Skip to content. | Skip to navigation

Personal tools

 

 

 

 
     

 

 

 

 

 

 

 

 

 

 

 

 

You are here: Home / PDFs on demand / Bibliographical References of PDFs on demand / The use of automated identification of bat echolocation calls in acoustic monitoring: A cautionary note for a sound analysis

Danilo Russo and Christian Voigt (2016)

The use of automated identification of bat echolocation calls in acoustic monitoring: A cautionary note for a sound analysis

Ecological Indicators, 66:598-602.

Bats are a species-rich order of mammals providing key ecosystem services. Because bats are threatened by human action and also serve as important bioindicators, monitoring their populations is of utmost importance. However, surveying bats is difficult because of their nocturnal habits, elusiveness and sensitivity to disturbance. Bat detectors allow echolocating bats to be surveyed non-invasively and record species that would otherwise be difficult to observe by capture or roost inspection. Unfortunately, several bat species cannot be identified confidently from their calls so acoustic classification remains ambiguous or impossible in some cases. The popularity of automated classifiers of bat echolocation calls has escalated rapidly, including that of several packages available on purchase. Such products have filled a vacant niche on the market mostly in relation to the expanding monitoring efforts related to the development of wind energy production worldwide. We highlight that no classifier has yet proven capable of providing correct classifications in 100\% of cases or getting close enough to this ideal performance. Besides, from the literature available and our own experience we argue that such tools have not yet been tested sufficiently in the field. Visual inspection of calls whose automated classification is judged suspicious is often recommended, but human intervention a posteriori represents a circular argument and requires noticeable experience. We are concerned that neophytes - including consultants with little experience with bats but specialized into other taxonomical groups - will accept passively automated responses of tools still awaiting sufficient validation. We remark that bat call identification is a serious practical issue because biases in the assessment of bat distribution or habitat preferences may lead to wrong management decisions with serious conservation consequences. Automated classifiers may crucially aid bat research and certainly merit further investigations but the boost in commercially available software may have come too early. Thorough field tests need to be carried out to assess limitations and strengths of these tools. (C) 2016 Elsevier Ltd. All rights reserved.

Misclassification, Environmental impact assessment, signatures, Ecological consultants, artificial neural-networks, classification, Windfarms, Biosonar, bioindicators, chiroptera, field identification, Call library, vespertilionidae, time-expanded recordings, recognition, plasticity
WOS:000388912300062
Year

1875 1876 1877 1878 1879
1880 1881 1882 1883 1884
1885 1886 1887 1888 1889
1890 1891 1892 1893 1894
1895 1896 1897 1898 1899

1900 1901 1902 1903 1904
1905 1906 1907 1908 1909
1910 1911 1912 1913 1914
1915 1916 1917 1918 1919
1920 1921 1922 1923 1924

1925 1926 1927 1928 1929
1930 1931 1932 1933 1934
1935 1936 1937 1938 1939
1940 1941 1942 1943 1944
1945 1946 1947 1948 1949

1950 1951 1952 1953 1954
1955 1956 1957 1958 1959
1960 1961 1962 1963 1964
1965 1966 1967 1968 1969
1970 1971 1972 1973 1974

1975 1976 1977 1978 1979
1980 1981 1982 1983 1984
1985 1986 1987 1988 1989
1990 1991 1992 1993 1994
1995 1996 1997 1998 1999

2000 2001 2002 2003 2004
2005 2006 2007 2008 2009
2010 2011 2012 2013 2014
2015 2016 2017 2018 2019
2020 2021 2022 2023 2024

 
e-ressources

 

PDFs on demand
 

 

 

RBINS private PDFs