The application of the pedigree approach to the distributions foreseen in ecoinvent v3

Purpose

Data used in life cycle inventories are uncertain (Ciroth et al. Int J Life Cycle Assess 9(4):216–226, 2004). The ecoinvent LCI database considers uncertainty on exchange values. The default approach applied to quantify uncertainty in ecoinvent is a semi-quantitative approach based on the use of a pedigree matrix; it considers two types of uncertainties: the basic uncertainty (the epistemic error) and the additional uncertainty (the uncertainty due to using imperfect data). This approach as implemented in ecoinvent v2 has several weaknesses or limitations, one being that uncertainty is always considered as following a lognormal distribution. The aim of this paper is to show how ecoinvent v3 will apply this approach to all types of distributions allowed by the ecoSpold v2 data format.

Methods

A new methodology was developed to apply the semi-quantitative approach to distributions other than the lognormal. This methodology and the consequent formulas were based on (1) how the basic and the additional uncertainties are combined for the lognormal distribution and on (2) the links between the lognormal and the normal distributions. These two points are summarized in four principles. In order to test the robustness of the proposed approach, the resulting parameters for all probability density functions (PDFs) are tested with those obtained through a Monte Carlo simulation. This comparison will validate the proposed approach.

Results and discussion

In order to combine the basic and the additional uncertainties for the considered distributions, the coefficient of variation (CV) is used as a relative measure of dispersion. Formulas to express the definition parameters for each distribution modeling a flow with its total uncertainty are given. The obtained results are illustrated with default values; they agree with the results obtained through the Monte Carlo simulation. Some limitations of the proposed approach are cited.

Conclusions

Providing formulas to apply the semi-quantitative pedigree approach to distributions other than the lognormal will allow the life cycle assessment (LCA) practitioner to select the appropriate distribution to model a datum with its total uncertainty. These data variability definition technique can be applied on all flow exchanges and also on parameters which play an important role in ecoinvent v3.

     

Optimal sampling for pedigree analysis: parameter estimation and genotypic uncertainty

Many problems of sampling strategy arise in pedigree analysis. Although specific questions have been previously considered, there is a need for a general study of the form of the likelihood surface for genetic models. Were genotypes observable, the log-likelihood would have a very simple form. The two classes of factors of genealogical structure affecting general questions of inference are thus those (such as inbreeding or assortive mating) which affect the genotype distribution within a pedigree, and those affecting the extent to which these unobservable genotypes can be inferred from phenotypes. The latter aspect is considered in some detail.     

Inversion of a part of the numerator relationship matrix using pedigree information

Background

In recent theoretical developments, the information available (e.g. genotypes) divides the original population into two groups: animals with this information (selected animals) and animals without this information (excluded animals). These developments require inversion of the part of the pedigree-based numerator relationship matrix that describes the genetic covariance between selected animals (A₂₂). Our main objective was to propose and evaluate methodology that takes advantage of any potential sparsity in the inverse of A₂₂ in order to reduce the computing time required for its inversion. This potential sparsity is brought out by searching the pedigree for dependencies between the selected animals. Jointly, we expected distant ancestors to provide relationship ties that increase the density of matrix A₂₂ but that their effect on A22-1 might be minor. This hypothesis was also tested.

Methods

The inverse of A₂₂ can be computed from the inverse of the triangular factor (T^-1) obtained by Cholesky root-free decomposition of A₂₂. We propose an algorithm that sets up the sparsity pattern of T^-1 using pedigree information. This algorithm provides positions of the elements of T^-1 worth to be computed (i.e. different from zero). A recursive computation of A22-1 is then achieved with or without information on the sparsity pattern and time required for each computation was recorded. For three numbers of selected animals (4000; 8000 and 12 000), A₂₂ was computed using different pedigree extractions and the closeness of the resulting A22-1 to the inverse computed using the fully extracted pedigree was measured by an appropriate norm.

Results

The use of prior information on the sparsity of T^-1 decreased the computing time for inversion by a factor of 1.73 on average. Computational issues and practical uses of the different algorithms were discussed. Cases involving more than 12 000 selected animals were considered. Inclusion of 10 generations was determined to be sufficient when computing A₂₂.

