and Seal 1988). Analysis included those individuals that were sampled most consistently, while attempting to achieve near equal representation of sur- viving and dead calves. The UN:C ratio of urine samples were log e transformed to stabilize the variance in the dataset prior to analysis (DelGiudice et al. 1989). Samples were initially grouped by fate (mortality or survivor), and samples within each group were pooled at 2-week intervals (each individual was sampled every other week). A two-way ANOVA was used to examine differences in the mean UN:C ratio of samples collected from cows, surviving calves, and dead calves across col- lection intervals. Tukey’s range (HSD) test was used to make post-hoc comparisons between multiple collection periods. RESULTS Winter mortality of radio-marked calves in 2014 – 2016 averaged 71%, dropping to 30% in 2017; the leading cause of death (> 90%) was winter tick parasitism (Ellingwood 2018, Jones et al. 2019). A total of 158 snow urine samples were collected from 38 radio-marked calves (23 winter mortalities and 15 survivors) in the winters of 2014–2017. Samples (n = 57) were also collected from 17 unmarked adult cows accompanying a portion of these marked calves; all adult cows were presumed to sur- vive through winter. Maximum annual snow depth during the collection periods ranged from 17.8 – 71.1 cm. From ~15 January – 14 February, there were no statistical differences between UN:C ratios of unmarked cows, surviving calves, and calves that died (P > 0.05). From ~ 15 Feb – 15 March, the mean UN:C ratio of calves that died and those that survived diverged significantly (P < 0.05), whereas the UN:C ratio of cows and surviving calves remained similar. The UN:C ratios of unmarked adult cows stayed stable throughout the sampling season (x̅ = 2.35 ± 0.85), with individual samples ranging from 0.8–4.54 with no difference detected between collection intervals (P > 0.05; Fig. 2). The average UN:C ratio of calves that died increased through the second week of March, peaking at 4.68 ± 2.93; the ratio of survivors was lower and relatively stable during this same time period (x̅ = 2.43 ± 0.74; Table 1). In the weeks following this spike in UN:C ratios, the average ratio of calves that died never returned to levels < 3.5, and mortality occurred 1–5 weeks after their UN:C ratio peaked (x̅ = 3 weeks). ALCES VOL. 55, 2019 SNOW URINE SAMPLING – ELLINGWOOD ET AL. 17 Spring snowmelt prevented sample collec- tion from 14 calves within 2 weeks of death. DISCUSSION Moose are on a negative nutritional plane from winter through early spring, although winter mortality from malnutrition is considered rare in the northeastern United States. Adult survival rates in late winter average 97% and starvation has not been identified as a source of mortality regionally (Musante et al. 2010, Jones et al. 2019). A low level of undernutrition during winter is typical and reversible, as fat stores are used to supplement the reduced nutritional quality of winter browse (DelGiudice and Seal 1988, DelGiudice and Moen 1997, Schwartz and Renecker 2007). Winter diets have limited digestible protein which is reflected by low UN:C ratios in moose urine, and as fat stores deplete, moose increase cat- abolism of muscle protein (rich in nitrogen) Fig. 2. Mean (± SE) UN:C ratios in snow urine samples collected from radio-marked calves and unmarked adult cow moose in northern New Hampshire (January-April, 2014–2017). Dotted line at UN:C ratio = 3.5 represents the survival threshold described by DelGiudice (1995). Table 1. Summary of UN:C ratios of snow-urine samples (n) from moose in 2014–2017, New Hampshire, USA. Original UN:C data are presented here with statistical comparisons made after data were log e transformed. Dead calves had significantly higher (P < 0.05; *) UN:C ratios from late February onward. Collection interval Surviving calves