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Articles

The influence of season and landscape on the water quality of ponds at multiple spatial scales

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Pages 477-487 | Received 28 Oct 2021, Accepted 06 May 2022, Published online: 26 Sep 2022
 

ABSTRACT

Understanding the spatial relationships between land use/land cover (LULC) and physicochemical water quality in pond ecosystems is vital to the conservation and management of ponds. This knowledge is especially critical to reconcile landscape planning and management, particularly in urban regions with rapid population growth. In this study we measured (1) seasonal differences in water quality and (2) the impact of the surrounding landscape at 4 spatial scales (10 m, 100 m, 500 m, and full catchment) on water quality of 50 ponds in the Auckland region, New Zealand. For each pond, 9 physicochemical water quality variables and 9 landscape properties (LULC and physical features of the ponds) were measured in winter and summer. We found significantly higher measures of conductivity, total dissolved solids, percentage of dissolved oxygen at saturation (%DO), pH, salinity, and phosphate concentrations in summer. By contrast, ammoniacal nitrogen concentration was higher in winter. These findings indicated impaired water quality during summer. Multiple linear regression and redundancy analyses showed that LULC and physical landscape features had different influences on the physicochemical variables across the different spatial scales and seasons. The landscape properties at all 4 spatial scales were good indicators of pond temperature and %DO only in summer. Overall, variations in pond water quality were explained better by general landscape characteristics than by LULC alone at the catchment and 500 m scale in winter and at the 100 m scale in summer. This study highlights the importance of including different spatial scales, seasons, and landscapes when quantifying land–water interactions.

Acknowledgements

We thank the landowners for permission to use their ponds for this study. The authors declare that no competing interests exist.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Funding was provided by the School of Natural and Computational Sciences, Massey University, New Zealand.

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