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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.


Mean Acoustic Complexity Index values (±standard error) for each month summarized over six sites in Glacier Bay, Alaska.
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ece32242-fig-0003: Mean Acoustic Complexity Index values (±standard error) for each month summarized over six sites in Glacier Bay, Alaska.

Mentions: We found the highest mean ACI at Bartlett Cove (0.56 ± 0.02) and at Point McLeod (0.60 ± 0.05). In Bartlett Cove, we found the highest mean ACI in 2014 (0.71 ± 0.03), and lowest in 2012 (0.59 ± 0.03). Among years and sites, we found that ACI values peaked from late spring (April) to summer (June; Fig. 3).


Using bioacoustics to examine shifts in songbird phenology
Mean Acoustic Complexity Index values (±standard error) for each month summarized over six sites in Glacier Bay, Alaska.
© Copyright Policy - creativeCommonsBy
Related In: Results  -  Collection

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

ece32242-fig-0003: Mean Acoustic Complexity Index values (±standard error) for each month summarized over six sites in Glacier Bay, Alaska.
Mentions: We found the highest mean ACI at Bartlett Cove (0.56 ± 0.02) and at Point McLeod (0.60 ± 0.05). In Bartlett Cove, we found the highest mean ACI in 2014 (0.71 ± 0.03), and lowest in 2012 (0.59 ± 0.03). Among years and sites, we found that ACI values peaked from late spring (April) to summer (June; Fig. 3).

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.