Dead calves Unmarked adult cows n x̅ SD n x̅ SD n x̅ SD 15–31 Jan. 12 2.17 0.85 13 2.57 1.04 7 1.96 0.60 1–14 Feb. 11 2.50 0.80 19 2.88 0.97 12 2.37 0.87 15–28 Feb 15 2.99 0.75 18 3.58* 1.19 11 2.56 0.77 1–14 Mar. 14 2.43 0.74 15 4.68* 2.93 9 2.42 0.93 15–31 Mar. 10 2.47 0.53 12 3.66* 0.88 13 2.50 1.01 1–14 Apr. 10 2.18 0.87 9 4.27* 2.37 5 1.96 0.77 SNOW URINE SAMPLING – ELLINGWOOD ET AL. ALCES VOL. 55, 2019 18 to meet protein and energy requirements, causing an abrupt spike in UN:C ratios (DelGiudice et al. 1987, DelGiudice and Seal 1988). Ratios > 3.5 represent serious deterioration in body condition with esti- mated losses of 0.5–0.8 kg/day of lean body (muscle) mass for a 400 kg moose (DelGuidice et al. 1997). For an average (174 kg) calf expressing similar UN:C ratios, this would equate to 0.2–0.3 kg/day or ~5% weight loss in 30 days. Low UN:C levels (< 3.5) were measured in this study from January through late- February each year, suggesting that all cows and calves were in an early phase of under- nutrition. The spike in UN:C ratios mea- sured in calves that died is symptomatic of animals experiencing prolonged undernu- trition and catabolizing muscle. Similar effects have been measured in white-tailed deer (Odocoileus virginianus), elk (Cervus canadensis), and other moose populations due to limited forage diversity, availability, and quality associated with marginal habitat and deep snow (DelGiudice et al. 1989, 1991a, 1991b). All dead calves expressed signs of anemia and emaciation including severe weight loss (23 ± 7%) in 3.5 months (Ellingwood 2018). This degree of weight loss is comparable to that measured in white- tailed deer experiencing prolonged and irre- versible levels of malnutrition (DelGiudice and Seal 1988). In contrast to the abovementioned exam- ples, the impact of undernutrition in this study was not evident population-wide or associated with habitat or winter severity. Calves that died experienced a UN:C spike in March, whereas surviving calves and adult cows did not. Surviving calves and adults shared the same habitat as the dead calves, and forage availability in the study area is not considered limiting (Bergeron et al. 2011, Dunfey-Ball 2017). Limited mobility and increased mortality due to snow depth for moose occurs at >90 cm (Coady 1974); however, in the winters of 2014–2017, average snow depth was ≤ 71 cm in northern New Hampshire and the highest rate of calf mortality occurred in the year of lowest maximum snow depth (Jones et al. 2019). The timing of the spike in dead calves aligns with the peak feeding period of adult winter ticks in mid- to late March (Samuel 2004). Arguably, calves were experiencing an increasing protein and energy deficit due to the physiological requirement to replenish blood (protein) loss associated with feeding by winter ticks. Tick load estimates derived from half-hide counts of dead calves aver- aged 47,000 (Jones et al. 2019), and com- pensation for blood loss associated with this infestation level requires 50 to >100% of the daily protein requirement of a calf during the peak 2-week feeding period of adult winter ticks (Musante et al. 2007). Metabolically, this depletion of muscle mass (protein) mim- ics that of a starving animal, producing a similar response in the UN:C ratios. For example, DelGiudice and Seal (1988) identi- fied UN:C ratios ranging from 4 - >23 mg/dL in urine samples collected from white-tailed deer experiencing prolonged undernutrition. The average UN:C ratio peaked at 4.68 for dead calves; however, given the average period (20 ± 13 days) between the date of the last sample collection and mortality, our data do not reflect the higher ratios that occur closer to death. The tick load measured at January cap- ture was the primary determinant of calf fate, as tick load and probability of survival were inversely related. For calves with low and moderate