Seasonal Climate Research Articles

A Study of Member Displacement According to Seasonal Climate of the Sungnyemun Gate, a Korean Wooden Architectural Heritage Site

This study analyzes the results of a displacement measurement of the Sungnyemun Gate’s structural members, such as column, girder, and hip rafter, carried out by the National Institute of Cultural Heritage for about 10 years from December 2013 to October 2022. Through this, we attempt to examine the behavior of wooden architectural heritage sites according to seasonal changes and infer the factors influencing structural deformation. As a result of the analysis, it was confirmed that the structural members of the Sungnyemun Gate, including the columns, girders, and hip rafters, continued to move and that the displacement of members was accumulated, and the structure was deformed. It was also confirmed that member displacements accumulated in a specific direction. In the case of the Sungnyemun Gate, the column leaning south, the hip rafters’ endpoint sagging, and the girders’ center deflecting were continuously observed. Furthermore, the behavior of wooden architectural heritage sites, where displacement accumulates as it undergoes repeated deformation and recovery according to seasonal changes, was also revealed in detail. The deformation of the Sungnyemun Gate’s members shows a pattern that reflects the mechanical properties of wood, which repeatedly increases and decreases displacement depending on the season. However, seasonal deformation did not appear the same in all the members. Even the same member has an uneven drying speed due to differences in the amount of sunlight it receives depending on its location, which leads to uneven distribution of deformation. The significance of this study is that it examined the behavior of a wooden architectural heritage site in detail based on the quantitative results of long-term measurements and prepared primary data for the future management of wooden architectural heritage sites.

Analysis of Uneven Settlement of Long-Span Bridge Foundations Based on SBAS-InSAR

Bridge foundation settlement monitoring is crucial for infrastructure safety management, as uneven settlement can lead to stress redistribution, structural damage, and potentially catastrophic collapse. While traditional contact sensors provide reliable measurements, their deployment is labor-intensive and costly, especially for long-span bridges. Current remote sensing methods have not been thoroughly evaluated for their capability to detect and analyze complex foundation settlement patterns in challenging environments with multiple influencing factors. Here, we applied Small Baseline Subsets Synthetic Aperture Radar Interferometry (SBAS-InSAR) technology to monitor foundation settlement of a long-span bridge. Our analysis revealed distinct deformation patterns: uplift in the north bank approach bridge foundation and the left-side main bridge foundation (maximum rate: 36.97 mm/year), concurrent with subsidence in the right-side main bridge foundation and south bank approach bridge foundation (maximum rate: 35.59 mm/year). We then investigated the relationship between these settlement patterns and various environmental factors, including geological conditions, Sediment Transport Index (STI), Topographic Wetness Index (TWI), precipitation, and temperature. The observed settlement patterns were attributed to the combined effects of stratigraphic heterogeneity, dynamic hydrological conditions, and seasonal climate variations. These findings demonstrate that SBAS-InSAR technology can effectively capture complex bridge foundation deformation processes, offering a cost-effective alternative to traditional monitoring methods. This advancement in bridge monitoring technology could enable more widespread and frequent assessment of bridge foundation stability, ultimately improving infrastructure safety management.

