Evidence map›Paper›PMID 32321948›Full record

ArticleScientific reports2020

Conceptual framework and uncertainty analysis for large-scale, species-agnostic modelling of landscape connectivity across Alberta, Canada.

Ronan Marrec, Hossam E Abdel Moniem, Majid Iravani, Branko Hricko, Jahan Kariyeva, Helene H Wagner

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Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  3. Review
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  9. Modeling an aspirational connected network of protected areas across North America.Ecological applications : a publication of the Ecological Society of America · 2021
    Article
4 · The record

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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

6 authors.

Ronan Marrec *Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada. ronan.marrec@u-picardie.fr.ORCID http://orcid.org/0000-0003-1607-4939
Hossam E Abdel Moniem *Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.
Majid IravaniAlberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, Alberta, Canada.
Branko HrickoAlberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, Alberta, Canada.
Jahan KariyevaAlberta Biodiversity Monitoring Institute, University of Alberta, Edmonton, Alberta, Canada.
Helene H WagnerDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.ORCID http://orcid.org/0000-0001-6261-5922

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sustainable land-use planning should consider large-scale landscape connectivity. Commonly-used species-specific connectivity models are difficult to generalize for a wide range of taxa. In the context of multi-functional land-use planning, there is growing interest in species-agnostic approaches, modelling connectivity as a function of human landscape modification. We propose a conceptual framework, apply it to model connectivity as current density across Alberta, Canada, and assess map sensitivity to modelling decisions. We directly compared the uncertainty related to (1) the definition of the degree of human modification, (2) the decision whether water bodies are considered barriers to movement, and (3) the scaling function used to translate degree of human modification into resistance values. Connectivity maps were most sensitive to the consideration of water as barrier to movement, followed by the choice of scaling function, whereas maps were more robust to different conceptualizations of the degree of human modification. We observed higher concordance among cells with high (standardized) current density values than among cells with low values, which supports the identification of cells contributing to larger-scale connectivity based on a cut-off value. We conclude that every parameter in species-agnostic connectivity modelling requires attention, not only the definition of often-criticized expert-based degrees of human modification.

Identifiers

PMID32321948
PMCPMC7176682

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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.