Urban biodiversity and human well-being in East-Southeast Asia’s megacities

The "Urban Butterflies in Asia Research Network" involves researchers across East-Southeast Asia. Information can be found on the project's website (Wilson and Sing 2020) and ResearchGate project page (https://www.researchgate.net/project/Urban-Butterflies-in-Asia-Research-Network).

In urban green spaces, such as city parks, native insects provide important ecosystem services including pollination of plants that provide food for humans and other animals and enrich human well-being. These important services proceed largely unnoticed and have received limited attention. Several studies of insect diversity in city parks, thought of as urban wildlife refuges, have been conducted in Europe and North America, but few have been conducted in rapidly urbanising countries in East-Southeast Asia (Ramírez-Restrepo and MacGregor-Fors 2016). Without further research into the diversity of insects in urbanisation hotspots, we cannot predict how future development will affect the ecosystem services and benefits they provide. Our project focuses on megacities across the region (Fig. 1) and on butterflies – a model “biodiversity indicator” group for biodiversity studies (Syaripuddin et al. 2015).

Figure 1.  

Megacities in East-Southeast Asia featured in Figure 1 of Schneider et al. (2015). Butterfly sampling has been completed in urban parks by the "Urban Butterflies in Asia Research Network" (Sing et al. 2017, Sing et al. 2016a, Sing et al. 2016b, Sing et al. 2019, Wilson and Sing 2020) at those megacities with blue markers. Butterfly sampling has been completed in urban parks by other researchers (Matsumoto 2015, Nagase et al. 2019, Lee et al. 2015) at those megacities with orange markers. To our knowledge, no butterfly sampling has been published for urban parks at those megacities with magenta markers.

We will (1) generate data from urban parks in megacities across East-Southeast Asia to enable region-wide meta-analyses of butterfly diversity in this rapidly urbanising region (Sing et al. 2017); (2) examine the value of urban parks as refuges for butterflies through investigating the relationships between butterfly species richness and the age, size and distance from the central business district of parks in East-Southeast Asian cities (Sing et al. 2016a, Sing et al. 2016b, Sing et al. 2019); (3) identify which type of microhabitat within urban parks provides suitable breeding and foraging habitat for butterflies (Sing et al. 2016a, Sing et al. 2016b); and (4) contribute to DNA barcode reference libraries of urban butterflies to enable rapid surveys of these species in future studies (Wilson et al. 2013).

The project has received funding from the Asia-Pacific Network for Global Change Research (CRYS2017-03SY-Sing); Fundamental Research Funds for the Central Nonprofit Research Institution of CAF (CAFYBB2020ZB008); Biodiversity Conservation Programme of the Ministry of Ecology and Environment, China (China-BON Butterflies) (SDZXWJZ01059-2018). We have also received support from the Kunming Institute of Zoology, Chinese Academy of Sciences; Fairy Lake Botanical Garden, Shenzhen & Chinese Academy of Sciences; Naresuan University, Thailand. We are grateful to all the park managers and local authorities who have provided permission to conduct butterfly surveys and supported the project (in kind) in many ways.

Ten parks managed by the Bangkok Metropolitan Authority were selected for sampling (Fig. 2). These represent a range of park areas, ages and degree of urbanisation i.e. distance from the urban core.

Figure 2.  

Location of ten parks within the Bangkok Metropolitan Region where we conducted butterfly surveys.

Each park was sampled over three consecutive days comprising 180 minutes each day. We followed an active search-timed survey method used in our butterfly surveys in Kuala Lumpur (Sing et al. 2016b), Shenzhen (Sing et al. 2016a) and Beijing (Sing et al. 2019), where butterflies were collected during the 180 minutes survey period within accessible areas. This method allowed a full search of green areas in parks and avoided sampling biases due to differences in size and shape between parks. Butterflies were collected by an experienced collector using a hand net between 09:00 h and 14:00 h during calm weather to correspond with the peak flight activity period of most adult butterflies.

Sampling limitations

While we followed a standardised sampling approach to aid comparison with surveys conducted in other megacities, the number of species recorded will have been limited by the collecting method (i.e. hand net only, no bait trapping), time of day (i.e. crepusular species could be missed) and the season (i.e. some species will not have been present as adults at this time of year).

Species identification

We combined both morphological methods (i.e. comparision with images and descriptions in Ek-Amnuay 2012) and DNA barcoding (i.e. matches in the DNA barcode library) for species identification. All collected butterflies were brought back to the university. DNA was extracted from a single leg, or 2–3 legs in the case of small lycaenids, of each butterfly using the TIANamp extraction kit following the manufacturer’s instructions (Tiangen Biotech, Beijing). DNA barcode fragments of COI mtDNA were amplified (following standard protocols in Wilson 2012) using LCO1490/HCO2198 primers. PCR products were Sanger-sequenced and checked for quality (following standard protocols in Wilson et al. 2019). Specimen data and any generated DNA barcodes were submitted to Barcode of Life Datasystems (BOLD; Ratnasingham and Hebert 2007). In BOLD, the DNA barcodes were automatically sorted into Barcode Index Numbers (BINs; Ratnasingham and Hebert 2013) which greatly aided the application of names to specimens with sequences. At present, five species could only be given a genus name (from genera, Borbo, Parnara and Pelopidas) (Suppl. material 1); however, these may be updated as the BOLD library grows and the taxonomy applied in BOLD is refined.

Bangkok Metropolitan Region, Thailand

13.495 and 13.955 Latitude; 100.328 and 100.938 Longitude.