RESUMEN
The Clean Water Act presents a daunting task for states by requiring them to assess and restore all their waters. Traditional monitoring has led to two beliefs: (1) ad hoc sampling (i.e., non-random) is adequate if enough sites are sampled and (2) more intensive sampling (e.g., collecting more organisms) at each site is always better. We analyzed the 1,500 Maryland Biological Stream Survey (MBSS) random sites sampled in 2000-2004 to describe the variability of Index of Biotic Integrity (IBI) scores at the site, reach, and watershed scales. Average variability for fish and benthic IBI scores increased with increasing spatial scale, demonstrating that single site IBI scores are not representative at watershed scales and therefore at best 25% of a state's stream length can be representatively sampled with non-random designs. We evaluated the effects on total taxa captured and IBI precision of sampling for twice as many benthic macroinvertebrates at 73 MBSS sites with replicate samples. When sampling costs were fixed, the precision of the IBI decreased as the number of sites had to be reduced by 15%. Only 1% more taxa were found overall when the 73 sites where combined. We concluded that (1) comprehensive assessment of a state's waters should be done using probability-based sampling that allows the condition across all reaches to be inferred statistically and (2) additional site sampling effort should not be incorporated into state biomonitoring when it will reduce the number of sites sampled to the point where overall assessment precision is lower.
Asunto(s)
Recolección de Datos/métodos , Monitoreo del Ambiente , Agua Dulce , Probabilidad , Abastecimiento de Agua , Animales , Conservación de los Recursos Naturales/métodos , Ambiente , Monitoreo del Ambiente/métodos , Monitoreo del Ambiente/estadística & datos numéricos , MarylandRESUMEN
In this report, predictions of the species that were expected to occur at stream sites were generated and probable stressors to fish species that were predicted to occur but were absent were diagnosed. Predictions were generated based on the hierarchical screening method of Smith and Powell (1971, Am. Mus. Novit. 2458, 1-30), using fish abundance in conjunction with 25 environmental variables at 895 sites. The sites were sampled throughout Maryland and represent the entire range of environmental quality from severely degraded to minimally degraded. Stressor variable values that exceeded tolerance thresholds for species that were expected to occur, but were absent, were considered to be probable stressors. This method was tested for efficacy in stream site assessments and stressor diagnosis using an independent data set. Sites that were classified as degraded according to the IBI and to non-biological criteria had fewer predicted species present compared to minimally influenced sites, indicating that the proportion of predicted species present accurately represents the biological integrity of a stream site. The nine stressors that were applied to the test data set accounted for species absences in 43.7% of degraded sites. Impervious land cover was the most common stressor identified. In addition to assessing stream biological integrity and identifying stressors to fish species, this approach also provides tolerance thresholds for predicted fish species that are useful endpoints necessary to plan effective restoration of fish species in Maryland.