Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study
Abstract Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-02-01
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| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.5928 |
| _version_ | 1819161487504048128 |
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| author | Markus Milchram Marcela Suarez‐Rubio Annika Schröder Alexander Bruckner |
| author_facet | Markus Milchram Marcela Suarez‐Rubio Annika Schröder Alexander Bruckner |
| author_sort | Markus Milchram |
| collection | DOAJ |
| description | Abstract Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible. We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (a) density estimates from the literature and to (b) Royle–Nichols (RN) models of detection/nondetection data. Our estimates for M. nattereri matched both the published data and RN‐model results. For E. nilssonii, the gREM yielded similar estimates to the RN‐models, but the published estimates were more than twice as high. This discrepancy might be because the high‐altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were ~10 times higher than those of RN‐models. RN‐models use detection/nondetection data, and this loss of information probably affected population estimates of very active species like P. pipistrellus. gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates. |
| first_indexed | 2024-12-22T17:13:08Z |
| format | Article |
| id | doaj.art-dd795abae5304de786200f0407cd85fd |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-12-22T17:13:08Z |
| publishDate | 2020-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-dd795abae5304de786200f0407cd85fd2022-12-21T18:19:01ZengWileyEcology and Evolution2045-77582020-02-011031135114410.1002/ece3.5928Estimating population density of insectivorous bats based on stationary acoustic detectors: A case studyMarkus Milchram0Marcela Suarez‐Rubio1Annika Schröder2Alexander Bruckner3Institute of Zoology Department of Integrative Biology and Biodiversity Research University of Natural Resources and Life Sciences Vienna Vienna AustriaInstitute of Zoology Department of Integrative Biology and Biodiversity Research University of Natural Resources and Life Sciences Vienna Vienna AustriaInstitute of Zoology Department of Integrative Biology and Biodiversity Research University of Natural Resources and Life Sciences Vienna Vienna AustriaInstitute of Zoology Department of Integrative Biology and Biodiversity Research University of Natural Resources and Life Sciences Vienna Vienna AustriaAbstract Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible. We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (a) density estimates from the literature and to (b) Royle–Nichols (RN) models of detection/nondetection data. Our estimates for M. nattereri matched both the published data and RN‐model results. For E. nilssonii, the gREM yielded similar estimates to the RN‐models, but the published estimates were more than twice as high. This discrepancy might be because the high‐altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were ~10 times higher than those of RN‐models. RN‐models use detection/nondetection data, and this loss of information probably affected population estimates of very active species like P. pipistrellus. gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates.https://doi.org/10.1002/ece3.5928acoustic monitoringautomated recording unitsChiropteraenvironmental assessmentgeneralized random encounter modelspopulation density |
| spellingShingle | Markus Milchram Marcela Suarez‐Rubio Annika Schröder Alexander Bruckner Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study Ecology and Evolution acoustic monitoring automated recording units Chiroptera environmental assessment generalized random encounter models population density |
| title | Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study |
| title_full | Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study |
| title_fullStr | Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study |
| title_full_unstemmed | Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study |
| title_short | Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study |
| title_sort | estimating population density of insectivorous bats based on stationary acoustic detectors a case study |
| topic | acoustic monitoring automated recording units Chiroptera environmental assessment generalized random encounter models population density |
| url | https://doi.org/10.1002/ece3.5928 |
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