Evidence map›Paper›PMID 36919015›Full record

ArticleEcology and evolution2023

SER: An R package to characterize environmental regimes.

Naicheng Wu, Kun Guo, Yi Zou, Fengzhi He, Tenna Riis

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Article in Ecology and evolution, 2023. 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
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  3. Review
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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.

Naicheng WuDepartment of Geography and Spatial Information Techniques Ningbo University Ningbo China.ORCID https://orcid.org/0000-0002-5652-3631
Kun GuoSchool of Ecological and Environmental Sciences East China Normal University Shanghai China.ORCID https://orcid.org/0000-0001-9597-2977
Yi ZouDepartment of Health and Environmental Sciences Xi'an Jiaotong-Liverpool University Suzhou China.
Fengzhi HeLeibniz Institute of Freshwater Ecology and Inland Fisheries Berlin Germany.
Tenna RiisDepartment of Biology Aarhus University Aarhus C Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental regimes (or environmental legacy or historical legacy) are the dynamics of environmental characteristics over a given (either long or short) time period, such as frequency of mean or extreme events and rate of change, which might be absent by using only contemporary variables. We present SER, an R package for estimating environmental regimes for different environmental variables. Using the data included in the package, several examples are shown. SER is suitable for any type of environmental or biotic variables, including nutrient concentration, light, and dissolved oxygen. In addition, by changing the argument "days_bf," it is possible to compute environmental regimes over any time period, such as days, months, or years. Our case study showed that the inclusion of environmental regimes increased the explained variation of temporal β-diversity and its components. Environmental regimes are expected to advance the "environment-community" relationships in ecological studies. They can further be implemented in other subjects such as social science, socioeconomics, and epidemiology.

Indexed as

environmental legacyenvironmental variableshistorical legacyregimeR packageSER

Identifiers

PMID36919015
PMCPMC10008288

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Registered trials

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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.