Hi, Simon.

I think technology can help hugely with collecting and processing data, especially processing and identifying records from huge volumes of data such as are collected by audio detections devices, e.g. for bird surveys, or imagery from camera traps. If a survey is well designed, the data collection devices and sensors can spend a lot longer in the field than humans can, so can therefore collect a lot more data over a longer period of time. Obviously, this generates an awful lot of data (especially in the case of acoustic monitoring!), so data management and the processing of potentially huge volumes of data becomes more challenging and costly, which is where some of the 'AI/ML' tools and services are useful - not only can they process or resample a lot of data compared to other methods, but they can be very good at automated pattern recognition. However, in order to ensure data can be trusted - both raw data and post-processing/derived data - it still requires "ground truthing". So, whilst technology now gives us a lot more opportunity, I don't think it diminishes the need for human involvement at all - it just adds tools to our toolkit so we can do a lot more, more efficiently. And it's likely that technology, especially with respect to data collection, will find 'edge cases' that ecological theory has not considered.

Hi, Isabelle. I'm afraid funding is not something I can help with and I am not sure where you would actually begin looking, given you are based on Rwanda. As with many projects in development, scale is usually important as respective funders are often most interested in larger scale projects that have undertaken baseline assessments of their starting condition and are supported by widely accredited methods for measuring the baseline and measuring and forecasting the changes that follow the project's restoration activities.