Effects of elevated atmospheric carbon dioxide on biomass and carbon accumulation in a model regenerating longleaf pine community

Plant species vary in response to atmospheric CO2 concentration due to differences in physiology, morphology, phenology, and symbiotic relationships. These differences make it very difficult to predict how plant communities will respond to elevated CO2. Such information is critical to furthering our understanding of community and ecosystem responses to global climate change. To determine how a simple plant community might respond to elevated CO2, a model regenerating longleaf pine community composed of five species was exposed to two CO2 regimes (ambient, 365 micromol mol(-1) and elevated, 720 micromol mol(-1)) for 3 yr. Total above- and belowground biomass was 70 and 49% greater, respectively, in CO2-enriched plots. Carbon (C) content followed a response pattern similar to biomass, resulting in a significant increase of 13.8 Mg C ha(-1) under elevated CO2. Responses of individual species, however, varied. Longleaf pine (Pinus palustris Mill.) was primarily responsible for the positive response to CO2 enrichment. Wiregrass (Aristida stricta Michx.), rattlebox (Crotalaria rotundifolia Walt. Ex Gmel.), and butterfly weed (Asclepias tuberosa L.) exhibited negative above- and belowground biomass responses to elevated CO2, while sand post oak (Quercus margaretta Ashe) did not differ significantly between CO2 treatments. As with pine, C content followed patterns similar to biomass. Elevated CO2 resulted in alterations in community structure. Longleaf pine comprised 88% of total biomass in CO2-enriched plots, but only 76% in ambient plots. In contrast, wiregrass, rattlebox, and butterfly weed comprised 19% in ambient CO2 plots, but only 8% under high CO2. Therefore, while longleaf pine may perform well in a high CO2 world, other members of this community may not compete as well, which could alter community function. Effects of elevated CO2 on plant communities are complex, dynamic, and difficult to predict, clearly demonstrating the need for more research in this important area of global change science.     

Soil organic carbon and nitrogen accumulation in plots of rhizoma perennial peanut and bahiagrass grown in elevated carbon dioxide and temperature

Carbon sequestration in soils might mitigate the increase of carbon dioxide (CO2) in the atmosphere. Two contrasting subtropical perennial forage species, bahiagrass (BG; Paspalum notatum Flügge; C4), and rhizoma perennial peanut (PP; Arachis glabrata Benth.; C3 legume), were grown at Gainesville, Florida, in field soil plots in four temperature zones of four temperature-gradient greenhouses, two each at CO2 concentrations of 360 and 700 micromol mol(-1). The site had been cultivated with annual crops for more than 20 yr. Herbage was harvested three to four times each year. Soil samples from the top 20 cm were collected in February 1995, before plant establishment, and in December 2000 at the end of the project. Overall mean soil organic carbon (SOC) gains across 6 yr were 1.396 and 0.746 g kg(-1) in BG and PP, respectively, indicating that BG plots accumulated more SOC than PP. Mean SOC gains in BG plots at 700 and 360 micromol mol(-1) CO2 were 1.450 and 1.343 g kg(-1), respectively (not statistically different). Mean SOC gains in PP plots at 700 and 360 micromol mol(-1) CO2 were 0.949 and 0.544 g kg(-1), respectively, an increase caused by elevated CO2. Relative SON accumulations were similar to SOC increases. Overall mean annual SOC accumulation, pooled for forages and CO2 treatments, was 540 kg ha(-1) yr(-1). Eliminating elevated CO2 effects, overall mean SOC accumulation was 475 kg ha(-1) yr(-1). Conversion from cropland to forages was a greater factor in SOC accumulation than the CO2 fertilization effect.     

Experimental oxidative dissolution of sphalerite in the Aznalcollar sludge and other pyritic matrices

After the collapse on 25 Apr. 1998 of the Aznalcóllar mine tailings dike in southwestern Spain, 45 km2 of the Guadiamar valley were covered by a pyritic sludge containing up to 2% sphalerite (ZnS). Later, the sludge was mechanically removed and calcium carbonate was plowed into the soil to immobilize heavy metals. By June 2001 more than 60% of the sulfides in the residual sludge had oxidized and soil Zn contents reached locally phytotoxic levels. Therefore, the oxidative dissolution of sphalerite in the sludge and other pyritic samples was examined. Flow-through oxidation experiments showed that: (i) about 5 and 17% of the sludge Fe and Zn were in soluble form, respectively, because the sludge sample had been partly oxidized in the field; (ii) the oxidation rates of the residual pyrite and sphalerite were similar; (iii) the overall sulfide oxidation rate was relatively unaffected by the addition of calcite; and (iv) poorly crystalline Fe (hydr)oxides containing Zn in occluded form and Zn (hydroxi)carbonates were formed in the presence of calcite. The rate of oxidation of reference sphalerite greatly increased when it was incorporated in the sludge or in a reference pyrite matrix. This enhancement was due to galvanic interaction because pyrite oxidation was depressed in the presence of sphalerite. Oxidation by Fe3+ ions was less important because the oxidation rates of native sphalerite were not greater at low than at high pH. The fast oxidation rate of sphalerite in the Aznalcóllar sludge indicates a need for quick adoption of remediation measures in similar accidents elsewhere. The use of calcite amendments has little influence on the oxidation rate but does result in the accumulation of Zn in relatively insoluble forms.     

