Satellite-detected fluorescence reveals global physiology of ocean phytoplankton

Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

What are the local impacts of energy systems on marine ecosystem services: a systematic map protocol

Background: Increasing concentrations of atmospheric greenhouse gases (GHG) and its impact on the climate has resulted in many international governments committing to reduce their GHG emissions. The UK, for example, has committed to reducing its carbon emissions by 80% by 2050. Suggested ways of reaching such a target are to increase dependency on offshore wind, offshore gas and nuclear. It is not clear, however, how the construction, operation and decommissioning of these energy systems will impact marine ecosystem services, i.e. the services obtained by people from the natural environment such as food provisioning, climate regulation and cultural inspiration. Research on ecosystem service impacts associated with offshore energy technologies is still in its infancy. The objective of this review is to bolster the evidence base by firstly, recording and describing the impacts of energy technologies at the marine ecosystems and human level in a consistent and transparent way; secondly, to translate these ecosystem and human impacts into ecosystem service impacts by using a framework to ensure consistency and comparability. The output of this process will be an objective synthesis of ecosystem service impacts comprehensive enough to cover different types of energy under the same analysis and to assist in informing how the provision of ecosystem services will change under different energy provisioning scenarios. Methods: Relevant studies will be sourced using publication databases and selected using a set of selection criteria including the identification of: (i) relevant subject populations such as marine and coastal species, marine habitat types and the general public; (ii) relevant exposure types including offshore wind farms, offshore oil and gas platforms and offshore structures connected with nuclear; (iii) relevant outcomes including changes in species structure and diversity; changes in benthic, demersal and pelagic habitats; and changes in cultural services. The impacts will be synthesised and described using a systematic map. To translate these findings into ecosystem service impacts, the Common International Classification of Ecosystem Services (CICES) and Millennium Ecosystem Assessment (MEA) frameworks are used and a detailed description of the steps taken provided to ensure transparency and replicability.

Marine biodiversity and ecosystem function relationships:the potential for practical monitoring applications

There is an increasing demand for environmental assessments of the marine environment to include ecosystem function. However, existing schemes are predominantly based on taxonomic (i.e. structural) measures of biodiversity. Biodiversity and Ecosystem Function (BEF) relationships are suggested to provide a mechanism for converting taxonomic information into surrogates of ecosystem function. This review assesses the evidence for marine BEF relationships and their potential to be used in practical monitoring applications (i.e. operationalized). Five key requirements were identified for the practical application of BEF relationships: (1) a complete understanding of strength, direction and prevalence of marine BEF relationships, (2) an understanding of which biological components are influential within specific BEF relationships, (3) the biodiversity of the selected biological components can be measured easily, (4) the ecological mechanisms that are the most important for generating marine BEF relationships, i.e. identity effects or complementarity, are known and (5) the proportion of the overall functional variance is explained by biodiversity, and hence BEF relationships, has been established. Numerous positive and some negative BEF relationships were found within the literature, although many reproduced poorly the natural species richness, trophic structures or multiple functions of real ecosystems (requirement 1). Null relationships were also reported. The consistency of the positive and negative relationships was often low that compromised the ability to generalize BEF relationships and confident application of BEF within marine monitoring. Equally, some biological components and functions have received little or no investigation. Expert judgement was used to attribute biological components using spatial extent, presence and functional rate criteria (requirement 2). This approach highlighted the main biological components contributing the most to specific ecosystem functions, and that many of the particularly influential components were found to have received the least amount of research attention. The need for biodiversity to be measureable (requirement 3) is possible for most biological components although difficult within the functionally important microbes. Identity effects underpinned most marine BEF relationships (requirement 4). As such, processes that translated structural biodiversity measures into functional diversity were found to generate better BEF relationships. The analysis of the contribution made by biodiversity, over abiotic influences, to the total expression of a particular ecosystem function was rarely measured or considered (requirement 5). Hence it is not possible to determine the overall importance of BEF relationships within the total ecosystem functioning observed. In the few studies where abiotic factors had been considered, it was clear that these modified BEF relationships and have their own direct influence on functional rate. Based on the five requirements, the information required for immediate ‘operationalization’ of BEF relationships within marine functional monitoring is lacking. However, the concept of BEF inclusion within practical monitoring applications, supported by ecological modelling, shows promise for providing surrogate indicators of functioning.

