Projecting the fate of fish populations using ecological-economic modeling

Four marine fish species are among the most important on the world market: cod, salmon, tuna, and sea bass. While the supply of North American and European markets for two of these species - Atlantic salmon and European sea bass - mainly comes from fish farming, Atlantic cod and tunas are mainly caught from wild stocks. We address the question what will be the status of these wild stocks in the midterm future, in the year 2048, to be specific. Whereas the effects of climate change and ecological driving forces on fish stocks have already gained much attention, our prime interest is in studying the effects of changing economic drivers, as well as the impact of variable management effectiveness. Using a process-based ecological-economic multispecies optimization model, we assess the future stock status under different scenarios of change. We simulate (i) technological progress in fishing, (ii) increasing demand for fish, and (iii) increasing supply of farmed fish, as well as the interplay of these driving forces under different sce- narios of (limited) fishery management effectiveness. We find that economic change has a substantial effect on fish populations. Increasing aquaculture production can dampen the fishing pressure on wild stocks, but this effect is likely to be overwhelmed by increasing demand and technological progress, both increasing fishing pressure. The only solution to avoid collapse of the majority of stocks is institutional change to improve management effectiveness significantly above the current state. We conclude that full recognition of economic drivers of change will be needed to successfully develop an integrated ecosystem management and to sustain the wild fish stocks until 2048 and beyond.

Abundance, biomass and secondary production of benthic megafauna on the Barents Sea shelf in 2008 and 2009

Megabenthos plays a major role in the overall energy flow on Arctic shelves, but information on megabenthic secondary production on large spatial scales is scarce. Here, we estimated for the first time megabenthic secondary production for the entire Barents Sea shelf by applying a species-based empirical model to an extensive dataset from the joint Norwegian? Russian ecosystem survey. Spatial patterns and relationships were analyzed within a GIS. The environmental drivers behind the observed production pattern were identified by applying an ordinary least squares regression model. Geographically weighted regression (GWR) was used to examine the varying relationship of secondary production and the environment on a shelfwide scale. Significantly higher megabenthic secondary production was found in the northeastern, seasonally ice-covered regions of the Barents Sea than in the permanently ice-free southwest. The environmental parameters that significantly relate to the observed pattern are bottom temperature and salinity, sea ice cover, new primary production, trawling pressure, and bottom current speed. The GWR proved to be a versatile tool for analyzing the regionally varying relationships of benthic secondary production and its environmental drivers (R² = 0.73). The observed pattern indicates tight pelagic? benthic coupling in the realm of the productive marginal ice zone. Ongoing decrease of winter sea ice extent and the associated poleward movement of the seasonal ice edge point towards a distinct decline of benthic secondary production in the northeastern Barents Sea in the future.

Collection of aboveground community and species-specific plant biomass from the Jena Experiment (time series since 2002).

This data set comprises time series of aboveground community plant biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of several experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). Aboveground community biomass was normally harvested twice a year just prior to mowing (during peak standing biomass twice a year, generally in May and August; in 2002 only once in September) on all experimental plots in the Jena Experiment. This was done by clipping the vegetation at 3 cm above ground in up to four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned by random selection of new coordinates every year within the core area of the plots. The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship. The following series of datasets are contained in this collection: 1. Plant biomass form the Main Experiment: In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). 2. Plant biomass from the Dominance Experiment: In the Dominance Experiment, 206 grassland plots of 3.5 x 3.5 m were established from a pool of 9 species that can be dominant in semi-natural grassland communities of the study region. In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 3, 4, 6, and 9 species). 3. Plant biomass from the monoculture plots: In the monoculture plots the sown plant community contains only a single species per plot and this species is a different one for each plot. Which species has been sown in which plot is stated in the plot information table for monocultures (see further details below). The monoculture plots of 3.5 x 3.5 m were established for all of the 60 plant species of the Jena Experiment species pool with two replicates per species like the other experiments in May 2002. All plots were maintained by bi-annual weeding and mowing.

