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| Funder | Natural Environment Research Council |
|---|---|
| Recipient Organization | Lancaster University |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Mar 30, 2028 |
| Duration | 1,277 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2929024 |
The world's rainforests are incredible reservoirs of biodiversity, holding over 60% of the world's animal species and 67% of all tree species. While this remarkable diversity makes them a biologist's paradise, it also makes them very difficult to study, and there are many fundamental knowledge gaps about how these ecosystems function across time and space.
Ecoacoustics is a rapidly growing discipline within ecology, and holds much promise for improving our understanding of ecosystems. Automated recording units and advances in analysis techniques such as machine learning and acoustic indices have vastly expanded how sound can be used to understand ecosystems. It is now possible to record in multiple locations at once, acquiring terabytes of sound data throughout both the day and night.
We are also on the cusp of exciting developments, recording sounds in the soils, improving our understanding of sounds made by invertebrates, and linking soundscapes to ecosystem functioning.
This project will combine new soil soundscape recordings and data collection with a huge library of sound and other ecological data collected over multiple NERC grants. The fieldwork will take place in the Brazilian Amazon, benefitting from established field sites coordinated by the supervisory team and a placement at a host institution in the heart of the Amazon basin.
The work is organised across three complementary work packages that (1) advance the nascent field of soil ecoacoustics, linking soil soundscapes with the abundance and composition of soil-dwelling fauna; (2) explore how above and below ground soundscapes are associated with measures of forest functioning; and (3) examine how the biogeography of soundscape complexity is predicted by forest structural complexity and large-scale drivers of biodiversity (climate, etc).
Lancaster University
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