Passive acoustic surveys reveal interactions between frugivorous birds and fruiting trees on a large forest dynamics plot
Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on animals are constrained because of the disturbance produced by human observers. Recent advances in the automated identification of animal sounds on...
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Published in | Remote sensing in ecology and conservation Vol. 9; no. 2; pp. 284 - 295 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
John Wiley & Sons, Inc
01.04.2023
Wiley |
Subjects | |
Online Access | Get full text |
ISSN | 2056-3485 2056-3485 |
DOI | 10.1002/rse2.310 |
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Abstract | Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on animals are constrained because of the disturbance produced by human observers. Recent advances in the automated identification of animal sounds on large datasets of autonomously collected audio recordings hold the potential to describe plant–animal interactions, such as between frugivorous birds and fruiting trees, without such disturbance. We deployed an array of nine autonomous recording units (ARUs) on the 400 × 500 m Bubeng Forest Dynamics Plot, in Xishuangbanna, southwest China, and collected a total of 1965 h of recordings across two seasons. Animal Sound Identifier (ASI) software was used to detect the vocalizations of five frugivorous bird species, and the probability of detection was related to the number of mature fruiting trees within a 50 m radius of the ARUs. There were more significant positive relationships than would be expected by chance in analyses that investigated bird/tree interactions across 3 months, both in the wet season and the dry season, as well as in short‐term analyses within the dry season months of October and November. The analysis identified 54 interactions between bird and tree species with significant positive relationships. Follow‐up observations of birds on the plot validated that such interactions were more likely to be observed than other interactions. We demonstrate that ARUs and automated voice identification can map the distribution and/or movement of vocal animals across large vegetation plots, allowing this data on animals to be inter‐related to that on plants. We suggest that ARUs be added to the standardized protocols of the plot network, leveraging their vast amount of information about vegetation to describe plant–animal interactions currently, and monitor changes in the future.
We combine tree data ‐ the number of mature fruiting trees near the locations of autonomous recording units ‐ and bird data ‐ the amount of detections of frugivorous birds by the vocal identification software, Animal Sound Identifier. Short‐term (two days per month) and long term (everyday for three months) analyses showed non‐random results for some months/seasons, and identified potential tree species the birds were interacting with. Follow‐up observations verified that birds were interacting with the species they were associated with, demonstrating that this non‐invasive method can interrelate animal data to the vast amount of vegetation data that forest dynamic plots gather. |
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AbstractList | Abstract Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on animals are constrained because of the disturbance produced by human observers. Recent advances in the automated identification of animal sounds on large datasets of autonomously collected audio recordings hold the potential to describe plant–animal interactions, such as between frugivorous birds and fruiting trees, without such disturbance. We deployed an array of nine autonomous recording units (ARUs) on the 400 × 500 m Bubeng Forest Dynamics Plot, in Xishuangbanna, southwest China, and collected a total of 1965 h of recordings across two seasons. Animal Sound Identifier (ASI) software was used to detect the vocalizations of five frugivorous bird species, and the probability of detection was related to the number of mature fruiting trees within a 50 m radius of the ARUs. There were more significant positive relationships than would be expected by chance in analyses that investigated bird/tree interactions across 3 months, both in the wet season and the dry season, as well as in short‐term analyses within the dry season months of October and November. The analysis identified 54 interactions between bird and tree species with significant positive relationships. Follow‐up observations of birds on the plot validated that such interactions were more likely to be observed than other interactions. We demonstrate that ARUs and automated voice identification can map the distribution and/or movement of vocal animals across large vegetation plots, allowing this data on animals to be inter‐related to that on plants. We suggest that ARUs be added to the standardized protocols of the plot network, leveraging their vast amount of information about vegetation to describe plant–animal interactions currently, and monitor changes in the future. Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on animals are constrained because of the disturbance produced by human observers. Recent advances in the automated identification of animal sounds on large datasets of autonomously collected audio recordings hold the potential to describe plant–animal interactions, such as between frugivorous birds and fruiting trees, without such disturbance. We deployed an array of nine autonomous recording units (ARUs) on the 400 × 500 m Bubeng Forest Dynamics Plot, in Xishuangbanna, southwest China, and collected a total of 1965 h of recordings across two seasons. Animal Sound Identifier (ASI) software was used to detect the vocalizations of five frugivorous bird species, and the probability of detection was related to the number of mature fruiting trees within a 50 m radius of the ARUs. There were more significant positive relationships than would be expected by chance in analyses that investigated bird/tree interactions across 3 months, both in the wet season and the dry season, as well as in short‐term analyses within the dry season months of October and November. The analysis identified 54 interactions between bird and tree species with significant positive relationships. Follow‐up observations of birds on the plot validated that such interactions were more likely to be observed than other interactions. We demonstrate that ARUs and automated voice identification can map the distribution and/or movement of vocal animals across large vegetation plots, allowing this data on animals to be inter‐related to that on plants. We suggest that ARUs be added to the standardized protocols of the plot network, leveraging their vast amount of information about vegetation to describe plant–animal interactions currently, and monitor changes in the future. We combine tree data ‐ the number of mature fruiting trees near the locations of autonomous recording units ‐ and bird data ‐ the amount of detections of frugivorous birds by the vocal identification software, Animal Sound Identifier. Short‐term (two days per month) and long term (everyday for three months) analyses showed non‐random results for some months/seasons, and identified potential tree species the birds were interacting with. Follow‐up observations verified that birds were interacting with the species they were associated with, demonstrating that this non‐invasive method can interrelate animal data to the vast amount of vegetation data that forest dynamic plots gather. Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on animals are constrained because of the disturbance produced by human observers. Recent advances in the automated identification of animal sounds on large datasets of autonomously collected audio recordings hold the potential to describe plant–animal interactions, such as between frugivorous birds and fruiting trees, without such disturbance. We deployed an array of nine autonomous recording units (ARUs) on the 400 × 500 m Bubeng Forest Dynamics Plot, in Xishuangbanna, southwest China, and collected a total of 1965 h of recordings across two seasons. Animal Sound Identifier (ASI) software was used to detect the vocalizations of five frugivorous bird species, and the probability of detection was related to the number of mature fruiting trees within a 50 m radius of the ARUs. There were more significant positive relationships than would be expected by chance in analyses that investigated bird/tree interactions across 3 months, both in the wet season and the dry season, as well as in short‐term analyses within the dry season months of October and November. The analysis identified 54 interactions between bird and tree species with significant positive relationships. Follow‐up observations of birds on the plot validated that such interactions were more likely to be observed than other interactions. We demonstrate that ARUs and automated voice identification can map the distribution and/or movement of vocal animals across large vegetation plots, allowing this data on animals to be inter‐related to that on plants. We suggest that ARUs be added to the standardized protocols of the plot network, leveraging their vast amount of information about vegetation to describe plant–animal interactions currently, and monitor changes in the future. |
Author | He, Xuelian Deng, Yiming Lin, Luxiang Goodale, Eben Dong, Anran Ahumada, Jorge Lecours, Vincent |
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Snippet | Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on... Long-term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that on... Abstract Long‐term vegetation plots represent one of the largest types of research investments in ecology, but efforts to interrelate data on plants with that... |
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StartPage | 284 |
SubjectTerms | Acoustic surveying Acoustics Animals Automated vocal identification Autonomous recording Biodiversity Bird vocalizations Birds Community ecology Dry season Ecoacoustics Forest ecosystems Fruits Long‐term vegetation plots Plant species Plant–animal interactions Rainy season Remote sensing Seasons Trees Vegetation Vocalization behavior |
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Title | Passive acoustic surveys reveal interactions between frugivorous birds and fruiting trees on a large forest dynamics plot |
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