In spite of its size and biological significance, we know little about the ecology of the Pantanal, a 140,000 km 2 floodplain in west-central Brazil. Increasing human pressures make this lack of understanding particularly critical. Using transects and 1 m 2 circular plots, we documented floristic composition and interactingenvironmental conditions associated with littoral herbaceous vegetation along inundation gradients at two ecologically-distinct sites in the Pantanal. We recorded water depth and percent cover for each species in Baía Piuval, a bay in the Bento Gomes River (Mato Grosso), and in a bay in the Acurizal Reserve (Mato Grosso do Sul). Baía Piuval and Acurizal plots contained a total of 22 and 18 macrophyte species, respectively. At both sites Eichhornia azurea and Salvinia auriculata occurred most frequently as dominant or co-dominant species. Chi 2 analysis, used to quantify zonations along depth gradients, generated four different groups of species ( p < 0.05) for Baía Piuval. For Acurizal, two significantly different groups ( p < 0.05) occurred with an intermediate assemblage of species that could be assigned to either group. Canonical correspondence analysis, used to analyze species distributions, showed a pattern consistent with the Chi 2 results for Baía Piuval but not for Acurizal. Higher species richness and diversity occurred where dry season and low water levels coincided and richness was generally highest in proximal plots where water depths were lowest. Our results are consistent with the few other plant ecological studies reported for the Pantanal. This study can be considered additive to needed baseline data on biota and ecology of this region of South America.

To advance predictive ecology, the hypothesis of hierarchical predictability proposes that community measures for which species are interchangeable (e.g., structure and species richness) are more predictable than measures for which species identity matters (e.g., community composition). Predictability is hypothesized to decrease for response measures in order of the following categories: structure, species richness, function, and species composition. We tested this hypothesis using a 14-year, oak savanna-prairie restoration experiment that removed non-native pine plantations at 24 sites in northwestern Ohio, USA. Based on 24 response measures, the data showed minimal support for the hypothesis, because response measures varied in predictability within categories. Half of response measures had over half their variability modeled using fixed (restoration treatment and year) and random plot effects, and these "predictable" measures occurred in all four categories. Pine basal area, environment (e.g., soil texture), and antecedent vegetation accounted for over half the variation in change within the first three post-restoration years for 77% of response measures. Change between the 3rd and 14th years was less predictable, but most restoration measures increased favorably via sites achieving them in unique ways. We propose that variation will not conform with the hypothesis of hierarchical predictability in ecosystems with vegetation dynamics driven by stochastic processes such as seed dispersal, or where vegetation structure and species richness are influenced by species composition. The ability to predict a community measure may be more driven by the number of combinations of casual factors affecting a measure than by the number of values it can have.

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio’s Oak Openings region. Multiple regression models explained 37–77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.

A survey of biological crust components (bryophytes, lichens, chlorophyta, bacteria), soil fauna (nematodes, collembolans, mites) and vascular plants was conducted in a dry sand savanna in northwestern Ohio between 1995 and 2001. In soil, six free-living chlorophytes and seven cyanobacteria taxa were identified. Chlorophyta were more abundant than cyanobacteria with Desmococcus olivaeus and Stichococcus bacillaris being the most common species. For bryophytes, the most common species were Polytrichum piliferum and Ceratodon purpureus, and for lichens, Cladonia species. Notably, we found lichen species in the crusts have chlorophytes not cyanobacteria, as their photobionts. Twenty-seven families and 29 genera of nematodes, and four collembolan species were identified in crust and rhizosphere communities. Autotrophic denitrifying bacteria were not detectable with the method employed. The biological crust occurred among a vascular plant community with Robinia pseudoacacia, Rubus flagellaris, Bromus inermis, and Vicia villosa as the most abundant tree, shrub, graminoid, and non-grass herbaceous plants, respectively. To our knowledge, this is the first report of microbial crust community composition in xeric patches of northwestern Ohio. Moreover, our report includes a report of soil nematode or collembolan communities associated with soil biological crust communities.

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