↓ Skip to main content

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, November 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

news
5 news outlets
blogs
1 blog
twitter
42 X users
facebook
2 Facebook pages
googleplus
1 Google+ user

Readers on

mendeley
289 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems
Published in
Proceedings of the National Academy of Sciences of the United States of America, November 2016
DOI 10.1073/pnas.1608242113
Pubmed ID
Authors

Alena Sonia Gsell, Ulrike Scharfenberger, Deniz Özkundakci, Annika Walters, Lars-Anders Hansson, Annette B. G. Janssen, Peeter Nõges, Philip C. Reid, Daniel E. Schindler, Ellen Van Donk, Vasilis Dakos, Rita Adrian

Abstract

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 42 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 289 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Canada 2 <1%
United Kingdom 1 <1%
Switzerland 1 <1%
Argentina 1 <1%
Brazil 1 <1%
Unknown 280 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 68 24%
Student > Ph. D. Student 55 19%
Student > Master 39 13%
Student > Bachelor 14 5%
Professor 11 4%
Other 48 17%
Unknown 54 19%
Readers by discipline Count As %
Environmental Science 93 32%
Agricultural and Biological Sciences 57 20%
Earth and Planetary Sciences 18 6%
Engineering 12 4%
Physics and Astronomy 7 2%
Other 31 11%
Unknown 71 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 67. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2023.
All research outputs
#650,580
of 26,017,215 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#11,037
of 104,451 outputs
Outputs of similar age
#13,115
of 422,148 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#233
of 922 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 104,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 422,148 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 922 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.