Field report from sediment coring in peat for landscape analysis in Hjaltadalur, Skagafjörður, north Iceland 2010 : Sediment drilling in Hólar, Vidvik and Kolkuós, Hjaltadalur

This field report presents fieldwork undertaken in Hjaltadalur, Skagafjördur, northern Iceland during summer 2010. The main aim was to initiate coring in selected mires in order to determine the composition of organic material and sediments in the mires, sub-sample for sedimentological and palaeoecological analyses, and initiate advanced landscape analysis of Hjaltadalur. Three mires were selected for sediments coring in Hjaltadalur: Ástunga close to Kolkóus, Hólakot at Viðvik, and Hólar. All three represented a landscape transect in NW to SE direction, from close to the coast to valley interior, i.e. close to the old settlement at Hólar.

The impact of big-boxes on local retail : What happens when IKEA comes to town?

The development of large discount retailers, or big-boxes as they are sometimes referred to, are often subject to heated debate and their entry on a market is greeted with either great enthusiasm or dread. For instance, the world’s largest retailer Wal-Mart (Forbes 2014) has a number of anti- and pro-groups dedicated to its being and the event of a Wal-Mart entry tends to be met with protests and campaigns (Decamme 2013) but also welcomed by, for instance, consumers (Davis & DeBonis 2013). Also in Sweden, the entry of a big box is a hot topic and before IKEA’s opening i Borlänge 2013, the first in Sweden in more than five years, great expectations were mixed with worry (Västerbottens-Kuriren 2011).The presence of large scale discount retailers is not, however, a novel phenomenon but a part of a long-term change in retailing that has taken place globally over the past couple of decades (Taylor & Smalling, 2005). As noted by Dawson (2006), the trend in Europe has over the past few decades gone towards an increasing concentration of large firms along with a decrease of smaller firms.This trend is also detectable in the Swedish retail industry. Over the past decade, the retailing industry in Sweden has increased by around 190 Billion SEK, and its share of GDP has risen from 2,7% to 2,9%, while the number of employees have increased from 200 000 to 250 000 (HUI 2013). This growth, however, has not been distributed evenly but rather it has been oriented mainly towards out-of-town retail clusters. Parallel to this development, the number of large retailers has risen at the expense of market shares of smaller independent firms (Rämme et al 2010). Thereby, the presence of large scale retailers is simply part of a changing retail landscape.The effects of this development, where large scale retailing agents relocate shopping to out-of-town shopping areas, have been heavily debated. On the one hand, the big-boxes are accused of displacing independent small retail businesses in the city-centers and the residential areas, resulting in, to some extent, reduced employment opportunities and less availability for the consumers - especially the elderly (Ljungberg et al 2006). In addition, as access to shopping now tends to require some sort of a motorized vehicle, environmental aspects to the discussion have emerged. Ultimately these types of concerns have resulted in calls for regulations against this development (Olsson 2010). On the other hand, the proponents of the new shopping landscape argue that this evolution implies productivity gains, the benefits of lower prices and an increased variety of products (Maican & Orth 2012). Moreover it is argued that it leads to, for instance, better services (such as longer opening hours) and a creative destruction transformation pressure on retailers, which brings about a renewal of city-centerIIretail and services, increasing their attractivity (Bergström 2010). The belief in benefits of a big box entry can be exemplified by the attractivity of IKEA, and the fact that municipalities are prepared to commit to expenses amounting up to hundreds of millions in order to attract the entry of this big-box. Borlänge municipality, for instance, agreed to expenses of about 350 million SEK in order to secure the entry of IKEA, which opened in 2013 (Blomgren 2009).Against this backdrop, the overall effects of large discount retailers become important: Are the economic benefits enough to warrant subsidies or are there, on the contrary, some very compelling grounds for regulations against these types of establishments? In other words; how is overall retail in a region where a store like IKEA enters affected? And how are local retail firms affected?In order to answer these questions, the purpose of this thesis is to study how entry of a big-box retailer affects the entry region. The object of this study is IKEA - one of the world’s largest retailers, with 345 stores, active in over 40 countries and with profits of about 3.3 billion (IKEA 2013; IKEA 2014). By studying the effects of IKEA-entry, both on an aggregated level and on firm level, this thesis intends to find indications of how large discount retail establishments in general can be expected to affect the economic development both in a region overall, but also on the local firm level, something which is of interest to both policymakers as well as the retailing industry in general.The first paper examines the effects of IKEA on retail revenues and employment in the municipalities that IKEA chose to enter between 2000 and 2011; Gothenburg, Haparanda, Kalmar and Karlstad. By means of a matching method we first identify non-entry municipalities that have a similar probability of IKEA entry as the true entry municipalities. Then, using these non-entry municipalities as a control group, the causal effects of IKEA entry can be estimated using a treatment-control approach. We also extend the analysis to examine the spatial impact of IKEA by estimating the effects on retail in neighboring municipalities. It is found that a new IKEA store increases revenues in durable goods trade with 20% in the entry municipality and the number of employees with 17%. Only small, and in most cases statistically insignificant, negative effects were found in neighboring municipalities.It appears that there is a positive net effect on durables retail sales and employment in the entry municipality. However, the analysis is based on data on an aggregated municipality level and thereby it remains unclear if and how the effects vary within the entry municipalities. In addition, the data used in the first study includes the sales and employment of IKEA itself, which could account for the majority of the increases in employment and retail. Thereby the potential spillover effects on incumbent retailers in the entry municipalities cannot be discerned in the first study.IIITo examine effects of IKEA entry on incumbent retail firms, the second paper in this thesis analyses how IKEA entry affects the revenues and employment of local retail firms in three municipalities; Haparanda, Kalmar and Karlstad, which experienced entry by IKEA between 2000 and 2010. In this second study, we exclude Gothenburg due to the fact that big-box entry appears to have weaker effects in metropolitan areas (as indicated by Artz & Stone 2006). By excluding Gothenburg we aim to reduce the geographical heterogeneity in our study. We obtain control municipalities that are as similar as possible to the three entry municipalities using the same method as in the previous study, but including a slightly different set of variables in the selection equation. Using similar retail firms in the control municipalities as our comparison group, we estimate the impact of IKEA entry on revenues and employment for retail firms located at varying distances from the IKEA entry site.The results generated in this study imply that entry by IKEA increases revenues in incumbent retail firms by, on average, 11% in the entry municipalities. In addition, we do not find any significant impact on retail revenues in the city centers of the entry municipalities. However, we do find that retail firms within 1 km of the IKEA experience increases in revenues of about 26%, which indicates large spillover effects in the area nearby the entry site. As expected, this impact decreases as we expand the buffer zone: firms located between 0-2 km experiences a 14% increase and firms in 2-5 km experiences an increase of 10%. We do not find any significant impacts on retail employment.

Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar)

BACKGROUND: Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. RESULTS: Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. CONCLUSIONS: Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.