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Santillán-Sarmiento A, Pazzaglia J, Ruocco M, Dattolo E, Ambrosino L, Winters G, Marin-Guirao L, Procaccini G. Gene co-expression network analysis for the selection of candidate early warning indicators of heat and nutrient stress in Posidonia oceanica. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162517. [PMID: 36868282 DOI: 10.1016/j.scitotenv.2023.162517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 02/01/2023] [Accepted: 02/24/2023] [Indexed: 05/06/2023]
Abstract
The continuous worldwide seagrasses decline calls for immediate actions in order to preserve this precious marine ecosystem. The main stressors that have been linked with decline in seagrasses are 1) the increasing ocean temperature due to climate change and 2) the continuous inputs of nutrients (eutrophication) associated with coastal human activities. To avoid the loss of seagrass populations, an "early warning" system is needed. We used Weighed Gene Co-expression Network Analysis (WGCNA), a systems biology approach, to identify potential candidate genes that can provide an early warning signal of stress in the Mediterranean iconic seagrass Posidonia oceanica, anticipating plant mortality. Plants were collected from both eutrophic (EU) and oligotrophic (OL) environments and were exposed to thermal and nutrient stress in a dedicated mesocosm. By correlating the whole-genome gene expression after 2-weeks exposure with the shoot survival percentage after 5-weeks exposure to stressors, we were able to identify several transcripts that indicated an early activation of several biological processes (BP) including: protein metabolic process, RNA metabolic process, organonitrogen compound biosynthetic process, catabolic process and response to stimulus, which were shared among OL and EU plants and among leaf and shoot apical meristem (SAM), in response to excessive heat and nutrients. Our results suggest a more dynamic and specific response of the SAM compared to the leaf, especially the SAM from plants coming from a stressful environment appeared more dynamic than the SAM from a pristine environment. A vast list of potential molecular markers is also provided that can be used as targets to assess field samples.
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Affiliation(s)
| | - Jessica Pazzaglia
- Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy; Department of Life Sciences, University of Trieste, Trieste, Italy
| | - Miriam Ruocco
- Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy
| | - Emanuela Dattolo
- Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy
| | - Luca Ambrosino
- Research Infrastructure for Marine Biological Resources Department, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy
| | - Gidon Winters
- Dead Sea and Arava Science Center (DSASC), Masada National Park, Mount Masada 8698000, Israel.; Eilat Campus, Ben-Gurion University of the Negev, Hatmarim Blv, Eilat 8855630, Israel
| | - Lázaro Marin-Guirao
- Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy; Seagrass Ecology Group, Oceanographic Center of Murcia, Spanish Institute of Oceanography (IEO-CSIC), Murcia, Spain
| | - Gabriele Procaccini
- Department of Integrative Marine Ecology, Stazione Zoologica Anton Dohrn, 80121 Naples, Italy.
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Abstract
Studying ecosystem dynamics is critical to monitoring and managing linked systems of humans and nature. Due to the growth of tools and techniques for collecting data, information on the condition of these systems is more widely available. While there are a variety of approaches for mining and assessing data, there is a need for methods to detect latent characteristics in ecosystems linked to temporal and spatial patterns of change. Resilience-based approaches have been effective at not only identifying environmental change but also providing warning in advance of critical transitions in social-ecological systems (SES). In this study, we examine the usefulness of one such method, Fisher Information (FI) for spatiotemporal analysis. FI is used to assess patterns in data and has been established as an effective tool for capturing complex system dynamics to include regimes and regime shifts. We employed FI to assess the biophysical condition of eighty-five Swedish lakes from 1996–2018. Results showed that FI captured spatiotemporal changes in the Swedish lakes and identified distinct spatial patterns above and below the Limes Norrlandicus, a hard ecotone boundary which separates northern and southern ecoregions in Sweden. Further, it revealed that spatial variance changed approaching this boundary. Our results demonstrate the utility of this resilience-based approach for spatiotemporal and spatial regimes analyses linked to monitoring and managing critical watersheds and waterbodies impacted by accelerating environmental change.
