Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages
Abstract LiDAR (light detection and ranging) allows for the quantification of three‐dimensional seascape structure, which is an important driver of coral reef communities. We hypothesized that three‐dimensional LiDAR‐derived covariables support more robust models of coral reef fish assemblages, comp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-06-01
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| Series: | Remote Sensing in Ecology and Conservation |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/rse2.115 |
| _version_ | 1818325575111016448 |
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| author | Lisa M. Wedding Stacy Jorgensen Christopher A. Lepczyk Alan M. Friedlander |
| author_facet | Lisa M. Wedding Stacy Jorgensen Christopher A. Lepczyk Alan M. Friedlander |
| author_sort | Lisa M. Wedding |
| collection | DOAJ |
| description | Abstract LiDAR (light detection and ranging) allows for the quantification of three‐dimensional seascape structure, which is an important driver of coral reef communities. We hypothesized that three‐dimensional LiDAR‐derived covariables support more robust models of coral reef fish assemblages, compared to models using 2D environmental co variables. Predictive models of coral reef fish density, diversity, and biomass were developed using linear mixed effect models. We found that models containing combined 2D and 3D covariables outperformed models with only 3D covariables, followed by models containing only 2D covariables. Areas with greater three‐dimensional structure provide fish more refuge from predation and are crucial to identifying priority management locations that can potentially enhance reef resilience and recovery. Two‐dimensional seascape metrics alone do not adequately capture the elements of the seascape that drive reef fish assemblage characteristics, and the application of LiDAR data in this work serves to advance seascape ecology theory and practice in the third dimension. |
| first_indexed | 2024-12-13T11:46:39Z |
| format | Article |
| id | doaj.art-a1b5cc256411452999be717c065b3e41 |
| institution | Directory Open Access Journal |
| issn | 2056-3485 |
| language | English |
| last_indexed | 2024-12-13T11:46:39Z |
| publishDate | 2019-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Remote Sensing in Ecology and Conservation |
| spelling | doaj.art-a1b5cc256411452999be717c065b3e412022-12-21T23:47:30ZengWileyRemote Sensing in Ecology and Conservation2056-34852019-06-015215015910.1002/rse2.115Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblagesLisa M. Wedding0Stacy Jorgensen1Christopher A. Lepczyk2Alan M. Friedlander3School of Geography and the Environment University of Oxford Oxford United KingdomTexas Health and Human Services Commission Austin TexasSchool of Forestry and Wildlife Sciences Auburn University Auburn AlabamaPristine Seas National Geographic Society Washington District of ColumbiaAbstract LiDAR (light detection and ranging) allows for the quantification of three‐dimensional seascape structure, which is an important driver of coral reef communities. We hypothesized that three‐dimensional LiDAR‐derived covariables support more robust models of coral reef fish assemblages, compared to models using 2D environmental co variables. Predictive models of coral reef fish density, diversity, and biomass were developed using linear mixed effect models. We found that models containing combined 2D and 3D covariables outperformed models with only 3D covariables, followed by models containing only 2D covariables. Areas with greater three‐dimensional structure provide fish more refuge from predation and are crucial to identifying priority management locations that can potentially enhance reef resilience and recovery. Two‐dimensional seascape metrics alone do not adequately capture the elements of the seascape that drive reef fish assemblage characteristics, and the application of LiDAR data in this work serves to advance seascape ecology theory and practice in the third dimension.https://doi.org/10.1002/rse2.115Coral reef fishesLiDARlight detection and rangingpredictive modelingremote sensingseascape ecology |
| spellingShingle | Lisa M. Wedding Stacy Jorgensen Christopher A. Lepczyk Alan M. Friedlander Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages Remote Sensing in Ecology and Conservation Coral reef fishes LiDAR light detection and ranging predictive modeling remote sensing seascape ecology |
| title | Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages |
| title_full | Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages |
| title_fullStr | Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages |
| title_full_unstemmed | Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages |
| title_short | Remote sensing of three‐dimensional coral reef structure enhances predictive modeling of fish assemblages |
| title_sort | remote sensing of three dimensional coral reef structure enhances predictive modeling of fish assemblages |
| topic | Coral reef fishes LiDAR light detection and ranging predictive modeling remote sensing seascape ecology |
| url | https://doi.org/10.1002/rse2.115 |
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