The cause and influence of self-cementing properties of fine recycled concrete aggregates on the properties of unbound sub-base

The use of coarse recycled concrete aggregates (CRCA) in conjunction with fine recycled concrete aggregates (FRCA) as sub-base materials has been widely studied. Although research results indicate that it is feasible to employ both CRCA and FRCA as granular sub-base, the influence of the unhydrated cement in the adhered mortar of the RCA on the properties of the sub-base materials has not been thoroughly studied. Generally, it is known that the strength of the sub-base materials prepared with RCA increases over time. However, this mechanism, known as the self-cementing properties, is not well understood and is believed to be governed by the properties of the fine portion of the RCA (<5mm). This paper presents an investigation on the cause of the self-cementing properties by measuring X-ray diffraction patterns, pH values, compressive strength and permeability of various size fractions of the FRCA obtained from a commercially operated construction and demolition waste recycling plant. Their influence on the overall sub-base materials was determined. The results indicate that the size fractions of <0.15 and 0.3-0.6mm (active fractions) were most likely to be the principal cause of the self-cementing properties of the FRCA. However, the effects on the properties of the overall RCA sub-base materials were minimal if the total quantity of the active fractions was limited to a threshold by weight of the total fine aggregate.     

Evaluating Ecological Condition Using Soil Biogeochemical Parameters and Near Infrared Reflectance Spectra

Rapid, repeatable assessment of ecological condition is critical for quantitative ecosystem monitoring. Soils provide a sensitive, integrative indicator for which sampling and analysis techniques are well defined. We evaluated soil properties as indicators of ecological condition (subjectively classified into minimally/moderately/severely degraded based on vegetative, hydrologic and edaphic cues) at 526 sites within Ft. Benning military installation (Georgia, USA). For each sample, we measured 17 biogeochemical parameters, and collected high-resolution diffuse reflectance spectra using visible/near infrared reflectance spectroscopy (VNIRS). VNIR spectra have been related to numerous soil attributes — we examine them here for diagnosing integrated response (i.e., ecological condition). We used ordinal logistic regression (OLR) and classification trees (CT) to discriminate between condition categories using both sets of predictors (biogeochemistry and spectra). Sixteen biogeochemical parameters were significantly different across condition categories; however, multivariate models greatly improved discrimination ([calibration, validation] accuracy of [69%, 66%] and [96%, 73%] for OLT and CT models, respectively). Important predictors included total C, total P, and Mehlich K/Ca/Mg. VNIR spectra further improved discrimination ([calibration, validation] accuracy of [74%, 70%] and [96%, 75%] for OLR and CT models, respectively). While spectra were comparably effective at discriminating minimally degraded sites, they were significantly more effective at discriminating severely degraded sites. Error rates across confounding factors suggest that watershed of origin and landscape position were the only important confounders, likely due to imbalanced sampling. We conclude that multivariate diagnosis improves accuracy, and that VNIR spectroscopy, which yields substantial cost and logistical improvements over conventional analyses, provides an effective tool for rapid condition diagnosis.     

Landscape resistance to dispersal: simulating long-term effects of human disturbance on a small and isolated wolf population in southwestern Manitoba, Canada

Landscape fragmentation affects wildlife population viability, in part, through the effects it has on individual dispersal. In addition, some forms of human disturbance impinge on dispersal without physically fragmenting habitats. Here, we use the term "landscape resistance" to capture constraints to dispersal that cannot be linked directly to fragmentation. The extent to which landscape resistance can influence population persistence is not well understood. Agricultural development over the past 60?years has resulted in considerable habitat fragmentation in the Riding Mountain National Park (RMNP) region in southwestern Manitoba, Canada. We examined how park boundaries, roads outside park boundaries and negative human attitudes have altered dispersal success and population persistence. We examined whether stochastic disturbance, representing infectious disease epidemics, further reduced long-term population persistence for various scenarios. Finally, we assessed whether the simultaneous occurrence of the three features had additive effects. We simulated dispersal using HexSim, a spatially explicit individual-based population model, parameterised with data on wolves (Canis lupus) in the RMNP region. Simulations that separately accounted for negative human attitudes and roads outside the park boundaries exhibited lower mean population size than those that ignored these details. Increasing deflection from park boundaries did not appear to have significant impacts. Our results did not indicate the presence of additive effects, and scenarios incorporating all three features had similar results as that of roads. Stochastic disturbance further reduced mean population size. Our results do illustrate how less-visible human disturbances (i.e. those that do not clearly alter landscape characteristics) can significantly limit dispersal and population persistence.     

