Acoustic monitoring data of avian species inside and outside the evacuation zone of the Fukushima Daiichi power plant accident

Study Extent

The study area was located in the eastern part of Fukushima Prefecture, northeastern Japan, and was enclosed within the following four sets of coordinates: (37.80137°N, 140.53747°E), (37.80136°N, 141.00048°E), (36.99588°N, 141.00048°E), and (36.99588°N, 140.53747°E). The study area contained the evacuation zone, which has been categorized into three subzones since October 2013: a zone in preparation for lifting the evacuation order (≤20 mSv/year, Zone 1), a restricted residence area (20–50 mSv/year, Zone 2), and a difficult-to-return-to zone (>50 mSv/year, after five years the air dose rate will be > 20 mSv/year, Zone 3). We set up 52 monitoring sites inside and outside the evacuation zone in 2014 (33 sites outside the evacuation zone, six sites in Zone 1, seven sites in Zone 2, and six sites in Zone 3), which were the same as the insect monitoring sites used by Yoshioka et al. (2015). After that we set up 57 monitoring sites (33 sites outside the evacuation zone, eight sites in Zone 1, ten sites in Zone 2, and six sites in Zone 3) in 2015 and 55 monitoring sites (33 sites outside the evacuation zone, six sites in Zone 1, ten sites in Zone 2, and six sites in Zone 3) in 2016. All monitoring sites were located within schoolyards (including those that had been converted to community centers) to minimize differences in the local site conditions and to examine the bird assemblages in the urban and rural landscapes that were heavily altered by land abandonment due to the nuclear plant accident.

Sampling

A digital voice recorder (DS-850, Olympus, Tokyo, Japan) was installed at each monitoring site during May–July in each year. The recorders were adjusted to timer-recording mode and recorded for 10 min before and after sunrise (total 20 min) every day until the batteries were depleted. The recorders were fixed to tripod stands at a height of about 0.9 m. The recorded data were split into 1-min segments in MP3 (124 kbps) format, which was treated as the minimum sample unit. We identified species of birds from acoustic data. Bioacoustics signals is a promised source of information for avian species identification (Lopes et al. 2011), and acoustic monitoring can produce similar result as traditional on-site survey methods in comparative ecological studies (Haselmayer & Quinn 2000; Hobson et al. 2002; Klingbeil & Willig 2015). Because the number of segments was very large, we chose a subset of segments evenly throughout the sampling period (8.08 days/site and 17.0 segments/day/site in 2014, 7.65 days/site and 17.8 segments/day/site in 2015, and 5.74 days/site and 16.8 segments/day/site in 2016, in average). A total of 7,138 of the 45,540 segments were chosen in 2014, 7,945 of the 46,440 segments were chosen in 2015, and 5,221 of the 42,440 segments were chosen in 2016. Species that appeared in each segment were identified by experts and their presence-absence was recorded. Some of the segments were identified through a citizen-scientific project, “Bird Data Challenge (Fukasawa et al. 2017)”, in which we listened to audio data and prepared a species list of birds with involvement of local citizen experts. Data identified through the Bird Data Challenge was checked by authors or other experts to correct misspecifications of species. We were careful to avoid the negative impact (e.g., pressure of photographing and illegal capture) on endangered and attractive species when we made the species distribution data accessible online. We filled the location ID with 'NA' and assigned the mean latitude and longitude of the study area in the presence-absence records for endangered species (i.e., species ranked VU, EN, and CR in the National or Prefectural Red List) and species attracting particular public interest (Terpsiphone atrocaudata and Halcyon coromanda).

Quality Control

All species were identified by the authors or by professional experts or local citizen experts. Core members of the local citizen experts belonged to chapters of the Wild Bird Society of Japan in Fukushima Prefecture. If we could not obtain sufficient information to identify a species from acoustic data, we recorded the next highest taxonomic level (e.g., genus) that could be specified with certainty. Scientific names followed the Ornithological Society of Japan (2012). Noise including rain sound was detected in acoustic records during the monitoring, which was indicated in 'eventRemarks'.

Method steps

1. (1) Presence-absence records with uncertain identification of species were removed.
2. (2) Presence-absence records were summed up as daily data.

1. Aves
   rank: class

Fukushima, Japan