Evidence map›Paper›PMID 30604087›Full record

ArticleOecologia2019

Community composition influences the population growth and ecological impact of invasive species in response to climate change.

Danielle Denley, Anna Metaxas, Katja Fennel

Abstract read
PubMed Publisher
In one paragraph

Article in Oecologia, 2019. 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. Review
  2. 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.

Danielle DenleyDepartment of Oceanography, Dalhousie University, Halifax, NS, B3H 4R2, Canada. danielle.denley@dal.ca.
Anna MetaxasDepartment of Oceanography, Dalhousie University, Halifax, NS, B3H 4R2, Canada.
Katja FennelDepartment of Oceanography, Dalhousie University, Halifax, NS, B3H 4R2, Canada.

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2016-04878
6 · The paper itself

Abstract

Predicting long-term impacts of introduced species is challenging, since stressors related to global change can influence species-community interactions by affecting both demographic rates of invasive species and the structure of the invaded ecosystems. Invasive species can alter ecosystem structure over time, further complicating interactions between invasive species and invaded communities in response to additional stressors. Few studies have considered how cumulative impacts of species invasion and global change on the structure of invaded ecosystems may influence persistence and population growth of introduced species. Here, we present an empirically based population model for an invasive epiphytic bryozoan that can dramatically alter the structure of its invaded kelp bed ecosystems. We use this model to predict the response of invasive species to climate change and associated changes in the invaded community. Population growth of the bryozoan increased under near-future projections of increasing ocean temperature; however, the magnitude of population growth depended on the community composition of invaded kelp beds. Our results suggest that, in some cases, indirect effects of climate change mediated through changes to the structure of the invaded habitat can modulate direct effects of climate change on invasive species, with consequences for their long-term ecological impact. Our findings have important implications for management of invasive species, as modifying invaded habitats at local to regional scales may be more logistically feasible than addressing stressors related to global climate change.

Indexed as

Introduced SpeciesKelpClimate ChangeEcosystemPopulation GrowthBryozoanKelp bedsPopulation dynamicsPopulation modelTemperature

Identifiers

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.