Variation in overstory biomass and mean annual biomass increment (MABI) of upland forest stands was studied at two spatial scales: glacial landforms (1: 250 000–1: 000 000) and ecological land units (1: 10 000–1: 80 000). Ecological land units were defined based on combinations of ground-flora vegetation, soil, and physiography. Biomass estimates were based on allometric regression equations developed in the Lake States area. Analyses of covariance were used to study the patterns of total biomass and biomass increment among glacial landforms and among ecological land units; stand age was used as the covariate. Overstory biomass ranged from 105 t/ha (MABI = 1.5 t ha−1 year−1) on glacial outwash landforms to 208 t/ha (MABI = 3.2 t ha−1 year−1) on morainal landforms; 37% of the total variation in biomass was accounted for by landform. Analysis at the ecological land unit scale accounted for a higher proportion of variation, approximately 60% of the total. Overstory biomass among ecological land units ranged from 85 t/ha (MABI = 1.3 t ha−1 year−1) for oak-dominated forests occurring on xeric sandy outwash sediments to almost 250 t/ha (MABI = 3.6 t ha−1 year−1) for sugar maple–red oak forests occurring in mesic morainal positions. Variation in biomass appeared to be strongly related to differences in species composition and variation in soil moisture availability, as evidenced by differences in soil texture and the presence or absence of deep-lying textural bands. Since ground-flora composition often reflects variation in soil properties, we examined the relationship between ground-flora composition and biomass increment. Detrended correspondence analysis was used to ordinate stands along a floristic gradient. Regression of stand ordination scores against MABI was significant (r2 = 0.65), indicating a relatively strong association between ground-flora composition and productivity. One advantage of understanding spatial variation in site productivity is that ecological land units can be readily mapped, whereas traditional estimates of site potential, such as site index, are point specific.
In large-scale gradient studies, selection of the best research sites is critical but time-consuming and costly. Multivariate methods can be used to quickly identify suitable sites from existing data bases. Based on a study of acid deposition in the Great Lakes region (the Michigan Gradient Study), we illustrate the use of multivariate methods in screening potential research sites for similarity. Sites were examined using cluster analysis, principal coordinates analysis, and correspondence analysis. The graphical displays generated by the multivariate methods were used to identify similar sites across the gradient. A list of 31 potential sites was reduced to 5 similar research sites and several alternative sites. The results of the multivariate methods compared well with more traditional methods of research site selection but allowed for multiple comparisons of many potential sites using a variety of data from existing data bases. By eliminating sites that are unacceptable with respect to available data, the multivariate methods reduce the number of sites that require field visitation prior to final site verification. This process represents a substantial savings in time and effort when dealing with a long list of potential research sites.
Thirty-six sour (Prunus cerasus L.), sweet (P. avium L.), and ground cherry (P. fruticosa Pall.) selections were evaluated for seven enzyme systems and principal coordinate analysis was used to examine isozyme divergence among these cherry species. The enzyme systems studied were phosphoglucose isomerase (PGI), isocitrate dehydrogenase (IDH), phosphoglucomutase (PGM), 6-phosphogluconate dehydrogenase (6-PGD), leucine aminopeptidase (LAP), shikimate dehydrogenase (SKDH), and malate dehydrogenase (MDH). The first principal coordinate, which accounted for 41% of the total variation, separated the diploid sweet cherry selections from the sour, ground, and sour x ground cherry tetraploids. An additional 86 selections were evaluated for up to six of the enzyme systems to determine the polymorphisms at the enzyme loci and the level of heterozygosity between the diploid sweet cherry and the tetraploid species and interspecific hybrids. 6-PGD was the most polymorphic enzyme exhibiting 16 patterns. The tetraploid cherry species were more heterozygous than the diploid sweet cherry with an average heterozygosity of 78% compared to 19% for the diploids.
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