Evidence map›Paper›PMID 24829284›Full record

ArticleJournal of the Royal Society, Interface2014

A unifying framework for quantifying the nature of animal interactions.

Jonathan R Potts, Karl Mokross, Mark A Lewis

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2014. 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
–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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution.Ecological applications : a publication of the Ecological Society of America · 2022
    Review
  7. Article
  8. Article
  9. The importance of individual variation in the dynamics of animal collective movements.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Review
  10. Collective movement in ecology: from emerging technologies to conservation and management.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
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

3 authors.

Jonathan R PottsCentre for Mathematical Biology, Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1 jrpotts@ualberta.ca.
Karl MokrossSchool of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA INPA, Projeto Dinâmica Biológica de Fragmentos Florestais, Avenue André Araújo 2936, Petrópolis, Manaus 69083-000, Brazil.
Mark A LewisCentre for Mathematical Biology, Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada T6G 2G1.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest.

Indexed as

Behavior, AnimalModels, BiologicalAnimalsBirdsPopulation DynamicsRainforestTerritorialityanimal movementcollective behaviourinsectivore birdsstep selectionterritorialitytheoretical ecology

Identifiers

PMID24829284
PMCPMC4032549

What OpenQuestion holds

Textmetadata
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.