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Project properties |
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| Title | FIELDWORK BRAZIL: Eco-accoustics for nature-positive food production |
| Group | Behavioural Ecology |
| Project type | thesis |
| Credits | 36-39 |
| Supervisor(s) | Filipe Cunha, Lysanne Snijders |
| Examiner(s) | Filipe Cunha, Lysanne Snijders, Marc Naguib |
| Contact info | Cunha, Filipe filipe.cunha@wur.nl; Asst. Prof. Dr. Snijders, Lysanne lysanne.snijders@wur.nl |
| Begin date | 2023/10/01 |
| End date | 2024/07/01 |
| Description | The current project ‘Eco-accoustics for nature-positive food production’ is open for up to two MSc students at the moment. The project involves field work in Brazil with automated recorders of bird song at agricultural fields. In this project, students will examine whether species-specific and/or biodiversity indices extracted from passive acoustic recordings are predictive of pest abundance, damage and yield. This project will be building upon three earlier MSc theses (from spring 2023) Additional own research questions are welcome!
Applications from bird enthusiasts with affinity for (automated) acoustic analysis are highly encouraged. Project Description - Eco-acoustics for nature-positive food production While ecological farming aims for sustainable production with the least impact on the environment, a natural consequence of that is the presence of pests. A lack of biodiversity in the natural prey of the pests leads to significant farm losses and even chemical interventions. A bio-positive food production system requires a balanced interplay of pest and prey, for a successful production system. However, quantifying the impact of a bio-diverse ecosystem on pest management and farm production is a major challenge in ecological farming systems. The main issue being on the measurement of biodiversity. It is often too time-consuming, too expensive, or both. In the last decade, automated eco-acoustic surveying has emerged as relevant technology for large-scale monitoring of natural as well as urban habitats. Acoustic recording devices facilitate environment monitoring over lengthy temporal and spatial scales, making acoustic monitoring a relatively economically accessible method compared to traditional surveying and bio-diversity monitoring approaches. The automatization of such systems would yield continuous and inexpensive data, allowing actions to be adjusted on a micro-temporal scale. For that matter machine learning, including deep learning, is being increasingly applied to acoustic data, to automatically identify a range of sounds, from different bird species, to amphibians, grasshoppers and humans. To make the task of measuring biodiversity in farming systems swifter and more tangible from a producer perspective, we will use eco-acoustic monitoring as a tool to quantify the impact of a bio-diverse ecosystem on pest management, and finally on-farm production, in ecological farming systems. A biodiverse farming ecosystem must include natural counter-balances against such pests and producers must be able to access this measurement to be able to include it in the production process. A direct intended impact of this project is to design automated systems for acoustic biodiversity monitoring and connect that to farm yield. The aim is to quantify the benefits of a balanced bio-positive system against an imbalanced one. More info on the larger project: http://www.behaviouralecology.nl/ecoacoustics |
| Used skills | Experimental design, fieldwork, acoustic analysis, bird identification |
| Requirements | Affinity/skill for birds and bird song in the Netherlands. Affinity/skill in acoustic data analysis |