Conclusions

Depending on the size and structure of the selected sub-population, gains in time to compute A22-1 are possible and these gains may increase as the number of selected animals increases. Given the sequential nature of most computational steps, the proposed algorithm can benefit from optimization and may be convenient for genomic evaluations.     

First series of seafood datasets in ecoinvent: setting the pace for future development

The International Journal of Life Cycle Assessment - The number of life cycle assessment studies related to seafood has risen considerably in the past decade. Despite this proliferation, major life...     

Discovery of hidden pedigree errors combining genomic information with the genomic relationship matrix in Texel sheep

Genomic variants such as Single Nucleotide Polymorphisms and animal pedigree are now used widely in routine genetic evaluations of livestock in many countries. The use of genomic information not only can be used to enhance the accuracy of prediction but also to verify pedigrees for animals that are extensively managed using natural mating and enabling multiple-sire mating groups to be used. By so doing, the rate of genetic gain is enhanced, and any bias associated with incorrect pedigrees is removed. This study used a set of 8 764 sheep genotypes to verify the pedigree based on both the conventional opposing homozygote method as well as a novel method when combined with the inclusion of the genomic relationship matrix (GRM). The genomic relationship coefficients between verified pairs of animals showed on average a relationship of 0.50 with parent, 0.25 with grandparent, 0.13 with great grandparent, 0.50 with full-sibling and 0.27 with half-sibling. Minimum obtained values from these verified pairs were then used as thresholds to determine the pedigree for unverified pairs of animals, to detect potential errors in the pedigree. Using a case study from a population partially genotyped UK sheep, the results from this study illustrate a powerful way to resolve parentage inconsistencies, when combining the conventional ‘opposing homozygote’ method using genomic information together with GRM for pedigree checking. In this way, previously undetected pedigree errors can be resolved.     

Extrapolation, uncertainty factors, and the precautionary principle

This essay examines the relationship between the precautionary principle and uncertainty factors used by toxicologists to estimate acceptable exposure levels for toxic chemicals from animal experiments. It shows that the adoption of uncertainty factors in the United States in the 1950s can be understood by reference to the precautionary principle, but not by cost-benefit analysis because of a lack of relevant quantitative data at that time. In addition, it argues that uncertainty factors continue to be relevant to efforts to implement the precautionary principle and that the precautionary principle should not be restricted to cases involving unquantifiable hazards.     

An RFLP linkage map for loblolly pine based on a three-generation outbred pedigree

A genetic linkage map for loblolly pine (Pinus taeda L.) was constructed using segregation data from a three-generation outbred pedigree consisting of four grandparents, two parents, and 95 F₂ progeny. The map was based predominantly on restriction fragment length polymorphism (RFLP) loci detected by cDNA probes. Sixty-five cDNA and three genomic DNA probes revealed 90 RFLP loci. Six polymorphic isozyme loci were also scored. One-fourth (24%) of the cDNA probes detected more than 1 segregating locus, an indication that multigene families are common in pines. As many as six alleles were observed at a single segregating locus among grandparents and it was not unusual for the progeny to segregate for three or four alleles per locus. Multipoint linkage analysis placed 73 RFLP and 2 isozyme loci into 20 linkage groups; the remaining 17 RFLP and 4 isozyme loci were unlinked. The mapped RFLP probes provide a new set of codominant markers for genetic analyses in loblolly pine.     

Selected applications of reduced uncertainty factors in noncancer risk assessment

Guidelines have been developed within the Environmental Protection Agency (EPA) for applying uncertainty factors to noncancer risk assessments. In many recent cases, reduced values for uncertainty factors of less than 10 have been used. The specific circumstances that justify reduced uncertainty are: partial definition of the sensitive subpopulation among humans, partial database limitations, use of a minimal LOAEL, risk assessment for an essential nutrient, and risk assessments based upon studies in nonhuman primates. Details of the rationale for each of these circumstances are provided.     

Prioritizing regionalization efforts in life cycle assessment through global sensitivity analysis: a sector meta-analysis based on ecoinvent v3

The International Journal of Life Cycle Assessment - Regionalization in life cycle assessment (LCA) aims to increase the representativeness of LCA results and reduce the uncertainty due to spatial...     

