To evaluate the potential development of a macroinvertebrate Index of Biotic Integrity (IBI) for Prairie Pothole Region wetlands, we sampled the aquatic macroinvertebrate and fish communities in 24 semipermanent wetlands located throughout central North Dakota. Wetland basins were selected to encompass a range of surrounding land-use, ranging from 100% grassland to 100% cropland. We used redundancy analysis (RDA) to identify the influences of fish, and temporal and spatial variation on the macroinvertebrate community. We also used RDA to look for relationships between wetland macroinvertebrate communities and land-use. Seventeen potential invertebrate metrics were tested by graphical analyses. We identified a strong influence on the macroinvertebrate community due to the presence of fish. A number of invertebrate taxa decreased in abundance as the summer progressed, and there was noticeable variation in the invertebrate community among individual wetlands of the region. However, we detected no strong relationships between the varying degrees of agricultural land-use in the wetland catchments and the invertebrate community. Consequently, we were unable to identify any effective IBI metrics indicative of land-use disturbance. Lack of correspondence between land-use and macroinvertebrates in this habitat is most likely due to a high degree of natural disturbance (e.g., presence of fish, temporal changes) and a low diversity community of resilient taxa in Prairie Pothole Region wetlands.
How to translate text using browser tools
1 March 2003
WEAK CORRESPONDENCE BETWEEN MACROINVERTEBRATE ASSEMBLAGES AND LAND USE IN PRAIRIE POTHOLE REGION WETLANDS, USA
Brian A. Tangen,
Malcolm G. Butler,
Michael J. Ell
ACCESS THE FULL ARTICLE
It is not available for individual sale.
This article is only available to subscribers.
It is not available for individual sale.
It is not available for individual sale.
Wetlands
Vol. 23 • No. 1
March 2003
Vol. 23 • No. 1
March 2003
agricultural land-use
bioassessment
Index of Biotic Integrity (IBI)
metrics
redundancy analysis
variance partitioning