DOI: 10.5061/dryad.80gb5mkrj
title: Context dependent fitness costs of reproduction despite stable body mass costs in an Arctic herbivore

description: 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.
description: 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 (&gt;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 &gt;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.
description: 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