Estimation of Genetic Parameters of Biomass Production and Composition Traits in Miscanthus Sinensis Using a Staggered-start Design

Traits for biomass production and composition make Miscanthus a promising bioenergy crop for different bioconversion routes. They need to be considered in miscanthus breeding programs as they are subjected to genetic and genetic x environment factors. The objective was to estimate the genetic parameters of an M. sinensis population grown during four years in two French locations. In each location, the experiment was established according to a staggered-start design in order to decompose the year effect into age and climate effects. Linear Mixed Models were used to estimate genetic variance, genotype x age, genotype x climate interaction variances and residual variances. Individual plant broad-sense heritability means ranged from 0.42 to 0.62 for biomass production traits, and were more heritable than biomass composition traits with means ranging from 0.26 to 0.47. Heritability increased through time for most of the biomass production and composition traits. Low genetic variance along with large genotype x age and genotype x climate interaction variances tended to decrease the heritability of biomass production traits for young plant ages. Most of the production traits showed large interaction variances for age and climate in both locations, while biomass composition traits highlighted large interaction variances due to climate in Orléans. The genetic and phenotypic correlations between biomass production and composition traits were moderate and positive, while hemicelluloses were negatively correlated with all traits. Efficient genetic progress is achievable for miscanthus breeding when plants get older. The joint improvement of biomass production and composition traits would help provide a better response of miscanthus to selection.

Environmental Variability of Thousand Kernel Weight in Maize Hybrids of Different Maturity Groups

Thousand kernel weight (TKW) is an important yield component trait affected by the environmental conditions. This study’s objectives were to determine an environmental variability for the TKW in 32 maize hybrids, sorted in four FAO maturity groups (FAO300, 400, 500 and 600), and to compare 12 environments in Croatia (six locations in two years) according to the joint linear regression and stability analyses across the maturity groups. In general, the effects of the environment, genotype, and their interaction (GEI) were significant. A three-factor ANOVA revealed the greatest and highly significant year effect, while the location effect was non-significant across all four FAO groups. A stability analysis did not detect any preferences with regard to the locations and trends across the FAO groups. It indicates that all locations in the Pannonian region included in this study were suitable for an evaluation of the TKW in maize genotypes belonging to all maturity groups. The TKW seems to be an appropriate yield-component trait for maize breeding due to a high heritability and linear GEI nature.

Recruitment of Ostrea chilensis (Philippi, 1844) in Foveaux Strait, Southern New Zealand

<p>This research evaluates fundamental ecological processes to facilitate an understanding of recruitment in Ostrea chilensis from Foveaux Strait, southern New Zealand. Foveaux Strait represents an extreme habitat for oysters that differs to the sheltered nearshore, muddy habitats of most other oyster populations. O. chilensis exhibits the extreme end of brooding strategies in Ostreinae, does not form extensive reefs, and comprises putative self-recruiting populations. The Foveaux Strait oyster fishery is nationally important. Recurrent disease mortality in these populations has put greater onus on understanding recruitment. To evaluate the strength of a recruit-per-spawner relationship in oysters, seasonality in the settlement of larvae was determined. Most recruitment in any given year, over a 6-year period, occurred in the austral spring and summer (November to February). Fishery-wide, recruitment varied significantly between years, with most variation (50.8%) explained by a year effect that represents the combined influences of climatic and biological conditions. Spawner densities and fishery areas explain further variation (13.8% and 11.6%, respectively), with further 2-way interactions between these factors. Recruits-per-spawner declined serially over time, despite similar or increasing densities of spawning-sized oysters. Average recruitment was lowest when spawner densities were highest; this suggests a more complex relationship between recruitment and density that has implications for management of this oyster fishery. Recruitment to the O. chilensis fishery declined abruptly to low levels in 2010 and remained low until 2017. Relatively high spawning-stock sizes over this period had previously supported high recruitment. Density and oyster mortality from Bonamia exitiosa (a proxy for one or more infections) and their two-way interaction were the main determinants of recruitment. The highest recruitment occurred at times of low mortality and low density, suggesting reduced effects of disease on gametogenesis and reduced disease transmission. The contributions of climate factors were minor; however, a 3-way interaction between oyster density, mortality, and climate is likely to drive variation in recruitment. Pathobiomes (multiple infections in populations) may be important determinants of shellfish recruitment and population dynamics. This research evaluates the hypothesis of self-recruitment from distributions of recruit densities around an isolated natal population, and from the relationship between recruitment and brooding-sized oyster densities. Distance from the natal population, direction along or across the tidal current, or brooders did not predict recruit densities. Recruit distributions imply greater dispersal and larval mixing than previously reported. The swift tidal currents and possibility of more variable pelagic larval durations may enhance mixing and connectivity between populations in Foveaux Strait. Post-settlement mortality is the primary determinant of spatial structure in Foveaux Strait oysters. Productive fishery areas comprise mostly stable substrates of shells, sand, and gravel, with no or little other epifauna. Most (66.8%) post-settlement survivors were on the heavy shells of both live and dead O. chilensis, which suggests an unusual recruit-adult relationship based on survival rather than settlement. Recruits and 1+ year spat grew larger and had lower mortality at eastern sites with the lowest exposure to oceanic swells and putative lowest sediment movement. Moreover, recruits on spat collectors also grew larger and had lower mortality at heights ≥ 12 cm than those 2 cm off the seabed. This research suggests the effects of disease on brooding percentages and thereby larval supply may be the main determinant of the variation in recruitment in O. chilenesis, and the spatial structure of oyster populations in Foveaux Strait shaped by abiotic as well as biotic post-settlement mortality.</p>

