Seasonal Calendar Research Articles

Role of local wisdom community Dayak Kanayatn in the fire disaster prevention (forest fires for the opening of farming fields in West Kalimantan)

Human activities in meeting their needs such as fulfillment of clothing, food and shelter require people to sacrifice what is around them, for example in agriculture, so people have to burn the forest. For Dayak tribes, forests are also commonly used for farming. So that the role of government and local communities is very important in maintaining the preservation of forest areas, for example by optimizing the role of local wisdom owned by the Kanayatn Dayak community, Bahuma Batahutn. Bahuma Batahutn is a wise way to manage the environment owned by the Kanayatn Dayak tribe. Forest management for daily life with a seasonal calendar system to be planted in the fields. Forest burning as part of land clearing is done in the right way and time so that it naturally does not cause disaster. During the forest burning process, involving many people (family or community) by keeping the points prone to burning and providing water to prevent forest fires.

Commodification of forestlands and assault on indigenous knowledge within forest-dependent communities of Cross River State, Nigeria

The basic component of any society’s knowledge system is undoubtedly its indigenous knowledge. This consists of skills, experiences and insights which the people apply to maintain and improve their lives. Indigenous patterns of behaviour are well known for not only being relevant for preserving local forest resources but also for enriching livelihood systems. Adopting participatory rural appraisal research methods consisting of transects, trend analyses, seasonal calendars, institutional analyses and direct observations, this paper discusses how increased privatisation of forestlands and resources within forest-dependent communities of Cross River, Nigeria is evolving into well-developed alienating structures of neoliberal markets, thereby incapacitating local populations in adapting to environmental changes and resulting stressors of extreme events. This issue is also complicated by their cultural ability to tackle challenges of external adaptation and internal integration that confront them. Hence, actions and policies of forest conservation within forest-dependent communities of Cross River need to be more directed at promoting indigenous knowledge systems that brace common meaning for forests. Indigenous educational systems should also be strengthened in ways that help community people begin to think historically about alternative outcomes, and how they are agents and victims of history and their forestlands and resources are no longer for the public good.

Co-developing Indigenous seasonal calendars to support 'healthy Country, healthy people' outcomes.

In caring for Country, Indigenous Australians draw on laws, knowledge and customs that have been inherited from ancestors and ancestral beings, to ensure the continued health of lands and seas with which they have a traditional attachment or relationship. This is a reciprocal relationship, whereby land is understood to become wild/sick if not managed by its people, and in turn individuals and communities suffer without a maintained connection to Country. It is well understood by Indigenous people that if you 'look after country, country will look after you'. Indigenous knowledge systems that underpin the local care (including use and management) of Country are both unique and complex. These knowledge systems have been built through strong observational, practice-based methods that continue to be enacted and tested, and have sustained consecutive generations by adapting continually, if incrementally, to the local context over time. This paper describes a research partnership that involved the sharing and teaching of Ngan'gi Aboriginal ecological knowledge in order to reveal and promote the complex attachment of Ngan'gi language speakers of the Daly River, Australia, to water places. This engagement further led to the incremental co-development of an Indigenous seasonal calendar of aquatic resource use. The seasonal calendar emerged as an effective tool for supporting healthy Country, healthy people outcomes. It did this by facilitating the communication of resource management knowledge and connection with water-dependent ecosystems both inter-generationally within the Ngan'gi language group, as well as externally to non-Indigenous government water resource managers. The Indigenous seasonal calendar form has subsequently emerged as a tool Indigenous language groups are independently engaging with to document and communicate their own knowledge and understanding of Country, to build recognition and respect for their knowledge, and to make it accessible to future generations.

Surveillance of infections in long-term care facilities (LTCFs): The impact of participation during multiple years on health care-associated infection incidence.

