The ecology of forest soils is an important field of research due to the role of forests as carbon sinks. Consequently, a significant amount of information has been accumulated concerning their ecology, especially for temperate and boreal forests. Although most studies have focused on fungi, forest soil bacteria also play important roles in this environment. In forest soils, bacteria inhabit multiple habitats with specific properties, including bulk soil, rhizosphere, litter, and deadwood habitats, where their communities are shaped by nutrient availability and biotic interactions. Bacteria contribute to a range of essential soil processes involved in the cycling of carbon, nitrogen, and phosphorus. They take part in the decomposition of dead plant biomass and are highly important for the decomposition of dead fungal mycelia. In rhizospheres of forest trees, bacteria interact with plant roots and mycorrhizal fungi as commensalists or mycorrhiza helpers. Bacteria also mediate multiple critical steps in the nitrogen cycle, including N fixation. Bacterial communities in forest soils respond to the effects of global change, such as climate warming, increased levels of carbon dioxide, or anthropogenic nitrogen deposition. This response, however, often reflects the specificities of each studied forest ecosystem, and it is still impossible to fully incorporate bacteria into predictive models. The understanding of bacterial ecology in forest soils has advanced dramatically in recent years, but it is still incomplete. The exact extent of the contribution of bacteria to forest ecosystem processes will be recognized only in the future, when the activities of all soil community members are studied simultaneously.

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This article provides a synthesis of literature values to trace the fate of 150 Tg/yr anthropogenic nitrogen applied by humans to the Earth's land surface. Approximately 9 TgN/yr may be accumulating in the terrestrial biosphere in pools with residence times of ten to several hundred years. Enhanced fluvial transport of nitrogen in rivers and percolation to groundwater accounts for approximately 35 and 15 TgN/yr, respectively. Greater denitrification in terrestrial soils and wetlands may account for the loss of approximately 17 TgN/yr from the land surface, calculated by a compilation of data on the fraction of N(2)O emitted to the atmosphere and the current global rise of this gas in the atmosphere. A recent estimate of atmospheric transport of reactive nitrogen from land to sea (NO(x) and NH(x)) accounts for 48 TgN/yr. The total of these enhanced sinks, 124 TgN/yr, is less than the human-enhanced inputs to the land surface, indicating areas of needed additional attention to global nitrogen biogeochemistry. Policy makers should focus on increasing nitrogen-use efficiency in fertilization, reducing transport of reactive N to rivers and groundwater, and maximizing denitrification to its N(2) endproduct.

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The impact of exotic species on native organisms is widely acknowledged, but poorly understood. Very few studies have empirically investigated how invading plants may alter delicate ecological interactions among resident species in the invaded range. We present novel evidence that antifungal phytochemistry of the invasive plant, Alliaria petiolata, a European invader of North American forests, suppresses native plant growth by disrupting mutualistic associations between native canopy tree seedlings and belowground arbuscular mycorrhizal fungi. Our results elucidate an indirect mechanism by which invasive plants can impact native flora, and may help explain how this plant successfully invades relatively undisturbed forest habitat.

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The task of modeling the distribution of a large number of tree species under future climate scenarios presents unique challenges. First, the model must be robust enough to handle climate data outside the current range without producing unacceptable instability in the output. In addition, the technique should have automatic search mechanisms built in to select the most appropriate values for input model parameters for each species so that minimal effort is required when these parameters are fine-tuned for individual tree species. We evaluated four statistical models--Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS)--for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model. To test, we applied these techniques to four tree species common in the eastern United States: loblolly pine (Pinus taeda), sugar maple (Acer saccharum), American beech (Fagus grandifolia), and white oak (Quercus alba). When the four techniques were assessed with Kappa and fuzzy Kappa statistics, RF and BT were superior in reproducing current importance value (a measure of basal area in addition to abundance) distributions for the four tree species, as derived from approximately 100,000 USDA Forest Service's Forest Inventory and Analysis plots. Future estimates of suitable habitat after climate change were visually more reasonable with BT and RF, with slightly better performance by RF as assessed by Kappa statistics, correlation estimates, and spatial distribution of importance values. Although RTA did not perform as well as BT and RF, it provided interpretive models for species whose distributions were captured well by our current set of predictors. MARS was adequate for predicting current distributions but unacceptable for future climate. We consider RTA, BT, and RF modeling approaches, especially when used together to take advantage of their individual strengths, to be robust for predictive mapping and recommend their inclusion in the ecological toolbox.

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Mercury accumulation in fish is a global public health concern, because fish are the primary source of toxic methylmercury to humans. Fish from all lakes do not pose the same level of risk to consumers. One of the most intriguing patterns is that potentially dangerous mercury concentrations can be found in fish from clear, oligotrophic lakes whereas fish from greener, eutrophic lakes often carry less mercury. In this study, we experimentally tested the hypothesis that increasing algal biomass reduces mercury accumulation at higher trophic levels through the dilution of mercury in consumed algal cells. Under bloom dilution, as algal biomass increases, the concentration of mercury per cell decreases, resulting in a lower dietary input to grazers and reduced bioaccumulation in algal-rich eutrophic systems. To test this hypothesis, we added enriched stable isotopes of Hg to experimental mesocosms and measured the uptake of toxic methylmercury (CH3 200Hg+) and inorganic 201Hg2+ by biota at several algal concentrations. We reduced absolute spike detection limits by 50-100 times compared with previous techniques, which allowed us to conduct experiments at the extremely low aqueous Hg concentrations that are typical of natural systems. We found that increasing algae reduced CH3Hg+ concentrations in zooplankton 2-3-fold. Bloom dilution may provide a mechanistic explanation for lower CH3Hg+ accumulation by zooplankton and fish in algal-rich relative to algal-poor systems.

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