Evidence map›Paper›PMID 28886208›Full record

ArticleThe Journal of animal ecology2018

Interacting effects of unobserved heterogeneity and individual stochasticity in the life history of the southern fulmar.

Stéphanie Jenouvrier, Lise M Aubry, Christophe Barbraud, Henri Weimerskirch, Hal Caswell

Open access · hybridAbstract read
In one paragraph

Article in The Journal of animal ecology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. Article
  3. Exposing the role of individual heterogeneity in bighorn sheep population dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Uncovering bighorn sheep life-history trajectories in multidimensional trait space.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  6. Nutritional state variations in a tropical seabird throughout its breeding season.Journal of comparative physiology. B, Biochemical, systemic, and environmental physiology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 3 countries.

Stéphanie JenouvrierBiology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA.ORCID http://orcid.org/0000-0003-3324-2383
Lise M AubryFish, Wildlife and Conservation Biology Department, Colorado State University, Fort Collins, CO, USA.
Christophe BarbraudCentre d'Etudes Biologiques de Chizé, UMR 7372 CNRS, Univ La Rochelle, Villiers en Bois, France.
Henri WeimerskirchCentre d'Etudes Biologiques de Chizé, UMR 7372 CNRS, Univ La Rochelle, Villiers en Bois, France.
Hal CaswellBiology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA.
Centre National de la Recherche Scientifique · FRColorado Parks and Wildlife · USWoods Hole Oceanographic Institution · US

Funding

European Research Council 322989
6 · The paper itself

Abstract

Individuals are heterogeneous in many ways. Some of these differences are incorporated as individual states (e.g. age, size, breeding status) in population models. However, substantial amounts of heterogeneity may remain unaccounted for, due to unmeasurable genetic, maternal or environmental factors. Such unobserved heterogeneity (UH) affects the behaviour of heterogeneous cohorts via intra-cohort selection and contributes to inter-individual variance in demographic outcomes such as longevity and lifetime reproduction. Variance is also produced by individual stochasticity, due to random events in the life cycle of wild organisms, yet no study thus far has attempted to decompose the variance in demographic outcomes into contributions from UH and individual stochasticity for an animal population in the wild. We developed a stage-classified matrix population model for the southern fulmar breeding on Ile des Pétrels, Antarctica. We applied multievent, multistate mark-recapture methods to estimate a finite mixture model accounting for UH in all vital rates and Markov chain methods to calculate demographic outcomes. Finally, we partitioned the variance in demographic outcomes into contributions from UH and individual stochasticity. We identify three UH groups, differing substantially in longevity, lifetime reproductive output, age at first reproduction and in the proportion of the life spent in each reproductive state. -14% of individuals at fledging have a delayed but high probability of recruitment and extended reproductive life span. -67% of individuals are less likely to reach adulthood, recruit late and skip breeding often but have the highest adult survival rate. -19% of individuals recruit early and attempt to breed often. They are likely to raise their offspring successfully, but experience a relatively short life span. Unobserved heterogeneity only explains a small fraction of the variances in longevity (5.9%), age at first reproduction (3.7%) and lifetime reproduction (22%). UH can affect the entire life cycle, including survival, development and reproductive rates, with consequences over the lifetime of individuals and impacts on cohort dynamics. The respective role of UH vs. individual stochasticity varies greatly among demographic outcomes. We discuss the implication of our finding for the gradient of life-history strategies observed among species and argue that individual differences should be accounted for in demographic studies of wild populations.

Indexed as

Life History TraitsLongevityReproductionAge FactorsAnimalsAntarctic RegionsBirdsModels, BiologicalStochastic Processesfrailtyindividual qualitylatentlife expectancylifetime reproductive success

Identifiers

PMID28886208
PMCPMC5765524
OpenAlexW2753498134

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.