profiling the beast · – bubalus quarlesi –highlander – bubalus depressicornis –lowlander...

PROFILING THE BEASTUnderstanding anoa ecology through tracks and turds

Asri A. DwiyahreniDepartment of Biological Sciences

Scarborough Centre of Environmental and Marine SciencesUniversity of Hull

WHY ANOA?

• Endemic Sulawesi • Endangered species (IUCN)• Appendix I CITES• Protected species under Indonesians law

• Largest mammal in Sulawesi Island• Southeast Sulawesi’s symbol• Flagship species

Almost nothing is known about this beast!

FACTS ABOUT ANOA

• Two species – Bubalus quarlesi – Highlander– Bubalus depressicornis – Lowlander

• Confused taxonomy; work in progress

• Solitary-forest dwelling browsers

• Inhabits lowland to montane forests including mangroves and secondary formations

• Population number– 0.9 ind/km2 ; 2500 individual in Sulawesi– Lambusango: 150 individual

• Rough estimation based on indirect evidences– Zoo population: 250 animals

Populations are declining all over Sulawesidue to hunting and habitat degradation!

Anoa Distribution in Sulawesi

ACTIONS NEEDED

• Baseline information for conservation– Robust density estimate– Basic ecology – Understanding threats

‘Traditional’ methods (distance sampling, conventional tagging,

signs sampling, camera traps) don’t work!

Distance sampling (Line transect) 2 anoas along 182.1 km in Tanjung Peropa,3 in 50 km in Tanjung Batikolo3 in 202.7 km in Rawa Aopa Watumohai (Riley et al. 2001)20 sightings in 372 km transects in Tanjung Peropa 8 in 124.3 km in Tanjung Amolengo (Mustari 2003).

Signs samplingRequire conversion factors (production and decomposition rates) Gathering production and decomposition rates datais time consuming and expensive.

Conventional taggingNeed to catch the animals, might be harmful to endangeredspecies

Camera trapsEffective for animals that are easy to individually identified from photographs

LAMBUSANGO ANOA

PROJECT

Lambusango Forest Reserve

Limited Production Forest

Lapago

WabalambaWahalaka

AnoaBala

Lasolo

3 km

•Study sites

•The study

Estimating density (non invasive genetic analysis)

Occupancy(tracks distribution analysis)

Understanding threats (hunting survey)

ESTIMATING DENSITY

Non invasive genetic studies for rare elusive mammals:

Brown bears (Bellemain et al. 2005)Eurasian badgers (Frantz et al. 2004)African forest elephants (Eggert et al. 2003)

Non-invasive genetic tagging

Faecal sampling• Preserved in 95% ethanol

DNA analysis• Species identification

anoa or domestic cow• Individual identification • Density: capture mark

recapture

Dung map

Faecal sample distribution in six sampling blocks

Capture Mark Recapture 250 m square virtual grid

Faecal samples (N=159)

Sites 2005 2006 2007Anoa 6 23 11Lapago - 2 7Lasolo - 5 8Lawele - 6 4Wabalamba 8 30 26Wahalaka 3 19 1

Total 17 85 57

Genetic analysis

• Microsatellite• Cytochrome B • Sex markers

10 cm

Genetic analysisMicrosatellite

• Microsatellite primers design33 cattle primers

Tested using water buffalo meatTested on anoa faecal samples

many bands

– Filtered the large DNA bands, all bands gone

– Re-tested all cattle primers using anoa meat

17 primer pairs have good results– Re-designing primers using anoa

sequences to amplify 70 to 130 bp

• 10 loci : 4 loci are amplified so far• Nested PCR to specify amplification:

amplify anoa DNA discard other DNA (bacterial DNA)

Genetic analysisCytochrome B and Sex markers

• Cytochrome B gene150 Bp is amplified from faecal DNA

• Sex markersTesting primers toamplify sex markers

Other information fromDNA analysis

Home rangeMovement/dispersalPopulation structure

OCCUPANCY

Anoa tracksHuman trails

Patch occupancy analysis Program PRESENCE

Probability of area occupied (PAO)‘Colonisation’, ‘Extinction’The influencing factors

Using likelihood-based approach that include the heterogeneity in probability of detecting animals

PAO analysisPrinciples

• Basic problem in animal survey:– Undetected presence of animal

• Probability a site is occupied: ψ• Probability species detected at

site, given it is there: p

• Models p and ψ based on repeat observations of a ‘patch’.

• The probability of observing the history 1001 (i.e. the species was detected in the first and fourth

surveys of the site) is: ψ × p[1](1-p[2])(1-p[3])p[4].

• The probability of never detecting the species at a site (0000) would therefore be:

ψ × (1-p[1])(1-p[2])(1-p[3])(1-p[4]) + (1-ψ)

this represents the fact that either the species was there, but was never detected, or the species was genuinely absent from the site (1-ψ).

By combining these probabilistic statements for all N sites, maximum likelihood estimates ψ and p can obtained.

Sampling design

Line transect 50 m sampling replicate

500 m landscape unit

10 Cm

Occupancy and detection probabilitySingle-season model

0

0.2

0.4

0.6

0.8

1

2004 2005 2006

Naïve Psi Psi P

The occurrence of human trails were negatively related with p and ψ

Extinction probability over years Multi-seasons model

0

0.1

0.2

0.3

0.4

0.5

2005 2006 2007

Year

Extin

ctio

n pr

obab

ility

Lapago

Wahalaka

Bala

•From 2005 to 2007Extinctions in Anoa, Lasolo and Wabalambaare 0.

•Colonisation in Lapago, Wahalaka and Bala are negatively related with the occurrence of human trail.

UNDERSTANDING THREATS

Hunting for bushmeat in Sulawesi

is BIG

Hunting level survey

Semi-structured interviewsConsumption levelCommunity perceptions

Villages around Lambusango

Preliminary results

• October to December 2007• 274 respondents and 17

hunters from 45 villages• 53% of respondents have

eaten anoa.• Hunters sell:

– anoa meat £1/kg– Anoa head as trophy £10 to

£20 per head

Immediate Conservation Recommendations

• Fully protect Lasolo and Wabalamba

from human activities. Propose

as anoa sanctuary.

• Increase law enforcement to

stop hunting and other illegal

activities in Anoa, Lapago, Lawele,

and Wahalaka

SUMMARY• Human trails and hunting are negatively

related to Anoa occupancy and detection probability.

• PRESENCE analysis provides fast, easy and efficient tool to monitor Anoa population.

• Genetic data will highly increase understanding about Anoa ecology.

• With combined results, robust PVA and effective conservation recommendations will be possible to make.

THANKS TO GEF WORLD BANKOPERATION WALLACEA

CHESTER ZOOWILDLIFE CONSERVATION SOCIETY

DRS PHIL WHEELER, BILL HUTCHINSONINDONESIAN MINISTRY OF FORESTRY

LA AU, LA MARENE, RAKHMAD, HARDINODE CAMPS AND LABUNDO BUNDO STAFF

AMBANG, UNI, SALAM, PAU, MARKOPWALL VOLUNTEERS