We studied trends in the incidence of health care-associated infections (HAIs) in LTCFs between 2009 and 2015 and determined the effect of participation in our network. Elder-care physicians reported weekly the number of cases of influenza-like illness, gastroenteritis, (probable) pneumonia, urinary tract infections (UTIs) and all-cause mortality. Trends in the incidence of infection and mortality in relation to LTCF characteristics were calculated using multilevel univariate and multivariate logistic regression. Thirty LTCF participated for 3 years or more, 16 for 2 years and the remaining 12 LTCF for 1 year. During the study period, the median number of beds decreased from 158 to 139, whereas the percentage of residents with private bedrooms increased from 14% to 87%. UTIs were the most frequently reported infections, followed by (probable) pneumonia and gastroenteritis. Adjusted for calendar year and season, we observed a statistically significant decrease in the incidence of influenza-like illness (odds ratio (OR) = 0.8, P < 0.01) and (probable) pneumonia (OR = 0.8, P < 0.01) for each extra year an LTCF participated. Although there are other likely contributors, such as more private rooms and enhanced infection control measures, the decreasing trend of HAI in LTCFs participating in surveillance implies that surveillance is a valuable addition to current strategies to optimise infection control.

Indigenous use of stellar scintillation to predict weather and seasonal change

Indigenous peoples across the world observe the motions and positions of stars to develop seasonal calendars. Changing properties of stars, such as their brightness and colour, are also used for predicting weather. Combining archival studies with ethnographic fieldwork in Australia’s Torres Strait, we explore the various ways Indigenous peoples utilise stellar scintillation (twinkling) as an indicator for predicting weather and seasonal change, and examine the Indigenous and Western scientific underpinnings of this knowledge. By observing subtle changes in the ways the stars twinkle, Meriam people gauge changing trade winds, approaching wet weather and temperature changes. We then examine how the Northern Dene of Arctic North America utilise stellar scintillation to forecast weather.

Obserwacje pobierania wody przez prosięta ssące w różnych porach roku

The aim of the study was to observe and quantify the intake of water by piglets in the sucking period up to 28 days. An attempt was made to compare the quantity of taken water sinks in four different periods, similar to the occurrence of calendar seasons in Poland's climatic conditions. The research was conducted in the conditions of a pig farm, producing fatteners in a closed cycle. The observations included 17 litters obtained from Polish Landrace (PL) sows mated by four Polish Large White (PLW) boars. They were conducted during the full calendar year in four groups, depending on the date of birth and rearing: from 1 December to 28 February (Group I), from 1 March to 31 May (Group II), from 1 June to 31 August (Group III) and from 1 September to 30 November (Group IV). The number piglets in litters, total weight of litter and individual weight of piglets were similar among groups. Some piglets (Group I) started taking water from the first day of life, but it was a small amount. The regular intake of all piglets started at 3 days of age. The highest water intake was recorded in spring-summer (Group II and III), and as a percentage of 1 kg body weight of piglets, the highest consumption occurred in group II (March-May). It was hypothesized that the increased water requirement in the spring and summer months may be due to the variability of the conditions related to the outdoor temperature, the length of the light day and thus the varied life activities of the piglets. Perhaps, it is also related to atavistic symptoms in pigs. However, this requires further research.

Elite football teams that do not have a winter break lose on average 303 player-days more per season to injuries than those teams that do: a comparison among 35 professional European teams

ObjectiveTo compare injury rates among professional men’s football teams that have a winter break in their league season schedule with corresponding rates in teams that do not.Methods56 football teams from...

A higher-order Markov chain-modulated model for electricity spot-price dynamics

Over the last three decades, the electricity sector worldwide underwent massive deregulation. Power market participants have encountered a growing number of challenges due to competition and other pertinent factors. For most markets at present, electricity is a non-storable commodity and its price is extremely sensitive to changes in supply and demand. The evolution of electricity prices exhibits pronounced mean reversion and cyclical patterns, possesses extreme volatility and relatively frequently occurring spikes, and manifests presence of memory property. These observed features necessitate the development of models aimed to simultaneously capture such price characteristics for forecasting, risk management, and valuation of electricity-driven derivatives. Majority of current research studies examining electricity spot prices are based on one-state models. Such models though may not accurately capture the stylised behaviours of price evolution, especially during periods of sudden spikes driven by the abrupt changes of market sentiments. This paper tackles the modelling and estimation problems under a new paradigm that integrates the deterministic calendar seasons and stochastic factors governing electricity prices with a regime-switching feature. The de-seasonalised component of our proposed model has both the jump and mean-reverting properties to account for spikes and periodic cycles alternating between lower price returns and compensating periods of higher price returns. The parameters of the de-seasonalised model components are also modulated by a higher-order hidden Markov chain (HOHMC) in discrete time. This provides a mechanism to extract latent information from historical data. The HOHMC’s state is interpreted as the “state of the world” resulting from the interaction of various forces impacting the electricity market. Filters are developed to generate optimal estimates of HOHMC-relevant quantities using the observation process, and these provide online estimates of model parameters. Empirical demonstrations using the daily electricity spot prices, compiled by the Alberta Electric System Operator (AESO), show that our HOHMM approach has considerable merits in terms of price data fitting and forecasting metrics. Our proposed framework driven by a hidden Markov chain with a state memory-capturing mechanism provides a powerful alternative to support the pricing of contracts in the electricity markets.

