A Dynamic Model for Determining the Temporal Distribution of Environmental Burden

Abstract: In an article on the role of temporal information in life-cycle assessment in this journal, Field and colleagues argued that frequently it is not the single product but the "fleet" (or cohort) of products that "is the appropriate unit of analysis," and that in focusing on the fleet one "explicitly introduces the notion of time as a critical element of comparative life-cycle assessments. …" Major transitions, such as replacement of one fleet of products by an alternative fleet, correspond to a system in a transient rather than steady state, and explicit consideration of time is central to transient analysis.
One tool increasingly used as part of life-cycle assessment, economic input-output (EIO) analysis, at best deals with time in an implicit fashion. This article illustrates how the sequential interindustry model (SIM), a formulation of the EIOmodel that explicitly represents time, might be utilized in life-cycle assessment. SIM introduces this temporal component by explicitly accounting for the time required by production activities and the resulting sequencing of the inputs. This can be thought of as engineering rather than accounting information. The data demands of such a model are not likely to be met at present or at any time in the near future. Even so, simulation methods and the use of so-called synthetic data have a history of productive use in a number of fields, including the social sciences.
SIM also utilizes the contribution of Joshi on the application of the EIO model to environmental impact and the inclusion of the use as well as the production phases of a product in EIO analysis. The possibility of accounting for discounting of future events, with its impact on decision making, is also briefly discussed.     

Characterizing,Propagating, and Analyzing Uncertainty in Life‐Cycle Assessment: A Survey of Quantitative Approaches

Life‐cycle assessment (LCA) practitioners build models to quantify resource consumption, environmental releases, and potential environmental and human health impacts of product systems. Most often, practitioners define a model structure, assign a single value to each parameter, and build deterministic models to approximate environmental outcomes. This approach fails to capture the variability and uncertainty inherent in LCA. To make good decisions, decision makers need to understand the uncertainty in and divergence between LCA outcomes for different product systems. Several approaches for conducting LCA under uncertainty have been proposed and implemented. For example, Monte Carlo simulation and fuzzy set theory have been applied in a limited number of LCA studies. These approaches are well understood and are generally accepted in quantitative decision analysis. But they do not guarantee reliable outcomes. A survey of approaches used to incorporate quantitative uncertainty analysis into LCA is presented. The suitability of each approach for providing reliable outcomes and enabling better decisions is discussed. Approaches that may lead to overconfident or unreliable results are discussed and guidance for improving uncertainty analysis in LCA is provided.     

A Spatial Modeling Approach to Identify Potential Butternut Restoration Sites in Mammoth Cave National Park

Incorporation of disease resistance is nearly complete for several important North American hardwood species threatened by exotic fungal diseases. The next important step toward species restoration would be to develop reliable tools to delineate ideal restoration sites on a landscape scale. We integrated spatial modeling and remote sensing techniques to delineate potential restoration sites for Butternut (Juglans cinerea L.) trees, a hardwood species being decimated by an exotic fungus, in Mammoth Cave National Park (MCNP), Kentucky. We first developed a multivariate habitat model to determine optimum Butternut habitats within MCNP. Habitat characteristics of 54 known Butternut locations were used in combination with eight topographic and land use data layers to calculate an index of habitat suitability based on Mahalanobis distance (D²). We used a bootstrapping technique to test the reliability of model predictions. Based on a threshold value for the D² statistic, 75.9% of the Butternut locations were correctly classified, indicating that the habitat model performed well. Because Butternut seedlings require extensive amounts of sunlight to become established, we used canopy cover data to refine our delineation of favorable areas for Butternut restoration. Areas with the most favorable conditions to establish Butternut seedlings were limited to 291.6 ha. Our study provides a useful reference on the amount and location of favorable Butternut habitat in MCNP and can be used to identify priority areas for future Butternut restoration. Given the availability of relevant habitat layers and accurate location records, our approach can be applied to other tree species and areas.     

