ArticlePloS one2014
Early warning signals of ecological transitions: methods for spatial patterns.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
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Who cites it
79 citing papers in PubMed.
- Early Warning Signals in Ecological Time-Series.Entropy (Basel, Switzerland) · 2026Review
- Climatic Legacies Drive Spatial Aggregation of Plants in Drylands.Global change biology · 2026Article
- Spatial early-warning assessment of ecological security in the Poyang Lake Basin based on PSR and Spatial Durbin Modeling.Scientific reports · 2026Article
- How spatial patterns can lead to less resilient ecosystems.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Spatial early warning signals to assess economic resilience.iScience · 2025Article
- Utilizing Causal Network Markers to Identify Tipping Points ahead of Critical Transition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Eco-Inspired terraform networks emerge from material self-organization.Scientific reports · 2025Article
- Mechanisms causing the transition between spatial pattern long transients.Royal Society open science · 2025Article
- Medium plant cover maximizes fine-scale spatial heterogeneity in humid grasslands of Southwest China.Scientific reports · 2025Article
- Identifying COVID-19 peaks using early warning signals.PLoS computational biology · 2025Article
- Anticipating depression trajectories by measuring plasticity and change through symptom network dynamics.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Revealing Physical Mechanisms of Spatial Pattern Formation and Switching in Ecosystems via Nonequilibrium Landscape and Flux.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Applicability of spatial early warning signals to complex network dynamics.Journal of the Royal Society, Interface · 2025Article
- Insights Into Spatial Synchrony Enabled by Long-Term Data.Ecology letters · 2025Review
- Evaluation of early warning signals for soil erosion using remote sensing indices in northeastern Iran.Scientific reports · 2025Article
- The population dynamics of clustered consumer-resource spatial patterns: Insights from the demographics of a Turing mechanism.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Assessing and comparing early warning signal performance in spatially-structured systems.PloS one · 2025Article
- Article
- An Assessment of Vegetation Changes in the Three-River Headwaters Region, China: Integrating NDVI and Its Spatial Heterogeneity.Plants (Basel, Switzerland) · 2024Article
- Early warning signals for bifurcations embedded in high dimensions.Scientific reports · 2024Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data.
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