A GENERALIZED BLOCK BOOTSTRAP FOR SEASONAL TIME SERIES

When time‐series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its asymptotic consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite‐sample performance of the GSBB is also illustrated by means of a small simulation experiment.     

Seasonality of meningitis in Africa and climate forcing: aerosols stand out

Bacterial meningitis is an ongoing threat for the population of the African Meningitis Belt, a region characterized by the highest incidence rates worldwide. The determinants of the disease dynamics are still poorly understood; nevertheless, it is often advocated that climate and mineral dust have a large impact. Over the last decade, several studies have investigated this relationship at a large scale. In this analysis, we scaled down to the district-level weekly scale (which is used for in-year response to emerging epidemics), and used wavelet and phase analysis methods to define and compare the time-varying periodicities of meningitis, climate and dust in Niger. We mostly focused on detecting time-lags between the signals that were consistent across districts. Results highlighted the special case of dust in comparison to wind, humidity or temperature: a strong similarity between districts is noticed in the evolution of the time-lags between the seasonal component of dust and meningitis. This result, together with the assumption of dust damaging the pharyngeal mucosa and easing bacterial invasion, reinforces our confidence in dust forcing on meningitis seasonality. Dust data should now be integrated in epidemiological and forecasting models to make them more realistic and usable in a public health perspective.     

Influence of birth rates and transmission rates on the global seasonality of rotavirus incidence

Rotavirus is a major cause of mortality in developing countries, and yet the dynamics of rotavirus in such settings are poorly understood. Rotavirus is typically less seasonal in the tropics, although recent observational studies have challenged the universality of this pattern. While numerous studies have examined the association between environmental factors and rotavirus incidence, here we explore the role of intrinsic factors. By fitting a mathematical model of rotavirus transmission dynamics to published age distributions of cases from 15 countries, we obtain estimates of local transmission rates. Model-predicted patterns of seasonal incidence based solely on differences in birth rates and transmission rates are significantly correlated with those observed (Spearman''s ρ = 0.65, p < 0.05). We then examine seasonal patterns of rotavirus predicted across a range of different birth rates and transmission rates and explore how vaccination may impact these patterns. Our results suggest that the relative lack of rotavirus seasonality observed in many tropical countries may be due to the high birth rates and transmission rates typical of developing countries rather than being driven primarily by environmental conditions. While vaccination is expected to decrease the overall burden of disease, it may increase the degree of seasonal variation in the incidence of rotavirus in some settings.     

Human Activity in Landscape Seasonality: The Case of Tourism in Crete

As an integral quality of the landscape, seasonality greatly affects, informs and interweaves with human livelihood systems, such as the tourism-based economies of Greek island communities, currently almost entirely dependent upon summer holiday tourism for their survival. The multiple facets and impacts of seasonality produced and inscribed by tourism on the landscape, and specifically on the landscape of northern Crete, are described and discussed. For this purpose, a three-fold analytical framework of tourist resort evolution for a Greek island or rural tourist destination, from the stage of discovery to the stage of establishment and institutionalization of tourism, is employed. The three different stages of this tourism destination lifecycle model are roughly represented by three different zones of tourism impact in the broader region of Hersonissos in northern Crete. Here, tourism-induced changes roughly attenuate with distance from the coast, acquiring distinctive geographical patterns that follow those of spatial tourist concentration, scale of development, and incorporation of tourism into Cretan society and space. It is illustrated that the role and impact of tourism-induced seasonality seems to be most pronounced and significant during the second stage of the lifecycle of a tourism area such as the Cretan region under study.     

Seasonality in Estonian Traditional Landscape: The Example of Large Village Swings

Like every nation, Estonians have their own indigenous customs and habits. Village swings and the place of these swings in the landscape are focused upon as an example of such Estonian customs, and changes in landscape as related to seasonality and liminality are discussed. The word ‘swing’ is used to denote a large construction (traditionally made of wood) that is able to carry and swing at least two people. Village swings (for public use) are usually located in the middle of a village and the site is commonly used by young people as a place to meet and have a good time. Swinging takes place mostly in the spring and summer, forming one of the many seasonal activities that make up the Estonian traditional calendar. The seasonal break in swinging activity contributes to the eagerness with which swinging is resumed when spring returns, so seasonality creates frames, with the most valued time being the spring. With swinging, the spring has been celebrated as a very valuable and long-awaited season. Although the religious background for swinging has been forgotten, the place is still special and is visited mostly on certain festive occasions. As there is no comparable alternative to swing sites as a socializing place in the village, they have persisted through the centuries. The importance of preserving such unique seasonal places in Estonia's social landscape is demonstrated.     

