Changes
On October 22, 2024, 8:37:20 PM UTC,
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Updated description of Simple feedback explains complex channel patterns in coastal wetlands (Chapter 3 in PhD thesis Roeland C. van de Vijsel) from
Spatial patterns are omnipresent in nature (Rodriguez-Iturbe and Rinaldo, 1997; Kondo, 2002; Meinhardt, 2003; Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009) and directly affect the functioning and resilience of the (eco)systems in which they manifest themselves (Rietkerk et al., 2004; van de Koppel et al., 2005; Weerman et al., 2010; Liu et al., 2014b). Scale-dependent feedback, which typically is positive nearby and negative further away, provides a widely accepted explanation for the formation of simple, single-scale patterns (Meinhardt, 2003; Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009). However, it is unclear whether the more complex, multi-scale patterns that characterize many natural systems can be explained by equally generic mechanisms. As a model system, we here study the tidal channels that characterize coastal wetlands (Hughes, 2012), as these channels constitute patterns that vary greatly in geometry, ranging from simple parallel channels (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel et al., 2020) to complexly branching networks (Rodriguez-Iturbe and Rinaldo, 1997; Rinaldo et al., 1999), with direct consequences for the functioning and resilience of valuable wetland ecosystems. We reveal that the broad spectrum of geometries typical for tidal channel patterns can be explained by one scale-dependent feedback. This is a biogeomorphic feedback that roughly follows Turing’s activator-inhibitor principle (Rietkerk and van de Koppel, 2008) and results from flow deflection and channel incision around biotically (biofilms, algae, plants) stabilized sediment (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel et al., 2020). Using a mathematical model, we now show that as the biogeomorphic feedback gets stronger, complex multi-scale patterns emerge due to self-induced recursion of the scale-dependent feedback, which results in nesting of regular channel patterns at successively finer scales. This recursive mechanism provides an explanation for poorly understood geometric properties of real-world tidal networks (Rinaldo et al., 1999). We further find that increased network complexity directly translates to enhanced drainage efficiency, sediment accretion rates and ecosystem productivity. These results highlight the vital importance of network complexity for the functioning of coastal wetlands, ultimately determining their resilience to sea level rise (Kirwan and Megonigal, 2013) and storm surge buffering capacity (Temmerman et al., 2013), and with that their potential to mitigate the effects of global change that threaten densely populated coastal lowlands worldwide.
toSpatial patterns are omnipresent in nature (Rodriguez-Iturbe and Rinaldo, 1997; Kondo, 2002; Meinhardt, 2003; Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009) and directly affect the functioning and resilience of the (eco)systems in which they manifest themselves (Rietkerk et al., 2004; van de Koppel et al., 2005; Weerman et al., 2010; Liu et al., 2014b). Scale-dependent feedback, which typically is positive nearby and negative further away, provides a widely accepted explanation for the formation of simple, single-scale patterns (Meinhardt, 2003; Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009). However, it is unclear whether the more complex, multi-scale patterns that characterize many natural systems can be explained by equally generic mechanisms. As a model system, we here study the tidal channels that characterize coastal wetlands (Hughes, 2012), as these channels constitute patterns that vary greatly in geometry, ranging from simple parallel channels (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel et al., 2020) to complexly branching networks (Rodriguez-Iturbe and Rinaldo, 1997; Rinaldo et al., 1999), with direct consequences for the functioning and resilience of valuable wetland ecosystems. We reveal that the broad spectrum of geometries typical for tidal channel patterns can be explained by one scale-dependent feedback. This is a biogeomorphic feedback that roughly follows Turing???s activator-inhibitor principle (Rietkerk and van de Koppel, 2008) and results from flow deflection and channel incision around biotically (biofilms, algae, plants) stabilized sediment (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel et al., 2020). Using a mathematical model, we now show that as the biogeomorphic feedback gets stronger, complex multi-scale patterns emerge due to self-induced recursion of the scale-dependent feedback, which results in nesting of regular channel patterns at successively finer scales. This recursive mechanism provides an explanation for poorly understood geometric properties of real-world tidal networks (Rinaldo et al., 1999). We further find that increased network complexity directly translates to enhanced drainage efficiency, sediment accretion rates and ecosystem productivity. These results highlight the vital importance of network complexity for the functioning of coastal wetlands, ultimately determining their resilience to sea level rise (Kirwan and Megonigal, 2013) and storm surge buffering capacity (Temmerman et al., 2013), and with that their potential to mitigate the effects of global change that threaten densely populated coastal lowlands worldwide.
