127 research outputs found

    The spatial temporal regime of stream flow of the conterminous U.S. in connection with indices of global atmospheric circulation

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    Long-term stream flow records (1929-1988) from seventy one U.S. Geological Survey gauging stations with drainage area in range 1000-10000 sq mi were analyzed using multivariate statistics. Factor analysis of average annual flow revealed seven patterns of river runoff within seven distinct regions of the territory. This factor model reflected 69% variance of the initial matrix. The second set of stream flow records (1939-1972) from ninety-seven gauging stations was used as control. This set contains all seventy one from first one and additional stations with shorter observation period. Factor analysis of this expended set again yielded seven factors (69% variance of the initial matrix) with very similar spatial distribution of gauging stations.

Every group of watersheds obtained as a factor was presented by one gauging station with time series of annual discharges (1- 05474000, 2- 14321000, 3- 07019000, 4- 0815000, 5- 11186001, 6- 01666000, 7- 06800500) as the most typical for group. For the same time interval, streams represented by all patterns have increasing values (i. e. the positive difference between two time subintervals); but only the positive linear trend for patterns 1 and 7 are statistically significant. 

For the seven typical flow records, monthly average values were obtained from three to five seasons composed from different ensembles of months. 

For each annual time series of the typical seven stream flow patterns, regression equations were obtained from indices of global atmospheric circulation (AO, NAO, NPO and AAO). The equations contain from one to five variables (predictors) and have coefficients of correlation from 32% to 73%. 
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    Pathways of Anaerobic Carbon Cycling Across an Ombrotrophic–Minerotrophic Peatland Gradient

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    Peatland soils represent globally significant stores of carbon, and understanding carbon cycling pathways in these ecosystems has important implications for global climate change. We measured aceticlastic and autotrophic methanogenesis, sulfate reduction, denitrification, and iron reduction in a bog, an intermediate fen, and a rich fen in the Upper Peninsula of Michigan for one growing season. In 3-d anaerobic incubations of slurried peat, denitrification and iron reduction were minor components of anaerobic carbon mineralization. Experiments using 14C-labeled methanogenic substrates showed that methanogenesis in these peatlands was primarily through the aceticlastic pathway, except early in the growing season in more ombrotrophic peatlands, where the autotrophic pathway was dominant or codominant. Overall, methane production was responsible for 3-70% of anaerobic carbon mineralization. Sulfate reduction accounted for 0-26% of anaerobic carbon mineralization, suggesting a rapid turnover of a very small sulfate pool. A large percentage of anaerobic carbon mineralization (from 29% to 85%) was unexplained by any measured process, which could have resulted from fermentation or possibly from the use of organic molecules (e.g., humic acids) as alternative electron acceptors

    Quantifying Peat Carbon Accumulation in Alaska Using a Process-Based Biogeochemistry Model

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    This study uses an integrated modeling framework that couples the dynamics of hydrology, soil thermal regime, and ecosystem carbon and nitrogen to quantify the long-term peat carbon accumulation in Alaska during the Holocene. Modeled hydrology, soil thermal regime, carbon pools and fluxes, and methane emissions are evaluated using observation data at several peatland sites in Minnesota, Alaska, and Canada. The model is then applied for a 10,000 year (15 ka to 5 ka; 1 ka = 1000 cal years before present) simulation at four peatland sites. We find that model simulations match the observed carbon accumulation rates at fen sites during the Holocene (R2 = 0.88, 0.87, 0.38, and -0.05 using comparisons in 500 year bins). The simulated (2.04 m) and observed peat depths (on average 1.98 m) were also compared well (R2 = 0.91). The early Holocene carbon accumulation rates, especially during the Holocene thermal maximum (HTM) (35.9 g Cm-2 yr-1), are estimated up to 6 times higher than the rest of the Holocene (6.5 g Cm-2 yr-1). Our analysis suggests that high summer temperature and the lengthened growing season resulted from the elevated insolation seasonality, along with wetter-than-before conditions might be major factors causing the rapid carbon accumulation in Alaska during the HTM. Our sensitivity tests indicate that, apart from climate, initial water table depth and vegetation canopy are major drivers to the estimated peat carbon accumulation. When the modeling framework is evaluated for various peatland types in the Arctic, it can quantify peatland carbon accumulation at regional scales

    Nutrient Control of Microbial Carbon Cycling Along an Ombrotrophicminerotrophic Peatland Gradient