Week 3\u20134 predictability over the United States assessed from two operational ensemble prediction systems

The subseasonal predictability of surface temperature and precipitation is examined using two global ensemble prediction systems (ECMWF VarEPS and NCEP CFSv2), with an emphasis on the week 3–4 lead (i.e. 15–28 days ahead) fortnight-average anomaly correlation skill over the United States, in each calendar season. Although the ECMWF system exhibits slightly higher skill for both temperature and precipitation in general, these two systems show similar geographical variations in the week 3–4 skill in all seasons and encouraging skill in certain regions. The regions of skill are then interpreted in terms of large-scale teleconnection patterns. Over the southwest US in summer, the North American monsoon system leads to higher skill in precipitation and surface temperature, while high skill over northern California in spring is found to be associated with the seasonal variability of the Arctic Oscillation (AO). During winter, in particular, week 3–4 predictability is found to be higher during extreme phases of the El Niño–Southern Oscillation, Pacific-North American (PNA)/Tropical-Northern Hemisphere mode, and AO/North Atlantic Oscillation (NAO). Both forecast systems are found to predict these teleconnection indices quite skillfully, with the anomaly correlation of the wintertime NAO and PNA exceeding 0.5 for both models. In both models, the subseasonal contribution to the PNA skill is found to be larger than for the NAO, where the seasonal component is large.

Annual cycle of temperature trends in Europe, 1961–2000

Abstract Recent global warming has not been ubiquitous: there are seasons, regions, and time periods with negligible or even negative air temperature trends (frequently referred to as warming holes). This paper presents a novel method enabling a proper localization of specific trend events, such as periods of warming holes, of a particularly strong warming, and of rapid transitions of trend amplitudes during the calendar year. The method consists in analyzing trends for periods of a given length (10 to 90 days) that are sliding over the year with a one day step. This allows a detailed description of the annual cycle of trends. The analysis is conducted for daily maximum and minimum temperature at 135 stations in Europe in 1961–2000. Despite an overall warming in Europe, several warming holes are uncovered during various parts of the year, not only in autumn when a warming hole has already been reported. The autumn warming hole concentrates in Eastern Europe, but it changes its strength and spatial extent: it spreads into Western Europe in September and retreats to Eastern Europe in November when it intensifies especially north of the Black Sea. Three shorter warming holes are detected: In February and March, cooling occurs in the Eastern Mediterranean and Iceland, while in early April, cooling is detected over Central, Southern, and Southeastern Europe. Another large-scale cooling occurs in Central, Northern, and Northwestern Europe in mid-June. The periods of strongest warming occur around the middle of January in Eastern Europe, in early March over almost entire Europe, and in mid-May and early August mainly over Central and Western Europe. Cluster analysis of stations with respect to the annual cycles of trends demonstrates a spatial coherence of the trends; the lack of spatial coherence points to local peculiarities or data problems of individual stations. The method of sliding seasons proves to be much more effective in the identification and localization of notable trend events than the ordinary approach of trend detection for fixed calendar seasons and/or months.

