Evidence map›Paper›PMID 26668731›Full record

ArticleEcology and evolution2015

Modeling directional spatio-temporal processes in island biogeography.

José C Carvalho, Pedro Cardoso, François Rigal, Kostas A Triantis, Paulo A V Borges

Abstract read
In one paragraph

Article in Ecology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Ecosystem services provided by spiders.Biological reviews of the Cambridge Philosophical Society · 2025
    Review
  2. Comparative phylogeography of oceanic archipelagos: Hotspots for inferences of evolutionary process.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Review
  3. 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

5 authors.

José C CarvalhoCE3C - Centre for Ecology Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores - Departamento de Ciências Agrárias 9700-042 Angra do Heroísmo Açores Portugal ; Department of Biology CBMA - Centre for Molecular and Environmental Biology University of Minho 4710-087 Braga Portugal.
Pedro CardosoCE3C - Centre for Ecology Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores - Departamento de Ciências Agrárias 9700-042 Angra do Heroísmo Açores Portugal ; Finnish Museum of Natural History University of Helsinki P.O. Box 17, 00014 Helsinki Finland.
François RigalCE3C - Centre for Ecology Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores - Departamento de Ciências Agrárias 9700-042 Angra do Heroísmo Açores Portugal.
Kostas A TriantisCE3C - Centre for Ecology Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores - Departamento de Ciências Agrárias 9700-042 Angra do Heroísmo Açores Portugal ; Department of Ecology and Taxonomy Faculty of Biology National and Kapodistrian University Athens GR-15784 Greece ; Conservation Biogeography and Macroecology Programme School of Geography and the Environment University of Oxford, South Parks Road Oxford OX1 3QY UK.
Paulo A V BorgesCE3C - Centre for Ecology Evolution and Environmental Changes / Azorean Biodiversity Group and Universidade dos Açores - Departamento de Ciências Agrárias 9700-042 Angra do Heroísmo Açores Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key challenge in island biogeography is to quantity the role of dispersal in shaping biodiversity patterns among the islands of a given archipelago. Here, we propose such a framework. Dispersal within oceanic archipelagos may be conceptualized as a spatio-temporal process dependent on: (1) the spatial distribution of islands, because the probability of successful dispersal is inversely related to the spatial distance between islands and (2) the chronological sequence of island formation that determines the directional asymmetry of dispersal (hypothesized to be predominantly from older to younger islands). From these premises, directional network models may be constructed, representing putative connections among islands. These models may be translated to eigenfunctions in order to be incorporated into statistical analysis. The framework was tested with 12 datasets from the Hawaii, Azores, and Canaries. The explanatory power of directional network models for explaining species composition patterns, assessed by the Jaccard dissimilarity index, was compared with simpler time-isolation models. The amount of variation explained by the network models ranged from 5.5% (for Coleoptera in Hawaii) to 60.2% (for Pteridophytes in Canary Islands). In relation to the four studied taxa, the variation explained by network models was higher for Pteridophytes in the three archipelagos. By the contrary, small fractions of explained variation were observed for Coleoptera (5.5%) and Araneae (8.6%) in Hawaii. Time-isolation models were, in general, not statistical significant and explained less variation than the equivalent directional network models for all the datasets. Directional network models provide a way for evaluating the spatio-temporal signature of species dispersal. The method allows building scenarios against which hypotheses about dispersal within archipelagos may be tested. The new framework may help to uncover the pathways via which species have colonized the islands of a given archipelago and to understand the origins of insular biodiversity.

Indexed as

Community assemblydispersal limitationisland colonizationnetwork analysisoceanic islandsspatio‐temporal modeling

Identifiers

PMID26668731
PMCPMC4670066

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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.