Indicators of Riparian Wetland Health and Restoration Capability on the White Mountain Apache ReservationEPA Grant Number: U915717
Title: Indicators of Riparian Wetland Health and Restoration Capability on the White Mountain Apache Reservation
Investigators: Long, Jonathan W.
Institution: Northern Arizona University
EPA Project Officer: Jones, Brandon
Project Period: August 1, 2000 through August 1, 2002
Project Amount: $108,286
RFA: STAR Graduate Fellowships (2000) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Biology/Life Sciences , Ecological Indicators/Assessment/Restoration , Fellowship - Forestry , Tribal Environmental Health Research
The objective of this research project is to devise a framework for evaluating the health and restoration capability of riparian wetlands on the White Mountain Apache Reservation in east-central Arizona.
I am studying more than a dozen sites that have been subject to various restoration treatments in recent years. I am measuring how these sites have changed in terms of vegetation and channel morphology. I also am analyzing basic soil parameters to gauge how the geologies of sites relate to their current condition and potential. I am using a variety of analysis tools to stratify the sites into comparable groups, and to elucidate how indicators such as plant cover and composition have responded to changes in condition. In addition to examining the physical and biological dimensions of riparian health, I am interviewing tribal, cultural advisors regarding their conceptions of health at these sites.
My first hypothesis is that short-term indicators of wetland vegetation, soil quality, and hydro-geomorphologic conditions are sensitive to changes in health. My second hypothesis is that long-term factors related to geologic type govern the ranges of short-term indicators. Third, I hypothesize that a framework that classifies sites according to long-term indicators, and then evaluates conditions based on short-term indicators, is appropriate for evaluating health and designing restoration treatments. Finally, I hypothesize that this framework is compatible with Apache conceptions of stream health.