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Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity

Physical habitat complexity regulates the structure and function of biological communities, although the mechanisms underlying this relationship remain unclear. Urbanisation, pollution, unsustainable resource exploitation and climate change have resulted in the widespread simplification (and loss) o...

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Autores principales: Loke, Lynette H. L., Jachowski, Nicholas R., Bouma, Tjeerd J., Ladle, Richard J., Todd, Peter A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925107/
https://www.ncbi.nlm.nih.gov/pubmed/24551074
http://dx.doi.org/10.1371/journal.pone.0087990
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author Loke, Lynette H. L.
Jachowski, Nicholas R.
Bouma, Tjeerd J.
Ladle, Richard J.
Todd, Peter A.
author_facet Loke, Lynette H. L.
Jachowski, Nicholas R.
Bouma, Tjeerd J.
Ladle, Richard J.
Todd, Peter A.
author_sort Loke, Lynette H. L.
collection PubMed
description Physical habitat complexity regulates the structure and function of biological communities, although the mechanisms underlying this relationship remain unclear. Urbanisation, pollution, unsustainable resource exploitation and climate change have resulted in the widespread simplification (and loss) of habitats worldwide. One way to restore physical complexity to anthropogenically simplified habitats is through the use of artificial substrates, which also offer excellent opportunities to explore the effects of different components (variables) of complexity on biodiversity and community structure that would be difficult to separate in natural systems. Here, we describe a software program (CASU) that enables users to visualise static, physical complexity. CASU also provides output files that can be used to create artificial substrates for experimental and/or restoration studies. It has two different operational modes: simple and advanced. In simple mode, users can adjust the five main variables of informational complexity (i.e. the number of object types, relative abundance of object types, density of objects, variability and range in the objects’ dimensions, and their spatial arrangement) and visualise the changes as they do so. The advanced mode allows users to design artificial substrates by fine-tuning the complexity variables as well as alter object-specific parameters. We illustrate how CASU can be used to create tiles of different designs for application in a marine environment. Such an ability to systematically influence physical complexity could greatly facilitate ecological restoration by allowing conservationists to rebuild complexity in degraded and simplified habitats.
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spelling pubmed-39251072014-02-18 Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity Loke, Lynette H. L. Jachowski, Nicholas R. Bouma, Tjeerd J. Ladle, Richard J. Todd, Peter A. PLoS One Research Article Physical habitat complexity regulates the structure and function of biological communities, although the mechanisms underlying this relationship remain unclear. Urbanisation, pollution, unsustainable resource exploitation and climate change have resulted in the widespread simplification (and loss) of habitats worldwide. One way to restore physical complexity to anthropogenically simplified habitats is through the use of artificial substrates, which also offer excellent opportunities to explore the effects of different components (variables) of complexity on biodiversity and community structure that would be difficult to separate in natural systems. Here, we describe a software program (CASU) that enables users to visualise static, physical complexity. CASU also provides output files that can be used to create artificial substrates for experimental and/or restoration studies. It has two different operational modes: simple and advanced. In simple mode, users can adjust the five main variables of informational complexity (i.e. the number of object types, relative abundance of object types, density of objects, variability and range in the objects’ dimensions, and their spatial arrangement) and visualise the changes as they do so. The advanced mode allows users to design artificial substrates by fine-tuning the complexity variables as well as alter object-specific parameters. We illustrate how CASU can be used to create tiles of different designs for application in a marine environment. Such an ability to systematically influence physical complexity could greatly facilitate ecological restoration by allowing conservationists to rebuild complexity in degraded and simplified habitats. Public Library of Science 2014-02-14 /pmc/articles/PMC3925107/ /pubmed/24551074 http://dx.doi.org/10.1371/journal.pone.0087990 Text en © 2014 Loke et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Loke, Lynette H. L.
Jachowski, Nicholas R.
Bouma, Tjeerd J.
Ladle, Richard J.
Todd, Peter A.
Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title_full Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title_fullStr Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title_full_unstemmed Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title_short Complexity for Artificial Substrates (CASU): Software for Creating and Visualising Habitat Complexity
title_sort complexity for artificial substrates (casu): software for creating and visualising habitat complexity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925107/
https://www.ncbi.nlm.nih.gov/pubmed/24551074
http://dx.doi.org/10.1371/journal.pone.0087990
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