Evidence map›Paper›PMID 28095496›Full record

ArticlePloS one2017

Opportunities for Integrated Ecological Analysis across Inland Australia with Standardised Data from Ausplots Rangelands.

Greg R Guerin, Ben Sparrow, Andrew Tokmakoff, Anita Smyth, Emrys Leitch, Zdravko Baruch, Andrew J Lowe

Abstract read
In one paragraph

Article in PloS one, 2017. 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
  2. Article
  3. Effective ecosystem monitoring requires a multi-scaled approach.Biological reviews of the Cambridge Philosophical Society · 2020
    Article
  4. Article
  5. Article
  6. Bacterial natural product biosynthetic domain composition in soil correlates with changes in latitude on a continent-wide scale.Proceedings of the National Academy of Sciences of the United States of America · 2017
    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

7 authors.

Greg R GuerinTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Ben SparrowTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Andrew TokmakoffTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Anita SmythTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Emrys LeitchTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Zdravko BaruchTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
Andrew J LoweTerrestrial Ecosystem Research Network, Adelaide-node, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Australian rangelands ecosystems cover 81% of the continent but are understudied and continental-scale research has been limited in part by a lack of precise data that are standardised between jurisdictions. We present a new dataset from AusPlots Rangelands that enables integrative rangelands analysis due to its geographic scope and standardised methodology. The method provides data on vegetation and soils, enabling comparison of a suite of metrics including fractional vegetation cover, basal area, and species richness, diversity, and composition. Cover estimates are robust and repeatable, allowing comparisons among environments and detection of modest change. The 442 field plots presented here span a rainfall gradient of 129-1437 mm Mean annual precipitation with varying seasonality. Vegetation measurements include vouchered vascular plant species, growth form, basal area, height, cover and substrate type from 1010 point intercepts as well as systematically recorded absences, which are useful for predictive modelling and validation of remote sensing applications. Leaf and soil samples are sampled for downstream chemical and genomic analysis. We overview the sampling of vegetation parameters and environments, applying the data to the question of how species abundance distributions (SADs) vary over climatic gradients, a key question for the influence of environmental change on ecosystem processes. We found linear relationships between SAD shape and rainfall within grassland and shrubland communities, indicating more uneven abundance in deserts and suggesting relative abundance may shift as a consequence of climate change, resulting in altered diversity and ecosystem function. The standardised data of AusPlots enables such analyses at large spatial scales, and the testing of predictions through time with longitudinal sampling. In future, the AusPlots field program will be directed towards improving coverage of space, under-represented environments, vegetation types and fauna and, increasingly, re-sampling of established plots. Providing up-to-date data access methods to enhance re-use is also a priority.

Indexed as

Climate ChangeEcosystemGrasslandRainAustraliaEnvironmental MonitoringSoilSoil

Identifiers

PMID28095496
PMCPMC5241013

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.