Acoustic profiling of Orthoptera

for species monitoring and

discovery in a changing world

Klaus Riede

Institute for Zoology, Graz University, Austria

& Zoological Research Museum Bonn, Germany

Bioacoustic recording and classification of Orthoptera allows non-invasive Rapid Assessment of species communities, particularly in species-rich tropical forest habitats

Species discovery: species presence/absence species ranges/endemisms

The vision

Species monitoring: species abundance activity patterns community patterns extirpation rates species recovery

Outline

• Acoustic profiling: state of the art

• Datasets and databases

• Lessons learnt

• Creating the infrastructure: from data loggers to

web-based song classification

• Hot spots for acoustic profiling

Grasshopper score

Alexandre Yersin (1854): Mémoire sur quelques faits relatifs à la stridulation des Orthoptères et leur distribution géographique en Europe.

Bulletin des Séances de la Société Vaudoise

des Sciences Naturelles 4: 108-128

From: Ragge & Reynolds 1998, p 65

38 species, differentiating between

Chorthippus mollis (30), C. brunneus (28) and C.

biguttulus,

„silent stridulation“ by C. mollis larvae

Evolution of Acoustic Analysis

Sonagraph

MEDAV

FastFourierTransform

Courtesy:

http://www.sfu.ca/sonic-studio/handbook/Spectrograph.html, Handbook of ethological methods. P. N. Lehner 1998

Extraction of sound parameters by using

MatLab Software

Pulse rate

Carrier

frequency

Carrier

frequency

State of the art Datasets Lessons Infrastructure Hot spots

Macaulay

State of the art Datasets Lessons Infrastructure Hot spots

Soundscapes from different sites

Map

Ecuador

Sabah Panama

Piemonte

State of the art Datasets Lessons Infrastructure Hot spots

soundscapes

Valdiere (Piemonte, Italy) Poring (Sabah, Malaysia - Borneo)

Rio Aguarico (Ecuador - Amazonia) Barro Colorado Island (Panama)

State of the art Datasets Lessons Infrastructure Hot spots

20 kHz

0

20 kHz

0

landscapes

Acoustic grasshopper identification is used in temperate habitats (grasslands)

From: Bellmann, H.:Heuschrecken: beobachten, bestimmen 1993

Chorthippus mollis ignifer Ramme, 1923

State of the art Datasets Lessons Infrastructure Hot spots

Acoustic Orthoptera identification is used

in temperate habitats (Europe)

State of the art Datasets Lessons Infrastructure Hot spots

Cicadas are a main component of SEA dusk chorus

Panama BCI Big Tree

State of the art Datasets Lessons Infrastructure Hot spots

Spectral similarities between Neotropical dusk

chorusses

20 kHz

6

3

0

20 kHz

15

12

9

4.5

0

Ecuador - San Pablo - Aguarico

0 -30 dB I I

0 -30 dB I I

Panama, BCI, early evening - 1 min

20 kHz

6

0 1000 ms

Panama, BCI, early evening - 1 min

20 kHz

6

0 1000 ms

Identifying morphospecies and ethospecies

Chirps

Chirp interval: 1170ms

109 122

pulses/chirp: 7 Pulsrate - PR (pulses/s): 64

Pulse rate (Pulse/s): (7/109)*1000= 64

Carrier Frequency (CF):7500 Hz

Chirp[ms]: 109, 122 Chirp interval: 1170

0 200 ms

0 1000 2000 ms

Identifying morphospecies and ethospecies

Chirps

Chirp interval: 1170ms

109 122

pulses/chirp: 7 Pulsrate - PR (pulses/s): 64

Pulse rate (Pulse/s): (7/109)*1000= 64

Carrier Frequency (CF):7500 Hz

Chirp[ms]: 109, 122 Chirp interval: 1170

0 200 ms

0 1000 2000 ms

A16,20,21: identische Sequenzen und Gesaenge

A21: 7514 Hz

A20: 7550-7730 Hz

A16: 7640-7895 Hz Pulse rate 64 Hz

State of the art Datasets Lessons Infrastructure Hot spots

State of the art Datasets Lessons Infrastructure Hot spots

Inventorying morphospecies and ethospecies

at Barro Colorado Island

Frequency - Pulse distance

Trigoniinae subset from Ecuador

Pulse

distance

[ms]

100

5 Frequency 18 kHz 2

Acoustic profiles of Orthoptera communities in...

Ecuadorian lowland and mountain forest: Riede 1993,Nischk & Riede 2001 Acoustic monitoring protocol Brandes 2004 - TEAM Conservation Int.

State of the art Datasets Lessons Infrastructure Hot spots

Orthoptera abundance in European grasslands Gardiner, T, Hill, J., Chesmore, D. 2005

Acoustic entropy in Tanzanian forest: Sueur, J. et al. 2008

Orthoptera in an Indian forest: Diwakar, Jain,& Balakrishnan 2007

Cricket recordings North America: Walker 1964-2009

O

o o O O

Australian crickets:

Otte & Alexander 1983

Acoustic profiling: lessons learnt

Method not generally established (except in Europe) Automatic classification is promising, but not sufficient for field applications Identification and classification still time-consuming Limited access to existing acoustic datasets Taxonomic impediment: lack of comprehensive, accessible species descriptions (preferably including songs)

State of the art Datasets Lessons Infrastructure Hot spots

BUT

huge potential and wide interest

Creating the infrastructure: databases

OSF: 140 taxa with songs

State of the art Datasets Lessons Infrastructure Hot spots

Systax: 2268 songs,

641 species

http://Orthoptera.SpeciesFile.org http://www.biologie.uni-ulm.de/systax/

From profiling to protocols

State of the art Datasets Lessons Infrastructure Hot spots

TROPICAL ECOLOGY, ASSESSMENT, AND MONITORING INITIATIVE Acoustic Monitoring Protocol

T. Scott Brandes, 2003

Automatic recording: www.arbimon,.net

State of the art Datasets Lessons Infrastructure Hot spots

Arbimon stations

State of the art Datasets Lessons Infrastructure Hot spots

Arbimon soundscapes

State of the art Datasets Lessons Infrastructure Hot spots

Arbimon web-based sound analysis: identification of Regions of Interest (ROIs)

State of the art Datasets Lessons Infrastructure Hot spots

Hot spots: endangered forests

http://rainforests.mongabay.com/0801.htm

State of the art Datasets Lessons Infrastructure Hot spots

http://www.millenniumassessment.org/en/GraphicResources.aspx

Thanks to ....

Austrian Science Fund FWF, project grant P 20882-B09 to H. Römer Arne Schmidt & Anne Einhäupl Inhabitants of San Pablo indigenous community, Rio Aguarico, Ecuador Mitch Aide, Arbimon Project, Puerto Rico