Evidence map›Paper›PMID 29554132›Full record

ArticlePloS one2018

Measuring resilience and assessing vulnerability of terrestrial ecosystems to climate change in South America.

Luciano J S Anjos, Peter Mann de Toledo

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

2 authors.

Luciano J S AnjosCampus de Parauapebas, Universidade Federal Rural da Amazônia - UFRA, Parauapebas, Pará, Brazil.ORCID 0000-0002-3270-6679
Peter Mann de ToledoPrograma de Pós-Graduação em Ciências Ambientais - PPGCA, Instituto de Geociências, Universidade Federal do Pará - UFPA, Belém, Pará, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change has been identified as the primary threat to the integrity and functioning of ecosystems in this century, although there is still much uncertainty about its effects and the degree of vulnerability for different ecosystems to this threat. Here we propose a new methodological approach capable of measuring and mapping the resilience of terrestrial ecosystems at large scales based on their climatic niche. To do this, we used high spatial resolution remote sensing data and ecological niche modeling techniques to calculate and spatialize the resilience of three stable states of ecosystems in South America: forest, savanna, and grassland. Also, we evaluated the sensitivity of ecosystems to climate stress, the likelihood of exposure to non-analogous climatic conditions, and their respective adaptive capacities in the face of climate change. Our results indicate that forests, the most productive and biodiverse terrestrial ecosystems on the earth, are more vulnerable to climate change than savannas or grasslands. Forests showed less resistance to climate stress and a higher chance of exposure to non-analogous climatic conditions. If this scenario occurs, the forest ecosystems would have less chance of adaptation compared to savannas or grasslands because of their narrow climate niche. Therefore, we can conclude that a possible consolidation of non-analogous climatic conditions would lead to a loss of resilience in the forest ecosystem, significantly increasing the chance of a critical transition event to another stable state with a lower density of vegetation cover (e.g., savanna or grassland).

Indexed as

Climate ChangeEcosystemAcclimatizationAdaptation, PhysiologicalAnimalsBiodiversityEcological Parameter MonitoringEndangered SpeciesForestsGrasslandModels, TheoreticalSouth AmericaStress, PhysiologicalTreesUncertainty

Identifiers

PMID29554132
PMCPMC5858834

What OpenQuestion holds

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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.