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Changed the version of Simple feedback explains complex channel patterns in coastal wetlands (Chapter 3 in PhD thesis Roeland C. van de Vijsel) to 2 (previously 1)
| f | 1 | { | f | 1 | { |
| 2 | "author": null, | 2 | "author": null, | ||
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| 4 | "code": "7b.b.tb", | 4 | "code": "7b.b.tb", | ||
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| 7 | "creators": "[{\"firstname\":\"Roeland C.\",\"lastname\":\"van de | 7 | "creators": "[{\"firstname\":\"Roeland C.\",\"lastname\":\"van de | ||
| 8 | Vijsel\",\"affiliation\":\"Royal Netherlands Institute for Sea | 8 | Vijsel\",\"affiliation\":\"Royal Netherlands Institute for Sea | ||
| 9 | scorrespondingauthor\":true},{\"firstname\":\"Jim\",\"lastname\":\"van | 9 | scorrespondingauthor\":true},{\"firstname\":\"Jim\",\"lastname\":\"van | ||
| 10 | Belzen\",\"affiliation\":\"Royal Netherlands Institute for Sea | 10 | Belzen\",\"affiliation\":\"Royal Netherlands Institute for Sea | ||
| 11 | ddress\":\"\",\"iscorrespondingauthor\":false},{\"firstname\":\"Tjeerd | 11 | ddress\":\"\",\"iscorrespondingauthor\":false},{\"firstname\":\"Tjeerd | ||
| 12 | J.\",\"lastname\":\"Bouma\",\"affiliation\":\"Royal Netherlands | 12 | J.\",\"lastname\":\"Bouma\",\"affiliation\":\"Royal Netherlands | ||
| 13 | Institute for Sea | 13 | Institute for Sea | ||
| 14 | respondingauthor\":false},{\"firstname\":\"Daphne\",\"lastname\":\"van | 14 | respondingauthor\":false},{\"firstname\":\"Daphne\",\"lastname\":\"van | ||
| 15 | der Wal\",\"affiliation\":\"Royal Netherlands Institute for Sea | 15 | der Wal\",\"affiliation\":\"Royal Netherlands Institute for Sea | ||
| 16 | iladdress\":\"\",\"iscorrespondingauthor\":false},{\"firstname\":\"Bas | 16 | iladdress\":\"\",\"iscorrespondingauthor\":false},{\"firstname\":\"Bas | ||
| 17 | W.\",\"lastname\":\"Borsje\",\"affiliation\":\"University of | 17 | W.\",\"lastname\":\"Borsje\",\"affiliation\":\"University of | ||
| 18 | me\":\"Stijn\",\"lastname\":\"Temmerman\",\"affiliation\":\"University | 18 | me\":\"Stijn\",\"lastname\":\"Temmerman\",\"affiliation\":\"University | ||
| 19 | of | 19 | of | ||
| 20 | tname\":\"Loreta\",\"lastname\":\"Cornacchia\",\"affiliation\":\"Royal | 20 | tname\":\"Loreta\",\"lastname\":\"Cornacchia\",\"affiliation\":\"Royal | ||
| 21 | Netherlands Institute for Sea | 21 | Netherlands Institute for Sea | ||
| 22 | rrespondingauthor\":false},{\"firstname\":\"Johan\",\"lastname\":\"van | 22 | rrespondingauthor\":false},{\"firstname\":\"Johan\",\"lastname\":\"van | ||
| 23 | de Koppel\",\"affiliation\":\"Royal Netherlands Institute for Sea | 23 | de Koppel\",\"affiliation\":\"Royal Netherlands Institute for Sea | ||
| 24 | 275\",\"contactemailaddress\":\"\",\"iscorrespondingauthor\":false}]", | 24 | 275\",\"contactemailaddress\":\"\",\"iscorrespondingauthor\":false}]", | ||
| 25 | "dataset_persistent_id": "DOI:10.25850/nioz/7b.b.tb", | 25 | "dataset_persistent_id": "DOI:10.25850/nioz/7b.b.tb", | ||
| 26 | "dates": | 26 | "dates": | ||
| 27 | 21-04-15T22:00:00.000Z\",\"type\":\"collected\",\"information\":\"This | 27 | 21-04-15T22:00:00.000Z\",\"type\":\"collected\",\"information\":\"This | ||
| 28 | is the entire dataset belonging to Chapter 3 of the PhD Thesis of | 28 | is the entire dataset belonging to Chapter 3 of the PhD Thesis of | ||
| 29 | Roeland C. van de Vijsel | 29 | Roeland C. van de Vijsel | ||
| 30 | (https://doi.org/10.33612/diss.160081233).\"}]", | 30 | (https://doi.org/10.33612/diss.160081233).\"}]", | ||
| 31 | "deposit_date": "2021-03-18", | 31 | "deposit_date": "2021-03-18", | ||