Long-term chemical characterization of aerosols at CVAO from 2007 to 2011

The first long-term aerosol sampling and chemical characterization results from measurements at the Cape Verde Atmospheric Observatory (CVAO) on the island of São Vicente are presented and are discussed with respect to air mass origin and seasonal trends. In total 671 samples were collected using a high-volume PM10 sampler on quartz fiber filters from January 2007 to December 2011. The samples were analyzed for their aerosol chemical composition, including their ionic and organic constituents. Back trajectory analyses showed that the aerosol at CVAO was strongly influenced by emissions from Europe and Africa, with the latter often responsible for high mineral dust loading. Sea salt and mineral dust dominated the aerosol mass and made up in total about 80% of the aerosol mass. The 5-year PM10 mean was 47.1 ± 55.5 µg/m**2, while the mineral dust and sea salt means were 27.9 ± 48.7 and 11.1 ± 5.5 µg/m**2, respectively. Non-sea-salt (nss) sulfate made up 62% of the total sulfate and originated from both long-range transport from Africa or Europe and marine sources. Strong seasonal variation was observed for the aerosol components. While nitrate showed no clear seasonal variation with an annual mean of 1.1 ± 0.6 µg/m**3, the aerosol mass, OC (organic carbon) and EC (elemental carbon), showed strong winter maxima due to strong influence of African air mass inflow. Additionally during summer, elevated concentrations of OM were observed originating from marine emissions. A summer maximum was observed for non-sea-salt sulfate and was connected to periods when air mass inflow was predominantly of marine origin, indicating that marine biogenic emissions were a significant source. Ammonium showed a distinct maximum in spring and coincided with ocean surface water chlorophyll a concentrations. Good correlations were also observed between nss-sulfate and oxalate during the summer and winter seasons, indicating a likely photochemical in-cloud processing of the marine and anthropogenic precursors of these species. High temporal variability was observed in both chloride and bromide depletion, differing significantly within the seasons, air mass history and Saharan dust concentration. Chloride (bromide) depletion varied from 8.8 ± 8.5% (62 ± 42%) in Saharan-dust-dominated air mass to 30 ± 12% (87 ± 11%) in polluted Europe air masses. During summer, bromide depletion often reached 100% in marine as well as in polluted continental samples. In addition to the influence of the aerosol acidic components, photochemistry was one of the main drivers of halogenide depletion during the summer; while during dust events, displacement reaction with nitric acid was found to be the dominant mechanism. Positive matrix factorization (PMF) analysis identified three major aerosol sources: sea salt, aged sea salt and long-range transport. The ionic budget was dominated by the first two of these factors, while the long-range transport factor could only account for about 14% of the total observed ionic mass.

How Much Greater Than the Sum of Its Parts? Evaluating Interactions Between Complex Policies

This presentation focuses on methods for the evaluation of complex policies. In particular, it focuses on evaluating interactions between policies and the extent to which two or more interacting policies mutually reinforce or hinder one another, in the area of environmental sustainability. Environmental sustainability is increasingly gaining recognition as a complex policy area, requiring a more systemic perspective and approach (e.g. European Commission, 2011). Current trends in human levels of resource consumption are unsustainable, and single solutions which target isolated issues independently of the broader context have so far fallen short. Instead there is a growing call among both academics and policy practitioners for systemic change which acknowledges and engages with the complex interactions, barriers and opportunities across the different actors, sectors, and drivers of production and consumption. Policy mixes, and the combination and ordering of policies within, therefore become an important focus for those aspiring to design and manage transitions to sustainability. To this end, we need a better understanding of the interactions, synergies and conflicts between policies (Cunningham et al., 2013; Geels, 2014). As a contribution to this emerging field of research and to inform its next steps, I present a review on what methods are available to try to quantify the impacts of complex policy interactions, since there is no established method among practitioners, and I explore the merits or value of such attempts. The presentation builds on key works in the field of complexity science (e.g. Anderson, 1972), revisiting and combining these with more recent contributions in the emerging field of policy and complex systems, and evaluation (e.g. Johnstone et al., 2010). With a coalition of UK Government departments, agencies and Research Councils soon to announce the launch of a new internationally-leading centre to pioneer, test and promote innovative and inclusive methods for policy evaluation across the energy-environment-food nexus, the contribution is particularly timely.

New contributions to the native and alien flora in riparian habitats of the Cantabrian watershed (Northern Spain)

As a result of a floristic survey carried out in riparian habitats of northern Spain, new chorological data are provided for 9 alien and 6 native plant species. Some species are reported for the first time at regional scale, such as Carex strigosa, Helianthus x laetiflorus and Persicaria pensylvanica in Cantabria. Also noteworthy is the finding of naturalised populations of the North American grass Muhlenbergia schreberi at the Urumea river basin, which represents the second reference for the Iberian Peninsula.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Can emerging biomarkers of myocardial remodelling identify asymptomatic hypertensive patients at risk for diastolic dysfunction and diastolic heart failure?

