Evidence map›Paper›PMID 32211168›Full record

ArticleEcology and evolution2020

From topography to hydrology-The modifiable area unit problem impacts freshwater species distribution models.

Martin Friedrichs-Manthey, Simone D Langhans, Thomas Hein, Florian Borgwardt, Harald Kling, Sonja C Jähnig, Sami Domisch

Abstract read
In one paragraph

Article in Ecology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

7 authors.

Martin Friedrichs-MantheyLeibniz-Institute of Freshwater Ecology and Inland Fisheries Berlin Germany.ORCID https://orcid.org/0000-0003-0644-7869
Simone D LanghansDepartment of Zoology University of Otago Dunedin New Zealand.
Thomas HeinInstitute of Hydrobiology and Aquatic Ecosystem Management University of Natural Resources and Life Sciences Vienna Austria.ORCID https://orcid.org/0000-0002-7767-4607
Florian BorgwardtInstitute of Hydrobiology and Aquatic Ecosystem Management University of Natural Resources and Life Sciences Vienna Austria.
Harald KlingPöyry Austria GmbH Vienna Austria.
Sonja C JähnigLeibniz-Institute of Freshwater Ecology and Inland Fisheries Berlin Germany.ORCID https://orcid.org/0000-0002-6349-9561
Sami DomischLeibniz-Institute of Freshwater Ecology and Inland Fisheries Berlin Germany.ORCID https://orcid.org/0000-0002-8127-9335

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors-a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90-m digital-elevation model by using the GRASS-GIS module

Indexed as

biomod2catchmentDanubefishmodifiable area unit problemriverspecies distribution model

Identifiers

PMID32211168
PMCPMC7083667

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.