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Conclusions
The goal of the MAIA study was to demonstrate how a probabilistic sampling design could be used to develop monitoring protocols and assess surface waters at a regional scale. The purpose of this document was to distill the critical lessons from the Mid-Atlantic experience and present approaches and conclusions that will be relevant to states as they move forward with their own monitoring programs.
Although EMAP's objectives are to support states in their assessment of surface waters by developing survey design methods, biomonitoring tools, and biocriteria, these tools will not necessarily be adopted by states. The MAIA pilot was a demonstration; and states in the region are not obligated to adopt EMAP methods. Currently, monitoring and assessment under the Clean Water Act is each state's responsibility, although the USEPA may intervene if a state's program or reporting is inadequate. Whether states in the region of this pilot will adopt or adapt EMAP protocols is unclear. Nonetheless, the initial MAIA pilot study has metamorphosed into a larger collaborative effort that coordinates data and information across multiple agencies responsible for water resources in this region.
Whether or not the specific methods and protocols developed by EMAP are appropriate for state monitoring programs, the issues related to sampling design, data management, and the development of assessment tools are relevant to any emerging monitoring program. For sampling design, the primary issue relates to sample site selection. Resolution of this issue depends on a clear understanding of how the data will be used before they are collected (Ward et al., 1986). The way data are entered into the computer seems remote from data analysis and interpretation, but when data management issues are left unresolved, they can derail or corrupt any analysis.
For the MAIA study, objective criteria were used to establish links between human disturbance and biological response. To ensure that biological monitoring tools were both meaningful and reliable, they were evaluated for their correlation with independent measures of human disturbance and for their variability through time. Multimetric indexes developed for fish, invertebrates and diatoms showed a strong and consistent correlation with multiple aspects of human disturbance measured at a variety of spatial scales. For all biological indexes, the more integrative the measure of human disturbance, the higher the correlation. All three indexes were capable of detecting small changes in biological condition within a few years of sampling (2.5% or less per year). Both their strong correlation with disturbance and their statistical precision support multimetric indexes in their role as biological monitoring tools for protecting water resources within the legal framework of the Clean Water Act.
The size of the MAIA project created some of its own new challenges; hundreds
of people have been involved in creating the sampling design and collecting,
managing and analyzing the data. As state programs grow to meet the requirements
of the Clean Water Act, the scale of this project appears less daunting (Ransel,
1995; NRC 2001). In fact, many states already assess hundreds of sites each
year. Consequently, the process and outcomes of the MAIA pilot serve to highlight
persistent issues or sticking points that states will continue to grapple
with as they develop adequate biological monitoring programs (Yoder and Rankin,
1998).
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