Gradients of marine biodiversity and linkages with eDNA across the Wallacea Region The interdependencies among organisms in ecological systems govern ecological function, responses to ecosystem change and the provision of ecosystem services. Complex multi-species interactions form ecological networks that increase community stability, where it is known that higher diversity promotes dynamic stability and counters pressures on the ecosystem. Understanding these ecological networks and dynamics in response to multiple chronic and acute environmental disturbances is key to designing conservation interventions, but network dynamics remain largely unknown in tropical marine systems.   The Wallacea region is not only the epicenter of global coral reef diversity, it's coral reefs are also the most important source of food and income for millions of people. The region is globally important for sustaining globally threatened reef biodiversity, because it is one among few reefs that have not yet experienced large-scale degradation due to climate stress events. However, the regions' reefs are greatly transformed by local stressors, most notably terrestrial derived sediment run-off and fisheries overexploitation. Management to mitigate these local stressors is underway, but is severely hampered by a pervasive lack of data and understanding how these stressors affect biodiversity and its interactions throughout the region. Given the limited local resources, time, and expertise, presently the lack of information to inform management will not be overcome for most reefs across Wallacea.   This project addresses three aims, which require addressing to overcome these challenges. Firstly, we will employ traditional visual observation techniques for reef corals, macro-invertebrates and fishes to determine how ecological networks differ between largely unimpacted, sedimented or reduced water quality, and fished sites. Ecological networks will be quantified based on field data using novel/cutting edge ecological modelling approaches and network theory. This aim focuses on easily observable non-cryptic taxa initially, and will form the basis of our comparative assessment of eDNA which has great potential but remains unvalidated in coral reef systems. Our second aim will validate eDNA's utility in describing reef biodiversity dynamics and test for the first time how networks constructed from eDNA compare to those from ecological surveys. Outcomes will provide unique insights and the potential for a step change in reef monitoring approaches by expanding opportunities to intensify spatial and temporal sampling, alongside providing confidence limits associated with ecological networks and their metrics that have been constructed using these novel eDNA data. Finally, having assessed the application of eDNA techniques, we plan to map the coral reef biodiversity of Wallacea with extensive eDNA sampling from remote regions. We will expand eDNA sampling to 10 further sites within Wallacea to provide novel data at unprecedented spatial and ecological complexity scales, enabling us to model and predict change in response to anthropogenic pressures at scales most relevant to Indonesian marine spatial planning.   Despite high functional redundancy in the mega-diverse coral reef ecosystems, the loss of species will shift community composition and functionality with wide-ranging ecological, social and economic implications. For conservation efforts in complex systems where cryptic species are under-sampled but play important functional roles, there is a real-world need to know true biodiversity and network interactions. We will develop and test novel approaches to tackle this challenge to inform sustainable development in the face of the coral reef crisis. The response dynamics in ecological networks inform community robustness and this information is key to management decision making. The Newton Fund builds research and innovation partnerships with developing countries across the world to promote the economic development and social welfare of the partner countries.