Seasonal predictability of benthic macroinvertebrate metrics and community structure with maturity-weighted abundances in a Missouri Ozark stream, USA

摘要

Benthic macroinvertebrates in lotic habitats are influenced by a wide range of physical and chemical environmental factors that change over a temporal continuum. Within a year, different species can occupy the same space at different points in time. Thus, the community structure itself is in flux from season to season. This study analyzed the structure of a riffle macroinvertebrate community in a single stream from a series of monthly samples over a year cycle. The goals of this study were to: (1) identify community measures that were least variable over the continuum and predict them in test samples from the next year; (2) explore the usefulness of maturity data in analyzing community structure; (3) construct a temporal River Invertebrate Prediction and Classification System like (RIVPACS-like) model that classifies seasons based on biota and predicts an expected community for any season. From a set of 120 metrics, nine metrics representing 5 measurement categories displaying low variability over the annual continuum were selected for multiple regression analysis. The Biotic Index was fairly predictable between years, regardless of season, whereas other measures were less so. Metrics with standard abundances compared to their maturity-weighted analogues revealed that measures based on finer taxonomic resolution or functional groups were more likely to differ. Three biologically determined seasons were identified from cluster analysis during the process of creating a multivariate predictive model. Temporal environmental variables were used to determine test date group membership and comparisons of expected to observed communities revealed that 1 of 3 test dates was predicted well by the model. Our results demonstrate that macroinvertebrate community structures can express high variability over a short period of time and this phenomenon deserves more understanding with regard to interpreting biological assessment results.