A comparative assessment of molecular biological and direct microscopic techniques for assessing aquatic systems

Molecular techniques have clear value for community characterization; however, almost all previous datasets are based upon non-molecular measurements and it is hard to compare "old" data with "new" data because few correlations have been made. Therefore, the purpose of this evaluation was to simultaneously use molecular and non-molecular methods within the same sampling program to determine how data compare. Three methods were used for characterizing microbial populations in Lake 260 (L260) at Experimental Lakes Area (Ontario, Canada) during a whole-lake exposure study. Methods included whole-cell microscopic counts (for bacteria, cyanobacteria, algae and zooplankton), chlorophyll a, and small sub-unit (ssu)-rRNA hybridization using EUB-338, EUB-785, CYAN-785-a/b, EUCA-1379 and UNIV-1390 gene probes. Strong correlations were found between the EUB-785 probe signal and "bacteria minus cyanobacteria" direct counts, and the EUB-338 probe signal and "bacteria plus cyanobacteria" counts. Furthermore, the difference in probe signal between EUB-338 and EUB-785 (a presumptive signature for cyanobacteria and plastids) correlated with cyanobacterial direct counts and also with chlorophyll a. However, EUCA-1379 probe signal did not correlate with algae counts, and UNIV-1390 probe signal only correlated with total bacteria counts. Results suggest that, although ssu-rRNA methods are fast, reproducible, and specifically detect "viable" organisms, their use may be limited to non-eukaryotic populations unless new probes are developed that are more specific.     

Regional data refine local predictions: modeling the distribution of plant species abundance on a portion of the central plains

Species distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the consequences of extrapolating locally collected data to regional landscapes. Similarly, the process of using regional data to inform local prediction for species distribution models has not been adequately evaluated. Using boosted regression trees, we examined errors associated with extrapolating models developed with locally collected abundance data to regional-scale spatial extents and associated with using regional data for predictions at a local extent for a native and non-native plant species across the northeastern central plains of Colorado. Our objectives were to compare model results and accuracy between those developed locally and extrapolated regionally, those developed regionally and extrapolated locally, and to evaluate extending species distribution modeling from predicting the probability of presence to predicting abundance. We developed models to predict the spatial distribution of plant species abundance using topographic, remotely sensed, land cover and soil taxonomic predictor variables. We compared model predicted mean and range abundance values to observed values between local and regional. We also evaluated model prediction performance based on Pearson's correlation coefficient. We show that: (1) extrapolating local models to regional extents may restrict predictions, (2) regional data can help refine and improve local predictions, and (3) boosted regression trees can be useful to model and predict plant species abundance. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network may improve our ability to monitor changes in local species abundance.     

The value of long-term environmental monitoring programs: an Ohio River case study

As a subset of environmental monitoring, fish sampling programs have been an important part of assessing the potential impacts of water withdrawals and effluent discharges on fish populations for many years. New environmental regulations often require that adverse environmental impacts to fish populations be minimized. Without long-term field data, population evaluations may incorrectly indicate adverse impacts where none exist or no impact where one is likely to occur. Several electric utility companies have funded the Ohio River Ecological Research Program, which has been in existence for over 40 years and consists of fish, habitat, and water quality studies at multiple power plant sites on the mainstem Ohio River. Sampling includes seasonal night-time electrofishing and daytime beach seining at three upstream and three downstream locations near each plant. The long-term nature of the program allows for the establishment of aquatic community indices to support evaluations of technology performance, the collaborative development of compliance metrics, and the assessment of fish population trends. Studies have concluded that the Ohio River fish community has improved in response to better water quality and that power plant fish entrainment and impingement and thermal discharges have had little or no measureable impact. Through collaboration and the use of long-term data, $6.3 million in monitoring costs have been saved during recent fish impingement studies. The ability to access a multiyear fish abundance database, with its associated data on age, growth, and fecundity, improves the quality of such evaluations and reduces the need for extensive field sampling at individual locations.     