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    Future climate change and other anthropogenic activities are likely to increase nutrient availability in many peatlands, and it is important to understand how these additional nutrients will influence peatland carbon cycling. We investigated the effects of nitrogen and phosphorus on aerobic CH4 oxidation, anaerobic carbon mineralization (as CO2 and CH4 production), and anaerobic nutrient mineralization in a bog, an intermediate fen, and a rich fen in the Upper Peninsula of Michigan. We utilized a 5-week laboratory nutrient amendment experiment in conjunction with a 6-year field nutrient fertilization experiment to consider how the relative response to nitrogen and phosphorus differed among these wetlands over the short and long term. Field fertilizations generally increased nutrient availability in the upper 15 cm of peat and resulted in shifts in the vegetation community in each peatland. High nitrogen concentrations inhibited CH4 oxidation in bog peat during short-term incubations; however, long-term fertilization with lower concentrations of nitrogen stimulated rates of CH4 oxidation in bog peat. In contrast, no nitrogen effects on CH4 oxidation were observed in the intermediate or rich fen peat. Anaerobic carbon mineralization in bog peat was consistently inhibited by increased phosphorus availability, but similar phosphorus additions had few effects in the intermediate fen and stimulated CH4 production and nutrient mineralization in the rich fen. Our results demonstrate that nitrogen and phosphorus are important controls of peatland microbial carbon cycling; however, the role of these nutrients can differ over the short and long term and is strongly mediated by peatland type

    Modeling Holocene Peatland Carbon Accumulation in North America

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    Peatlands are a large carbon reservoir. Yet the quantification of their carbon stock still has a large uncertainty due to lacking observational data and well‐tested peatland biogeochemistry models. Here, a process‐based peatland model was calibrated using long‐term peat carbon accumulation data at multiple sites in North America. The model was then applied to quantify the peat carbon accumulation rates and stocks within North America over the last 12,000 years. We estimated that 85–174 Pg carbon was accumulated in North American peatlands over the study period including 0.37–0.76 Pg carbon in subtropical peatlands. During the period from 10,000 to 8,000 years ago, the warmer and wetter conditions might have played an important role in stimulating peat carbon accumulation by enhancing plant photosynthesis. Enhanced peat decomposition due to warming slowed the carbon accumulation through the rest of the Holocene. While recent modeling studies indicate that the northern peatlands will continue to act as a carbon sink in this century, our studies suggest that future enhanced peat decomposition accompanied by peatland areal changes induced by permafrost degradation and other disturbances shall confound the sink and source analysis

    An Integrative Model for Soil Biogeochemistry and Methane Processes. II: Warming and Elevated CO2 Effects on Peatland CH4 Emissions

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    Peatlands are one of the largest natural sources for atmospheric methane (CH4), a potent greenhouse gas. Climate warming and elevated atmospheric carbon dioxide (CO2) are two important environmental factors that have been confirmed to stimulate peatland CH4 emissions; however, the mechanisms underlying enhanced emissions remain elusive. A data-model integration approach was applied to understand the CH4 processes in a northern temperate peatland under a gradient of warming and doubled atmospheric CO2 concentration. We found that warming and elevated CO2 stimulated CH4 emissions through different mechanisms. Warming initially stimulated but then suppressed vegetative productivity while stimulating soil organic matter (SOM) mineralization and dissolved organic carbon (DOC) fermentation, which led to higher acetate production and enhanced acetoclastic and hydrogenotrophic methanogenesis. Warming also enhanced surface CH4 emissions, which combined with warming-caused decreases in CH4 solubility led to slightly lower dissolved CH4 concentrations through the soil profiles. Elevated CO2 enhanced ecosystem productivity and SOM mineralization, resulting in higher DOC and acetate concentrations. Higher DOC and acetate concentrations increased acetoclastic and hydrogenotrophic methanogenesis and led to higher dissolved CH4 concentrations and CH4 emissions. Both warming and elevated CO2 had minor impacts on CH4 oxidation. A meta-analysis of warming and elevated CO2 impacts on carbon cycling in wetlands agreed well with a majority of the modeled mechanisms. This mechanistic understanding of the stimulating impacts of warming and elevated CO2 on peatland CH4 emissions enhances our predictability on the climate-ecosystem feedback

    Optimal fire management for maintaining community diversity

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    Disturbance events strongly influence the dynamics of plant and animal populations within nature reserves. Although many models predict the patterns of succession following a disturbance event, it is often unclear how these models can be used to help make management decisions about disturbances. In this paper we consider the problem of managing fire in Ngarkat Conservation park (CP), South Australia, Australia. We present a methematical model of community succession following a fire disturbance event. Ngarkat CP is a key habitat for several nationally rare and threatened species of birds, and because these species prefer different successional communities, we assume that the primary management objective is to maintain community diversity within the park. More specifically, the aim of management is to keep at least a certain fraction of the park, (e.g. 20%) in each of three successional stages. We assume that each year a manager may do one of the following: let wildfires burn unhindered, fight wildfires, or perform controlled burns. We apply stochastic dynamic programming to identify which of these three strategies is optimal, i.e. the one most likely to promote community diversity. Model results indicate that the optimal management strategy depends on the current state of the park, the cost associated with each strategy, and the time frame over which the manager has set his/her goal
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