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Drivers of complexity in ecosystem restoration.

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Title: Drivers of complexity in ecosystem restoration.
Authors: Waddell, Emily H.1,2 (AUTHOR) emily.waddell@glasgow.ac.uk, Woodcock, Ben3 (AUTHOR), Harris, Jim4 (AUTHOR), Park, Kirsty J.1 (AUTHOR), Fuentes‐Montemayor, Elisa1 (AUTHOR), Watts, Kevin1,5 (AUTHOR), Pawlett, Mark4 (AUTHOR), Larionov, Alexey4 (AUTHOR), Guy, Matt5 (AUTHOR), Rogerson, Samuel P.1 (AUTHOR), Barnett, Ross J.1 (AUTHOR), Weites, Maico G.3 (AUTHOR), Shears, Melanie3 (AUTHOR), Hibdige, Samuel4 (AUTHOR), Aguinaga, Oscar4,6 (AUTHOR), Roxbee Cox, Lynne4 (AUTHOR), Feeley, Emma4 (AUTHOR), Opris, Andrada D.1,7 (AUTHOR), Gee, Anna1,8 (AUTHOR), De Sanctis, Cecilia1 (AUTHOR)
Source: Journal of Applied Ecology. Apr2026, Vol. 63 Issue 4, p1-13. 13p.
Subjects: Restoration ecology, Biocomplexity, Ecosystem dynamics, Land use, Ecological resilience, Biodiversity
Abstract: Ecological complexity is linked to emergent properties, such as ecosystem processes and resilience. Enhancing complexity may therefore be a more effective goal for ecosystem restoration than the traditional focus of replicating reference communities, especially under global environmental change. However, ecological complexity is rarely empirically studied in real‐world systems, so the potential applications of complexity and the relationships between different aspects of complexity are poorly understood.Here, we examine complexity in the context of restoration within two contrasting ecosystems, 54 calcareous grasslands and 60 broadleaved woodlands. We derive 'ecological complexity' indices for multiple ecosystem attributes, including soil bacteria, soil fungi, habitat structure, plants, invertebrates and species networks. Using Structural Equation Models, we quantify the effect of key drivers (including site age and size, amount of grassland/woodland in surrounding landscape, former land‐use, establishment method and ongoing management) on complexity and the strength of associations among different aspects of complexity.We find that decisions made at the onset of restoration have a large role in the subsequent development of complexity, including grassland establishment method and former land‐use for woodlands.High structural complexity was identified as a positive driver of invertebrate complexity in both habitats, but in general we observed limited relationships between the different complexity aspects.Policy implications. This study shows that ecological complexity is empirically measurable, and its development in restoration can be influenced by key variables, which have mechanistic underpinnings. The foundational role of structural complexity driving other aspects of complexity could guide management efforts to enhance ecological complexity. Our results suggest, however, that ecological complexity is multi‐faceted and cannot be reduced to a few simple indicators. Thus, to gain a holistic understanding of how complex an ecosystem is, one needs to measure multiple aspects rather than focusing on, for example, taxonomic diversity of a few taxa. One approach is to consider a syndrome‐focussed framework, whereby a set of complexity measures provides a good indication of ecosystems status and resilience. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Drivers of complexity in ecosystem restoration.
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  Data: <searchLink fieldCode="AR" term="%22Waddell%2C+Emily+H%2E%22">Waddell, Emily H.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> emily.waddell@glasgow.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Woodcock%2C+Ben%22">Woodcock, Ben</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Harris%2C+Jim%22">Harris, Jim</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Park%2C+Kirsty+J%2E%22">Park, Kirsty J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fuentes‐Montemayor%2C+Elisa%22">Fuentes‐Montemayor, Elisa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Watts%2C+Kevin%22">Watts, Kevin</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pawlett%2C+Mark%22">Pawlett, Mark</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Larionov%2C+Alexey%22">Larionov, Alexey</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guy%2C+Matt%22">Guy, Matt</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rogerson%2C+Samuel+P%2E%22">Rogerson, Samuel P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Barnett%2C+Ross+J%2E%22">Barnett, Ross J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Weites%2C+Maico+G%2E%22">Weites, Maico G.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shears%2C+Melanie%22">Shears, Melanie</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hibdige%2C+Samuel%22">Hibdige, Samuel</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aguinaga%2C+Oscar%22">Aguinaga, Oscar</searchLink><relatesTo>4,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roxbee+Cox%2C+Lynne%22">Roxbee Cox, Lynne</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Feeley%2C+Emma%22">Feeley, Emma</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Opris%2C+Andrada+D%2E%22">Opris, Andrada D.</searchLink><relatesTo>1,7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gee%2C+Anna%22">Gee, Anna</searchLink><relatesTo>1,8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22De+Sanctis%2C+Cecilia%22">De Sanctis, Cecilia</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: Ecological complexity is linked to emergent properties, such as ecosystem processes and resilience. Enhancing complexity may therefore be a more effective goal for ecosystem restoration than the traditional focus of replicating reference communities, especially under global environmental change. However, ecological complexity is rarely empirically studied in real‐world systems, so the potential applications of complexity and the relationships between different aspects of complexity are poorly understood.Here, we examine complexity in the context of restoration within two contrasting ecosystems, 54 calcareous grasslands and 60 broadleaved woodlands. We derive 'ecological complexity' indices for multiple ecosystem attributes, including soil bacteria, soil fungi, habitat structure, plants, invertebrates and species networks. Using Structural Equation Models, we quantify the effect of key drivers (including site age and size, amount of grassland/woodland in surrounding landscape, former land‐use, establishment method and ongoing management) on complexity and the strength of associations among different aspects of complexity.We find that decisions made at the onset of restoration have a large role in the subsequent development of complexity, including grassland establishment method and former land‐use for woodlands.High structural complexity was identified as a positive driver of invertebrate complexity in both habitats, but in general we observed limited relationships between the different complexity aspects.Policy implications. This study shows that ecological complexity is empirically measurable, and its development in restoration can be influenced by key variables, which have mechanistic underpinnings. The foundational role of structural complexity driving other aspects of complexity could guide management efforts to enhance ecological complexity. Our results suggest, however, that ecological complexity is multi‐faceted and cannot be reduced to a few simple indicators. Thus, to gain a holistic understanding of how complex an ecosystem is, one needs to measure multiple aspects rather than focusing on, for example, taxonomic diversity of a few taxa. One approach is to consider a syndrome‐focussed framework, whereby a set of complexity measures provides a good indication of ecosystems status and resilience. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/1365-2664.70387
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      – Code: eng
        Text: English
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        PageCount: 13
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      – SubjectFull: Restoration ecology
        Type: general
      – SubjectFull: Biocomplexity
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      – SubjectFull: Ecosystem dynamics
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      – SubjectFull: Land use
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      – SubjectFull: Ecological resilience
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      – SubjectFull: Biodiversity
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