Recruitment of Ostrea chilensis (Philippi, 1844) in Foveaux Strait, Southern New Zealand

<p>This research evaluates fundamental ecological processes to facilitate an understanding of recruitment in Ostrea chilensis from Foveaux Strait, southern New Zealand. Foveaux Strait represents an extreme habitat for oysters that differs to the sheltered nearshore, muddy habitats of most other oyster populations. O. chilensis exhibits the extreme end of brooding strategies in Ostreinae, does not form extensive reefs, and comprises putative self-recruiting populations. The Foveaux Strait oyster fishery is nationally important. Recurrent disease mortality in these populations has put greater onus on understanding recruitment. To evaluate the strength of a recruit-per-spawner relationship in oysters, seasonality in the settlement of larvae was determined. Most recruitment in any given year, over a 6-year period, occurred in the austral spring and summer (November to February). Fishery-wide, recruitment varied significantly between years, with most variation (50.8%) explained by a year effect that represents the combined influences of climatic and biological conditions. Spawner densities and fishery areas explain further variation (13.8% and 11.6%, respectively), with further 2-way interactions between these factors. Recruits-per-spawner declined serially over time, despite similar or increasing densities of spawning-sized oysters. Average recruitment was lowest when spawner densities were highest; this suggests a more complex relationship between recruitment and density that has implications for management of this oyster fishery. Recruitment to the O. chilensis fishery declined abruptly to low levels in 2010 and remained low until 2017. Relatively high spawning-stock sizes over this period had previously supported high recruitment. Density and oyster mortality from Bonamia exitiosa (a proxy for one or more infections) and their two-way interaction were the main determinants of recruitment. The highest recruitment occurred at times of low mortality and low density, suggesting reduced effects of disease on gametogenesis and reduced disease transmission. The contributions of climate factors were minor; however, a 3-way interaction between oyster density, mortality, and climate is likely to drive variation in recruitment. Pathobiomes (multiple infections in populations) may be important determinants of shellfish recruitment and population dynamics. This research evaluates the hypothesis of self-recruitment from distributions of recruit densities around an isolated natal population, and from the relationship between recruitment and brooding-sized oyster densities. Distance from the natal population, direction along or across the tidal current, or brooders did not predict recruit densities. Recruit distributions imply greater dispersal and larval mixing than previously reported. The swift tidal currents and possibility of more variable pelagic larval durations may enhance mixing and connectivity between populations in Foveaux Strait. Post-settlement mortality is the primary determinant of spatial structure in Foveaux Strait oysters. Productive fishery areas comprise mostly stable substrates of shells, sand, and gravel, with no or little other epifauna. Most (66.8%) post-settlement survivors were on the heavy shells of both live and dead O. chilensis, which suggests an unusual recruit-adult relationship based on survival rather than settlement. Recruits and 1+ year spat grew larger and had lower mortality at eastern sites with the lowest exposure to oceanic swells and putative lowest sediment movement. Moreover, recruits on spat collectors also grew larger and had lower mortality at heights ≥ 12 cm than those 2 cm off the seabed. This research suggests the effects of disease on brooding percentages and thereby larval supply may be the main determinant of the variation in recruitment in O. chilenesis, and the spatial structure of oyster populations in Foveaux Strait shaped by abiotic as well as biotic post-settlement mortality.</p>

The Month-of-the-Year Effect in the European, American, Australian and Asian Markets

This paper examines the existence of the month-of-the-year effects in four different continents, namely Europe, Asia, America, and Oceania. Nine indexes were analyzed in order to verify differences between monthly returns from January 1990 to December 2013, followed by an examination of the January effect, Halloween effect, and the October effect, testing for statistical significance using an OLS linear regression in order to verify whether those effects offer consistent opportunities for investors. Investors with globally diversified portfolios benefit from the Halloween effect, with a 1.2% average monthly excess return in winter and spring, while the pre-dotcom-bubble period had a better performance than the post-dotcom-bubble period. In the global post-dotcom-bubble period, there is statistical evidence for 1.60% and 1% lower average monthly returns in January (the January effect) and in months other than October (the October effect), respectively, contradicting the literature. The dotcom bubble seems to be responsible for the January effect differing from what might otherwise have been expected in the later period. There is no consistent and clear impact on continental incidence. The Halloween effect is revealed to be a fruitful strategy in the FTSE, DAX, Dow Jones, BOVESPA, and N225 indexes taken one-by-one. The January effect excess average return was only statistically significative for the pre-dotcom-bubble period for globally diversified portfolios. This paper contributes to a wider global and comparable view upon month-of-the-year effect.

