Monitoring songbirds' online market

Monitoring songbirds' online market
Beni Okarda1, Sonya Dyah Kusumadewi1, Prof. Dr. Herry Purnomo1,2
1CIFOR-ICRAF Indonesia Country Program
2IPB University

GCRF TRADE HUB INDONESIA CLOSING EVENT
HARNESSING GREEN TRADE AND
LANDSCAPE SUSTAINABILITY
Date
Tuesday, 19th March 2024
13:00 – 19:00 Western Indonesian Time (WIB)
Location
Global Forestry Hall, CIFOR Bogor
Organizer
Supporting by

Introduction
Songbirds in Indonesia
• Keeping songbirds as pets is common and popular in Indonesia (Jepson and Ladle, 2005;
Jepson and Ladle, 2009). Cultural affinity particularly to Javanese (Iskandar et al., 2014).
Hobbyists, songbird contestants, breeders (Marshall et al., 2020)
Threat from the trade
• Wildlife trade is indicated as a major threat to biodiversity loss besides habitat destruction
(Nijman et al., 2018; Scheffers et al., 2019; Symes et al., 2018).
• Decrease of the populations in the wild as an impact of the trade as the songbirds traded
is coming from wild catch (Harris et al., 2017; Nijman et al., 2018; Shepherd et al., 2013).
• Households in Java that kept songbirds are increased from 14.2% in 2007 to 31.9% in 2018
(Marshall et al., 2020). The trend of songbirds contests also increases the songbirds trade
(Iskandar et al., 2019; Leupen et al., 2020)

Why online marketplace
• Existing studies mainly cover the physical market in big cities of Indonesia, particularly
in the Java region (Chng et al., 2015; Chng and Eaton, 2016; Iskandar et al., 2019;
Leupen et al., 2020; Nijman et al., 2018; Rentschlar et al., 2018).
• The trend of songbirds’ trade has extended to the online market (Harrison et al., 2016;
Leupen et al., 2020).
• The proportions of buying cage-bird from the online market are 12-21% (Marshall et
al., 2020).
• Complementary to offline market monitoring and as an option to monitor wider
region.

Date
Location
Organizer
Supporting by
Method
Ads Database
35% Sampling
Classified Bird
Advertisement
Training data
Validation data
Test data
Train-Valid-Test split
Build
ML Models
Accuracy
Assessment
8 models
(ANN, CNN, LR, GRU, LSTM, NB , RF, SVM)
80%
10%
10% Model
evaluation
Labelling
o Handbook of the Birds
of the World (2018)
o Indonesia Bird List V.2
(2007)
Machine learning
Online marketplace
 Online seller profiles
 Bird origin (Wild-caught, Captive-bred)
Step 1: Relevant / Not relevant Ads
Step 2: Species classification
Title
Price
Location
Optimal
models
Accuracy
assessment
Selected
ML Model
fine-tuning
Data pre-processing
Deploy model
Sampling data
Survey

Date
Location
Organizer
Supporting by
Machine learning approach
• Big data enables machine learning algorithms to uncover more fine-grained patterns
and make more timely and accurate predictions (Zhou et al., 2017)
• Machine learning has the potential to be used as a tool in monitoring wildlife trade
(Di Minin et al., 2019; Hernandez-Castro and Roberts, 2015; Stringham et al., 2021)
Unstructured information
(Bird Ads)
Algorithm
Structured information
(Classified species)
Classification
Training

Date
Location
Organizer
Supporting by
Machine learning model performances

Date
Location
Organizer
Supporting by
Result
Total ads 371,301
April 2020 – September 2021
247 Species
80% Native Indonesia
49 Families

Date
Location
Organizer
Supporting by
Geographic distribution
91.2%
5.7% 1.5%
1.4%
0.1%
• Java is the center of
population 151M or 56%
(Statistic Indonesia,
2020)
• Number of internet users
and advanced internet
infrastructures in
Indonesia are
distributed mostly in
Java (Statistic
Indonesia, 2019)
• Java as the biggest
regional source of
cage-bird demand
(Jepson and Ladle,
2005; Eaton et al., 2015;
Marshall et al., 2020)

Date
Location
Organizer
Supporting by
10 most advertised birds
Agapornis spp.
Lovebirds
30.2%
Geopelia striata
Zebra Dove
4.2%
Copsychus malabaricus
White-rumped Shama
14.7%
Pycnonotus goiavier
Yellow-vented Bulbul
2%
Serinus spp.
Canaries
14.7%
Gracupica jalla
Javan Pied Starling
2.6%
Streptopelia bitorquata
Sunda Collared-dove
2%
Copsychus saularis
Oriental Magpie-robin
4.2%
Lanius schach
Long-tailed Shrike
1.5%
Geokichla citrina
Orange-headed Thrush
1.4%

Date
Location
Organizer
Supporting by
IUCN Threatened Species
Garrulax bicolor
Sumatran Laughingthrush
Cissa thalassina
Short-tailed Green-
magpie
Chloropsis sonnerati
Greater Green Leafbird
Pycnonotus zeylanicus
Straw-headed Bulbul
Padda oryzivora
Java Sparrow
Acridotheres javanicus
Javan Myna
Gracupica jalla
Javan Pied Starling
Zosterops flavus
Javan White-eye
Leucopsar rothschildi
Bali Myna

Date
Location
Organizer
Supporting by
Mean asking price and ads proportion

Date
Location
Organizer
Supporting by
Online seller profiles for the songbird trade

Date
Location
Organizer
Supporting by
Respondent experience in the online market

Date
Location
Organizer
Supporting by
Songbird origin, preferences and reasons

Key finding
• The study demonstrated that machine learning is very effective in monitoring the songbird trade in
the online market.
• Java is the center of the songbird's online market with 91% of ads coming from there.
• 6% of advertised birds are IUCN’s threatened species.
• Advertised birds in the online market are related to songbird contests.
• Master birds have less concern compared with the competitive taxa, and several master bird taxa
are facing a serious threat of extinction in the wild
• Most online sellers are hobbyists and breeders, only 7% of respondents are bird traders.
• Most (79%) of the native bird advertised is coming from captive-bred and most of the sellers
preferred captive-bred.
• Realistically, Indonesia’s bird trade is too economically and culturally important to be stopped
completely (Marshall et al., 2020a, Marshall et al., 2020b). Therefore, a robust and effective
monitoring platform is needed to support a sustainable songbird trade, and this study has
demonstrated a monitoring framework that can meet this need.

CIFOR-ICRAF
The Center for International Forestry Research and World Agroforestry (CIFOR-ICRAF) harnesses
the power of trees, forests and agroforestry landscapes to address the most pressing global
challenges of our time –biodiversity loss, climate change, food security, livelihoods and inequity.
CIFOR and ICRAF are CGIAR Research Centers.
Thank you

Monitoring songbirds' online market

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