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Dryad

Svalbard reindeer winter diets (1995–2012) dataset

Cite this dataset

Hiltunen, Tamara A. et al. (2022). Svalbard reindeer winter diets (1995–2012) dataset [Dataset]. Dryad. https://doi.org/10.5061/dryad.ghx3ffbs7

Abstract

Arctic ecosystems are changing dramatically with warmer and wetter conditions resulting in complex interactions between herbivores and their forage. We investigated how Svalbard reindeer (Rangifer tarandus platyrhynchus) modify their late winter diets in response to long-term trends and interannual variation in forage availability and accessibility. By reconstructing their diets and foraging niches over a 17-year period (1995–2012) using serum δ13C and δ15N values, we found strong support for a temporal increase in the proportions of graminoids in the diets with a concurrent decline in the contributions of mosses. This dietary shift corresponds with graminoid abundance increases in the region and was associated with increases in population density, warmer summer temperatures and more frequent rain-on-snow (ROS) in winter. In addition, the variance in isotopic niche positions, breadths and overlaps also supported a temporal shift in the foraging niche and a dietary response to extreme ROS events. Our long-term study highlights the mechanisms by which winter and summer climate changes cascade through vegetation shifts and herbivore population dynamics to alter the foraging niche of Svalbard reindeer. Although it has been anticipated that climate changes in the Svalbard region of the Arctic would be detrimental to this unique ungulate, our study suggests that environmental change is in a phase where conditions are improving for this subspecies at the northernmost edge of the Rangifer distribution.

Methods

Sample & Data Collection

We collected serum from Svalbard reindeer in late winter, which is the critical period for their winter survival and reconstructed their diets using serum δ13C and δ15N values. Serum samples were obtained from 1995 to 2012, excluding the years 2003 and 2010, resulting in a total of 16 sampling campaigns. Altogether 232 samples were collected from 182 individual reindeer, thus, some individuals were sampled only once and others up to three times during our study period. The number of samples per campaign ranged from 10–21, with the average value being 15. For reconstructing the diets of Svalbard reindeer, foliar δ13C and δ15N values of plausible (terrestrial) forage plants, including graminoids, mosses, dwarf shrubs (S. polaris; D. octopetala) and forbs were obtained from previous studies (Hansen, Lorentzen, et al., 2019; Zhao et al., 2019). Briefly, plant samples were collected in Semmeldalen (77°90' N, 15°20' E) during July 2009 and 2013 from Luzula heath and graminoid vegetation communities (Zhao et al., 2019), and from reindeer feeding craters in Adventdalen (78°10' N, 16°02' E) in March 2013 (Hansen, Lorentzen, et al., 2019). Foliar δ13C and δ15N values may vary over time due to differences in environmental conditions, so to control for this, vegetation was re-sampled in Adventdalen in February 2019 from five randomly selected 4 m2 plots as no feeding craters were observed due to extreme ground icing. The plant samples collected were graminoids (n = 2), mosses (n = 4), S. polaris (n = 2) and D. octopetala (n = 5). Forbs (n= 4) were collected as they were present in the plots but not present in or collected from the craters sampled in 2013.

The δ13C and δ15N values were obtained after the serum samples were analysed at the Environment and Natural Resources Institute Stable Isotope Laboratory at the University of Alaska Anchorage (http://www.uaa.alaska.edu/enri/labs/sils) and the 2019 forage samples at the EcoCore Analytical Facility at the Colorado State University (https://ecocore.nrel.colostate.edu/ecocore-stable-isotope-analysis.html).  

Data preparation and analysis

Anthropogenic inputs of C from fossil fuel burning have resulted in measurable decreases in atmospheric δ13C known as the “Suess effect” and some authors utilise a time-dependent correction of -0.022 ‰ per year based on ice core records to account for this change. However, the discrimination of  δ13C during photosynthesis in C3 plants has been found to increase in response to increasing concentrations of atmospheric CO2 (pCO2) and decreasing atmospheric δ13CCO2 (Schubert & Jahren, 2012). Thus, we used the equation of Schubert & Jahren (2012) and annual pCO2 (Tans & Keeling, 2022) to correct all serum and forage samples' δ13C values to expected 2012 levels. 

The reindeer isotope data were used in conjunction with the forage isotope data and trophic discrimination factors derived in the R-package: SIDER, in Bayesian stable isotope mixing models (R-package: simmr) to estimate dietary proportions and isotopic niche space models (R-package: SIBER).

