Evidence map›Paper›PMID 29320564›Full record

ArticlePloS one2018

A time-lagged effect of conspecific density on habitat selection by snowshoe hare.

Toshinori Kawaguchi, André Desrochers

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Toshinori KawaguchiCentre d'étude de la forêt, and Département des sciences du bois et de la forêt, Université Laval, Québec, Québec, Canada.ORCID 0000-0001-8214-067X
André DesrochersCentre d'étude de la forêt, and Département des sciences du bois et de la forêt, Université Laval, Québec, Québec, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ideal free distribution theory predicts that increased conspecific density redistributes individuals to low-density, suboptimal habitat. However, possible lags in response to population density remain poorly documented. Snowshoe hares (Lepus americanus) may exhibit density-dependent habitat selection due to its marked variation in population density. Based on 11 years (2004-2014) of snow tracking in Quebec (Canada), we investigated snowshoe hares' short-term and delayed habitat selection responses to population density. We predicted that at high densities, hare distribution expands into low-density habitat, thus weakening the association between hares and high-density habitat. We surveyed hare tracks along 95 km of transects on average each year and georeferenced 14,240 tracks. We used Generalized Estimating Equations for track count per 100 m transect segment as a function of the proportion of different forest age classes (0-20 y, 20-40 y and 40-80 y) within 50 m of the segments. We used model coefficients for each age class as a measure of habitat preference, and modeled those coefficients as a function of a population density index in current and previous winters. Coefficients for 20- to 40-y-old forests were positive each year, indicating that this habitat was preferred. The association between track counts and 20- to 40-y-old forest significantly declined with density during the previous winter, suggesting that hare spread from preferred forest with a lagged response to density. To our knowledge, no previous empirical studies have documented a lagged habitat selection response to population density. Time lags offer possible explanation for documented deviations from ideal free distribution models.

Indexed as

Behavior, AnimalEcosystemAnimalsHaresPopulation DensityQuebecSeasons

Identifiers

PMID29320564
PMCPMC5761860

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Registered trials

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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.