Exploring Local Knowledge on Climate Variability in Bangladesh: a Cultural Psychological Inquiry

This article looks at the impact of climate variability on communities in northeast Bangladesh through narrative-based interviews with community actors. We investigate the construction of climate knowledge looking particularly at processes of knowing by applying a cultural psychological approach. The findings reveal that personal experiences with weather were the most common source of knowledge on climate variability. Existing knowledge systems, such as the seasonal calendar aided participants in reasoning and sense making about changes, and elders, media outlets, and science formed the most trusted sources of climate information. Lessons drawn from the study emphasize a need to include cultural and contextual factors when investigating how people construct and build climate knowledge in the future.

Indian time: time, seasonality, and culture in Traditional Ecological Knowledge of climate change

IntroductionWestern climate science and Traditional Ecological Knowledge (TEK) represent complementary and overlapping views of the causes and consequences of change. In particular, observations of changes in abundance, distribution, phenology, or behavior of the natural environment (including plants and animals) can have a rich cultural and spiritual interpretation in Indigenous communities that may not be present in western science epistemologies.ResultsUsing interviews with Indigenous elders and other Traditional Knowledge holders, we demonstrate that assumptions about the nature, perception, and utilization of time and timing can differ across knowledge systems in regard to climate change.ConclusionsOur interviewees’ focus on relationality predisposes them to notice interactional changes among humans and other species, to be sensitive to smaller scale examples of change, to be more likely to see climate change as part of a broader time scale, and to link changes to a greater suite of socio-political phenomena, including the long arc of colonialism. One implication of this research and the interactions among humans and other species is that policies restricting Native and non-Native access to resources (i.e., hunting and fishing) to certain calendar seasons may need to be revisited in a changing climate.

Influence of seasonal variation on in vitro fertilization success.

ObjectiveTo evaluate the influence of seasonal variation on in vitro fertilization (IVF) outcome in a large cohort population.Methods & materialsA total of 5,765 IVF cycles conducted in Sheba medical center between 2013 and 2016 were retrospectively analyzed. The treatment cycles included 4214 ovarian stimulation and ovum pick up (OPU) cycles of which 3020 resulted in fresh embryo transfer and 1551 vitrified- warmed cycles of which1400 resulted in warmed embryo transfer. Cycles were assigned to seasons according to the date of OPU for fresh embryo transfer cycles or according to the date of embryo warming for vitrified warmed embryo transfer cycles.ResultsThere were no statistically significant differences between the calendar months or seasons concerning the number of oocytes retrieved or fertilization rate in the fresh cycles. Throughout the 4 years of the study, the monthly clinical pregnancy rate fluctuated between 18.2% and 27.9% per fresh embryo transfer (mean 23.3%) and between 17.7% and 29.4% per vitrified warmed embryo transfer (mean 23%). These fluctuations did not follow any specific seasonal pattern.ConclusionsOur study did not demonstrate any significant influence of the calendar months or seasons on the clinical pregnancy rates of fresh or vitrified warmed embryo transfers. It might be speculated that the complete pharmaceutical control of the ovarian and endometrial function, as well as the homogeneous treatments, procedures and laboratory equipment used during the study period have lowered the influence of seasonal effect on IVF treatment outcome.

Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada.

Influenza A virus commonly circulating in swine (IAV-S) is characterized by large genetic and antigenic diversity and, thus, improvements in different aspects of IAV-S surveillance are needed to achieve desirable goals of surveillance such as to establish the capacity to forecast with the greatest accuracy the number of influenza cases likely to arise. Advancements in modeling approaches provide the opportunity to use different models for surveillance. However, in order to make improvements in surveillance, it is necessary to assess the predictive ability of such models. This study compares the sensitivity and predictive accuracy of the autoregressive integrated moving average (ARIMA) model, the generalized linear autoregressive moving average (GLARMA) model, and the random forest (RF) model with respect to the frequency of influenza A virus (IAV) in Ontario swine. Diagnostic data on IAV submissions in Ontario swine between 2007 and 2015 were obtained from the Animal Health Laboratory (University of Guelph, Guelph, ON, Canada). Each modeling approach was examined for predictive accuracy, evaluated by the root mean square error, the normalized root mean square error, and the model’s ability to anticipate increases and decreases in disease frequency. Likewise, we verified the magnitude of improvement offered by the ARIMA, GLARMA and RF models over a seasonal-naïve method. Using the diagnostic submissions, the occurrence of seasonality and the long-term trend in IAV infections were also investigated. The RF model had the smallest root mean square error in the prospective analysis and tended to predict increases in the number of diagnostic submissions and positive virological submissions at weekly and monthly intervals with a higher degree of sensitivity than the ARIMA and GLARMA models. The number of weekly positive virological submissions is significantly higher in the fall calendar season compared to the summer calendar season. Positive counts at weekly and monthly intervals demonstrated a significant increasing trend. Overall, this study shows that the RF model offers enhanced prediction ability over the ARIMA and GLARMA time series models for predicting the frequency of IAV infections in diagnostic submissions.