tick counts, body weight has some counter-balancing effect on survival, with heavier calves (> 174 kg) expressing height- ened resistance to mortality (Ellingwood 2018). This influence was also demon- strated in higher survival of heavier calves in ALCES VOL. 55, 2019 SNOW URINE SAMPLING – ELLINGWOOD ET AL. 19 northern Maine with similar tick loads. The body weight of 73% of calves captured in New Hampshire was less than the average weight (190 kg) in northern Maine where winter tick epizootics remain uncommon (Ellingwood 2018; L. Kantar, Maine Department of Inland Fisheries and Wildlife, unpublished data). Given the high propor- tion (17.5%) of optimal habitat (4–16 year old regenerating growth) in the region (Dunfey-Ball 2017), these low weights pre- sumably reflect the carry-over effects of compromised reproductive cows impacted by high annual tick loads (Musante et al. 2010, Jones et al. 2017). Temporal monitoring of UN:C ratios identified the occurrence and timing of nutritional restriction of calves that ulti- mately died from blood loss to winter ticks. While all moose exhibited some degree of undernutrition, the spike observed in the UN:C ratio of dead calves was related directly to the feeding period of adult female winter ticks. In more southern moose populations where winter ticks are of most concern, UN:C ratios from snow urine samples could be used to assess calf condition, identify a potential epizootic (DelGiudice et al. 1997), and predict mor- tality rate in the population. Collection and analysis of snow urine samples from calves in the second and third week in March should be adequate to identify the propor- tion with UN:C ratio > 3.5 and provide a reasonable estimate of the seasonal calf mortality rate. The ability to measure this metric provides critical recruitment infor- mation and is a useful proxy for productiv- ity, both necessary to develop effective management strategies. ACKNOWLEDGEMENTS Funding for this project was provided through Wildlife Restoration Program Grant No. F13AF01123 (NH W-104-R-1) to N.H. Fish and Game Department from the U.S. Fish and Wildlife Service, Division of Wildlife and Sport Fish Restoration, and Safari Club International Foundation. This research was made possible through the access granted by property owners includ- ing American Forest Management, the Conservation Fund, Plum Creek, T. R. Dillon, and Wagner Forest Management Ltd. The efforts of field technicians J. DeBow and T. Soucy were critical for the collection of these data. REFERENCES Bahnak, B. R., J. C. holland, l. J. VeRme, and J. J. ozoga. 1979. Seasonal and nutritional effects on serum nitrogen constituents in white-tailed deer. Journal of Wildlife Management 43: 454–460. BeRgeRon, d. h., and P. J. Pekins. 2014. Evaluating the usefulness of three indi- ces for assessing winter tick abundance in northern New Hampshire. Alces 50: 1–15. _______, _______, h.F. Jones, and W.B. leak. 2011. Moose browsing and forest regeneration: a case study in northern New Hampshire. Alces 47: 39–51. _____, _____, and k. Rines. 2013. Temporal assessment of physical characteristics and reproductive status of moose in New Hampshire. Alces 49: 39–48. Coady, J. W. 1974. Influence of snow on behavior of moose. Le Naturaliste Canadian 101: 417–436. degRaFF, R. m., m. yamasaki, W. B. leak, and J. W. lanieR. 1992. New England wildlife: management of forested habi- tats. General Technical Report NE-144. USDA Forest Service, Northeast Forest Experiment Station, Radnor, Pennsylvania, USA. delguidiCe g.d. 1995. Assessing winter nutritional restriction of northern deer with urine in snow: considerations, potential, and limitations. Wildlife Society Bulletin 23: 687–693. SNOW URINE SAMPLING – ELLINGWOOD ET AL. ALCES VOL. 55, 2019 20 _____, l. d. meCh, and u. s. seal. 1988. Chemical analyses of deer bladder urine and urine collected from snow. Wildlife Society Bulletin 16: 324–326. _______, _______, and _______. 