Dataset Information

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese.

ABSTRACT: Quantifying how key life-history traits respond to climatic change is fundamental in understanding and predicting long-term population prospects. Age at first reproduction (AFR), which affects fitness and population dynamics, may be influenced by environmental stochasticity but has rarely been directly linked to climate change. Here, we use a case study from the highly seasonal and stochastic environment in High-Arctic Svalbard, with strong temporal trends in breeding conditions, to test whether rapid climate warming may induce changes in AFR in barnacle geese, Branta leucopsis. Using long-term mark-recapture and reproductive data (1991-2017), we developed a multi-event model to estimate individual AFR (i.e. when goslings are produced). The annual probability of reproducing for the first time was negatively affected by population density but only for 2 year olds, the earliest age of maturity. Furthermore, advanced spring onset (SO) positively influenced the probability of reproducing and even more strongly the probability of reproducing for the first time. Thus, because climate warming has advanced SO by two weeks, this likely led to an earlier AFR by more than doubling the probability of reproducing at 2 years of age. This may, in turn, impact important life-history trade-offs and long-term population trajectories.

SUBMITTER: Fjelldal MA

PROVIDER: S-EPMC7211454 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese.

Fjelldal Mari Aas MA Layton-Matthews Kate K Lee Aline Magdalena AM Grøtan Vidar V Loonen Maarten J J E MJJE Hansen Brage Bremset BB

Biology letters 20200408 4

Quantifying how key life-history traits respond to climatic change is fundamental in understanding and predicting long-term population prospects<i>.</i> Age at first reproduction (AFR), which affects fitness and population dynamics, may be influenced by environmental stochasticity but has rarely been directly linked to climate change<i>.</i> Here, we use a case study from the highly seasonal and stochastic environment in High-Arctic Svalbard, with strong temporal trends in breeding conditions, t ...[more]

PMID: 32264780

Similar Datasets

Project description:Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues including digital online infrastructure representing a 'New Artic'. Arctic grazers, like Eastern Russian migratory populations of Tundra Bean Goose Anser fabalis and Greater White-fronted Goose A. albifrons, are representative examples and they are affected along the entire flyway in East Asia, namely China, Japan and Korea. Here we present the best publicly-available long-term (24 years) digitized geographic information system (GIS) data for the breeding study area (East Yakutia and Chukotka) and its habitats with ISO-compliant metadata. Further, we used seven publicly available compiled Open Access GIS predictor layers to predict the distribution for these two species within the tundra habitats. Using BIG DATA we are able to improve on the ecological niche prediction inference for both species by focusing for the first time specifically on biological relevant population cohorts: post-breeding moulting non-breeders, as well as post-breeding parent birds with broods. To assure inference with certainty, we assessed it with 4 lines of evidence including alternative best-available open access field data from GBIF.org as well as occurrence data compiled from the literature. Despite incomplete data, we found a good model accuracy in support of our evidence for a robust inference of the species distributions. Our predictions indicate a strong publicly best-available relative index of occurrence (RIO). These results are based on the quantified ecological niche showing more realistic gradual occurrence patterns but which are not fully in agreement with the current strictly applied parsimonious flyway and species delineations. While our predictions are to be improved further, e.g. when synergetic data are made freely available, here we offer within data caveats the first open access model platform for fine-tuning and future predictions for this otherwise poorly represented region in times of a rapid changing industrialized 'New Arctic' with global repercussions.

Dataset Information

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese.

Publications

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets