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 inRemote sensing in ecology and conservation Vol. 9; no. 2; pp. 284 - 295
Main Authors Dong, Anran, He, Xuelian, Deng, Yiming, Lin, Luxiang, Goodale, Eben, Lecours, Vincent, Ahumada, Jorge
Format Journal Article
LanguageEnglish
Published Oxford John Wiley & Sons, Inc 01.04.2023
Wiley
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Online AccessGet full text
ISSN2056-3485
2056-3485
DOI10.1002/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.
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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