Representing a Large Region with Few Sites: The Quality Index Approach for Field Studies

Session: 42. - Multi-Watershed Nutrient Study: Establishing a Monitoring Network in Agricultural Regions

Madeline Rosamond, University of Waterloo, m.rosamond@gmail.com
Christopher Wellen, Ryerson University, christopher.wellen@ryerson.ca
Meguel Yousif, University of Windsor, Mayousif@edu.uwaterloo.ca
Georgina Kaltenecker, Ontario Ministry of the Environment and Climate Change, Georgina.Kaltenecker@ontario.ca
Janis Thomas, Ont. Ministry of Environment & Climate Change, janis.thomas@ontario.ca
Pamela Joosse, Agriculture and Agri-Food Canada, pamela.joosse@agr.gc.ca
Natalie Feisthauer, Agriculture and Agri-Food Canada, natalie.feisthauer@agr.gc.ca
William Taylor, Department of Biology, University of Waterloo, wdtaylor@uwaterloo.ca
Mohamed Mohamed, Ontario Ministry of the Environment and Climate Change, Mohamed.Mohamed2@ontario.ca

Abstract

The Multi-Watershed Nutrient Study (MWNS) attempts to understand relationships between land use, landscape, and stream nutrient cycling and export. It aims to represent southern Ontario (~110,000 km²) with only 11 small headwater sites. Clearly, selecting sites that represent the larger area well is important. We therefore designed a new, systematic, method of selecting study sites. We divided the larger region into subregions, which were characterized with relevant variables, and displayed in mathematical variable space. Potential study sites were also displayed this way, and selected to cover the range in variables present in the region. We assessed site coverage with the Quality Index, which prioritizes sites that are well-distributed (i.e. not clumped) in variable space. For the MWNS, we used variables representing agricultural nutrient sources and transport pathways from commonly-available geospatial datasets. We were able to cover the range of variables in the larger region and avoid similar sites. Lastly, we used a genetic algorithm to select 11 sites with the highest possible QI and compared these, post-hoc, to our sites. This approach reduces subjectivity in site selection, considers practical constraints and easily allows for site reselection if necessary. The computer code to reproduce our approach is freely available.

1. Keyword
nutrients

2. Keyword
water quality

3. Keyword
experimental design

4. Additional Keyword
monitoring