Global carbon budget 2014

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (E-FF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004-2013), E-FF was 8.9 +/- 0.4 GtC yr(-1), E-LUC 0.9 +/- 0.5 GtC yr(-1), G(ATM) 4.3 +/- 0.1 GtC yr(-1), S-OCEAN 2.6 +/- 0.5 GtC yr(-1), and S-LAND 2.9 +/- 0.8 GtC yr(-1). For year 2013 alone, E-FF grew to 9.9 +/- 0.5 GtC yr(-1), 2.3% above 2012, continuing the growth trend in these emissions, E-LUC was 0.9 +/- 0.5 GtC yr(-1), G(ATM) was 5.4 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 2.5 +/- 0.9 GtC yr(-1). G(ATM) was high in 2013, reflecting a steady increase in E-FF and smaller and opposite changes between S-OCEAN and S-LAND compared to the past decade (2004-2013). The global atmospheric CO2 concentration reached 395.31 +/- 0.10 ppm averaged over 2013. We estimate that E-FF will increase by 2.5% (1.3-3.5 %) to 10.1 +/- 0.6 GtC in 2014 (37.0 +/- 2.2 GtCO(2) yr(-1)), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of E-FF and assumed constant E-LUC for 2014, cumulative emissions of CO2 will reach about 545 +/- 55 GtC (2000 +/- 200 GtCO(2)) for 1870-2014, about 75% from E-FF and 25% from E-LUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quere et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

The potential use of mapped extent and distribution of habitats as indicators of Good Environmental Status (GES)

The Healthy and Biologically Diverse Seas Evidence Group (HBDSEG) has been tasked with providing the technical advice for the implementation of the Marine Strategy Framework Directive (MSFD) with respect to descriptors linked to biodiversity. A workshop was held in London to address one of the Research and Development (R&D) proposals entitled: ‘Mapping the extent and distribution of habitats using acoustic and remote techniques, relevant to indicators for area/extent/habitat loss.’ The aim of the workshop was to identify, define and assess the feasibility of potential indicators of benthic habitat distribution and extent, and identify the R&D work which could be required to fully develop these indicators. The main points that came out of the workshop were: (i) There are many technical aspects of marine habitat mapping that still need to be resolved if cost-effective spatial indicators are to be developed. Many of the technical aspects that need addressing surround issues of consistency, confidence and repeatability. These areas should be tackled by the JNCC Habitat Mapping and Classification Working Group and the HBDSEG Seabed Mapping Working Group. (ii) There is a need for benthic ecologists (through the HBDSEG Benthic Habitats Subgroup and the JNCC Marine Indicators Group) to finalise the list of habitats for which extent and/or distribution indicators should be considered for development, building upon the recommendations from this report. When reviewing the list of indicators, benthic habitats could also be distinguished into those habitats that are defined/determined primarily by physical parameters (although including biological assemblages) (e.g. subtidal shallow sand) and those defined primarily by their biological assemblage (e.g. seagrass beds). This distinction is important as some anthropogenic pressures may influence the biological component of the ecosystem despite not having a quantifiable effect on the physical habitat distribution/extent. (iii) The scale and variety of UK benthic habitats makes any attempt to undertake comprehensive direct mapping exercises prohibitively expensive (especially where there is a need for repeat surveys for assessment). There is a clear need therefore to develop a risk-based approach that uses indirect indicators (e.g. modelling), such as habitats at risk from pressures caused by current human activities, to develop priorities for information gathering. The next steps that came out of the workshop were: (i) A combined approach should be developed by the JNCC Marine Indicators Group together with the HBDSEG Benthic Habitats Subgroup, which will compile and ultimately synthesise all the criteria used by the three different groups from the workshop. The agreed combined approach will be used to undertake a final review of the habitats considered during the workshop, and to evaluate any remaining habitats in order to produce a list of habitats for indicator development for which extent and/or distribution indicators could be appropriate. (ii) The points of advice raised at this workshop, alongside the combined approach aforementioned, and the final list of habitats for extent and/or distribution indicator development will be used to develop a prioritised list of actions to inform the next round of R&D proposals for benthic habitat indicator development in 2014. This will be done through technical discussions within JNCC and the relevant HBDSEG Subgroups. The preparation of recommendations by these groups should take into account existing work programmes, and consider the limited resources available to undertake any further R&D work.