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Tarazona A, Forment J, Elena SF. Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers. Viruses 2019; 12:E16. [PMID: 31861938 PMCID: PMC7019593 DOI: 10.3390/v12010016] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 12/17/2019] [Accepted: 12/19/2019] [Indexed: 12/16/2022] Open
Abstract
Complex systems exhibit critical thresholds at which they transition among alternative phases. Complex systems theory has been applied to analyze disease progression, distinguishing three stages along progression: (i) a normal noninfected state; (ii) a predisease state, in which the host is infected and responds and therapeutic interventions could still be effective; and (iii) an irreversible state, where the system is seriously threatened. The dynamical network biomarker (DNB) theory sought for early warnings of the transition from health to disease. Such DNBs might range from individual genes to complex structures in transcriptional regulatory or protein-protein interaction networks. Here, we revisit transcriptomic data obtained during infection of tobacco plants with tobacco etch potyvirus to identify DNBs signaling the transition from mild/reversible to severe/irreversible disease. We identified genes showing a sudden transition in expression along disease categories. Some of these genes cluster in modules that show the properties of DNBs. These modules contain both genes known to be involved in response to pathogens (e.g., ADH2, CYP19, ERF1, KAB1, LAP1, MBF1C, MYB58, PR1, or TPS5) and other genes not previously related to biotic stress responses (e.g., ABCI6, BBX21, NAP1, OSM34, or ZPN1).
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Affiliation(s)
- Adrián Tarazona
- Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, Paterna, 46980 València, Spain;
| | - Javier Forment
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), CSIC-Universitat Politècnica de València, 46022 València, Spain;
| | - Santiago F. Elena
- Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, Paterna, 46980 València, Spain;
- The Santa Fe Institute, Santa Fe, NM 87501, USA
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Sankaran S, Majumder S, Viswanathan A, Guttal V. Clustering and correlations: Inferring resilience from spatial patterns in ecosystems. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13304] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sumithra Sankaran
- Centre for Ecological Sciences Indian Institute of Science Bengaluru India
| | - Sabiha Majumder
- Centre for Ecological Sciences Indian Institute of Science Bengaluru India
- Institut für Integrative Biologie ETH Zurich Zürich Switzerland
| | - Ashwin Viswanathan
- Centre for Ecological Sciences Indian Institute of Science Bengaluru India
- Nature Conservation Foundation Bengaluru India
| | - Vishwesha Guttal
- Centre for Ecological Sciences Indian Institute of Science Bengaluru India
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Eason T, Chuang WC, Sundstrom S, Cabezas H. An information theory-based approach to assessing spatial patterns in complex systems. ENTROPY (BASEL, SWITZERLAND) 2019; 21:182. [PMID: 31402835 PMCID: PMC6688651 DOI: 10.3390/e21020182] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 02/14/2019] [Indexed: 01/14/2023]
Abstract
Given the intensity and frequency of environmental change, the linked and cross-scale nature of social-ecological systems, and the proliferation of big data, methods that can help synthesize complex system behavior over a geographical area are of great value. Fisher information evaluates order in data and has been established as a robust and effective tool for capturing changes in system dynamics, including the detection of regimes and regime shifts. Methods developed to compute Fisher information can accommodate multivariate data of various types and requires no a priori decisions about system drivers, making it a unique and powerful tool. However, the approach has primarily been used to evaluate temporal patterns. In its sole application to spatial data, Fisher information successfully detected regimes in terrestrial and aquatic systems over transects. Although the selection of adjacently positioned sampling stations provided a natural means of ordering the data, such an approach limits the types of questions that can be answered in a spatial context. Here, we expand the approach to develop a method for more fully capturing spatial dynamics. Results reflect changes in the index that correspond with geographical patterns and demonstrate the utility of the method in uncovering hidden spatial trends in complex systems.
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Affiliation(s)
- Tarsha Eason
- National Risk Management Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Wen-Ching Chuang
- National Research Council, U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive, Cincinnati, OH 45268, USA
| | - Shana Sundstrom
- School of Natural Resources, University of Nebraska-Lincoln, 103 Hardin Hall, 3310 Holdrege St., Lincoln, NE 68583, USA
| | - Heriberto Cabezas
- National Risk Management Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH 45268, USA
- Institute for Process Systems Engineering and Sustainability, Pazmany Peter Catholic University, Szentkiralyi utca 28, H-1088 Budapest, Hungary
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Abstract
The replacement of forest areas with human-dominated landscapes usually leads to fragmentation, altering the structure and function of the forest. Here we studied the dynamics of forest patch sizes at a global level, examining signals of a critical transition from an unfragmented to a fragmented state, using the MODIS vegetation continuous field. We defined wide regions of connected forest across continents and big islands, and combined five criteria, including the distribution of patch sizes and the fluctuations of the largest patch over the last sixteen years, to evaluate the closeness of each region to a fragmentation threshold. Regions with the highest deforestation rates-South America, Southeast Asia, Africa-all met these criteria and may thus be near a critical fragmentation threshold. This implies that if current forest loss rates are maintained, wide continental areas could suddenly fragment, triggering extensive species loss and degradation of ecosystems services.
