6 Conclusions

Has new research utilized the strengths of new technologies or are we doing the same old stuff with more expensive data? There are formidable challenges to landscape riverine research but the field is evolving rapidly to meet the needs of both science and management. New technologies have enabled datasets beyond the dreams of most scientists even 30 years ago; but, we remain somewhat hindered by the size and novel nature of these data as well as by our inability to use traditional experimental methods for uncovering meaningful patterns in these data. Spatial data often contain many inter-correlated variables, all of which are potentially of interest, and the uncertainty of these data often has a spatial component that might vary from variable to variable. For example, pool depth might be more accurately measured in larger, wider river systems but hillslope might be more accurately quantified in steeper terrain. As our understanding of the accuracies and inaccuracies of spatial data evolves, we will be better able to utilize use the existing information. We also need to improve our ability to interpret and display spatial data in ways that communicate both accuracy and precision.

Have we incorporated key concepts from landscape ecology to improve our understanding of how landscapes affect rivers? The field of landscape ecology has played a large role in the development of landscape riverine research. The importance of pattern-process interrelationships, connectivity, scale, and fragmentation has guided the development of new work on landscapes and rivers. However, adaptation of these concepts to riverine systems remains a challenge. For example, connectivity in a terrestrial landscape mosaic is quite different from connectivity along a riverine network with unidirectional flow or across an active floodplain with multiple channels. We need to expand our thinking about aquatic connectivity. As another example, landscape riverine research will benefit from a broader exploration of the significance of scale to include spatial grain and temporal scale.

Have we been able to use landscape analyses to address management and policy needs? Large-scale analysis of riverine systems has been effective in a wide range of applications. It has been critical in the development of conservation networks and monitoring programs. It has improved our understanding and management of riparian areas in diverse ecosystems. It has led to the improved use of a wide variety of bio-assessment tools. Restoration and rehabilitation prioritization schemes have been enhanced. And lastly, it may be a useful tool for management in the face of climate change. The impact of landscape riverine research has been concentrated in highly developed nations where data and resources are available. As we envisage methods for collecting and combining data across global scales, there will be opportunities for this type of research to affect policies in less developed countries.

Opportunities in landscape-scale riverine research

• There is a need to develop tools for studying mechanistic rather than correlative relationships over large spatial extents. Multi-scale analyses, multi-basin studies, combined process and statistical models, and large-scale experiments can all be harnessed to develop and test generalized theories about how landscape features drive instream responses. Working over larger and larger extents and/or work that leverages long-term data sets may also enable us to increase our sample sizes and generalize results.
• Another opportunity is to shift our perceptions about anthropogenic impacts. First, we must more explicitly model the impacts of economic incentives, human behavior, and population growth patterns on ecological systems. Second, we can benefit from considering the spatio-temporal aspect of human impacts such as the correlation between human development, environmental gradients, and the legacies of past land uses.
• Finally, there are opportunities for a greater number of researchers to incorporate the new statistical tools being designed specifically for linking landscapes to rivers. Quantitative opportunities may also be as simple as defining both landscape and response metrics in novel ways that can more efficiently capture the social, physical, and ecological processes of interest.