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Using bioacoustics to examine shifts in songbird phenology

View Article: PubMed Central - PubMed

ABSTRACT

 : Monitoring patterns in biodiversity and phenology have become increasingly important given accelerating levels of anthropogenic change. Long‐term monitoring programs have reported earlier occurrence of spring activity, reflecting species response to climate change. Although tracking shifts in spring migration represents a valuable approach to monitoring community‐level consequences of climate change, robust long‐term observations are challenging and costly. Audio recordings and metrics of bioacoustic activity could provide an effective method for monitoring changes in songbird activity and broader biotic interactions. We used 3 years of spring and fall recordings at six sites in Glacier Bay National Park, Alaska, an area experiencing rapid warming and glacial retreat, to examine the utility of bioacoustics to detect changes in songbird phenology. We calculated the Acoustic Complexity Index (ACI), an algorithm representing an index of bird community complexity. Abrupt changes in ACI values from winter to spring corresponded to spring transition, suggesting that ACI may be an effective, albeit coarse metric to detect the arrival of migrating songbirds. The first peak in ACI shifted from April 16 to April 11 from 2012 to 2014. Changes in ACI were less abrupt in the fall due to weather events, suggesting spring recordings are better suited to indicate phenology. To ensure changes in ACI values were detecting real changes in songbird activity, we explored the relationship between ACI and song of three species: varied thrush(Ixoreus naevius), Pacific wren (Troglodytes pacificus), and ruby‐crowned kinglet (Regulus calendula). ACI was positively related to counts of all species, but most markedly with song of the varied thrush, the most common species in our recordings and a known indicator of forest ecosystem health. We conclude that acoustic recordings paired with bioacoustic indices may be a useful method of monitoring shifts in songbird communities due to climate change and other sources of anthropogenic disturbance.

No MeSH data available.


Hourly median dBA values of broadband (12.5–20 kHz) sound pressure levels (median sound pressure level = L50) for (A) all data collected in spring (March/April) 2012–2014 at Bartlett Cove and (B) all data collected in fall (September) 2011 at 5 other recording sites in Glacier Bay. Dashed line represents mean monthly sunrise, and shaded areas represent standard deviation.
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ece32242-fig-0002: Hourly median dBA values of broadband (12.5–20 kHz) sound pressure levels (median sound pressure level = L50) for (A) all data collected in spring (March/April) 2012–2014 at Bartlett Cove and (B) all data collected in fall (September) 2011 at 5 other recording sites in Glacier Bay. Dashed line represents mean monthly sunrise, and shaded areas represent standard deviation.

Mentions: All audio data were collected in mp3 format at a sampling rate of 44.1 kHz. The audio data were then converted to calibrated 1‐sec 1/3 octave band sound pressure level (SPL) measurements from 12.5–6300 Hz (Mennitt and Fristrup 2012). To explore variation in sound levels among sites and years, we used hourly median levels of broadband A‐weighted SPLs (L50) calculated over the entire frequency range across all recording days. Broadband median sound levels represent an average background level including all sources. Because we were interested in sound associated with songbirds, we looked for any peaks in L50 around dawn, potentially associated with the dawn chorus. At all sites, we observed relatively high L50 values within 1 hr of sunrise (Fig. 2); thus, we limited further acoustic index analysis to 0.5 h before and 2.5 h after local sunrise. Sunrise times were calculated from the US Navy Astronomical Applications Department database (http://aa.usno.navy.mil/data/docs/RS_OneYear.php).


Using bioacoustics to examine shifts in songbird phenology
Hourly median dBA values of broadband (12.5–20 kHz) sound pressure levels (median sound pressure level = L50) for (A) all data collected in spring (March/April) 2012–2014 at Bartlett Cove and (B) all data collected in fall (September) 2011 at 5 other recording sites in Glacier Bay. Dashed line represents mean monthly sunrise, and shaded areas represent standard deviation.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4979700&req=5

ece32242-fig-0002: Hourly median dBA values of broadband (12.5–20 kHz) sound pressure levels (median sound pressure level = L50) for (A) all data collected in spring (March/April) 2012–2014 at Bartlett Cove and (B) all data collected in fall (September) 2011 at 5 other recording sites in Glacier Bay. Dashed line represents mean monthly sunrise, and shaded areas represent standard deviation.
Mentions: All audio data were collected in mp3 format at a sampling rate of 44.1 kHz. The audio data were then converted to calibrated 1‐sec 1/3 octave band sound pressure level (SPL) measurements from 12.5–6300 Hz (Mennitt and Fristrup 2012). To explore variation in sound levels among sites and years, we used hourly median levels of broadband A‐weighted SPLs (L50) calculated over the entire frequency range across all recording days. Broadband median sound levels represent an average background level including all sources. Because we were interested in sound associated with songbirds, we looked for any peaks in L50 around dawn, potentially associated with the dawn chorus. At all sites, we observed relatively high L50 values within 1 hr of sunrise (Fig. 2); thus, we limited further acoustic index analysis to 0.5 h before and 2.5 h after local sunrise. Sunrise times were calculated from the US Navy Astronomical Applications Department database (http://aa.usno.navy.mil/data/docs/RS_OneYear.php).

View Article: PubMed Central - PubMed

ABSTRACT

 : Monitoring patterns in biodiversity and phenology have become increasingly important given accelerating levels of anthropogenic change. Long‐term monitoring programs have reported earlier occurrence of spring activity, reflecting species response to climate change. Although tracking shifts in spring migration represents a valuable approach to monitoring community‐level consequences of climate change, robust long‐term observations are challenging and costly. Audio recordings and metrics of bioacoustic activity could provide an effective method for monitoring changes in songbird activity and broader biotic interactions. We used 3 years of spring and fall recordings at six sites in Glacier Bay National Park, Alaska, an area experiencing rapid warming and glacial retreat, to examine the utility of bioacoustics to detect changes in songbird phenology. We calculated the Acoustic Complexity Index (ACI), an algorithm representing an index of bird community complexity. Abrupt changes in ACI values from winter to spring corresponded to spring transition, suggesting that ACI may be an effective, albeit coarse metric to detect the arrival of migrating songbirds. The first peak in ACI shifted from April 16 to April 11 from 2012 to 2014. Changes in ACI were less abrupt in the fall due to weather events, suggesting spring recordings are better suited to indicate phenology. To ensure changes in ACI values were detecting real changes in songbird activity, we explored the relationship between ACI and song of three species: varied thrush(Ixoreus naevius), Pacific wren (Troglodytes pacificus), and ruby‐crowned kinglet (Regulus calendula). ACI was positively related to counts of all species, but most markedly with song of the varied thrush, the most common species in our recordings and a known indicator of forest ecosystem health. We conclude that acoustic recordings paired with bioacoustic indices may be a useful method of monitoring shifts in songbird communities due to climate change and other sources of anthropogenic disturbance.

No MeSH data available.