1. The cost of reproduction on demographic rates is often assumed to operate through changing body condition. Several studies have found that reproduction depresses body mass more if the current conditions are severe, such as high population densities or adverse weather, than under benign environmental conditions. However, few studies have investigated the association between the fitness and body mass costs of reproduction.

2. Using 25 years of individual-based capture-recapture data from Svalbard reindeer (Rangifer tarandus platyrhynchus), we built a novel Bayesian state-space model that jointly estimated inter-annual change in mass, annual reproductive success, and survival, while accounting for incomplete observations. The model allowed us to partition the differential effects of intrinsic and extrinsic factors on both non-reproductive mass change and the body mass cost of reproduction and to quantify their consequences on demographic rates.

3. Contrary to our expectation, the body mass cost of reproduction (mean = 5.8 kg) varied little between years (CV = 0.08) whereas the between-year variation in body mass changes, that were independent of the previous year’s reproductive state, varied substantially (CV = 0.4) in relation to autumn temperature and the amount of rain-on-snow in winter. This mass loss led to a cost of reproduction on the next reproduction, which was amplified by the same environmental covariates, from a 10% reduction in reproductive success in benign years, to a 50% reduction in harsh years. The reproductive mass loss also resulted in a small reduction in survival.

4. Our results show how demographic costs of reproduction, driven by inter-annual fluctuations in individual body condition, result from the balance between body mass costs of reproduction and body mass changes that are independent of previous reproductive state. We illustrate how a strong context dependent fitness cost of reproduction can occur, despite a relatively fixed body mass cost of reproduction. This suggests that female reindeer display a very conservative energy allocation strategy, either aborting their reproductive attempt at an early stage or weaning at a relatively constant cost. Such a strategy might be common in species living in a highly stochastic food limited environment.

The Svalbard reindeer population in Nordenskiöld Land, Svalbard (77°50’–78°20’ N, 15°00’–17°30’ E), was studied in and around the valleys of Reindalen, Semmeldalen and Colesdalen where individual-based monitoring has been conducted, uninterrupted since 1995 (Albon et al., 2017). Up to 2019 a total of 815 individual females have been caught during late winter (mostly April; range: mid-March to early May), using a net stretched between two snowmobiles (Omsjoe et al., 2009). New individuals were marked mainly in their first year of life (c.10 months of age) using coloured and numbered plastic ear tags and collars and were hence of known age. Captured females were weighed to the nearest 0.5 kg and the dataset includes on average 4 annual body mass measurements per individual (sd = 2.2, range = 1 - 12) over their lifetime yielding a total of 2801 mass estimates across these individuals. All capture and live animal handling procedures were performed under licenses from the Norwegian Food Inspection Authority and its predecessor, the Norwegian National Research Authority.

In summer, surveys were conducted by two or more observers using binoculars and telescopes, between 24 June and 25 August to assess the presence or absence of a calf associated with marked females. Average group size in summer is only 2-3 individuals (Loe et al., 2006) facilitating assignment of mother-calf pairs. Since Svalbard consists of open landscapes, animals can be easily spotted and identified at long distances (>1 km). When a female was observed with a calf at heel during the summer census, it was classified as a successful reproduction

We quantified ROS as the total rainfall occurring on days with mean temperatures above 0°C during the months of November to March. We quantified autumn environmental conditions using October degree-days for days with average temperature >0°C. ROS and October degree-days were log transformed. Annual summer environmental conditions were quantified using mean daily June–July temperature, which strongly influences peak plant biomass and consequently forage availability (Van der Wal & Stien, 2014). Also, we investigated the negative effect of high population size on the cost of reproduction. Population size estimates were obtained from an integrated population model (Lee et al., 2015). Population size estimates were detrended prior to the analysis to account for increasing carrying capacity (Hansen et al., 2019). All environmental variables were centred and scaled to a standard deviation of 1 to facilitate model convergence and parameter comparisons.

jagsDat.Rdata is a list containing all necessary data, ready to run the model. Can be imported into R using the load() function.

The .csv files contain the necessary data to re-create the same list but in plain text format.

apr.wt : body mass of females at capture in April (scaled values. mean=42.51285, sd=12.68977).

age: age of female in a given year (=1 the year of birth)

dateCapt: date of capture in April( Jullian day centered at day 107 and divided by sd (9.6). NAs were then filled with 0).

idVar: vector variables relating to individuals all timing numbers are relative to the observation matrix (not actual years)

          first.y: first year captured

          last.y : last year to be considered in the analysis (carcass found and known dead after or before removal (hunting or culling))

          yrbirth: year of birth   

timeVar:  vector variables with length = number of observation occasion

        ros: rain on snow (scale(log(x+1)))

       oct.dd: October degree days (scale(log(x+1)))

       summerTemp: average summer (June-July) temperature (scaled)

      dens: density (scaled(detrended))

      ageC_calf: vector of correspondence between age and age class for the probability to have a calf in august

      ageC_surv: vector of correspondence between age and age class for the probability to survive