Floodplains are highly productive and biodiverse ecosystems, and they provide many environmental services. Despite their importance, floodplains are under increasing pressure from human development and climate change. Worldwide, floodplains have witnessed those pressures translating into impacts that ultimately cause altered connectivity and impaired primary and secondary production. River floodplains in northern Australia are relatively intact compared to their counterparts in Australia, and play an important role in sustaining aquatic food webs. However, significant interest in agricultural expansion is being considered in northern Australia and the proposed intensive land and water resource development creates ecological concerns. The ecological functioning of those ecosystems relies on landscape connectivity and primary productivity. However, despite the importance of floodplain wetlands and the threats they face, a lack of information on those processes is apparent. The objective of this thesis is to develop a framework that accounts for primary production and connectivity in order to (a) inform river managers when identifying where to focus management and conservation efforts and (b) inform decision-makers in order to prioritise investment plans. Using the Mitchell River floodplain as a study area, I integrated field work, statistical models, remote sensing and graph theory to estimate rates of algal production and their statistical relationship to environmental features (Chapter 2); upscale those relationships across the landscape to identify hotspots of algal productivity (Chapter 3); and analyse connectivity across the Mitchell River floodplain and how water resources development can impact algal productivity and landscape connectivity (Chapter 4). The reason for focusing on algal production, especially epiphytic algae growing on aquatic macrophytes, is that this has been shown to be the major basal food resource for fish and other aquatic consumers in these river-floodplain systems, even though they represent a small fraction of the total primary productivity biomass. To address the first goal, I identified the environmental features that could be used to predict algal productivity and built a statistical model to measure the relationships between those environmental features and algal primary productivity. The observed data were obtained during field work, where I performed experiments to quantify the rates of algal production and measured physical, chemical and biological environmental features across a range of different wetland types and habitats in the Mitchell River floodplain. This analysis showed that turbidity and habitat type (as presence and type of aquatic vascular plants) are important predictors of algal productivity. This methodology demonstrated that the use of those predictors can provide an important tool for predicting algal productivity across the floodplain. To tackle the second goal, I adapted the statistical relationships found in the first chapter to predict algal productivity across larger spatial scales. I then predicted the rates of algal production across the Mitchell River floodplain and identified ‘hotspots’ (= areas of high algal productivity) by using spectral indices and bands from Landsat 8 remotely sensed images. The results of the study suggest that habitats with high algal productivity are located across the floodplain, in ephemeral river channels and wetlands, highlighting the importance of wetland habitats for ecosystem functioning. Further, this study identified an effective and transferrable methodology for mapping algal productivity at large spatial scales. In the final stage of the research, I developed a framework to understand the implications of hydrological connectivity on the availability of algal food resources in floodplain river ecosystems. Wetland habitats may support areas of high algal production in the riverine-floodplain ecosystem; however, they need to be accessible to mobile higher consumers in order to contribute to secondary production. I first combined the spatial variation of algal productivity (Chapter 3) with modelled scenarios of floodplain inundation using a graph theoretic approach to measure landscape connectivity. I then used this to predict how water resource development scenarios would impact connectivity and algal productivity. From these analyses, I estimated how much algal production would be lost as a result of changes to hydrology and landscape fragmentation. These results showed that water resources development can limit the inundation extent and impair connectivity, hence reducing the input of algal productivity to river–floodplain food webs. The results of the current research contribute to the fields of remote sensing, ecology and ecosystem management. Collectively the research provides an innovative body of research by combining field data and experiments with satellite-derived data and landscape modelling. The approach to quantifying and localising the sources of algal productivity across the landscape can be integrated into landscape graph theoretic methods to evaluate the impact of water resource development. This methodology, by identifying areas of high ecological value that may be sensitive to development, provides information for decisionmakers and river managers that will help to prioritise important regions based on those ecological assets that are often not considered. This study represents an important step forward because it combines spatial dynamics of primary productivity and connectivity into a comprehensive framework that can offer more ecologically meaningful protection to floodplains wetlands. The Mitchell River floodplain ecosystem provides a valuable case study in a relatively data rich environment, however, this approach could also be adapted for use in other riverine and floodplains ecosystems worldwide to improve future conservation planning and management globally.