Evidence map›Paper›PMID 32648358›Full record

ArticleBiological reviews of the Cambridge Philosophical Society2020

Effective ecosystem monitoring requires a multi-scaled approach.

Ben D Sparrow, Will Edwards, Samantha E M Munroe, Glenda M Wardle, Greg R Guerin, Jean-Francois Bastin, Beryl Morris, Rebekah Christensen, Stuart Phinn, Andrew J Lowe

Abstract read
In one paragraph

Article in Biological reviews of the Cambridge Philosophical Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Structured machine learning modeling to support conservation of deep-sea benthic biodiversity.Conservation biology : the journal of the Society for Conservation Biology · 2026
    Article
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  4. Article
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  10. Review
  11. Perspective: sustainability challenges, opportunities and solutions for long-term ecosystem observations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  12. Review
  13. Article
  14. 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

10 authors.

Ben D SparrowTerrestrial Ecosystem Research Network, The School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia.ORCID 0000-0003-2566-1895
Will EdwardsTerrestrial Ecosystem Research Network, College of Science and Engineering, James Cook University, PO Box 6811, Cairns, Queensland, 4870, Australia.
Samantha E M MunroeTerrestrial Ecosystem Research Network, The School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
Glenda M WardleTerrestrial Ecosystem Research Network, Desert Ecology Research Group, School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, 2006, Australia.
Greg R GuerinTerrestrial Ecosystem Research Network, The School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia.
Jean-Francois BastinComputational and Applied Vegetation Ecology Lab, Department of Applied Ecology and Environmental Biology, Faculty of Bioscience Engineering, Ghent University, Ghent, 9000, Belgium.
Beryl MorrisTerrestrial Ecosystem Research Network, The University of Queensland, St Lucia, Queensland, 4072, Australia.
Rebekah ChristensenInstitute for Future Environments, Queensland University of Technology, Gardens Point, Brisbane, Queensland, 4000, Australia.
Stuart PhinnSchool of Earth and Environmental Sciences, The University of Queensland, St Lucia, Queensland, 4072, Australia.
Andrew J LoweSchool of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ecosystem monitoring is fundamental to our understanding of how ecosystem change is impacting our natural resources and is vital for developing evidence-based policy and management. However, the different types of ecosystem monitoring, along with their recommended applications, are often poorly understood and contentious. Varying definitions and strict adherence to a specific monitoring type can inhibit effective ecosystem monitoring, leading to poor program development, implementation and outcomes. In an effort to develop a more consistent and clear understanding of ecosystem monitoring programs, we here review the main types of monitoring and recommend the widespread adoption of three classifications of monitoring, namely, targeted, surveillance and landscape monitoring. Landscape monitoring is conducted over large areas, provides spatial data, and enables questions relating to where and when ecosystem change is occurring to be addressed. Surveillance monitoring uses standardised field methods to inform on what is changing in our environments and the direction and magnitude of that change, whilst targeted monitoring is designed around testable hypotheses over defined areas and is the best approach for determining the causes of ecosystem change. The classification system is flexible and can incorporate different interests, objectives, targets and characteristics as well as different spatial scales and temporal frequencies, while also providing valuable structure and consistency across distinct ecosystem monitoring programs. To support our argument, we examine the ability of each monitoring type to inform on six key types of questions that are routinely posed for ecosystem monitoring programs, such as where and when change is occurring, what is the magnitude of change, and how can the change be managed? As we demonstrate, each type of ecosystem monitoring has its own strengths and weaknesses, which should be carefully considered relative to the desired results. Using this scheme, scientists and land managers can design programs best suited to their needs. Finally, we assert that for our most serious environmental challenges, it is essential that we include information from each of these monitoring scales to inform on all facets of ecosystem change, and this is best achieved through close collaboration between the scales. With a renewed understanding of the importance of each monitoring type, along with greater commitment to monitor cooperatively, we will be well placed to address some of our greatest environmental challenges.

Indexed as

EcosystemEnvironmental MonitoringConservation of Natural Resourcesbiodiversity monitoringcollaborationecological questionsecosystem monitoringenvironmental changeenvironmental monitoringlandscape monitoringresearch infrastructuresurveillance monitoringtargeted monitoring

Identifiers

PMID32648358
PMCPMC7689690

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.