AIMS: Hypertension is one of the main drivers of the heart failure (HF) epidemic. The aims of this study were to profile fibro-inflammatory biomarkers across stages of the hypertensive heart disease (HHD) spectrum and to examine whether particular biochemical profiles in asymptomatic patients identify a higher risk of evolution to HF.

METHODS AND RESULTS: This was a cross-sectional observational study involving a population of 275 stable hypertensive patients divided into two different cohorts: Group 1, asymptomatic hypertension (AH) (n= 94); Group 2, HF with preserved ejection fraction (n= 181). Asymptomatic hypertension patients were further subdivided according to left atrial volume index ≥34 mL/m(2) (n= 30) and <34 mL/m(2) (n= 64). Study assays involved inflammatory markers [interleukin 6 (IL6), interleukin 8 (IL8), monocyte chemoattractant protein 1 (MCP1), and tumour necrosis factor α], collagen 1 and 3 metabolic markers [carboxy-terminal propeptide of collagen 1, amino-terminal propeptide of collagen 1, amino-terminal propeptide of collagen 3 (PIIINP), and carboxy-terminal telopeptide of collagen 1 (CITP)], extra-cellular matrix turnover markers [matrix metalloproteinase 2 (MMP2), matrix metalloproteinase 9 (MMP9), and tissue inhibitor of metalloproteinase 1 (TIMP1)], and the brain natriuretic peptide. Data were adjusted for age, sex, systolic blood pressure, and creatinine. Heart failure with preserved ejection fraction was associated with an increased inflammatory signal (IL6, IL8, and MCP1), an increased fibrotic signal (PIIINP and CITP), and an increased matrix turnover signal (MMP2 and MMP9). Alterations in MMP and TIMP enzymes were found to be significant indicators of greater degrees of asymptomatic left ventricular diastolic dysfunction.

CONCLUSION: These data define varying fibro-inflammatory profiles throughout different stages of HHD. In particular, the observations on MMP9 and TIMP1 raise the possibility of earlier detection of those at risk of evolution to HF which may help focus effective preventative strategies.

Comparing long-term placements for young children in care: Does type of placement really matter?

This paper presents findings from the third phase of a longitudinal study, entitled Care Pathways and Outcomes, which has been tracking the placements and measuring outcomes for a population of children (n = 374) who were under the age of five and in care in Northern Ireland on the 31st March 2000. It explores how a sub-sample of these children at age nine to 14 years old were getting on in the placements provided for them, in comparative terms across five placement types: adoption; foster care; kinship foster care (with relatives); on Residence Order; and living with birth parents. This specifically focused on the development of attachment and self-concept from the perspective of the children, and behavioural and emotional function, and parenting stress, from the perspective of parents and carers. Findings showed no significant placement effect from the perspective of children, and a statistically weak, but descriptively compelling, effect from the perspective of parents. The findings challenge the notion of adoption as the gold standard in long-term placements, specifically from the perspective of children in terms of their parent/carer attachments and self-concept, and highlight what appears to be the central importance of placement longevity for delivering positive longer-term outcomes for these children, irrespective of placement type.

Product and Process Innovation: Antecedents and Performance outcomes in small IT firms in India