Analysis of Fatal and Injury Traffic Accidents in Istanbul Sarıyer District with Spatial Statistics Methods

Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been carried out in the world and in Turkey to reduce the number of traffic accidents, but these studies have not been very effective in reducing accidents. In this study, 3105 fatal or injured traffic accidents between 2010–2017 in Sarıyer district of Istanbul, Turkey’s largest city in terms of population, were discussed. We analyzed the statistical information on the subject in detail within the framework of geographic information systems. It has been tried to determine the sections where traffic accidents are concentrated in this region with studies based on spatial methods. Thematic accident map was created according to the accident types. In this context, the advantages and disadvantages of these methods were compared using Point Density, Kernel Density, Getis Ord Gi*, and Anselin Local Moran’s I (LISA) Spatial Autocorrelation. In addition, in order to observe the change in accidents, thematic accident and Kernel Density maps were created separately according to accident occurrence types in the beginning and last year. From this point of view, the changes that occurred in the accidents were interpreted. The current study determined that the most accidents were on some streets and these streets divided into regions in a plan. The cases were examined with statistical analyses according to accident types and using the Kernel Density method. In addition, it has been observed that Kernel Density method gives better visual results than other spatial methods. In this study, spatial analysis and statistical analysis methods were used to evaluate traffic accidents more realistically. The day of the week effect and month of the year effect on traffic accidents was investigated for the first time. In addition, it is proposed to bring a new approach to the prevention of traffic accidents by using hotspot, accident type, and day of the week effect.

Linkage Mapping of Biomass Production and Composition Traits in a Miscanthus Sinensis Population

Breeding miscanthus for biomass production and composition is essential for targeting high-yielding genotypes suited to different end-uses. Our objective was to understand the genetic determinism of these traits in M. sinensis, according to different plant ages and environmental conditions. A diploid population was established in two locations according to a staggered-start design, which made the “year” effect partitioned into “age” and “growing season” effects. An integrated genetic map of 2,602 SNP markers distributed across 19 LGs, was aligned with the M. sinensis reference genome and spanned 2,770 cM. The QTL mapping was based on Best Linear Unbiased Predictions estimated across three climatic conditions and at least three ages in both locations. 260 and 283 QTL were related to biomass production and composition traits, respectively. In each location, 40%-60% were related to biomass production traits and stable across different climatic conditions and ages, and 30% to biomass composition traits. Ten to fifteen% were stable for both trait types across locations. Twelve QTL clusters were established based on either biomass production or composition traits, and validated by high genetic correlations between the traits. Sixty-two putative M. sinensis genes, related to the cell-wall, were evidenced in the QTL clusters of biomass composition traits, and orthologous to those of sorghum and maize. Twelve of them were differentially expressed and belonged to gene families related to the cell-wall biosynthesis identified in other miscanthus studies. These stable QTL constitute new insights into Marker-Assisted Selection breeding while offering a joint improvement of biomass production or composition traits.

Validating a Simple Mechanistic Model That Describes Weather Impact on Pasture Growth

Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily maximum and minimum temperature and rainfall. The accuracy of the model was validated using ten site-years of measured pasture growth at a site under continuous stocking where management controlled the height of grazing (HOG) and a site under rotational stocking at a West Virginia University farm (WVU). Relative forage growth, expressed as a fraction of maximum growth observed at the sites, was reasonably accurate. At the HOG site constant bias in relative growth was not different from zero. There was a year effect due to the weather station used for predicting growth at HOG being 1.8 km from the pasture. However, the error was only about 10-percent. At the WVU site constant bias for relative growth was not different from zero and year effect was eliminated when adjusted for nitrogen status of the treatments. This simple model described relative pasture growth within 10-percent of average for a given site, environment, and management using only daily weather inputs that are readily available. Using predictions of climate change impact on temperature and rainfall frequency and intensity this model can be used to predict the impact on pasture growth.

Balancing the COVID-19 Disruption to Undergraduate Learning and Assessment with an Academic Student Support Package: Implications for Student Achievement and Engagement

In response to the COVID-19 pandemic-induced emergency pivot to online teaching and assessment, an Academic Safety Net was implemented at a regional Australian university to provide academic student support. Bayesian hierarchical models were used to compare student performance between 2019 and 2020. More students withdrew from subjects in 2020, while fewer students remained enrolled but failed. While there was no overall year effect for overall student achievement, exam achievement increased and on-course assessment achievement decreased in 2020. When achievement was analysed according to an assessment task change, a year effect emerged, with the magnitude and direction of the effect dependent on the task changes. The results indicate that the enrolment component of the Academic Safety Net was an effective equity measure that enabled students an extended opportunity to self-withdraw in response to general impacts of the pandemic; while the results component protected the integrity of results awarded during the emergency pivot.