The North Atlantic Oscillation and regional phenology prediction over Europe

We present an integrated modeling study designed to investigate changes in ecosystem level phenology over Europe associated with changes in climate pattern, by the North Atlantic Oscillation (NAO). We derived onset dates from processed NDVI data sets and used growing degree day (GDD) summations from the NCEP re‐analysis to calibrate and validate a phenology model to predict the onset of the growing season over Europe. In a cross‐validation hindcast, the model (PHENOM) is able to explain 63% of the variance in onset date for grid cells containing at least 50% mixed and boreal forest. Using a model developed from previous work we performed climate change scenarios, generating synthetic temperature and GDD distributions under a hypothetically increasing NAO. These new distributions were used to drive PHENOM and project changes in the timing of onset for forested cells over Europe. Results from the climate change scenarios indicate that, if the current trend in the NAO continues, there is the potential for a continued advance to the start of the growing season by as much as 13 days in some areas.     

Large-scale spatial and temporal dynamics of the vulnerable and highly mobile superb parrot

Aim To investigate the spatial and temporal dynamics of the vulnerable and highly mobile superb parrot (Polytelis swainsonii) across its range in south‐eastern mainland Australia. Location South‐eastern Australia (27°–37° S latitude and 141°–151° E longitude). Methods We used generalized additive models (GAMs) to model time‐specific bird atlas occurrence data against time‐specific plant productivity data, plus a range of environmental predictor variables. We then examined the effects of environmental variables on the temporal and spatial patterns of predicted abundance and distribution of the superb parrot using a correlative mapping approach. Results Key findings from GAM analysis were: (1) there was a strong positive relationship between abundance and plant productivity in all regions, but (2) the response of abundance to other predictor variables often differed between regions. Correlative mapping predictions of the abundance and distribution of the superb parrot also indicated that: (1) predicted abundance varied through time and space, (2) predicted abundance sometimes decreased in all regions, but at other times some regions had high abundance when others had low, and (3) changes in plant productivity (and therefore climate) were associated with this variation. Main conclusion The superb parrot favours productive landscapes that are also favoured for agriculture. Movements appear to be associated with seasonal and year to year climate variability. Thus, variation in the recorded abundance of the superb parrot may mask population trends, suggesting that existing population estimates are unreliable. Also, high abundances in some areas, and at some times, may reflect deteriorating habitat conditions elsewhere rather than species recovery. Temporal variability in the distribution of the superb parrot makes it difficult to identify specific drought refugia. Consequently, through time, as key habitat continues to deteriorate, the species will become increasingly vulnerable and threatened. Whole‐landscape habitat conservation and restoration strategies are therefore needed to sustain superb parrot populations in the long‐term.     

Estimating the effect of inbreeding on survival

Conservation biologists need to be able to estimate reliably the effects of inbreeding on survival, and need to be able to do so with a range of different data types. Kalinowski and Hedrick described a non-linear maximum likelihood estimation procedure for modelling relationships between survivorship and inbreeding. Although their method is useful for illustrating the concepts involved in modelling such relationships, it is only applicable to simple datasets. We illustrate that the parameter estimates generated by Kalinowski and Hedrick's method are easily obtained using generalized linear modelling procedures available in standard statistical packages, and that these offer several advantages even with simple datasets. We suggest procedures that can be used for modelling relationships between survival and inbreeding with more complex data types, including datasets with multiple and ragged encounters, uncertain detection and random effects.     

Structure-function relationship studies of PTH(1-11) analogues containing sterically hindered dipeptide mimetics.

