Evidence map›Paper›PMID 34738174›Full record

ArticleEnvironmental monitoring and assessment2021

The effects of climate change scenarios on Tilia ssp. in Turkey.

Ugur Canturk, Şemsettin Kulaç

Abstract read
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In one paragraph

Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. 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

2 authors.

Ugur CanturkDepartment of Forest Engineering, Faculty of Forestry, Düzce University, 81620, Düzce, Turkey.ORCID http://orcid.org/0000-0001-9552-7419
Şemsettin KulaçDepartment of Forest Engineering, Faculty of Forestry, Düzce University, 81620, Düzce, Turkey. semsettinkulac@duzce.edu.tr.ORCID http://orcid.org/0000-0002-8398-3246

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global climate change will cause significant changes in climate parameters, especially temperature increases and changes in precipitation regimes worldwide. Since the life of living things is directly related to climate parameters, this process will inevitably affect all living things. The plants will be the most affected living things from this process because they do not have an effective movement and migration mechanism. Therefore, global climate change will cause significant species and population losses in plants. To minimize the potential loss of species and populations, it is necessary to predetermine the potential changes in species' distribution areas and take necessary actions. Therefore, this study was aimed to determine the distribution areas of three Tilia species (Tilia tomentosa, Tilia cordata, and Tilia platyphyllos), which have economic, ecologic, and social value and show the local distribution in Turkey and to determine how they will be affected by global climate change. Within this scope, nineteen bioclimatic variables, Emberger climate classification, aspect, and topographic altitude variable were used in the modeling process. By modeling the scenarios SSP 245 and SSP 585, the projections were made for 2040, 2060, 2080, and 2100 regarding the areas suitable for the growth of these species and how these areas will change compared to their current situation. The results suggest that the distribution areas of all three Tilia species will change due to climate change, and the area of loss will be 43.5 km

Indexed as

Climate ChangeTiliaEcologyEnvironmental MonitoringHumansTurkeySSP 245SSP 585Tilia cordataTilia platyphyllosTilia tomentosa

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.