In addition, we used linear regressions to explore how reindeer serum isotopic values were driven by variation in forage production (summer warming - July Average temperature), forage accessibility (Rain-on-Snow - ROS [mm]), intra-specific competition (population density), and intrinsic drivers like nutritional status (body mass [kg]) and status concerning pregnancy (as determined by Progesterone. 

  • Population density in the Reindalen valley system the previous summer to account for density-dependent competitive effects (Albon et al., 2017).
  • ROS (mm), measured as the sum of precipitation when the average daily temperature was ≥1°C during the winter (1st November to the 31st March), as a proxy for ground ice (Peeters et al., 2019).
  • July average air temperatures at Svalbard Airport, obtained from the Norwegian Meteorological Institute (2021), as a proxy for summer plant biomass production (van der Wal & Stien, 2014).

Population density and ROS were ln-transformed before being fitted as predictor variables in the model for δ13C. 

References

  • Albon, S. D., Irvine, R. J., Halvorsen, O., Langvatn, R., Loe, L. E., Ropstad, E., Veiberg, V., van der Wal, R., Bjørkvoll, E. M., Duff, E. I., Hansen, B. B., Lee, A. M., Tveraa, T., & Stien, A. (2017). Contrasting effects of summer and winter warming on body mass explain population dynamics in a food‐limited Arctic herbivore. Global Change Biology, 23(4), 1374–1389. https://doi.org/10.1111/gcb.13435
  • Hansen, B. B., Lorentzen, J. R., Welker, J. M., Varpe, Ø., Aanes, R., Beumer, L. T., & Pedersen, Å. Ø. (2019). Reindeer turning maritime: ice‐locked tundra triggers changes in dietary niche utilization. Ecosphere, 10(4), e02672. https://doi.org/10.1002/ecs2.2672
  • Norwegian Meteorological Institute. (2021). Seasonal temperatures for Svalbard Airport. Environmental monitoring of Svalbard and Jan Mayen (MOSJ). http://www.mosj.no/en/climate/atmosphere/temperature-precipitation.html
  • Peeters, B., Pedersen, Å. Ø., Loe, L. E., Isaksen, K., Veiberg, V., Stien, A., Kohler, J., Gallet, J.-C., Aanes, R., & Hansen, B. B. (2019). Spatiotemporal patterns of rain-on-snow and basal ice in high Arctic Svalbard: detection of a climate-cryosphere regime shift. Environmental Research Letters, 14(1), 015002. https://doi.org/10.1088/1748-9326/aaefb3
  • Schubert, B. A., & Jahren, A. H. (2012). The effect of atmospheric CO2 concentration on carbon isotope fractionation in C3 land plants. Geochimica et Cosmochimica Acta, 96, 29–43. https://doi.org/10.1016/j.gca.2012.08.003
  • Tans, P. & Keeling, R. (2022). Mauna Loa CO2 annual mean data. NOAA/GML & Scripps Institution of Oceanography. https://gml.noaa.gov/ccgg/trends/data.html
  • van der Wal, R., & Stien, A. (2014). High-arctic plants like it hot: a long-term investigation of between-year variability in plant biomass. Ecology, 95(12), 3414–3427. https://doi.org/10.1890/14-0533.1.sm
  • Zhao, L. Z., Colman, A. S., Irvine, R. J., Karlsen, S. R., Olack, G., & Hobbie, E. A. (2019). Isotope ecology detects fine-scale variation in Svalbard reindeer diet: implications for monitoring herbivory in the changing Arctic. Polar Biology, 42(4), 793–805. https://doi.org/10.1007/s00300-019-02474-8

Usage notes

Microsoft Excel

All analyses were done in R version 4.05. (R Core Team, 2021) in R Studio (version 1.4.1106).

R-packages:

  • simmr version 0.4.5
  • SIDER version 1.0.0.0
  • SIBER (Stable Isotope Bayesian Ellipses in R package) version 2.1.5
  • lme4 version 1.1–27.1
  • cAIC4 version 1.0
  • piecewiseSEM version 2.1.2
  • redres version 0.0.0.9

Funding

National Science Foundation, Award: Major Research Instrumentation award 0953271

Natural Environment Research Council, Award: GR3/1083

UArctic Chairship, Award: Distinguished US Arctic Chairship-Norway Inaugural UArctic Research Chairship