Characterization of Brazilian green propolis throughout the seasons by headspace GC/MS and ESI-MS

BACKGROUND: A screening of the chemical composition of eight commercial classes of raw Brazilian green propolis throughout the seasons was carried out. A multivariate exploratory analysis of chemical composition obtained by gas chromatography associated with mass spectrometry with headspace extraction (HS‐GC/MS), and by mass spectrometry with electrospray ionization (ESI‐MS) was carried out using principal component analysis (PCA). RESULTS: Differences in the volatile and polyphenolic profiles of propolis samples were verified during the seasons. Within each season, the high quality commercial classes of propolis presented similar characteristics, while the low quality classes presented distinct compositions. In spring and summer, propolis of the trimming class, commonly considered of low quality by beekeepers, presented a composition similar to the superior quality propolis. CONCLUSION: Seasonality influences the chemical composition of the commercial classes of raw Brazilian green propolis. Headspace‐GC/MS and ESI‐MS assisted by PCA are effective to characterize volatile and non‐volatile compounds of the propolis samples, and to correlate it to the seasons. Copyright © 2011 Society of Chemical Industry     

Semiparametric Inference in Seasonal and Cyclical Long Memory Processes

Several semiparametric estimates of the memory parameter in standard long memory time series are now available. They consider only local behaviour of the spectrum near zero frequency, about which the spectrum is symmetric. However long-range dependence can appear as a spectral pole at any Nyqvist frequency (reflecting seasonal or cyclical long-memory), where the spectrum need display no such symmetry. We introduce Seasonal/Cyclical Asymmetric Long Memory (SCALM) processes that allow differing rates of increase on either side of such a pole. To estimate the two consequent memory parameters we extend two semiparametric methods that were proposed for the standard case of a spectrum diverging at the origin, namely the log-periodogram and Gaussian or Whittle methods. We also provide three tests of symmetry. Monte Carlo analysis of finite sample behaviour and an empirical application to UK inflation data are included. Our models and methods allow also for the possibility of negative dependence, described by a possibly asymmetric spectral zero.     

Temporal changes in the periphytic algal communities in a drowned tropical forest reservoir in Malaysia: Lake Kenyir

Periphytic algal assemblages, comprising bacillariophytes, cyanophytes and chlorophytes of standing dead trees in Lake Kenyir, a tropical drowned forest reservoir, were studied during 1995. A total of 317 algal taxa were identified in this study. The monthly floral mean species richness and cell count data demonstrated significant temporal differences between the months, in one-way anova (P < 0.05). Both redundancy analysis and cluster analysis on monthly blue-green abundance and diatom assemblages exhibited conspicuous groupings among the months, with underpinning seasonal differences. The responses were not similar, however, between the upstream and downstream ends of the lake. The grouping or clustering of months can be generalized as: (i) November, December and January as the monsoonal months; (ii) February, March, April and May as the transitional months; and (iii) June to October as the dry months. Based on stepwise multiple regression with forward selection, alkalinity and dissolved oxygen concentration were significant environmental predictors at the downstream dam sampling site, and reactive silica, electrical conductivity, Secchi depth transparency and sunshine hours were significant predicators at the upstream riverine sampling site, based on Monte Carlo tests. Being a ploymictic, mesotrophic lake, the limnology and temporal changes for Lake Kenyir appears to be complex and driven by monsoons, as evidenced from the temporal changes in its periphytic algae communities, particularly the diatom assemblages. The downstream sampling site (site 1) at the dam, in the main basin and deeper zone of the lake, the seasonal amplitude was likely complex because of thermocline formation and stratification processes. In contrast, the upstream sampling site in the Petang River (site 2) exhibited a clearer distinction between the dry and monsoon months, based on its cyanophyte and diatom floral assemblages. These study results are pertinent for lake management, especially for developing biomonitoring programmes or lake productivity studies, as well as for climate change studies, within the context of tropical lake ecology.     

