Introduction
In this contribution we investigate the online interest and market for songbirds in Indonesia. We relate data on the public interest in song birds, on the supply in an online pet market, and on sightings by bird watchers, using data collected from online sources. We found a significant correlation between public interest and sighting numbers, indicating that population numbers are indeed affected by the popularity of a species as pets.
The pet market for songbirds is on a steady rise in Indonesia (Shepherd 2014, 16, 18, some TRAFFIC report). Many of the traded animals are endangered, with the threat often due to poaching to meet the demand of the trade itself. Some species are protected by national regulations (UBU14?) and international agreements (CITES XX), the IUCN Red List categorises many as ‘vulnerable’, ‘endangered’ or ‘critically endangered’ (IUCN XY). This renders the trade in many species illegal. Despite this, market surveys have shown that sellers continue to openly display such animals in markets (TRAFFIC XX), indicating insufficient enforcement of existing regulations and hinting at a lack of awareness for animal welfare in the general public.
There are clear indications that rarity is a sought-after quality when pet owners choose a species, and in doing so putting endangered species at an even higher threat. Other influential characteristics include the perceived beauty and exoticism of birds’ songs, and an extraordinary appearance of the bird, such as e.g. long and colourful tails (REF). This is at least in part due to local, regional and even national competitions between song bird owners who showcase their pets and their songs (REF).
Similar to other illegal trade in wildlife, a large portion of the market in songbirds has moved online. The illegal market in ivory, rhino horn and similar wildlife commodities saw a shift to closed groups on social media (e.g. Facebook, WhatsApp; see Yu & Jia, 2015), these channels also play an important role in the pet bird trade (personal communication, Stuart Butchart).
OLX is an online market place for small ads, operating in various countries around the globe. On its Indonesian page (
https://olx.com.id), we found listings advertising song birds for sale, amongst them protected species. Listings include photos, asking price and location.
There is a significant number of videos of song birds posted to online video platforms, e.g. Youtube (
https://youtube.com/), presumably because a bird’s value is determined by its song’s quality, which can be best demonstrated in a recording. Some videos serve the purpose of showing off with one’s pet, others openly advertise an animal for sale. More often then not, the price or value of an animal is discussed in the comment section underneath a video posting.
Wikipedia has an application programming interface (API) to access statistics on the visitation of its encyclopaedia entries, including those on species. This data is available at a fine temporal resolution, and can be compiled into fine-grained time series to illustrate a change in interest on a certain topic (Mittermeier XY, Correia XY). The general public’s interest in a topic and its change over time can also be estimated from Google Trends data. Google Trends measures the frequency (and popularity) of search terms queried for on the Google search engine. These data, while subject to a number of biases, have been successfully used in contributions to conservation culturomics that measured BLABLa and BLIBLU (e.g. Correia, XY, Diogo, ZY).
eBird (
https://ebird.org/, Sullivan et al. 2009) is an app and website for bird watchers that allows them to report their sightings and share them with other enthusiasts and with scientists conducting research on birds. Bird sighting data are subject to a reporting bias; rare species might in fact be over-represented (see REF, 20XX). This can be overcome by looking at the relative changes rather than absolute numbers of bird sightings. The eBird data set spans a long time series and features large sample sizes.
A genus particularly affected by illegal and legal trade is the Laughingthrush (Garrulax spp.), with the Rufus-fronted Laughingthrush (G. rufifrons) being recently upgraded from an ‘endangered’ to a ‘critically endangered’ status on the IUCN Red List (IUCN, XY, see also Shephard et al 2016, 2007). Another species, the Sumatran Laughingthrush (G. bicolor), is currently listed as ‘vulnerable’, the remaining four species as ‘least concern’.
Only a small part of digital data sources contains metadata that directly refers to the geographic location of content. For instance, photos on Flickr and short messages on Twitter can be georeferenced, i.e. tagged with a coordinate pair and thus linked to a location. Not all users decide to enable this feature, and many platforms’ APIs do not return precise coordinates, but rather the name of a nearby place (Toivonen 2019). On the one hand, this is to be seen positive in the interest of users’ data privacy (Di Minin, Fink et al. 2020), and might also prevent researchers from unreflectedly assuming that eucledian space is the primary reference for research on spatial relationships (QUOTE). Most quantitative analyses, though, need a positivist, cartesian, view on space, and precise geolocation. Data from Youtube, i.e. video metadata and comments, do not contain such information (QUOTE Google API Doc). We observed that many of the video titles, descriptions, and comments contained place names, thus allowing indirect georeferencing, using natural language processing methods to identify geographic names, then a gazetteer to assign geographic coordinates (see Methods).