Innovation is a strategic necessity for the survival of today’s organizations. The wide recognition of innovation as a competitive necessity, particularly in dynamic market environments, makes it an evergreen domain for research. This dissertation deals with innovation in small Information Technology (IT) firms in India. The IT industry in India has been a phenomenal success story of the last three decades, and is today facing a crucial phase in its history characterized by the need for fundamental changes in strategies, driven by innovation. This study, while motivated by the dynamics of changing times, importantly addresses the research gap on small firm innovation in Indian IT.This study addresses three main objectives: (a) drivers of innovation in small IT firms in India (b) impact of innovation on firm performance (c) variation in the extent of innovation adoption in small firms. Product and process innovation were identified as the two most contextually relevant types of innovation for small IT firms. The antecedents of innovation were identified as Intellectual Capital, Creative Capability, Top Management Support, Organization Learning Capability, Customer Involvement, External Networking and Employee Involvement.Survey method was adopted for data collection and the study unit was the firm. Surveys were conducted in 2014 across five South Indian cities. Small firm was defined as one with 10-499 employees. Responses from 205 firms were chosen for analysis. Rigorous statistical analysis was done to generate meaningful insights. The set of drivers of product innovation (Intellectual Capital, Creative Capability, Top Management Support, Customer Involvement, External Networking, and Employee Involvement)were different from that of process innovation (Creative Capability, Organization Learning Capability, External Networking, and Employee Involvement). Both product and process innovation had strong impact on firm performance. It was found that firms that adopted a combination of product innovation and process innovation had the highest levels of firm performance. Product innovation and process innovation fully mediated the relationship between all the seven antecedents and firm performance The results of this study have several important theoretical and practical implications. To the best of the researcher’s knowledge, this is the first time that an empirical study of firm level innovation of this kind has been undertaken in India. A measurement model for product and process innovation was developed, and the drivers of innovation were established statistically. Customer Involvement, External Networking and Employee Involvement are elements of Open Innovation, and all three had strong association with product innovation, and the latter twohad strong association with process innovation. The results showed that proclivity for Open Innovation is healthy in the Indian context. Practical implications have been outlined along how firms can organize themselves for innovation, the human talent for innovation, the right culture for innovation and for open innovation. While some specific examples of possible future studies have been recommended, the researcher believes that the study provides numerous opportunities to further this line of enquiry.

Macroeconomic Risk Factors and the Role of Mispriced Credit in the Returns from International Real Estate Securities

The benefits of diversification from international real estate securities are generally well established. However, the drivers of international real estate securities returns are insufficiently understood. We jointly examine the empirical implications of three major international asset pricing models that account for broad macroeconomic risk factors. In addition, we develop the hypothesis that an indicator of mispriced credit is significant in explaining the time series variation in international real estate securities returns. We employ the returns generated by a large sample of firms from 20 countries over the period 1999 to 2011 to test our hypothesis. We find support for the predictions of the major international asset pricing models. We also find evidence in favour of our hypothesised link between local credit conditions and the performance of international real estate securities.

On the Capital Structure of Real Estate Firms

The leverage and debt maturity choices of real estate companies are interdependent, and are not made separately as is often assumed in the literature. We use three-stage least squares (3SLS) regression analysis to explore this interdependence for a sample of listed U.S. real estate companies and Real Estate Investment Trusts (REITs) traded between 1973 and 2006.We find substantial differences in the nature of the relationship between leverage and maturity for the two firm types. Leverage is a determinant of maturity for non-REITs, whereas maturity is a determinant of leverage for REITs. We also find that the drivers of capital structure choices in real estate companies and REITs clearly reflect the effects of the REIT regulation.

Music Learning Networks: Supporting the Music Learning of Adolescents

Thesis (Ph.D.)--University of Washington, 2016-08

“I know, therefore I adapt?” Complexities of individual adaptation to climate-induced forest dieback in Alaska

Individual actions to avoid, benefit from, or cope with climate change impacts partly shape adaptation; much research on adaptation has focused at the systems level, overlooking drivers of individual responses. Theoretical frameworks and empirical studies of environmental behavior identify a complex web of cognitive, affective, and evaluative factors that motivate stewardship. We explore the relationship between knowledge of, and adaptation to, widespread, climate-induced tree mortality to understand the cognitive (i.e., knowledge and learning), affective (i.e., attitudes and place attachment), and evaluative (i.e., use values) factors that influence how individuals respond to climate-change impacts. From 43 semistructured interviews with forest managers and users in a temperate forest, we identified distinct responses to local, climate-induced environmental changes that we then categorized as either behavioral or psychological adaptations. Interviewees developed a depth of knowledge about the dieback through a combination of direct, place-based experiences and indirect, mediated learning through social interactions. Knowing that the dieback was associated with climate change led to different adaptive responses among the interviewees, although knowledge alone did not explain this variation. Forest users reported psychological adaptations to process negative attitudes; these adaptations were spurred by knowledge of the causes, losses of intangible values, and impacts to a species to which they held attachment. Behavioral adaptations exclusive to a high level of knowledge included actions such as using the forests to educate others or changing transportation behaviors to reduce personal energy consumption. Managers integrated awareness of the dieback and its dynamics across spatial scales into current management objectives. Our findings suggest that adaptive management may occur from the bottom up, as individual managers implement new practices in advance of policies. As knowledge of climate-change impacts in local environments increases, resource users may benefit from programs and educational interventions that facilitate coping strategies.