9781934874561-ch2

Advances in Understanding Landscape Influences on Freshwater Habitats and Biological Assemblages

Strengths and Weaknesses of Data Sources for Describing Exposure of Aquatic Ecosystems to Human Activity

Adam G. Yates, Joseph M. Culp, Robert C. Bailey, and Patricia A. Chambers

doi: https://doi.org/10.47886/9781934874561.ch2

Abstract.—Over the past decade, numerous studies have identified correlative relationships between aquatic biota and human activities at landscape scales. In addition to demonstrating the pervasive effects of these activities on aquatic biota, these findings have encouraged researchers to suggest that predictive relationships between human activities and aquatic biota could be used to enhance diagnostic power of biological assessments, predict future changes in species distributions, and inform land-use planning. However, to achieve these important goals, descriptions of human activities will need to become more detailed than the simple land use/land cover classifications frequently used. Our purpose is to highlight four sources of human activity data (existing geographic information system layers, census data, remotely sensed images, and visual landscape surveys) that can be used to increase the level of detail with which the human environment is described. Strengths and weaknesses of each data source are discussed and methods for adapting those data to aquatic studies are described by drawing on experiences from studies in the agricultural landscapes of southern Manitoba and southwestern Ontario, Canada. Based on the observations and lessons learned from our previous experiences, we make recommendations for how researchers can identify and apply the data sources that best meet their needs. We also discuss challenges and possible solutions for applying the described data sources as well as for improving data availability in the future. Moreover, we encourage aquatic researchers to allot more time to detailed description of human activities because we believe this to be an effective approach to improving our ability to predict the effects of human activity and thus better assist decision makers in protecting aquatic ecosystems.