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Saltcedar had more individual arthropods per unit area than either cottonwood or Russian olive late in the breeding season, although cottonwoods generally had more arthropods per tree because of their larger size Thus, saltcedar and Russian olive may support an abundant source of arboreal arthropods for breeding birds (Mund-Meyerson, 1998) That saltcedar and Russian olive can be utilized successfully by a variety of wildlife does not mean that these plants should be allowed to continue their spread through the valley unchecked In low densities, both species probably will not adversely affect wildlife communities However, the extent to which they alter riparian ecosystems when densities become high, and particularly their effect on river hydrology through stream bank stabilization, mean that control measures are necessary (Cox, 1999) Although the cost of controlling exotics can be quite high, native plants can be restored successfully (Taylor and McDaniel, 1998).

More reliable identi cation is possible by using statistical tests However, these methods typically assume that the gene expression data follow a certain distribution, and require suf ciently large sample size that often cannot be achieved due to microarray experimental conditions or budget constraints Alternative techniques, such as bootstrapping, impose less rigorous requirements on the sample size and distribution while still providing reliable identi cation of differentially expressed genes Given the data, a statistical test explores whether a null hypothesis is valid and calculates the p-value, which refers to the probability that the observed statistics are generated by the null model If the p-value is smaller than some xed threshold (eg, 005), the null hypothesis is rejected.

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The Bosque del Apache National Wildlife Refuge is located approximately 160 km south of Albuquerque, New Mexico (Figure 3-1), at an elevation of about 1400 m, and contains roughly 14.5 km of the Rio Grande and its associated riparian vegetation. We established two study sites in mixed cottonwood forest at the Refuge during the summer of 1991. These primary study sites were located 3.7 km apart in a strip of continuous forest, 200 to 300 m wide, with each intensive study area of approximately 3.1 ha. The canopy of each was dominated by Rio Grande cottonwood ranging from 8 to 15 m in height, with a subcanopy of Salix gooddingii (Goodding willow) and Tamarix ramosissima (saltcedar). The most common understory shrubs were Baccharis glutinosa (seepwillow), Forestiera neomexicana (New Mexico olive), and Amorpha fruticosa (desert indigobush). The composition and density of the herbaceous understory varied among years, but generally included Conyza canadensis, Chamaesyce serpyllifolia, Ratibida tagetes, Solanum elaeagnifolium, and Sphaeralcea angustifolia. The sites were approximately 0.5 km west of the Rio Grande and separated from it by the low- ow conveyance channel and riverside levee that parallel the river. After we had collected baseline data at both sites for two years, one site, designated the Experimental Flood site, was inundated for approximately one month during each of the following three years: 1993 (May 17 to June 12), 1994 (May 19 to June 19), and 1995 (May 17 to June 17). Floods were timed to match the historical peak ow for the upper Rio Grande, based on the mean annual hydrograph for 1889 1990

If the p-value is above the threshold, however, it should not be concluded that the original hypothesis is con rmed; the result of the test is that the observed events do not provide a reason to overturn it [25] The most common null hypothesis in microarray data analysis is that there is no difference between two groups of expression values for a given gene In this section, we brie y introduce the assumptions and requirements for several statistical tests that are often used for the identi cation of differentially expressed genes 4311 Parametric Statistical Approaches The Student s t-test examines the null hypothesis that the means of distributions from which two samples are obtained are equal The assumptions required for t-test are that the two distributions are normal and that their variances are equal.

This will be an important component of restoring the natural ow regime..

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