Improving fire season definition by optimized temporal modelling of daily human-caused ignitions

Wildfire suppression management is usually based on fast control of all ignitions, especially in highly populated countries with pervasive values-at-risk. To minimize values-at-risk loss by improving response time of suppression resources it is necessary to anticipate ignitions, which are mainly caused by people. Previous studies have found that human-ignition patterns change spatially and temporally depending on socio-economic activities, hence, the deployment of suppression resources along the year should consider these patterns. However, full suppression capacity is operational only within legally established fire seasons, driven by past events and budgets, which limits response capacity and increases damages out of them. The aim of this study was to assess the temporal definition of fire seasons from the perspective of human-ignition patterns for the case study of Spain, where people cause over 95% of fires. Humans engage in activities that use fire as a tool in certain periods within a year, and in locations linked to specific spatial factors. Geographic variables (population, infrastructures, physiography and land uses) were used as explanatory variables for human-ignition patterns. The changing influence of these geographic variables on occurrence along the year was analysed with day-by-day logistic regression models. Daily models were built for all the municipal units in the two climatic regions in Spain (Atlantic and Mediterranean Spain) from 2002 to 2014, and similar models were grouped within continuous periods, designated as ignition-based seasons. We found three ignition-based seasons in the Mediterranean region and five in the Atlantic zones, not coincidental with calendar seasons, but with a high degree of agreement with current legally designated operational fire seasons. Our results suggest that an additional late-winter-early-spring fire season in the Mediterranean area and the extension of this same season in the Atlantic zone should be re-considered for operational purposes in the future.

Perceived impacts of climate change and disaster risk management by rural communities in Ethiopia

In developing countries including Ethiopia changing pattern of rainfall, increasing temperature, recurrent drought, massive land degradation, and poor performance of agricultural sector contribute for failure to meet the growing demands for food for the rural communities and left dependent on foreign food aid and seasonal migration. This study aims at examining the perceived impacts of climate change and disaster risk management by rural communities in Ethiopia. Cross-sectional socio-economic data were used. Dejen district was purposively selected as it is highly susceptible to climate related problems. Stratified and snowball sampling techniques were employed to select a sample of 398 households. Household survey was employed to collect data on climate change impacts perceived by local communities. Focus group discussions were carried out using guiding questions and seasonal calendar. Key informant interviews were used to triangulate households’ perceived climate change impacts. Field observations were used to observe biophysical, economic, social, and institutional features of the district. The results indicate that crop pests, soil erosion, crop disease, frost, drought, flood, hailstorm, and erratic rainfall were the major contributing factor for the loss of 50,555 quintals of agricultural cops over the period 2009-2016. The community seasonal calendar indicate that erratic rainfall, hailstorm, dry period, flood, landslide, livestock disease, crop disease and pests, and human diseases were the major climatic events in the study areas of rural communities. The lowland households were more susceptible to climate change impacts. Policy priority should be given based on the agro-ecology and households livelihood assets vulnerability levels

The Season Calendar System of Gorontalo Society: Socio-Cultural Analysis Based on Local Wisdom and Appropriate Technology

Gorontalo society is well-known to have a great combination between traditional and cultural nuances. One of the undeniable phenomena is the habit of doing activities and transactions at particular times. This phenomenon then creates several terms such as wedding season, planting season and Hajatan season where those certain custom rituals are only performed in Gorontalo region. The process of inventory of this phenomenon becomes an important step that should be done to ensure that the values contained in the local wisdom of the people of Gorontalo can be documented and become written legacy for future generations. By applying a social research method, this preliminary study aims at creating an inventory for the ongoing local wisdoms in Gorontalo, especially dealing with the creation of a written document containing their season calendar. The draft of season calendar document that had been produced, in the next stage, was then analyzed. Later stage was to create a computer application to be developed in the form of information system prototype containing local calendar module based on local wisdom of Gorontalo society. The application should be easily accessible by local, national and global community, enriched with spatial data presentations and serving as a support for documentation and digital publications. The study is expected to be an effort to preserve local wisdom of Gorontalo as well as become the part of modern culture and knowledge.