| 32 | "depositor": "Roeland van de Vijsel", | 32 | "depositor": "Roeland van de Vijsel", | ||
| 33 | "distribution_date": "2021-03-18", | 33 | "distribution_date": "2021-03-18", | ||
| 34 | "distributor": "Research Data Management(NIOZ Royal Netherlands | 34 | "distributor": "Research Data Management(NIOZ Royal Netherlands | ||
| 35 | Institute for Sea Research)", | 35 | Institute for Sea Research)", | ||
| 36 | "doi_date_published": "2023-11-22", | 36 | "doi_date_published": "2023-11-22", | ||
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| 42 | modelling HPP\"}]", | 42 | modelling HPP\"}]", | ||
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| 53 | "name": "7bbtb", | 53 | "name": "7bbtb", | ||
| 54 | "notes": "Spatial patterns are omnipresent in nature | 54 | "notes": "Spatial patterns are omnipresent in nature | ||
| 55 | (Rodriguez-Iturbe and Rinaldo, 1997; Kondo, 2002; Meinhardt, 2003; | 55 | (Rodriguez-Iturbe and Rinaldo, 1997; Kondo, 2002; Meinhardt, 2003; | ||
| 56 | Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009) and | 56 | Rietkerk and van de Koppel, 2008; Petit and Anfodillo, 2009) and | ||
| 57 | directly affect the functioning and resilience of the (eco)systems in | 57 | directly affect the functioning and resilience of the (eco)systems in | ||
| 58 | which they manifest themselves (Rietkerk et al., 2004; van de Koppel | 58 | which they manifest themselves (Rietkerk et al., 2004; van de Koppel | ||
| 59 | et al., 2005; Weerman et al., 2010; Liu et al., 2014b). | 59 | et al., 2005; Weerman et al., 2010; Liu et al., 2014b). | ||
| 60 | Scale-dependent feedback, which typically is positive nearby and | 60 | Scale-dependent feedback, which typically is positive nearby and | ||
| 61 | negative further away, provides a widely accepted explanation for the | 61 | negative further away, provides a widely accepted explanation for the | ||
| 62 | formation of simple, single-scale patterns (Meinhardt, 2003; Rietkerk | 62 | formation of simple, single-scale patterns (Meinhardt, 2003; Rietkerk | ||
| 63 | and van de Koppel, 2008; Petit and Anfodillo, 2009). However, it is | 63 | and van de Koppel, 2008; Petit and Anfodillo, 2009). However, it is | ||
| 64 | unclear whether the more complex, multi-scale patterns that | 64 | unclear whether the more complex, multi-scale patterns that | ||
| 65 | characterize many natural systems can be explained by equally generic | 65 | characterize many natural systems can be explained by equally generic | ||
| 66 | mechanisms. As a model system, we here study the tidal channels that | 66 | mechanisms. As a model system, we here study the tidal channels that | ||
| 67 | characterize coastal wetlands (Hughes, 2012), as these channels | 67 | characterize coastal wetlands (Hughes, 2012), as these channels | ||
| 68 | constitute patterns that vary greatly in geometry, ranging from simple | 68 | constitute patterns that vary greatly in geometry, ranging from simple | ||
| 69 | parallel channels (Temmerman et al., 2007; Weerman et al., 2010; van | 69 | parallel channels (Temmerman et al., 2007; Weerman et al., 2010; van | ||
| 70 | de Vijsel et al., 2020) to complexly branching networks | 70 | de Vijsel et al., 2020) to complexly branching networks | ||
| 71 | (Rodriguez-Iturbe and Rinaldo, 1997; Rinaldo et al., 1999), with | 71 | (Rodriguez-Iturbe and Rinaldo, 1997; Rinaldo et al., 1999), with | ||
| 72 | direct consequences for the functioning and resilience of valuable | 72 | direct consequences for the functioning and resilience of valuable | ||
| 73 | wetland ecosystems. We reveal that the broad spectrum of geometries | 73 | wetland ecosystems. We reveal that the broad spectrum of geometries | ||
