Multi-scale comparisons of cliff vegetation in Colorado

We developed a nested vegetation sampling protocol to sample the plant diversity on south-facing cliffs and cliff bases in Jefferson County, Colorado. The multi-scale plots included three nested spatial scales, 1 m², 20 m², and 40 m². We compared plant species richness and species diversity among large cliffs, medium cliffs, small cliffs, and non-cliff sites using Hill's diversity numbers (N ₀, N ₁, and N ₂) for the 1-m² quadrats. Species richness (N ₀) was calculated for the 20-m² and 40-m² plots. Our results indicate that plant species diversity on the cliff faces did not increase with increasing cliff area. This pattern was consistent at all three sampling scales. A model selection was run to determine if plant species diversity values on the cliff faces were associated with cliff variables. None of the cliff variables measured were good predictors of diversity at the 1-m² scale. However, at the 20-m² scale, canyon differences and a positive relationship with increasing cliff surface roughness explained 70% of the variability in species richness. Although most plant species sampled on the cliff faces were also found in the base plots, 13 species were sampled only on the cliff faces. Additionally, dry south facing cliffs support a mix of xeric and mesic plants indicating that cliffs may provide unique microenvironments for plant establishment. This revised version was published online in August 2006 with corrections to the Cover Date.     

Diversity of woody species in forest,treefall gaps,and edge in Kibale National Park,Uganda

If specialization influences species presence, then high tropical tree and shrub diversity should correspond with high environmental heterogeneity. Such heterogeneity may be found among different successional communities (i.e., canopy types). We explore species associations in three forest-dominated canopy types, forest, gap, and edge, in Kibale National Park, Uganda and determine environmental, soil and light, differences among canopy types. To determine the strength of differences among forested canopy types, they are also compared to grasslands. Tree and shrub density and species richness using rarefaction analysis were determined based on data from 24 small plots (5 × 5 m) in all four canopy types and 16 large plots (10 × 50 m) in forest and grassland canopy types. Environmental variables were determined along 10 (20 m) transects in the four canopy types. Using analysis of variance and principal components analysis, we demonstrate that forest and gap environments had similar soils, but forest had lower light levels than gap. We also found that grassland and edge were more similar to one another than to forest and gap, but differed in a number of important biotic and abiotic factors controlling soil water availability (e.g., edge had higher root length density of small roots < 2 mm diameter in the top 20 cm than grassland). Using principal components analysis to assess similarities in community composition, we demonstrate that gap and forest had indistinguishable communities and that edge was similar to but distinct from both communities. Complete species turnover only occurred between grassland and the three forested canopy types. Even though overall community composition was similar in the three forested canopy types, in analyses of individual species using randomization tests, many common species were most frequently found in only one canopy type; these patterns held across size classes. These results suggest that despite differences among environments, community composition was similar among forested canopy types, which are likely intergrading into one another. Interestingly, individual species are more frequently found in a single canopy type, indicating species specialization.     

Relative influence of size,connectivity and disturbance history on plant species richness and assemblages in fragmented grasslands

Questions: What is the relative influence of size, connectivity and disturbance history on plant species richness and assemblages of fragmented grasslands? What is the contribution of small fragments to the conservation of native species pool of the region? Location: Tandilia's Range, Southern Pampa, Argentina. Methods: Cover of plants was registered within 24 fragments of tall‐tussock grassland remnants within an agricultural landscape using modified Whittaker nested sampling. We analysed the influence of site variables related to disturbance history (canopy height, litter thickness) and fragment variables (size, connectivity) on species richness (asymptotic species richness, slope of the species–area curve) as well as on species assemblages by multiple regressions analysis and canonical correspondence analyses, respectively. Cumulative area was used for analysing whether small fragments or large fragments are more important to species diversity in the landscape. Results: Asymptotic species richness was significantly influenced by site variables, in particular by Paspalum quadrifarium's canopy height, but not by fragment variables. Species assemblages were also affected by site variables (12.2% of total variation), but no additional portion of the species assemblage variability was significantly explained by fragment size and connectivity. Sampling of several small fragments rendered more exotic and native species than sampling of few large fragments of the same total area. Conclusions: Our results agree with previous studies reporting low sensitivity of species diversity to size and isolation of grassland fragments in fragmented landscapes and high sensitivity of species diversity to local variables. The higher capture of regional native species pool by small grassland fragments than by few larger ones of equivalent accumulated area highlights the value of small fragments for conservation.     