Metocean Comparisons of Jason-2 and AltiKa—A Method to Develop a New Wind Speed Algorithm

As well as range, the AltiKa altimeter provides estimates of wave height, Hs and normalized backscatter, s0, that need to be assessed prior to statistics based on them being included in climate databases. An analysis of crossovers with the Jason-2 altimeter shows AltiKa Hs values to be biased high by only »0.05m, with a standard deviation (s.d.) of »0.1m for seven-point averages. AltiKa’s s 0 values are 2.5–3 dB less than those from Jason-2, with a s.d. of »0.3 dB, with these relatively large mismatches to be expected as AltiKa measures a different part of the spectrum of sea surface roughness. A new wind speed algorithm is developed through matchinghistogram of s0 values to that for Jason-2 wind speeds. The algorithm is robust to the use of short durations of data, with a consistency at roughly the 0.1 m/s level. Incorporation of Hs as a secondary input reduces the assessed error at crossovers from 0.82 m/s to 0.71 m/s. A comparison across all altimeter frequencies used to date demonstrates that the lowest wind speeds preferentially develop the shortest scales of roughness.

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (<1 tonne CO2 d−1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations.

Global Carbon Budget 2015

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).

New wild Brassica oleracea L. germplasm at its western distribution limit in the Iberian Peninsula

An exploration and collection mission for wild Brassica oleracea populations was carried out in spring and summer of 2013. The aim of this collection was to expand the number of accessions of wild Brassica oleracea available for basic and applied research in plant breeding. In this paper we report a new accession of wild Brassica oleracea in an unexplored coastal area of Galicia, NW Iberian Peninsula. Details of population ecology and vegetation, soil, climate and geographic data were recorded for this population. The “Endangered” threat category for the region is proposed, and actions for in situ and ex situ conservation are proposed. Seeds will be added to the germplasm collections of University of Santiago de Compostela and Misión Biológica de Galicia (CSIC) for further research on diverse aspects of the dynamics and ecophysiology of the population along with characterization and evaluation of useful traits.

Examination of the flow rheological and textural properties of polymer gels composed of poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone): rheological and mathematical interpretation of textural parameters.

The purpose of this study was to mathematically characterize the effects of defined experimental parameters (probe speed and the ratio of the probe diameter to the diameter of sample container) on the textural/mechanical properties of model gel systems. In addition, this study examined the applicability of dimensional analysis for the rheological interpretation of textural data in terms of shear stress and rate of shear. Aqueous gels (pH 7) were prepared containing 15% w/w poly(methylvinylether-co-maleic anhydride) and poly(vinylpyrrolidone) (PVP) (0, 3, 6, or 9% w/w). Texture profile analysis (TPA) was performed using a Stable Micro Systems texture analyzer (model TA-XT 2; Surrey, UK) in which an analytical probe was twice compressed into each formulation to a defined depth (15 mm) and at defined rates (1, 3, 5, 8, and 10 mm s-1), allowing a delay period (15 s) between the end of the first and beginning of the second compressions. Flow rheograms were performed using a Carri-Med CSL2-100 rheometer (TA Instruments, Surrey, UK) with parallel plate geometry under controlled shearing stresses at 20.0°?±?0.1°C. All formulations exhibited pseudoplastic flow with no thixotropy. Increasing concentrations of PVP significantly increased formulation hardness, compressibility, adhesiveness, and consistency. Increased hardness, compressibility, and consistency were ascribed to enhanced polymeric entanglements, thereby increasing the resistance to deformation. Increasing probe speed increased formulation hardness in a linear manner, because of the effects of probe speed on probe displacement and surface area. The relationship between formulation hardness and probe displacement was linear and was dependent on probe speed. Furthermore, the proportionality constant (gel strength) increased as a function of PVP concentration. The relationship between formulation hardness and diameter ratio was biphasic and was statistically defined by two linear relationships relating to diameter ratios from 0 to 0.4 and from 0.4 to 0.563. The dramatically increased hardness, associated with diameter ratios in excess of 0.4, was accredited to boundary effects, that is, the effect of the container wall on product flow. Using dimensional analysis, the hardness and probe displacement in TPA were mathematically transformed into corresponding rheological parameters, namely shearing stress and rate of shear, thereby allowing the application of the power law (??=?k?n) to textural data. Importantly, the consistencies (k) of the formulations, calculated using transformed textural data, were statistically similar to those obtained using flow rheometry. In conclusion, this study has, firstly, characterized the relationships between textural data and two key instrumental parameters in TPA and, secondly, described a method by which rheological information may be derived using this technique. This will enable a greater application of TPA for the rheological characterization of pharmaceutical gels and, in addition, will enable efficient interpretation of textural data under different experimental parameters.

