Passive Acoustic Monitoring (PAM) has emerged as a possible alternative to traditional field surveys, which are tedious, expensive, and often limited to a few sites. Although PAM eases collection of data, the sheer volume of data generated complicates the analysis process. Recently, researchers have simplified the analysis process by using soundscape-based machine learning models that can extract information such as species richness and occurrence from audio data. But most of these methods either fail to generalize to various landscapes and across anthropogenic gradients or have not been tested in such environments. Thus, for my first objective, I will develop soundscape-based methods to determine habitat quality across different tropical landscapes. I aim to collect audio data across different tropical habitats along a gradient of land use and test the performance of current soundscape-based models and build better generalizable models. Soundscape-based methods have also been able to track spatiotemporal avian biodiversity patterns in temperate climates at coarser timescales and infer species occurrence. Thus, for my second objective, I will test if we can use these methods to track avian spatiotemporal biodiversity patterns at finer timescales in tropical habitats, and if we can use soundscapes to predict presence of non-vocalizing species. I aim to collect fine scale audio data along with ground truthed bird species observations and test performance of these algorithms on the data. I also aim to build a model that can use soundscapes to predict the occurrence of non-vocalizing species. Studies have shown that insects are the most vocalizing species in tropical habitats, however, most studies don't focus on insect vocalizations. This can be attributed to the fact that building automated models for insect species identification using acoustic data is a challenging problem. Thus, for my third objective, I will use recent developments in the field of machine learning, such as transformers, to build acoustic identification models for insects and quantify insect biodiversity.