The number of studies focused on the transformation and sequestration of soil organic carbon (C) has dramatically increased in recent years due to growing interest in understanding the global C cycle. While it is readily accepted that terrestrial C dynamics are heavily influenced by the catabolic and anabolic activities of microorganisms, the incorporation of microbial biomass components into stable soil C pools (via microbial living cells and necromass) has received less attention. Nevertheless, microbialderived C inputs to soils are now increasingly recognized as playing a far greater role in stabilization of soil organic matter than previously believed. Our understanding, however, is limited by the difficulties associated with studying microbial turnover in soils. Here, we describe the use of an Absorbing Markov Chain (AMC) to model the dynamics of soil C transformations among three microbial states: living microbial biomass, microbial necromass, and C removed from living and dead microbial sources. We find that AMC provides a powerful quantitative approach that allows prediction of how C will be distributed among these three states, and how long it will take for the entire amount of initial C to pass through the biomass and necromass pools and be moved into atmosphere. Further, assuming constant C inputs to the model, we can predict how C is eventually distributed, along with how much C sequestrated in soil is microbial-derived. Our work represents a first step in attempting to quantify the flow of C through microbial pathways, and has the potential to increase our understanding of the microbial role in soil C dynamics.

Understanding the temperature sensitivity of soil respiration is critical for predicting the response of ecosystems to climate change, yet the microbial communities responsible are rarely considered explicitly in studies or models. In this study, we assessed total microbial community composition, quantified bacterial respiration temperature response, and investigated the temperature dependence of bacterial carbon substrate utilization in tropical, temperate, and taiga soils (from Puerto Rico, California, and Alaska). Microbial community composition was characterized using phospholipid fatty acid analysis. Bacterial community respiration on a standardized set of substrates was ascertained using the BiOLOGt substrate utilization assay incubated at four temperatures: 4, 12, 28, and 40 1C. First, we found that microbial communities from the three latitudes were compositionally distinct and that the bacterial component of the three communities had markedly different respiration temperature-response curves corresponding with their experienced temperature regimes. We use these data to highlight limitations of widely used temperature-response equations and investigate temperaturedependent patterns of substrate utilization. We found that temperature response, in terms of both respiration rates and substrate use, varied for these bacterial communities independent of substrate quality or quantity interactions such as labile depletion. In contrast to the common assumption of heterotrophic microbial ubiquity, we found that bacterial community differences from these diverse systems appeared to determine both rates of respiration and patterns of carbon substrate usage. We suggest that microbial community composition-specific responses to changing climate may be important in predicting the long-term role of ecosystems in atmospheric CO 2 dynamics.

BackgroundLeaf-cutter ants use fresh plant material to grow a mutualistic fungus that serves as the ants' primary food source. Within fungus gardens, various plant compounds are metabolized and transformed into nutrients suitable for ant consumption. This symbiotic association produces a large amount of refuse consisting primarily of partly degraded plant material. A leaf-cutter ant colony is thus divided into two spatially and chemically distinct environments that together represent a plant biomass degradation gradient. Little is known about the microbial community structure in gardens and dumps or variation between lab and field colonies.Methodology/Principal FindingsUsing microbial membrane lipid analysis and a variety of community metrics, we assessed and compared the microbiota of fungus gardens and refuse dumps from both laboratory-maintained and field-collected colonies. We found that gardens contained a diverse and consistent community of microbes, dominated by Gram-negative bacteria, particularly γ-Proteobacteria and Bacteroidetes. These findings were consistent across lab and field gardens, as well as host ant taxa. In contrast, dumps were enriched for Gram-positive and anaerobic bacteria. Broad-scale clustering analyses revealed that community relatedness between samples reflected system component (gardens/dumps) rather than colony source (lab/field). At finer scales samples clustered according to colony source.Conclusions/SignificanceHere we report the first comparative analysis of the microbiota from leaf-cutter ant colonies. Our work reveals the presence of two distinct communities: one in the fungus garden and the other in the refuse dump. Though we find some effect of colony source on community structure, our data indicate the presence of consistently associated microbes within gardens and dumps. Substrate composition and system component appear to be the most important factor in structuring the microbial communities. These results thus suggest that resident communities are shaped by the plant degradation gradient created by ant behavior, specifically their fungiculture and waste management.

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A proliferation of data gathered to predict a critically important, urgent and social-policy related question often leads to debate and divergent model results. This classic feature of complex systems is currently being evidenced in assessing a potentially serious feedback response of soil respiration with increased temperatures due to global climate change.Here we apply soft systems modelling (SSM) for a detailed analysis of the ''soft'' aspects of the topic. Supported by a literature review, we conclude that that varied perspectives on the system's dynamics and its web of controlling factors have led to seemingly conflicting results. We present a simplified hierarchy organizing the comprehensive universe of interacting controls across scales. This model is implemented as a relational database, including relationships between factors such as nesting and feedbacks. We conclude that although this model is currently limited to pairwise interactions, it provides a useful tool to assess potential interactions and factors of interest.

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Abstract. The challenges that face scientists in the bourgeoning field of hydropedology include many of those that face investigations in complex systems. We suggest hierarchy theory as being particularly helpful in teasing through complexity in hydropedological investigations. We present a brief overview of hierarchy theory highlighting the importance of defining levels of analysis, the role of theory in prediction, and the importance of narrative in science. These concepts are highlighted by references from the hydropological literature. We point out several issues common to scientists faced with complex systems analysis, and suggest several strategies to help hydropedologists deal with them. In order to help bridge the gap between theory and application, we present several specific examples of how hierarchical treatments have helped scientists deal with the modeling and analysis of complex systems related to hydropedology. We conclude that hierarchy theory offers many powerful tools with which to tackle the complexity inherent in soil water interactions, and that its use would benefit a more systematic and robust integration of the hydrologic and soil sciences.