The adaptations of a quality of life questionnaire for routine use in clinical practice: the Chronic Respiratory Disease Questionnaire in Cystic Fibrosis.

The assessment of quality of life (QOL) is necessary to monitor the course of disease and to assess the effect of new and existing interventions in clinical practice. This will only be achieved if QOL can be measured accurately and routinely. The aim of this study was to demonstrate the methodology involved in the adaptation and shortening of the Chronic Respiratory Disease Questionnaire (CRDQ) in a population of adults with cystic fibrosis (CF). A single interviewer administered the CRDQ to a sample of 45 adult patients (32 males) with CF prior to assessment of spirometric measures of lung function. Those patients whose lung function was stable at the time of study, and who could attend for a retest within 14 days, were asked to complete the questionnaire at a subsequent visit (n=10). The average interval between visits was 7 days (range 5-14 days). Correlations between spirometry and CRDQ dimensions ranged from -0.003 to 0.426. The fatigue, emotion and mastery dimensions showed high internal consistency, and adequate construct validity. In the small number of patients suitable for retest, the results indicated that the dimensions exhibited adequate test retest reliability. In contrast low internal consistency was demonstrated for the dyspnoea dimension. The fatigue, emotion and mastery dimensions could be reduced, in terms of their number of items without a substantial loss in explanatory power. This study suggests that QOL measurement can be made convenient, and so more easily accessible for routine clinical assessment.

How optimal life history changes with the community size-spectrum

This paper derives optimal life histories for fishes or other animals in relation to the size spectrum of the ecological community in which they are both predators and prey. Assuming log-linear size-spectra and well known scaling laws for feeding and mortality, we first construct the energetics of the individual. From these we find, using dynamic programming, the optimal allocation of energy between growth and reproduction as well as the trade-off between offspring size and numbers. Optimal strategies were found to be strongly dependent on size spectrum slope. For steep size spectra (numbers declining rapidly with size), determinate growth was optimal and allocation to somatic growth increased rapidly with increasing slope. However, restricting reproduction to a fixed mating season changed optimal allocations to give indeterminate growth approximating a von Bertalanffy trajectory. The optimal offspring size was as small as possible given other restrictions such as newborn starvation mortality. For shallow size spectra, finite optimal maturity size required a decline in fitness for large size or age. All the results are compared with observed size spectra of fish communities to show their consistency and relevance.

Do pigs form preferential associations?

This investigation examined whether pigs form long-term preferential associations or ‘friendships’ and factors that may influence the formation of these relationships. Thirty-three pigs from 16 litters were housed together from 4 weeks of age. At 10 weeks they were split into two groups of 16 and 17 pigs and each introduced into 3.05 m × 3.66 m observation pens (1st pen). At 17 weeks the two groups swapped pens (2nd pen). The lying patterns of each group were recorded over 3 weeks in both the 1st and 2nd pens. To identify dyads with preferential associations, association indices were calculated for each pair based on their lying patterns and analysed using SOCPROG1.3 and the permutation method [Whitehead, H., 1999. Programs for analysing social structure. SOCPROG 1.2, http://is.dal.cal/~whitelab/index.htm]. Dyads with high association indices for at least 2 out of 3 weeks in either pen, i.e. =0.10 (twice the mean), were classed as having preferential associations. Mantel tests were used to examine the relationship between the relative sex, weight, familiarity and relatedness of a dyad and their level of association and to examine consistency of associations between pens. The existence of preferential associations was identified in both groups, since the standard deviations for the observed half-weight association index means were significantly higher than for the randomly permuted half-weight association index means (P < 0.001). Of the 33 pigs observed, 32 formed preferential associations with one or more pigs in their group, resulting in 50 dyads. Only six dyads (12 pigs) formed preferential associations in both pens, suggesting that the remaining dyads either formed short-term associations only or were simply displaying a shared preference for the same lying location. Levels of association between pens showed no significant correlation. The relative sex, weight, familiarity and relatedness of dyad members also showed no significant correlation with their level of association. These findings suggest that unrelated pigs are capable of forming preferential associations. However, it is unclear whether such associations are widespread or important to pigs, since most dyads’ preferential associations were not consistent between pens.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.