title: Finding clean water habitats in urban landscapes: professional researcher vs citizen science approaches.
abstract: This study investigated patterns of nutrient pollution in waterbody types across Greater London. Nitrate and phosphate data were collected by both citizen scientists and professional ecologists and their results were compared. The professional survey comprised 495 randomly selected pond, lake, river, stream and ditch sites. Citizen science survey sites were self-selected and comprised 76 ponds, lakes, rivers and streams. At each site, nutrient concentrations were assessed using field chemistry kits to measure nitrate-N and phosphate-P. The professional and the citizen science datasets both showed that standing waterbodies had significantly lower average nutrient concentrations than running waters. In the professional datasets 46% of ponds and lakes had nutrient levels below the threshold at which biological impairment is likely, whereas only 3% of running waters were unimpaired by nutrients. The citizen science dataset showed the same broad pattern, but there was a trend towards selection of higher quality waterbodies with 77% standing waters and 14% of rivers and streams unimpaired. Waterbody nutrient levels in the professional dataset were broadly correlated with landuse intensity. Rivers and streams had a significantly higher proportion of urban and suburban land cover than other waterbody types. Ponds had higher percentage of semi-natural vegetation within their much smaller catchments. Relationships with land cover and water quality were less apparent in the citizen-collected dataset probably because the areas visited by citizens were less representative of the landscape as whole. The results suggest that standing waterbodies, especially ponds, may represent an important clean water resource within urban areas. Small waterbodies, including ponds, small lakes<50ha and ditches, are rarely part of the statutory water quality monitoring programmes and are frequently overlooked. Citizen scientist data have the potential to partly fill this gap if they are co-ordinated to reduce bias in the type and location of the waterbodies selected.
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Elaine
authors.initials: E
authors.lastname: McGoff
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Francesca
authors.initials: F
authors.lastname: Dunn
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Luis Moliner
authors.initials: LM
authors.lastname: Cachazo
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK. Electronic address: info@freshwaterhabitats.org.uk.
authors.forename: Penny
authors.initials: P
authors.lastname: Williams
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Biggs
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Pascale
authors.initials: P
authors.lastname: Nicolet
authors.affiliation: Freshwater Habitats Trust, Bury Knowle House, North Place, Headington, Oxford OX3 9HY, UK.
authors.forename: Naomi C
authors.initials: NC
authors.lastname: Ewald
mesh_terms: D002947:Cities; D003256:Community Participation; D003625:Data Collection / Q000379:methods*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D006801:Humans; D060106:Lakes; D008131:London; D045483:Rivers; D060753:Water Quality
keywords: Ditch; Lake; Nutrients; Pond; River; Stream