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http://hdl.handle.net/1893/31214
Appears in Collections: | Biological and Environmental Sciences eTheses |
Title: | Avian communities and ecoacoustics in a tropical human-modified landscape |
Author(s): | Bradfer-Lawrence, Tom |
Supervisor(s): | Dent, Daisy Bunnefeld, Nils Willis, Steve |
Keywords: | Birds Tropical Human-modified landscape Community ecology Acoustics Wildlife monitoring Soundscape Remote sensing |
Issue Date: | Dec-2019 |
Publisher: | University of Stirling |
Citation: | Tom Bradfer-Lawrence, Nick Gardner, Lynsey Bunnefeld, Nils Bunnefeld, Stephen G. Willis, Daisy H. Dent (2019). Guidelines for the use of acoustic indices in environmental research. Methods in Ecology and Evolution, 10, 1796 – 1807 Tom Bradfer-Lawrence, Nils Bunnefeld, Nick Gardner, Stephen G. Willis, Daisy H. Dent (2020). Rapid assessment of avian species richness and abundance using acoustic indices, Ecological Indicators, 115, 106400 |
Abstract: | Large areas of the tropics have been cleared of forest and converted to agriculture. The consequent human-modified landscapes (HMLs) comprise a heterogenous mix of habitats; forest fragments and riparian strips are embedded in a matrix of cattle pasture, non-native timber plantations, and urban centres. These habitat changes can have dramatic consequences for wildlife, leading to range shifts and extirpations. In turn, this can influence the integrity of ecosystem services such as frugivory and seed dispersal. Understanding how habitat conversion affects natural ecosystems is critical to inform conservation interventions, but requires long-term biodiversity monitoring and detailed knowledge of species-level responses to HMLs. The research presented in this thesis was conducted in the Emparador HML, in central Republic of Panama. In Chapter 2, we show that the regional avian community is shaped by extent of forest cover across the landscape, and to a lesser degree, extent of forest fragmentation and distance to core forest. Effects of forest cover and fragmentation were examined at local (10 ha) and landscape (500 ha) scales. Species-level responses to these factors varied widely; while abundance of many species increased with greater local-scale forest cover, greater landscape-scale forest cover was often associated with declines. Generalist species that readily persist in HMLs still responded positively to local-scale forest cover, suggesting that even smaller forest fragments in these landscapes are important for maintaining diverse avian assemblages. Critically, we found that species’ responses were not associated with particular traits such as dietary composition or forest dependence, highlighting that species may often exhibit idiosyncratic responses to landscape structure. Chapters 3 and 4 address the wider issue of long-term monitoring, and the potential for data collection over large spatiotemporal scales using remote audio recorders. Ecoacoustics, the study of environmental sound is a relatively new discipline, and as such there is still considerable uncertainty surrounding best-practice for collecting and processing recordings. One of the most straightforward means of utilising audio recordings for environmental monitoring is via acoustic indices. These are objective measures of sound based on features such as pitch and amplitude. To date, attempts to use these indices have been hindered by inconsistent or inappropriate methodologies. In Chapter 3, we determine how many recordings are required to comprehensively capture a soundscape, the acoustic energy of a location. Furthermore, we demonstrate that there are habitat-specific patterns in acoustic indices values, suggesting that these indices reflect differences in vegetation structure and wildlife. We develop this further in Chapter 4, where we show that avian species richness and abundance are clearly linked to patterns in acoustic indices values. Critically, these patterns were coherent among habitat types emphasising their potential for monitoring. Acoustic indices sensitive to the frequencies occupied by bird song have the greatest potential for monitoring an avian community. The results from these two chapters suggest that acoustic indices can be effective tools for monitoring biodiversity, with values reflecting consistent differences across habitats, and among avian assemblages. Audio recordings are a source of permanent, verifiable evidence that can be collected at much greater spatiotemporal scales than traditional biodiversity monitoring data. As the use of audio recorders grows, it is important to compare their efficacy with standard methods of data collection. In Chapter 5, we contrast data derived from audio recordings with that gathered using standard point count methods, and consider whether recorders are a feasible means of surveying antbirds (Thamnophilidae), a disturbance-sensitive avian taxon. Both approaches revealed species’ responses to landscape structure, with qualitatively similar patterns in response to forest cover and vegetation quality. We show that common species can be readily monitored using audio recorders, with greater levels of detectability compared with point counts. However, rarer species were more likely to be detected using point counts. The work presented in this thesis helps to explain the patterns seen in avian responses to Neotropical HMLs. In particular we emphasise the importance of forest cover for maintaining bird assemblages in these landscapes. We demonstrate the utility of audio recorders for data collection, and highlight their potential for future biodiversity monitoring. In the face of human population growth, and ongoing habitat disturbance and agricultural intensification, conservation efforts are essential to avoid widespread species extinctions and ecosystem collapse. Interventions must take place in HMLs, to bolster ecosystem services, provide buffer zones for protected areas, and improve connectivity in the wider landscape. |
Type: | Thesis or Dissertation |
URI: | http://hdl.handle.net/1893/31214 |
Files in This Item:
File | Description | Size | Format | |
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TBL thesis text FINAL.pdf | 22.32 MB | Adobe PDF | View/Open |
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