Evidence map›Paper›PMID 36443278›Full record

ArticleGlobal change biology2023

Challenges in upscaling laboratory studies to ecosystems in soil microbiology research.

Ji Chen, Yong Zhang, Yakov Kuzyakov, Dong Wang, Jørgen Eivind Olesen

Abstract read
In one paragraph

Article in Global change biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 citing papers in PubMed.

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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.

Ji ChenState Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China.ORCID 0000-0001-7026-6312
Yong ZhangKey Laboratory of Soil Ecology and Health in Universities of Yunnan Province, School of Ecology and Environmental Sciences, Yunnan University, Kunming, China.ORCID 0000-0002-1181-032X
Yakov KuzyakovDepartment of Soil Science of Temperate Ecosystems, University of Göttingen, Göttingen, Germany.ORCID 0000-0002-9863-8461
Dong WangInternational Joint Research Laboratory of Global Change Ecology, School of Life Sciences, Henan University, Kaifeng, China.ORCID 0000-0003-4533-1615
Jørgen Eivind OlesenDepartment of Agroecology, Aarhus University, Tjele, Denmark.ORCID 0000-0002-6639-1273

Funding

Aarhus Universitets Forskningsfond AUFF-E-2019-7-1Det Frie Forskningsråd 1127-00015BEU H2020 Marie Skłodowska-Curie Actions 839806National Natural Science Foundation of China 32130066Nordic Committee of Agriculture and Food ResearchRUDN University Strategic Academic Leadership Program
6 · The paper itself

Abstract

Soil microbiology has entered into the big data era, but the challenges in bridging laboratory-, field-, and model-based studies of ecosystem functions still remain. Indeed, the limitation of factors in laboratory experiments disregards interactions of a broad range of in situ environmental drivers leading to frequent contradictions between laboratory- and field-based studies, which may consequently mislead model development and projections. Upscaling soil microbiology research from laboratory to ecosystems represents one of the grand challenges facing environmental scientists, but with great potential to inform policymakers toward climate-smart and resource-efficient ecosystems. The upscaling is not only a scale problem, but also requires disentangling functional relationships and processes on each level. We point to three potential reasons for the gaps between laboratory- and field-based studies (i.e., spatiotemporal dynamics, sampling disturbances, and plant-soil-microbial feedbacks), and three key issues of caution when bridging observations and model predictions (i.e., across-scale effect, complex-process coupling, and multi-factor regulation). Field-based studies only cover a limited range of environmental variation that must be supplemented by laboratory and mesocosm manipulative studies when revealing the underlying mechanisms. The knowledge gaps in upscaling soil microbiology from laboratory to ecosystems should motivate interdisciplinary collaboration across experimental, observational, theoretic, and modeling research.

Indexed as

EcosystemSoil MicrobiologyModels, TheoreticalPlantsSoilSoilfield in situ observationglobal change factorslaboratory incubationmicrobial-based modelssoil biogeochemistrysoil microbiology

Identifiers

PMID36443278
PMCPMC10100248

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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.