Acoustic recordings and corresponding mammal, bird, human activity, vegetation, and climate data from a tropical forest landscape
Data files
Mar 31, 2022 version files 176.24 GB
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Bird_observations_with_the_continuous_counts_method.csv
15.11 KB
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Bird_observations_with_the_point_counts_method.csv
26.46 KB
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BT1.zip
13.05 GB
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BT2.zip
7.67 GB
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BT3.zip
13.02 GB
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BT4.zip
12.68 GB
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BT5.zip
14.56 GB
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BT6.zip
4.68 GB
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Direct_observations_of_great_ape_nests.csv
7.74 KB
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Direct_observations_of_mammal_signs.csv
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English_names_of_vegetation_types.csv
185 B
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Humidity.csv
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Identification_of_animal_species_in_audio_files.csv
3.29 MB
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Indirect_observations_of_human_activities.csv
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Indirect_observations_of_mammal_signs.csv
27.99 KB
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Local_English_and_scientific_names_of_animal_species.csv
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Moon_phases.csv
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NT1.zip
12.23 GB
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NT2.zip
7.47 GB
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NT3.zip
7.01 GB
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NT4.zip
12.10 GB
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NT5.zip
3.27 GB
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NT6.zip
2.87 GB
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Number_of_analysed_audio_files.csv
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PT1.zip
11.57 GB
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PT2.zip
10.25 GB
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PT3.zip
6.06 GB
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PT4.zip
13.17 GB
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PT5.zip
11.92 GB
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PT6.zip
12.63 GB
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Rainfall_during.csv
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README.txt
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Sensors.csv
605 B
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Temperature.csv
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Vegetation_types.csv
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Abstract
Obtaining and analysing sound data can be a tedious and lengthy process. We present sound data consisting of 38,065 1-minute sound recordings obtained in three sites within a rainforest landscape in southeast Cameroon. The sites differ in anthropogenic disturbance. We also present meta data corresponding to 20,485 of these recordings with the identification of all animal vocalisations in each 1-minute sound recording. Additionally, we provide a raw database with data on habitat, human activities, remoteness, accessibility, temperature, humidity, rainfall, moon phase, and mammal and bird observations in the area during the recording period. The data were used by Diepstraten & Willie (2021) to investigate the structure and drivers of biological sounds along a disturbance gradient. The data contribute to call libraries of tropical species and can also be used to build classifiers for automatic detection and classification of animal vocalisations.
Methods
- Data were obtained in three study sites that differ in land-use type and conservation management in the northern part of the Dja Faunal Reserve’s buffer zone in Cameroon.
- Data were collected between February and May 2020.
- In every study site, 6 transects of 1-km each were opened.
- Audio data were obtained using the following procedure:
- An AudioMoth bioacoustics sensor was deployed in the middle of every transect.
- The sensors were deployed at a 2-m height at a 90° orientation.
- The sensors were kept in zip lock bags within a protective case, with a small hole at the location of the sensors’ microphone, to protect them from rain and animals.
- All sensors were set to record the first minute of every hour at 48kHz and 30.6dB.
- Recordings made during the night were screened beforehand. Only night recordings with vocalisations from other species than easily recognisable insects, amphibians or western tree hyraxes were played to the local experts.
- Recordings were played to two local experts, who identified all audible species.
- Names of the vocalising species were noted down in Badjué (local language).
- Vocalisations of birds and mammals were identified by species. Vocalisations of insects and amphibians were identified by class. Unidentifiable vocalisations were recorded as “Animal unknown” or “Bird unknown”.
- Field surveys were conducted to collect data on anthropogenic and ecological factors:
- Vegetation types were described at every 50-m interval in each transect.
- Human activity was described by identifying all human signs within a 2-m range perpendicular to each transect. For each sign, the location along the transect and the vegetation type was recorded.
- Mammal activity was described indirectly by identifying animal signs within 2-m on either side of the transect and corresponding location along the transect, vegetation type, canopy openness, understory openness, and horizontal visibility. The local guide identified the type of animal sign and local name of the species. All transects were walked twice. Rainfall between the two surveys prevented overlap.
- Presence of great apes, central chimpanzees (Pan troglodytes troglodytes), and western lowland gorillas (Gorilla gorilla gorilla) was described by the observation of their nests along the transects. For every nest, age, location along the transect (m), perpendicular distance from the transect (m), and circumference (cm) were recorded. Furthermore, vegetation type, canopy openness, understory openness, and horizontal visibility (m) were noted. Additionally, for gorillas, the type of nest was described by the composition of plants used for construction. For chimpanzee nests, the type of nest was described by its position in the tree. These surveys were conducted twice for each transect, with one month in between surveys. No nest was counted twice.
- Mammal activity was described directly by slowly walking along each transect (1km/h). For all observed mammals, number, location along the transect (m), distance between the observer and the mammal (m), angle of observation, vegetation type, canopy openness, understory openness, and horizontal visibility (m) were recorded.
- Bird activity was surveyed using point counts in fixed stations and direct observations. For the point counts, birds were recorded for 8 minutes at the start, middle, and end of each transect. An initial observation direction was randomly chosen and, after two minutes of observation, the observers rotated 90° in a clockwise direction. During direct observations, birds were recorded while walking the transect in the same manner as during the direct mammal surveys. For every observation, vegetation type, canopy openness, understory openness, and horizontal visibility (m) were recorded.
- Data on rainfall, humidity, and temperature were obtained in one site. Rainfall (mm) was measured daily. Temperature (°C) and humidity (RH) were measured hourly.
- To assess additional anthropogenic factors, the shortest straight-line distance (m) between each sound recorder and the closest village and trail was measured using ArcGIS to give a proxy of remoteness and accessibility, respectively.