Testing association between species abundance and a continuous variable with Kolmogorov-Smirnov statistics

Association of species abundance with a continuous environmental variable is frequently tested with regression or correlation analyses. However, because these methods ignore the range and frequency distribution of levels of the variable occurring in the study area, they may generate misleading results. We give examples to illustrate the argument. A better approach to test the association between species abundance and a continuous variable should compare levels of the variable in the study area to levels of the variable occurring in sites occupied by the species. If a particular species abundance is not associated with a given continuous variable, then the frequency distribution of levels of this variable measured where individuals of the species occur should mirror the frequency distribution of levels of the variable measured over the study area. We explain how to use the one- and two-sample Kolmogorov-Smirnov statistics to compare the cumulative relative frequencies of levels of the variable where individuals are present with points in the study area. We discuss the statistics, assumptions, limitations, and advantages of these tests.     

Plant biomass and species composition along an environmental gradient in montane riparian meadows

In riparian meadows, narrow zonation of the dominant vegetation frequently occurs along the elevational gradient from the stream edge to the floodplain terrace. We measured plant species composition and above- and belowground biomass in three riparian plant communities—a priori defined as wet, moist, and dry meadow—along short streamside topographic gradients in two montane meadows in northeast Oregon. The objectives were to: (1) compare above- and belowground biomass in the three meadow communities; (2) examine relations among plant species richness, biomass distribution, water table depth, and soil redox potential along the streamside elevational gradients. We installed wells and platinum electrodes along transects (perpendicular to the stream; n=5 per site) through the three plant communities, and monitored water table depth and soil redox potential (10 and 25 cm depth) from July 1997 to August 1999. Mean water table depth and soil redox potential differed significantly along the transects, and characterized a strong environmental gradient. Community differences in plant species composition were reflected in biomass distribution. Highest total biomass (live+dead) occurred in the sedge-dominated wet meadows (4,311±289 g/m²), intermediate biomass (2,236±221 g/m²) was seen in the moist meadow communities, dominated by grasses and sedges, and lowest biomass (1,403±113 g/m²) was observed in the more diverse dry meadows, dominated by grasses and forbs. In the wet and moist communities, belowground biomass (live+dead) comprised 68–81% of the totals. Rhizome-to-root ratios and distinctive vertical profiles of belowground biomass reflected characteristics of the dominant graminoid species within each community. Total biomass was positively correlated with mean water table depth, and negatively correlated with mean redox potential (10 cm and 25 cm depths; P <0.01) and species richness (P <0.05), indicating that the distribution of biomass coincided with the streamside edaphic gradient in these riparian meadows.Electronic Supplementary Material Supplementary material is available in the online version of this article at     

Non-Parametric Methods for the 2-Period-Cross-Over Design Under Weak Model Assumptions

A nonparametric analysis for the two period cross-over design has first been suggested by Koch (1972) and has been discussed by Hills and Armitage (1979). As known rank tests on sums or differences of the data are applied in this procedure, the results on the one hand are not invariant under monotonous transformations and on the other hand the procedure is only correct for models with additive effects. Therefore, in the present article generalized effects will first be defined in the 2-period cross-over design without the assumption of a linear model and then rank test will be presented which test tese effects without the need of sums or differences of the data. In the appendix the equivalence of the hypothesis for the generalized effects to the known hypotheses for the effects in the linear model will be shown. The application of the procedures will be demonstrated by means of an example in literature.