Fingerprinting of petroleum hydrocarbons (PHC) and other biogenic organic compounds (BOC) in oil-contaminated and background soil samples

Total petroleum hydrocarbons (TPH) or petroleum hydrocarbons (PHC) are one of the most widespread soil contaminants in Canada, the United States and many other countries worldwide. Clean-up of PHC-contaminated soils costs the Canadian economy hundreds of millions of dollars annually. In Canada, most PHC-contaminated site evaluations are based on the methods developed by the Canadian Council of the Ministers of the Environment (CCME). However, the CCME method does not differentiate PHC from BOC (the naturally occurring biogenic organic compounds), which are co-extracted with petroleum hydrocarbons in soil samples. Consequently, this could lead to overestimation of PHC levels in soil samples. In some cases, biogenic interferences can even exceed regulatory levels (300 μg g(-1) for coarse soils and 1300 μg g(-1) for fine soils for Fraction 3, C(16)-C(34) range, in the CCME Soil Quality Level). Resulting false exceedances can trigger unnecessary and costly cleanup or remediation measures. Therefore, it is critically important to develop new protocols to characterize and quantitatively differentiate PHC and BOC in contaminated soils. The ultimate objective of this PERD (Program of Energy Research and Development) project is to correct the misconception that all detectable hydrocarbons should be regulated as toxic petroleum hydrocarbons. During 2009-2010, soil and plant samples were collected from over forty oil-contaminated and paired background sites in various provinces. The silica gel column cleanup procedure was applied to effectively remove all target BOC from the oil-contaminated sample extracts. Furthermore, a reliable GC-MS method in combination with the derivatization technique, developed in this laboratory, was used for identification and characterization of various biogenic sterols and other major biogenic compounds in these oil-contaminated samples. Both PHC and BOC in these samples were quantitatively determined. This paper reports the characterization results of this set of 21 samples. In general, the presence of petroleum-characteristic alkylated PAH homologues and biomarkers can be used as unambiguous indicators of the contamination of oil and petroleum product hydrocarbons; while the absence of petroleum-characteristic alkylated PAH homologues and biomarkers and the presence of abundant BOC can be used as unambiguous indicators of the predominance of natural organic compounds in soil samples.     

An Integrated Ecosystem Assessment of the Interior Columbia Basin

Driven by the need to replace interim direction, address recent species listings as threatened or endangered under the Endangered Species Act, and break the gridlock of implementing actions, the U.S. Department of Agriculture, Forest Service (FS) and the U.S. Department of the Interior, Bureau of Land Management (BLM), initiated an effort to develop a scientifically-sound, ecosystem-based strategy for lands they administer in the Interior Columbia Basin. The effort included an integrated assessment of 58.3 million ha in seven states describing the Basin's current conditions and risks associated with different management strategies. The assessment provides the foundation for environmental impact statements outlining management direction for 31 million hectares of FS and BLM administered lands. The process produced a framework for ecosystem management, ecosystem component (social, economic, landscape, terrestrial, and aquatic) assessments, and estimates of ecological integrity and socioeconomic resiliency.     

Agrochemical spray drift; assessment and mitigation--a review

During application of agrochemicals spray droplets can drift beyond the intended target to non-target receptors, including water, plants and animals. Factors affecting this spray drift include mode of application, droplet size, which can be modified by the nozzle types, formulation adjuvants, wind direction, wind speed, air stability, relative humidity, temperature and height of released spray relative to the crop canopy. The rate of fall of spray droplets depends upon the size of the droplets but is modified by entrainment in a mobile air mass and is also influenced by the rate of evaporation of the liquid constituting the aerosol. The longer the aerosol remains in the air before falling to the ground (or alternatively striking an object above ground) the greater the opportunity for it to be carried away from its intended target. In general, all size classes of droplets are capable of movement off target, but the smallest are likely to move the farthest before depositing on the ground or a non-target receptor. It is not possible to avoid spray drift completely but it can be minimized by using best-management practices. These include using appropriate nozzle types, shields, spray pressure, volumes per area sprayed, tractor speed and only spraying when climatic conditions are suitable. Field layout can also influence spray drift, whilst crop-free and spray-free buffer zones and windbreak crops can also have a mitigating effect. Various models are available to estimate the environmental exposure from spray drift at the time of application.