scholarly journals Description of Echolocation Call Parameters for Urban Bats in Vietnam as a Step Towards a More Integrated Acoustic Monitoring of Urban Wildlife in Southeast Asia

Diversity ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 18
Author(s):  
Long Kim Pham ◽  
Bang Van Tran ◽  
Quy Tan Le ◽  
Trung Thanh Nguyen ◽  
Christian C. Voigt
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Quantitative Description ◽  
Southeast Asian ◽  
Asian Countries ◽  
Echolocation Call ◽  
Echolocation Calls ◽  
Pilot Work ◽  
Southeast Asian Countries

This study is the first step towards more systematic monitoring of urban bat fauna in Vietnam and other Southeast Asian countries by collecting bat echolocation call parameters in Ho Chi Minh and Tra Vinh cities. We captured urban bats and then recorded echolocation calls after releasing in a tent. Additional bat’s echolocation calls from the free-flying bats were recorded at the site where we captured bat. We used the obtained echolocation call parameters for a discriminant function analysis to test the accuracy of classifying these species based on their echolocation call parameters. Data from this pilot work revealed a low level of diversity for the studied bat assemblages. Additionally, the discriminant function analysis successfully classified bats to four bat species with an accuracy of >87.4%. On average, species assignments were correct for all calls from Taphozous melanopogon (100% success rate), for 70% of calls from Pipistrellus javanicus, for 80.8% of calls from Myotis hasseltii and 67.3% of calls from Scotophilus kuhlii. Our study comprises the first quantitative description of echolocation call parameters for urban bats of Vietnam. The success in classifying urban bats based on their echolocation call parameters provides a promising baseline for monitoring the effect of urbanization on bat assemblages in Vietnam and potentially also other Southeast Asian countries.

Search-phase echolocation calls of the New Zealand lesser short-tailed bat (Mystacina tuberculata) and long-tailed bat (Chalinolobus tuberculatus)

1997 ◽  
Vol 75 (9) ◽  
pp. 1487-1494 ◽  
Author(s):  
Stuart Parsons
Keyword(s):  
New Zealand ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
High Rate ◽  
Echolocation Calls ◽  
Spectral Components ◽  
Lower South ◽  
Rate Of Success ◽  
Multivariate Discriminant

This paper describes the search-phase echolocation calls of lesser short-tailed bats (Mystacina tuberculata) and long-tailed bats (Chalinolobus tuberculatus). Calls were recorded from all three subspecies of short-tailed bat and seven populations of long-tailed bat, three in Northland, two in the central North Island, and two in the lower South Island. The calls were recorded in the field and digitised, then three spectral components and one temporal component of the calls were measured. Calls of the lesser short-tailed bat could be loosely classified into subspecies by means of multivariate discriminant function analysis. Similarly, long-tailed bat calls showed regional variation, and discriminant function analysis was able to fit calls to regional groups with a high rate of success. The significance of the results presented is discussed in terms of the conservation of New Zealand bats and the unique ecology of the lesser short-tailed bat.

scholarly journals Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

2000 ◽  
Vol 203 (17) ◽  
pp. 2641-2656 ◽  
Author(s):  
S. Parsons ◽  
G. Jones
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Curve Fitting ◽  
Function Analysis ◽  
Species Level ◽  
Correct Classification ◽  
Echolocation Calls ◽  
Artificial Neural

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

Factors Affecting Bank Risk-Taking: Evidence from Southeast Asian Countries

2016 ◽  
Vol 23 (2) ◽  
pp. 120-136
Author(s):  
NGUYEN THANH LIEM ◽  
TRAN HUNG SON ◽  
HOANG TRUNG NGHIA
Keyword(s):  
Risk Taking ◽  
Southeast Asian ◽  
Bank Risk ◽  
Asian Countries ◽  
Factors Affecting ◽  
Southeast Asian Countries

Transboundary Haze-Free for Southeast Asian Countries by 2020: A Delusional Vision?

2020 ◽  
Vol 24 (02) ◽  
pp. 1923-1929
Author(s):  
Nurhidayatuloh ◽  
Febrian ◽  
Mada Apriandi ◽  
Annalisa Y ◽  
Helena Primadianti Sulistyaningrum ◽  
...  
Keyword(s):  
Southeast Asian ◽  
Asian Countries ◽  
Southeast Asian Countries

scholarly journals How do Southeast Asian countries participate in the development of the Arctic

2021 ◽  
Vol 625 ◽  
pp. 012009
Author(s):  
E E Krasnozhenova ◽  
S V Kulik ◽  
T Chistalyova ◽  
K Yu Eidemiller ◽  
P L Karabushenko
Keyword(s):  
Southeast Asian ◽  
The Arctic ◽  
Asian Countries ◽  
Southeast Asian Countries
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