1989. Physiological assessment of deer popu- lations by analysis of urine in snow. Journal of Wildlife Management 53: 284–291. _______, _______, _______, and P. d. kaRns. 1987. Winter fasting and refeed- ing effects on urine characteristics in white-tailed deer. Journal of Wildlife Management 51: 860–864. _______, and R. moen. 1997. Simulating nitrogen metabolism and urea nitrogen: creatinine ratios in ruminants. Journal of Wildlife Management 61: 881–894. ______, R. o. PeteRson, and W. m. samuel. 1997. Trends of winter nutritional restriction, ticks, and numbers of moose on Isle Royale. Journal of Wildlife Management 61: 895–903. _______, _____, and u. s. seal. 1991b. Differences in urinary chemistry pro- files of moose on Isle Royale during winter. Journal of Wildlife Diseases 27: 407–416. _____, and u. s. seal. 1988. Classifying winter undernutrition in deer via serum and urinary urea nitrogen. Wildlife Society Bulletin 16: 27–32. _____, F. J. singeR, and u. s. seal. 1991a. Physiological assessment of winter nutri- tional deprivation in elk of Yellowstone National Park. Journal of Wildlife Management 55: 653–664. dunFey-Ball, k. 2017. Moose density, habitat and winter tick epizootics in a changing climate. M. S. Thesis. University of New Hampshire, Durham, New Hampshire, USA. ellingWood, d. 2018. Assessing the impact of winter tick epizootics on moose condition and population dynamics in northern New Hampshire. M. S. Thesis. University of New Hampshire, Durham, New Hampshire, USA. Jones, H., P. J. Pekins, l. e. kantaR, m. o’neil, and d. ellingWood. 2017. Fecundity and summer calf survival of moose during 3 successive years of inter tick epizootics. Alces 53: 85–98. _______, _______, _______, d. ellingWood, i. sidoR, a. liChtenWalneR, and m. o’neil. 2019. Mortality assessment of calf moose during successive years of winter tick epizootics in New Hampshire and Maine. Canadian Journal of Zoology: 97: 22–30. kiRkPatRiCk, R.l., d.e. BuCkland, W.a. aBleR, P.F. sCanlon, J.B. Whalen, and h.e. BuCkhaRt. 1975. Energy and protein influences on blood urea nitrogen of white-tailed fawns. Journal of Wildlife Management 39: 692–698. mason, g. l., and d. J. madden. 2007. Performing the field necropsy examina- tion. Veterinary Clinics Food Animal Practice 23: 503–526. meCh, d. l. 1983. Handbook of Animal Radio Tracking. University of Minnesota Press, Minneapolis, Minnesota, USA. munson, l. 2015. Necropsy of Wild Animals. Wildlife Health Center, School of Veterinary Medicine, University of California Davis, Davis, California, USA. musante, a. R., P. J. Pekins, and d. l. sCaRPitti. 2007. Metabolic impacts of winter tick infestations on calf moose. Alces 43: 101–110. _____, _____, and _____. 2010. Char acteris- tics and dynamics of a regional moose (Alces alces) population in the northeast- ern United States. Wildlife Biology 16: 185–204. neW hamPshiRe Fish and game dePaRtment (nhFg). 2015. New Hampshire Game Management Plan: 2016–2025. New Hampshire Fish and Game Department, Concord, New Hampshire, USA. samuel, W. m. 2004. White as a Ghost: Winter Ticks and Moose. Natural History ALCES VOL. 55, 2019 SNOW URINE SAMPLING – ELLINGWOOD ET AL. 21 Series, Volume 1. Federation of Alberta Naturalists, Edmonton, Alberta, Canada. sChWaRtz, C. C., and l. a. ReneCkeR. 2007. Nutrition and energetics. Pages 441–478 in A. W. Franzmann and C. C. Schwartz, editors. Ecology and Management of the North American Moose, 2nd edition. University Press of Colorado, Boulder, Colorado, USA. seal, u. s., l. J. VeRme, J. J. ozoga, and a. W. eRiCkson. 1972. Nutritional effects on thyroid activity and blood of white-tailed deer. Journal of Wildlife Management 36: 1041–1051. sine, m. e., k. moRRis, and d. knuPP. 2009. Assessment of a line transect method to determine winter tick abundance on moose. Alces 45: 143–146.