Quantifying relationships between land-use gradients and structural and functional indicators of stream ecological integrity
Article first published online: 29 SEP 2011
© 2011 Blackwell Publishing Ltd
Volume 57, Issue 1, pages 74–90, January 2012
How to Cite
CLAPCOTT, J. E., COLLIER, K. J., DEATH, R. G., GOODWIN, E. O., HARDING, J. S., KELLY, D., LEATHWICK, J. R. and YOUNG, R. G. (2012), Quantifying relationships between land-use gradients and structural and functional indicators of stream ecological integrity. Freshwater Biology, 57: 74–90. doi: 10.1111/j.1365-2427.2011.02696.x
- Issue published online: 29 NOV 2011
- Article first published online: 29 SEP 2011
- (Manuscript accepted 1 September 2011)
- boosted regression;
- ecological response curves;
- ecosystem processes;
- stream health;
1. Modification of natural landscapes and land-use intensification are global phenomena that can result in a range of differing pressures on lotic ecosystems. We analysed national-scale databases to quantify the relationship between three land uses (indigenous vegetation, urbanisation and agriculture) and indicators of stream ecological integrity. Boosted regression tree modelling was used to test the response of 14 indicators belonging to four groups – water quality (at 578 sites), benthic invertebrates (at 2666 sites), fish (at 6858 sites) and ecosystem processes (at 156 sites). Our aims were to characterise the ecological response curves of selected functional and structural metrics in relation to three land uses, examine the environmental moderators of these relationships and quantify the relative utility of metrics as indicators of stream ecological integrity.
2. The strongest indicators of land-use effects were nitrate + nitrite, delta-15 nitrogen value (δ15N) of primary consumers and the Macroinvertebrate Community Index (a biotic index of organic pollution), while the weakest overall indicators were gross primary productivity, benthic invertebrate richness and fish richness. All indicators declined in response to removal of indigenous vegetation and urbanisation, while variable responses to agricultural intensity were observed for some indicators.
3. The response curves for several indicators suggested distinct thresholds in response to urbanisation and agriculture, specifically at 10% impervious cover and at 0.1 g m−3 nitrogen concentration, respectively.
4. Water quality and ecosystem process indicators were influenced by a combination of temperature, slope and flow variables, whereas for macroinvertebrate indicators, catchment rainfall, segment slope and temperature were significant environmental predictor variables. Downstream variables (e.g. distance to the coast) were significant in explaining residual variation in fish indicators, not surprisingly given the preponderance of diadromous fish species in New Zealand waterways. The inclusion of continuous environmental variables used to develop a stream typology improved model performance more than the inclusion of stream type alone.
5. Our results reaffirm the importance of accounting for underlying spatial variation in the environment when quantifying relationships between land use and the ecological integrity of streams. Of distinctive interest, however, were the contrasting and complementary responses of different indicators of stream integrity to land use, suggesting that multiple indicators are required to identify land-use impact thresholds, develop environmental standards and assign ecological scores for reporting purposes.