Evidence map›Paper›PMID 39614423›Full record

ArticleGlobal change biology2024

Global Land Use Change and Its Impact on Greenhouse Gas Emissions.

Lidong Li, Tala Awada, Yao Zhang, Keith Paustian

Abstract read
In one paragraph

Article in Global change biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Lidong LiUniversity of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0001-5420-260X
Tala AwadaUniversity of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0002-0462-2339
Yao ZhangColorado State University, Fort Collins, Colorado, USA.ORCID 0000-0002-2669-1378
Keith PaustianColorado State University, Fort Collins, Colorado, USA.ORCID 0000-0001-5262-5596

Funding

Partnership on Data Innovation (PDI) of the Agricultural Research Service (ARS), United States Department of Agriculture (USDA)Walmart Foundation
6 · The paper itself

Abstract

Anthropogenic activities have altered approximately two-thirds of the Earth's land surface. Urbanization, industrialization, agricultural expansion, and deforestation are increasingly impacting the terrestrial landscapes, leading to shifts of areas in artificial surface (i.e., humanmade), cropland, pasture, forest, and barren land. Land use patterns and associated greenhouse gas (GHG) emissions play a critical role in global climate change. Here we synthesized 29 years of global historical data and demonstrated how land use impacts global GHG emissions using structural equation modeling. We then obtained predictive estimates of future global GHG emissions using a deep learning model. Our results show that, from 1992 to 2020, the global terrestrial areas covered by artificial surface and cropland have expanded by 133% and 6% because of population growth and socioeconomic development, resulting in 4.0% and 3.8% of declines in pasture and forest areas, respectively. Land use was significantly associated with GHG emissions (p < 0.05). Artificial surface dominates global GHG emissions, followed by cropland, pasture, and barren land. The increase in artificial surfaces has driven up global GHG emissions through the increase in energy consumption. Conversely, improved agricultural management practices have contributed to mitigating agricultural GHG emissions. Forest, on the other hand, serves as a sink of GHG. In total, global GHG emissions increased from 31 to 46 GtCO

Indexed as

AgricultureClimate ChangeGreenhouse GasesConservation of Natural ResourcesModels, TheoreticalUrbanizationGreenhouse Gasesbarren landcropland expansiondeforestationglobal emission predictionpasture loss

Identifiers

PMID39614423
PMCPMC11607391

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.