An examination of labor time-use on spring-calving dairy farms in Ireland

The seasonal workload associated with pasture-based dairy farms, combined with increasing herd sizes, has led to a renewed focus on labor time-use and efficiency on dairy farms. The objective of this study was to examine labor time-use on pasture-based dairy farms in the spring and summer seasons. A total of 82 spring-calving Irish dairy farms completed the study from February 1 to June 30, 2019 (150 d). Each farmer recorded their labor input on one alternating day each week using a smartphone app. Any labor input by farm workers not using the app was recorded through a weekly online survey. Farms with data for each month (n = 76) were classified into 1 of 4 herd size categories (HSC) for analysis: farms with 50 to 90 cows (HSC 1); 91 to 139 cows (HSC 2); 140 to 239 cows (HSC 3); and ≥240 cows (HSC 4). Total hours of labor input was similar on HSC 1 (1,821 h) and HSC 2 (2,042 h) farms, but predictably as HSC increased further, total hours of labor input increased (HSC 3: 2,462 h, HSC 4: 3,040 h). On a monthly basis, labor input peaked in February (15.4 h/d) and March (15.7 h/d). The farmer worked on average 60.0 h/wk over the duration of the study period. Hired labor and contractors completed a greater amount of work as HSC increased. Labor efficiency, as measured by hours/cow, improved as HSC increased (HSC 1: 26.3 h/cow, HSC 2: 17.7 h/cow, HSC 3: 14.3 h/cow, HSC 4: 10.9 h/cow), though there were large variations in labor efficiency within HSC. Milking was the most time-consuming task, representing 31% of farm labor input making it an important focus for potential improvements in efficiency. The next 5 most time-consuming tasks were calf care (14%), grassland management (13%), cow care (10%), repairs and maintenance (10%), and administration/business (8%). This study contributes to the understanding of labor use during the busiest (most labor demanding) time of the year on pasture-based dairy farms and points to areas where labor efficiency improvements can be made on farms. The considerable variation in farm labor efficiency observed within HSCs emphasizes the necessity for a greater focus on knowledge transfer of methods to achieve improved labor efficiency and a better work–life balance on many dairy farms. As the 2 busiest months on most dairy farms, February and March require the most focus for identification of potential labor savings.     

Both sampling seasonality and geographic origin contribute significantly to variations in raw milk microbiota,but sampling seasonality is the more determining factor

Accurately profiling and characterizing factors shaping raw milk microbiota would provide practical information for detecting microbial contamination and unusual changes in milk. The current work was an observational study aiming to profile the microbiota of raw milk collected across wide geographic regions in China in different seasons and to investigate the contribution of geographical, seasonal, and environmental factors in shaping the raw milk microbiota. A total of 355 raw cow milk samples from healthy Holsteins and 41 environmental samples (farm soil and surface of milking room floor) were collected from 5 dairy farms in 5 Chinese provinces (namely, Daqing in Heilongjiang province, Jiaozuo in Henan province, Qingyuan in Guangdong province, Suqian in Jiangsu province, and Yinchuan in Ningxia Hui Autonomous Region) in January, May, and September 2018. The microbial communities in raw milk and farm environmental samples were determined using the PacBio small-molecule real-time circular consensus sequencing, which generated high-fidelity microbiota profiles based on full-length 16S rRNA genes; such technology was advantageous in producing accurate species-level information. Our results showed that both seasonality and sampling region were significant factors influencing the milk microbiota; however, the raw milk microbiota was highly diverse according to seasonality, and sampling region was the less determining factor. The wide variation in raw milk microbial communities between samples made it difficult to define a representative species-level core milk microbiota. Nevertheless, 3 most universal milk-associated species were identified: Lactococcus lactis, Enhydrobacter aerosaccus, and Acinetobacter lwoffii, which were consistently detected in 99%, 95%, and 94% of all analyzed milk samples, respectively (n = 355). The top taxa accounting for the overall seasonal microbiota variation were Bacillus (Bacillus cereus, Bacillus flexus, Bacillus safensis), Lactococcus (Lactococcus lactis, Lactococcus piscium, Lactococcus raffinolactis), Lactobacillus (Lactobacillus helveticus, Lactobacillus delbrueckii), Lactiplantibacillus plantarum, Streptococcus agalactiae, Enhydrobacter aerosaccus, Pseudomonas fragi, and Psychrobacter cibarius. Unlike the milk microbiota, the environmental microbiota did not exhibit obvious pattern of seasonal or geographic variation. However, this study was limited by the relatively low number and types of environmental samples, making it statistically not meaningful to perform further correlation analysis between the milk and environmental microbiota. Nevertheless, this study generated novel information on raw milk microbiota across wide geographic regions of China and found that seasonality was more significant in shaping the raw milk microbiota compared with geographic origin