Scheimpflug lidar range profiling of bee activity patterns and spatial distributions
Abstract Background Recent declines of honeybees and simplifications of wild bee communities, at least partly attributed to changes of agricultural landscapes, have worried both the public and the scientific community. To understand how wild and managed bees respond to landscape structure it is esse...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-04-01
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| Series: | Animal Biotelemetry |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40317-022-00285-z |
| _version_ | 1818278496789594112 |
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| author | Klas Rydhmer Jord Prangsma Mikkel Brydegaard Henrik G. Smith Carsten Kirkeby Inger Kappel Schmidt Birte Boelt |
| author_facet | Klas Rydhmer Jord Prangsma Mikkel Brydegaard Henrik G. Smith Carsten Kirkeby Inger Kappel Schmidt Birte Boelt |
| author_sort | Klas Rydhmer |
| collection | DOAJ |
| description | Abstract Background Recent declines of honeybees and simplifications of wild bee communities, at least partly attributed to changes of agricultural landscapes, have worried both the public and the scientific community. To understand how wild and managed bees respond to landscape structure it is essential to investigate their spatial use of foraging habitats. However, such studies are challenging since the foraging behaviour of bees differs between species and can be highly dynamic. Consequently, the necessary data collection is laborious using conventional methods and there is a need for novel methods that allow for automated and continuous monitoring of bees. In this work, we deployed an entomological lidar in a homogenous white clover seed crop and profiled the activity of honeybees and other ambient insects in relation to a cluster of beehives. Results In total, 566,609 insect observations were recorded by the lidar. The total measured range distribution was separated into three groups, out of which two were centered around the beehives and considered to be honeybees, while the remaining group was considered to be wild insects. The validity of this model in separating honeybees from wild insects was verified by the average wing modulation frequency spectra in the dominating range interval for each group. The temporal variation in measured activity of the assumed honeybee observations was well correlated with honeybee activity indirectly estimated using hive scales as well as directly observed using transect counts. Additional insight regarding the three-dimensional distribution of bees close to the hive was provided by alternating the beam between two heights, revealing a “funnel like” distribution around the beehives, widening with height. Conclusions We demonstrate how lidar can record very high numbers of insects during a short time period. In this work, a spatial model, derived from the detection limit of the lidar and two Gaussian distributions of honeybees centered around their hives was sufficient to reproduce the observations of honeybees and background insects. This methodology can in the future provide valuable new information on how external factors influence pollination services and foraging habitat selection and range of both managed bees and wild pollinators. |
| first_indexed | 2024-12-12T23:18:22Z |
| format | Article |
| id | doaj.art-9f7b5935bfac4df1904964bd9f061d0b |
| institution | Directory Open Access Journal |
| issn | 2050-3385 |
| language | English |
| last_indexed | 2024-12-12T23:18:22Z |
| publishDate | 2022-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Animal Biotelemetry |
| spelling | doaj.art-9f7b5935bfac4df1904964bd9f061d0b2022-12-22T00:08:22ZengBMCAnimal Biotelemetry2050-33852022-04-0110111310.1186/s40317-022-00285-zScheimpflug lidar range profiling of bee activity patterns and spatial distributionsKlas Rydhmer0Jord Prangsma1Mikkel Brydegaard2Henrik G. Smith3Carsten Kirkeby4Inger Kappel Schmidt5Birte Boelt6Department of Geosciences and Natural Resource Management, University of CopenhagenFaunaPhotonics APSFaunaPhotonics APSCentre of Environmental and Climate Science & Department of Biology, Lund UniversityFaunaPhotonics APSDepartment of Geosciences and Natural Resource Management, University of CopenhagenDepartment of Agroecology - Crop Health, Aarhus UniversityAbstract Background Recent declines of honeybees and simplifications of wild bee communities, at least partly attributed to changes of agricultural landscapes, have worried both the public and the scientific community. To understand how wild and managed bees respond to landscape structure it is essential to investigate their spatial use of foraging habitats. However, such studies are challenging since the foraging behaviour of bees differs between species and can be highly dynamic. Consequently, the necessary data collection is laborious using conventional methods and there is a need for novel methods that allow for automated and continuous monitoring of bees. In this work, we deployed an entomological lidar in a homogenous white clover seed crop and profiled the activity of honeybees and other ambient insects in relation to a cluster of beehives. Results In total, 566,609 insect observations were recorded by the lidar. The total measured range distribution was separated into three groups, out of which two were centered around the beehives and considered to be honeybees, while the remaining group was considered to be wild insects. The validity of this model in separating honeybees from wild insects was verified by the average wing modulation frequency spectra in the dominating range interval for each group. The temporal variation in measured activity of the assumed honeybee observations was well correlated with honeybee activity indirectly estimated using hive scales as well as directly observed using transect counts. Additional insight regarding the three-dimensional distribution of bees close to the hive was provided by alternating the beam between two heights, revealing a “funnel like” distribution around the beehives, widening with height. Conclusions We demonstrate how lidar can record very high numbers of insects during a short time period. In this work, a spatial model, derived from the detection limit of the lidar and two Gaussian distributions of honeybees centered around their hives was sufficient to reproduce the observations of honeybees and background insects. This methodology can in the future provide valuable new information on how external factors influence pollination services and foraging habitat selection and range of both managed bees and wild pollinators.https://doi.org/10.1186/s40317-022-00285-zLidarRemote sensingEntomologyLandscape ecologyPollinationHoneybees |
| spellingShingle | Klas Rydhmer Jord Prangsma Mikkel Brydegaard Henrik G. Smith Carsten Kirkeby Inger Kappel Schmidt Birte Boelt Scheimpflug lidar range profiling of bee activity patterns and spatial distributions Animal Biotelemetry Lidar Remote sensing Entomology Landscape ecology Pollination Honeybees |
| title | Scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| title_full | Scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| title_fullStr | Scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| title_full_unstemmed | Scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| title_short | Scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| title_sort | scheimpflug lidar range profiling of bee activity patterns and spatial distributions |
| topic | Lidar Remote sensing Entomology Landscape ecology Pollination Honeybees |
| url | https://doi.org/10.1186/s40317-022-00285-z |
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