Performance characteristics of sequential separation and quantification of lead-210 and polonium-210 by ion exchange chromatography and nuclear spectrometric measurements

A selective separation and quantitative determination procedure for 210Pb and 210Po in various environmental matrices from different sources such as IAEA-326 soil, phosphate rocks (PR), and phosphogypsum (PG) was developed. The tested samples were digested sequentially using concentrated mineral acids (HF, HNO3) by a programmable high-pressure microwave digestion system. The sample solution was loaded onto a preconditioned ion exchange column (Sr-resin) for chromatographic separation. Polonium-210 was eluted by 6 M HNO3 then spontaneously deposited onto polished silver discs to be measured using low-background alpha spectrometry. Lead-210 was sequentially eluted using 6 M HCl solution, precipitated as lead oxalate, dissolved in HNO3 solution, and mixed with scintillation cocktail to be measured by liquid scintillation counting (LSC). Performance of the developed procedure was tested using a reference soil (IAEA-326), with recommended isotope values, that was used as a quality control to assess separation and quantification efficiency (recovery %). The minimum detectable activities of 210Pb and 210Po were found to be 24 and 0.28 Bq kg(-1) for the measurements using LSC and alpha spectrometry, respectively. The recoveries (%) of 210Pb and 210Po were found to be 80 and 60%, respectively. To test the validity of the proposed LSC method, a comparative study was performed by measuring 210Pb activity concentration in test samples by nondestructive gamma-ray spectrometry.     

Bedding and within-pen location effects on feedlot pen runoff quality using a rainfall simulator

Soluble salts, nutrients, and pathogenic bacteria in feedlot-pen runoff have the potential to cause pollution of the environment. A 2-yr study (1998-1999) was conducted at a beef cattle (Bos taurus) feedlot in southern Alberta, Canada, to determine the effect of bedding material [barley (Hordeum vulgare L.) straw versus wood chips] and within-pen location on the chemical and bacterial properties of pen-floor runoff. Runoff was generated with a portable rainfall simulator and analyzed for chemical content (nitrogen [N], phosphorus [P], soluble salts, electrical conductivity [EC], sodium adsorption ratio [SAR], dissolved oxygen [DO], and pH) and populations of three groups of bacteria (Escherichia coli, total coliforms, total aerobic heterotrophs at 27 degrees C) in 1998 and 1999. Bedding had a significant (P < or = 0.05) effect on NH4-N concentration and load in 1999, SO4 load in 1998, SO4 concentration and load in 1999, and total coliforms in both years; where these three variables were higher in wood than straw pens. Location had a significant effect on EC and concentrations of total Kjeldahl nitrogen (TKN), Na, K, SO4, and Cl in 1998, and total coliforms in both years. These seven variables were higher at the bedding pack than pen floor location, indicating that bedding packs were major reservoirs of TKN, soluble salts, and total coliforms. Significantly higher dissolved reactive phosphorus (DRP), total P, and NH4-N concentrations and loads at the bedding pack location in wood pens in 1998, and a similar trend for TKN concentration in 1999, indicated that this bedding-location treatment was a greater source of nutrients to runoff than the other three bedding-location treatments. Bedding, location, and their interaction may therefore be a potential tool to manage nutrients, soluble salts, and bacteria in feedlot runoff.     

EFFECTS OF STATSGO AND SSURGO AS INPUTS ON SWAT MODEL'S SNOWMELT SIMULATION1

ABSTRACT: Soil data comprise a basic input of SWAT (Soil and Water Assessment Tool) for a watershed application. For watersheds where site specific soil data are unavailable, the two U.S. Department of Agriculture (USDA) soil databases, the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) databases, may be the best alternatives. Although it has been noted that SWAT models using the STATSGO and SSURGO data may give different simulation results for water, sediment, and agricultural chemical yields, information is scarce on the effects of using these two databases in predicting streamflows that are predominantly generated from melting snow in spring. The objective of this study was to assess the effects of using STATSGO versus SSURGO as an input for the SWAT model's simulation of the streamflows in the upper 45 percent of the Elm River watershed in eastern North Dakota. Designating the model as SWAT‐STATSGO when the STATSGO data were used and SWAT‐SSURGO when the SSURGO data were used, SWAT‐STATSGO and SWAT‐SSURGO were separately calibrated and validated using the observed daily streamflows. The results indicated that SWAT‐SSURGO provided an overall better prediction of the discharges than SWAT‐STATSGO, although both did a good and comparable job of predicting the high streamflows. However, SWAT‐STATSGO predicted the low streamflows more accurately and had a slightly better performance during the validation period. In addition, the discrepancies between the discharges predicted by these two SWAT models tended to be larger at upstream locations than at those farther downstream within the study area.     