Polymorphisms in eggshell organic matrix genes are associated with eggshell quality measurements in pedigree Rhode Island Red hens

Novel and traditional eggshell quality measurements were made from up to 2000 commercial pedigree hens for a candidate gene association analysis with organic eggshell matrix genes: ovocleidin-116 , osteopontin ( SPP1 ), ovocalyxin-32 ( RARRES1 ), ovotransferrin ( LTF ), ovalbumin and ovocalyxin-36 , as well as key genes in the maintenance and function of the shell gland [ estrogen receptor ( ESR1 ) and carbonic anhydrase II ( CAII )]. Associations were found for (i) ovalbumin with breaking strength and shell thickness; (ii) ovocleidin-116 with elastic modulus, shell thickness and egg shape; (iii) RARRES1 with mammillary layer thickness; (iv) ESR1 with dynamic stiffness; (v) SPP1 with fracture toughness and (vi) CAII with egg shape. The marker effects are as large as 17% of trait standard deviations and could be used to improve eggshell quality.     

Challenges in inbreeding estimation of large populations based on Polish Holstein-Friesian cattle pedigree

The aim of this study was to evaluate observed and future inbreeding level in Polish Holstein-Friesian cattle population. In total, over 9.8 mln animals were used in the analysis coming from the pedigree of Polish Federation of Cattle Breeders and Dairy Farmers. Inbreeding level, as an average per birth year, was estimated with the method accounting for missing parent information with the assumption of year 1950 as the base year of the population. If an animal had no ancestral records, an average inbreeding level from its birth year was assigned. Twice the average inbreeding level served as relatedness of the animal to the population, which enabled estimation of inbreeding in its offspring. The future inbreeding of potential offspring was estimated as an average of animals (bulls and cows) available for mating in a certain year. It was observed that 30–50% of animals born between 1985 and 2015 had no relevant ancestral information, which is caused by a high number of new animals and/or entire farms entering the national milk recordings. For the year 2015, the observed inbreeding level was 3.30%, which was more than twice the inbreeding with the classical approach (without missing parent information) and higher by 0.4% than the future inbreeding. The average increase of inbreeding in years 2010–2015 was 0.10%, which is similar to other countries monitored by World Holstein-Friesian Federation. However, the values might be underestimated due to low pedigree completeness. The estimates of future inbreeding suggested that observed inbreeding could be even lower and also increase slower, which indicates a constant need to monitor rate of increase in inbreeding over time. The most important aspect of presented results is the necessity to advise individual farmers to keep precise recordings of the matings on their farm in order to improve the pedigree completeness of Polish Holstein-Friesian and to use suitable mating programs to avoid too rapid growth of inbreeding.     

Scientific basis for uncertainty factors used to establish occupational exposure limits for pharmaceutical active ingredients

The traditional “safety factor”; method has been used for years to establish occupational exposure limits (OELs) for active ingredients used in drugs. In the past, a single safety factor was used to address all sources of uncertainty in the limit setting process. The traditional 100‐fold safety factor commonly used to derive an acceptable daily intake value incorporates a default factor of 10 each to account for interindividual variability and interspecies extrapolation. Use of these defaults can lead to overly conservative health‐based limits, especially when they are combined with other (up to 10‐fold) factors to adjust for inadequacies in the available database. In recent years, attempts have been made to quantitate individual sources of uncertainty and variability to improve the scientific basis for OELs. In this paper we discuss the science supporting reductions in the traditional default uncertainty factors. A number of workplace‐specific factors also support reductions in these factors. Recently proposed alternative methodologies provide a framework to make maximum use of preclinical and clinical information, e.g., toxicokinetic and toxicodynamic data, to reduce uncertainties when establishing OELs for pharmaceutical active ingredients.     

Contribution-based prioritization of LCI database improvements: the most important unit processes in ecoinvent

The International Journal of Life Cycle Assessment - Improving the quality and quantity of unit process datasets in Life Cycle Inventory (LCI) databases affects every LCA they are used in. However,...