Designing a sustainable brand strategy for the fashion industry

Abstract Fashion is widely considered the second most destructive industry to the environment, with a global supply chain employing 58 million people worldwide. During the period of 2000–14, clothing production increased by 50 per cent, as fast-fashion evolved and the luxury sector ascended. Recently, a number of high-profile fashion designers are taking the decision to consciously depart from the constraints of the seasonal fashion calendar, enabling them to reconnect with the creative process, focusing on quality and customer experience. ‘With fashion there is too much fear, not enough time, and not enough love’ (Elbaz 2017). While sustainable fashion has often been considered a consumer-led movement, which brands have been pressured to act upon, it is important that businesses demonstrate social responsibility through a collaborative approach incorporating design, innovation, technology and communication to successfully create desirable sustainable products with integrity. With constant news updates as a result of technology and the overriding competitiveness of social media, brands need to design and launch unique products that attract attention. This article will explore the connection between sustainable design and brand identity in relation to the fashion industry. The article will identify economic and commercial business opportunities, incorporating how combining sustainable design principles with communicative story telling provides additional emotional value for both designer and consumer, and aligning brands with social and environmental issues that are directly related to the products they are selling.

Recovering banana production in bunchy top-affected areas in Sub-Saharan Africa: developing gender-responsive approaches

Banana bunchy top disease (BBTD), an invasive and devastating viral disease, is widespread in banana-producing areas in Sub-Saharan Africa. Recovery of banana production in BBTD-affected areas was undertaken in a research project through the CGIAR Research Program on Roots, Tubers and Bananas (CRP-RTB) in eight countries. Understanding household and community dynamics is vital to recovery because decision-making on banana production and resource allocation occur at household level, while opportunity structures for men and women to engage in such work are influenced by social norms expressed both at household and community levels. Studies were undertaken to understand gender norms, practices and experiences in intra- and inter household and community dynamics related to banana farming in BBTD-affected areas. A standardized methodology was applied in all sites including household survey, gender seasonal calendar, daily activity schedule and a community profile. Results from analysis of four cases studies from Burundi, Gabon, Democratic Republic of Congo (DRC) and Nigeria indicated that banana is an important crop for both female and male farmers in all pilot sites and considered as both a staple food and a source of income. Men, women and male and female children are all involved in different banana production activities at household level; some mostly done by men assisted by male children (land preparation in DRC (95%), Nigeria (83%), Gabon (82.5%) and Burundi (64%)) while others are mostly done by women assisted by female children (watering, weeding in Kisangani (87%)). Men and women have differential use, control and ownership rights to different types of productive resources within the household which have implications for effective BBTD control and the benefits derived. Insights from the study will be used to develop guidelines for the incorporation of gender-responsive strategies into the design and implementation of BBTD control strategies.

Application of AquaCrop model to predict sugarcane yield under the climate change impact: A case study of Son Hoa district, Phu Yen province in Vietnam

This work evaluates the climate change impact on sugarcane yield and proposes the solution to shift the seasonal calendar for matching with sugarcane in the Son Hoa District, Phu Yen Province of Vietnam. Future climate change scenarios for time periods in the 2020s, 2055s and 2090s corresponding to low emission scenario RCP4.5 and high emission scenario RCP8.5 were selected to evaluate sugarcane yield in the study area. Simulated results showed that climate change impact would increase sugarcane yield from 1.73 to 8.26% for both RCP4.5 and RCP8.5 scenarios. The increase of sugarcane yield can be significantly improved when the crop planting calendar will be shifted 40 days delay and sugarcane yield will increase from 1.12 to 8.42 t/ha for both RCP4.5 and RCP8.5 scenarios.