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Functional magnetic resonance imaging: Basic principles and application in the neurosciences. RADIOLOGIA 2018. [DOI: 10.1016/j.rxeng.2018.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Eom YH. Resilience of networks to environmental stress: From regular to random networks. Phys Rev E 2018; 97:042313. [PMID: 29758756 DOI: 10.1103/physreve.97.042313] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Indexed: 11/07/2022]
Abstract
Despite the huge interest in network resilience to stress, most of the studies have concentrated on internal stress damaging network structure (e.g., node removals). Here we study how networks respond to environmental stress deteriorating their external conditions. We show that, when regular networks gradually disintegrate as environmental stress increases, disordered networks can suddenly collapse at critical stress with hysteresis and vulnerability to perturbations. We demonstrate that this difference results from a trade-off between node resilience and network resilience to environmental stress. The nodes in the disordered networks can suppress their collapses due to the small-world topology of the networks but eventually collapse all together in return. Our findings indicate that some real networks can be highly resilient against environmental stress to a threshold yet extremely vulnerable to the stress above the threshold because of their small-world topology.
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Affiliation(s)
- Young-Ho Eom
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, United Kingdom and Departamento de Matemáticas, Universidad Carlos III de Madrid, 28911 Leganés, Spain
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Labbé Atenas T, Ciampi Díaz E, Cruz Quiroga JP, Uribe Arancibia S, Cárcamo Rodríguez C. Functional magnetic resonance imaging: basic principles and application in the neurosciences. RADIOLOGIA 2018; 60:368-377. [PMID: 29544987 DOI: 10.1016/j.rx.2017.12.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 12/25/2017] [Accepted: 12/26/2017] [Indexed: 11/25/2022]
Abstract
Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system.
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Affiliation(s)
- T Labbé Atenas
- Centro Interdisciplinario de Neurociencias, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - E Ciampi Díaz
- Departamento de Neurología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - J P Cruz Quiroga
- Departamento de Radiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - S Uribe Arancibia
- Departamento de Radiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; Centro de Imágenes Biomédicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - C Cárcamo Rodríguez
- Centro Interdisciplinario de Neurociencias, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; Departamento de Neurología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.
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Weissmann H, Kent R, Michael Y, Shnerb NM. Empirical analysis of vegetation dynamics and the possibility of a catastrophic desertification transition. PLoS One 2017; 12:e0189058. [PMID: 29261678 PMCID: PMC5737887 DOI: 10.1371/journal.pone.0189058] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Accepted: 11/17/2017] [Indexed: 11/18/2022] Open
Abstract
The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states. Some support to this idea comes from the analysis of static patterns, where peaks of the vegetation density histogram were associated with these alternative states. Here we present a large-scale empirical study of vegetation dynamics, aimed at identifying and quantifying directly the effects of positive feedback. To do that, we have analyzed vegetation density across 2.5 × 106 km2 of the African Sahel region, with spatial resolution of 30 × 30 meters, using three consecutive snapshots. The results are mixed. The local vegetation density (measured at a single pixel) moves towards the average of the corresponding rainfall line, indicating a purely negative feedback. On the other hand, the chance of spatial clusters (of many "green" pixels) to expand in the next census is growing with their size, suggesting some positive feedback. We show that these apparently contradicting results emerge naturally in a model with positive feedback and strong demographic stochasticity, a model that allows for a catastrophic shift only in a certain range of parameters. Static patterns, like the double peak in the histogram of vegetation density, are shown to vary between censuses, with no apparent correlation with the actual dynamical features. Our work emphasizes the importance of dynamic response patterns as indicators of the state of the system, while the usefulness of static modality features appears to be quite limited.
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Affiliation(s)
- Haim Weissmann
- Department of Physics, Bar-Ilan University, Ramat-Gan IL52900, Israel
- * E-mail:
| | - Rafi Kent
- Department of Geography and Environment, Bar-Ilan University, Ramat-Gan IL52900, Israel
| | - Yaron Michael
- Department of Geography and Environment, Bar-Ilan University, Ramat-Gan IL52900, Israel
| | - Nadav M. Shnerb
- Department of Physics, Bar-Ilan University, Ramat-Gan IL52900, Israel
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