| 74 | typical for tidal channel patterns can be explained by one | 74 | typical for tidal channel patterns can be explained by one | ||
| 75 | scale-dependent feedback. This is a biogeomorphic feedback that | 75 | scale-dependent feedback. This is a biogeomorphic feedback that | ||
| n | 76 | roughly follows Turing\u2019s activator-inhibitor principle (Rietkerk | n | 76 | roughly follows Turing???s activator-inhibitor principle (Rietkerk and |
| 77 | and van de Koppel, 2008) and results from flow deflection and channel | 77 | van de Koppel, 2008) and results from flow deflection and channel | ||
| 78 | incision around biotically (biofilms, algae, plants) stabilized | 78 | incision around biotically (biofilms, algae, plants) stabilized | ||
| 79 | sediment (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel | 79 | sediment (Temmerman et al., 2007; Weerman et al., 2010; van de Vijsel | ||
| 80 | et al., 2020). Using a mathematical model, we now show that as the | 80 | et al., 2020). Using a mathematical model, we now show that as the | ||
| 81 | biogeomorphic feedback gets stronger, complex multi-scale patterns | 81 | biogeomorphic feedback gets stronger, complex multi-scale patterns | ||
| 82 | emerge due to self-induced recursion of the scale-dependent feedback, | 82 | emerge due to self-induced recursion of the scale-dependent feedback, | ||
| 83 | which results in nesting of regular channel patterns at successively | 83 | which results in nesting of regular channel patterns at successively | ||
| 84 | finer scales. This recursive mechanism provides an explanation for | 84 | finer scales. This recursive mechanism provides an explanation for | ||
| 85 | poorly understood geometric properties of real-world tidal networks | 85 | poorly understood geometric properties of real-world tidal networks | ||
| 86 | (Rinaldo et al., 1999). We further find that increased network | 86 | (Rinaldo et al., 1999). We further find that increased network | ||
| 87 | complexity directly translates to enhanced drainage efficiency, | 87 | complexity directly translates to enhanced drainage efficiency, | ||
| 88 | sediment accretion rates and ecosystem productivity. These results | 88 | sediment accretion rates and ecosystem productivity. These results | ||
| 89 | highlight the vital importance of network complexity for the | 89 | highlight the vital importance of network complexity for the | ||
| 90 | functioning of coastal wetlands, ultimately determining their | 90 | functioning of coastal wetlands, ultimately determining their | ||
| 91 | resilience to sea level rise (Kirwan and Megonigal, 2013) and storm | 91 | resilience to sea level rise (Kirwan and Megonigal, 2013) and storm | ||
| 92 | surge buffering capacity (Temmerman et al., 2013), and with that their | 92 | surge buffering capacity (Temmerman et al., 2013), and with that their | ||
| 93 | potential to mitigate the effects of global change that threaten | 93 | potential to mitigate the effects of global change that threaten | ||
| 94 | densely populated coastal lowlands worldwide.", | 94 | densely populated coastal lowlands worldwide.", | ||
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| 364 | "display_name": "Coastal wetlands tidal flat tidal marsh tidal | 364 | "display_name": "Coastal wetlands tidal flat tidal marsh tidal | ||
| 365 | channel networks self-organization complexity mathema", | 365 | channel networks self-organization complexity mathema", | ||
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| 374 | coastal wetlands (Chapter 3 in PhD thesis Roeland C. van de Vijsel)", | 374 | coastal wetlands (Chapter 3 in PhD thesis Roeland C. van de Vijsel)", | ||
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