Linkages Between Nutrients and Assemblages of Macroinvertebrates and Fish in Wadeable Streams: Implication to Nutrient Criteria Development

We sampled 240 wadeable streams across Wisconsin for different forms of phosphorus and nitrogen, and assemblages of macroinvertebrates and fish to (1) examine how macroinvertebrate and fish measures correlated with the nutrients; (2) quantify relationships between key biological measures and nutrient forms to identify potential threshold levels of nutrients to support nutrient criteria development; and (3) evaluate the importance of nutrients in influencing biological assemblages relative to other physicochemical factors at different spatial scales. Twenty-three of the 35 fish and 18 of the 26 macroinvertebrate measures significantly correlated (P < 0.05) with at least one nutrient measure. Percentages of carnivorous, intolerant, and omnivorous fishes, index of biotic integrity, and salmonid abundance were fish measures correlated with the most nutrient measures and had the highest correlation coefficients. Percentages of Ephemeroptera–Plecoptera–Trichoptera individuals and taxa, Hilsenhoff biotic index, and mean tolerance value were macroinvertebrate measures that most strongly correlated with the most nutrient measures. Selected biological measures showed clear trends toward degradation as concentrations of phosphorus and nitrogen increased, and some measures showed clear thresholds where biological measures changed drastically with small changes in nutrient concentrations. Our selected environmental factors explained 54% of the variation in the fish assemblages. Of this explained variance, 46% was attributed to catchment and instream habitat, 15% to nutrients, 3% to other water quality measures, and 36% to the interactions among all the environmental variables. Selected environmental factors explained 53% of the variation in macroinvertebrate assemblages. Of this explained variance, 42% was attributed to catchment and instream habitat, 22% to nutrients, 5% to other water quality measures, and 32% to the interactions among all the environmental variables.     

Predicting Opportunities for Greening and Patterns of Vegetation on Private Urban Lands

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: “possible stewardship,” which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and “realized stewardship,” which is the proportion of possible stewardship land upon which vegetation is growing. These measures were calculated at the parcel level and averaged by US Census block group. Realized stewardship was further defined by proportion of tree canopy and grass. Expenditures on yard supplies and services, available by block group, were used to help understand where vegetation condition appears to be the result of current activity, past legacies, or abandonment. PRIZM™ market segmentation data were tested as categorical predictors of possible and realized stewardship and yard expenditures. PRIZM™ segmentations are hierarchically clustered into 5, 15, and 62 categories, which correspond to population density, social stratification (income and education), and lifestyle clusters, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and population density were found to be critical determinants of both stewardship metrics. A number of lifestyle factors, such as average family size, marriage rates, and percentage of single-family detached homes, were strongly related to realized stewardship. The percentage of African Americans by block group was positively related to realized stewardship but negatively related to yard expenditures.     

Using GIS to Generate Spatially Balanced Random Survey Designs for Natural Resource Applications

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.     

An integrated impact assessment and weighting methodology: evaluation of the environmental consequences of computer display technology substitution

Computer display technology is currently in a state of transition, as the traditional technology of cathode ray tubes is being replaced by liquid crystal display flat-panel technology. Technology substitution and process innovation require the evaluation of the trade-offs among environmental impact, cost, and engineering performance attributes. General impact assessment methodologies, decision analysis and management tools, and optimization methods commonly used in engineering cannot efficiently address the issues needed for such evaluation. The conventional Life Cycle Assessment (LCA) process often generates results that can be subject to multiple interpretations, although the advantages of the LCA concept and framework obtain wide recognition. In the present work, the LCA concept is integrated with Quality Function Deployment (QFD), a popular industrial quality management tool, which is used as the framework for the development of our integrated model. The problem of weighting is addressed by using pairwise comparison of stakeholder preferences. Thus, this paper presents a new integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), to assess the environmental behavior of alternative technologies in correlation with their performance and economic characteristics. Computer display technology is used as the case study to further develop our methodology through the modification and integration of various quality management tools (e.g., process mapping, prioritization matrix) and statistical methods (e.g., multi-attribute analysis, cluster analysis). Life cycle thinking provides the foundation for our methodology, as we utilize a published LCA report, which stopped at the characterization step, as our starting point. Further, we evaluate the validity and feasibility of our methodology by considering uncertainty and conducting sensitivity analysis.