The N-terminal 1-34 fragment of parathyroid hormone (PTH) is fully active in vitro and in vivo and reproduces all biological responses characteristic of the native intact PTH. In order to develop safer and non-parenteral PTH-like bone anabolic agents, we have studied the effect of introducing conformationally constrained dipeptide mimetics into the N-terminal portion of PTH in an effort to generate miniaturized PTH-mimetics. To this end, we have synthesized and conformationally and biologically characterized PTH(1-11) analogues containing 3R-carboxy-6S-amino-7,5-bicyclic thiazolidinlactam (7,5-bTL), a rigidified dipeptide mimetic unit. The wild type sequence of PTH(1-11) is H-Ser-Val-Ser-Glu-Ile-Gln-Leu-Met-His-Asn-Leu-NH(2). The following pseudo-undecapeptides were prepared: [Ala(1), 7,5-bTL(3, 4), Nle(8), Arg(11)]hPTH(1-11)NH(2) (I); [Ala(1), 7,5-bTL(6, 7), Nle(8), Arg(11)]hPTH(1-11)NH(2) (II); [Ala(1), Nle(8), 7,5-bTL(9, 10), Arg(11)]hPTH(1-11)NH(2) (III). In aqueous solution containing 20% TFE, only analogue I exhibited the typical CD pattern of the alpha-helical conformation. NMR experiments and molecular dynamics calculations located the alpha-helical stretch in the sequence Ile(5)-His(9). The dipeptide mimetic unit 7,5-bTL induces a type III beta-turn, occupying the positions i - 1 and i of the turn. Analogue II exhibited an equilibrium between a type I beta-turn and an alpha-helix, and analogue III did not show any ordered structure. Biological tests revealed poor activity for all analogues (EC(50) > 0.1 mM). Apparently, the relative side-chain orientation of Val(2), Ile(5) and Met(8) can be critical for effective analogue-receptor interaction. Considering helicity as an essential property to obtain active PTH agonists, one must decorate the correctly positioned dipeptide mimetic azabicycloalkane scaffold with substitutions corresponding to the displaced amino acids.     

One pot synthesis of GDP‐mannose by a multi‐enzyme cascade for enzymatic assembly of lipid‐linked oligosaccharides

Glycosylation of proteins is a key function of the biosynthetic‐secretory pathway in the endoplasmic reticulum (ER) and Golgi apparatus. Glycosylated proteins play a crucial role in cell trafficking and signaling, cell‐cell adhesion, blood‐group antigenicity, and immune response. In addition, the glycosylation of proteins is an important parameter in the optimization of many glycoprotein‐based drugs such as monoclonal antibodies. In vitro glycoengineering of proteins requires glycosyltransferases as well as expensive nucleotide sugars. Here, we present a designed pathway consisting of five enzymes, glucokinase (Glk), phosphomannomutase (ManB), mannose‐1‐phosphate‐guanyltransferase (ManC), inorganic pyrophosphatase (PmPpA), and 1‐domain polyphosphate kinase 2 (1D‐Ppk2) expressed in E. coli for the cell‐free production and regeneration of GDP‐mannose from mannose and polyphosphate with catalytic amounts of GDP and ADP. It was shown that GDP‐mannose is produced at various conditions, that is pH 7–8, temperature 25–35°C and co‐factor concentrations of 5–20 mM MgCl₂. The maximum reaction rate of GDP‐mannose achieved was 2.7 μM/min at 30°C and 10 mM MgCl₂ producing 566 nmol GDP‐mannose after a reaction time of 240 min. With respect to the initial GDP concentration (0.8 mM) this is equivalent to a yield of 71%. Additionally, the cascade was coupled to purified, transmembrane‐deleted Alg1 (ALG1ΔTM), the first mannosyltransferase in the ER‐associated lipid‐linked oligosaccharide (LLO) assembly. Thereby, in a one‐pot reaction, phytanyl‐PP‐(GlcNAc)₂‐Man₁ was produced with efficient nucleotide sugar regeneration for the first time. Phytanyl‐PP‐(GlcNAc)₂‐Man₁ can serve as a substrate for the synthesis of LLO for the cell‐free in vitro glycosylation of proteins. A high‐performance anion exchange chromatography method with UV and conductivity detection (HPAEC‐UV/CD) assay was optimized and validated to determine the enzyme kinetics. The established kinetic model enabled the optimization of the GDP‐mannose regenerating cascade and can further be used to study coupling of the GDP‐mannose cascade with glycosyltransferases. Overall, the study envisages a first step towards the development of a platform for the cell‐free production of LLOs as precursors for in vitro glycoengineering of proteins.