Benthic marine invertebrate herbivores diversify their algal diets in winter

AbstractChanges in the seasonal environment substantially influence organisms. Understanding how species respond to such changes, such as in their feeding interactions and physiology, is key to predicting their resilience to both seasonal and longer term climate changes. The Sitka Sound in Southeast Alaska, USA, is an attractive natural laboratory for studying change, as the marine environment experiences substantial seasonal fluctuations in parameters such as temperature, pH, and productivity between summer and winter. By sampling a suite of dominant macrophyte algae and their benthic herbivores in winter (January) and summer (July) 2019, we investigated how producers and their primary consumers may respond to seasonal change inferred through fatty acid trophic markers. We used a fatty acid logratio selection and analysis approach to ask the following: (1) Do fatty acid biomarkers for algae differ between seasons? (2) Do the same fatty acid biomarkers differ between seasons when applied to herbivores, with herbivore fatty acids tracking the presumed trophic resources? (3) Do fatty acid biomarkers for herbivores differ between seasons, when considered independently from algae? Comparing logratio sets selected each for the algae and the herbivore fatty acids, we found that algae fatty acids were different between our sampling seasons, but the algae‐selected fatty acid logratios did not clearly separate most herbivores by season. In contrast, the herbivore‐selected logratios strongly distinguished herbivore species between the January and June samplings. Further, dispersions of fatty acid logratios were greater within herbivore species in the winter than in the summer, potentially due to the utilization of more diverse resources when preferred algae are less abundant. In total, results suggest that herbivores are not simply tracking the seasonal fatty acid changes in the dominant algae as trophic resources; instead, herbivore fatty acid seasonal changes may occur largely through some other nonexclusive mechanisms, such as omnivory, reductions or shifts in dietary composition, and/or endogenous physiological responses. Thus, the benthic herbivores in our study appear not to be locked into their diets when faced with seasonal change and may use a range of strategies, including diet diversification, to cope with environmental variation.

Epidemiological characteristics and prevention and control strategies for Eimeria spp. in sheep and goats in China: a systematic review

AbstractSheep and goat coccidiosis has a worldwide distribution and is an important disease on lambing farms. Infection with multiple Eimeria species can lead to severe intestinal damage in sheep/goats and economic losses on farms. Disease is a serious constraint to the healthy development of small ruminant farming. Studies published on PubMed, CNKI, VIP, Wanfang and the resulting references of selected studies were included. Risk factors affecting prevalence were analyzed and stratified by geographic location and climatic variables, age, sex, feeding model, season, sample year, breeds and environment. The total prevalence of coccidia in sheep and goats reached more than 60% in most regions, in which the dominant species in sheep were mainly E. parva, E. ovinoidalis, and E. parva and E. ahsata. East China had the lowest prevalence of coccidia infection in sheep (43.24%), and the dominant species were different from those in the other regions, mainly E. bakuensis and E. gonzalezi. Southwestern China and Central China had slightly less than 40.0% goat coccidia infection, and the dominant species in goats were mainly E. arloingi, E. aligevi, E. hirci and E. ninakohlyakimovae. Sheep/goats of different ages can be infected with coccidiosis, but lambs between 1 and 3 months of age are more susceptible to the disease. When lambs become infected, the pathogen spreads rapidly throughout the herd. Spring, summer and autumn are the seasons with a high incidence of this disease. Environmental pollution may be a significant factor in the development of coccidiosis in sheep raised in large-scale housing. This study provides a comprehensive overview of the species, morphology and geographic distribution of Eimeria species in sheep and goats, summary prevalence in different regions of China, risk factors affecting prevalence, and prevention and control strategies.

Effects of seasonal climates and MIPS1 mutations on soybean germination through multi-omics analysis

This study delves into the combined effects of seasonal climate variations and MIPS1 gene mutations on the germination rates of soybean cultivars TW-1 and TW75. Through comprehensive metabolomic and transcriptomic analyses, we identified key KEGG pathways significantly affected by these factors, including starch and sucrose metabolism, lipid metabolism, and amino acid biosynthesis. These pathways were notably disrupted during the spring, leading to an imbalance in metabolic reserves critical for seedling development. Additionally, MIPS1 gene mutations further altered these pathways, exacerbating the metabolic disturbances. Our results underscore the intricate network of environmental and genetic interactions influencing soybean seed vigor and underscore the importance of understanding these pathways to enhance agricultural resilience and seed quality in fluctuating climates.

Structured tb risk factors in regions with low and high population density

In Russia, socio-demographic, health care management, climatic and environmental TB risk factors such as population density, intensity of social contacts, availability of medical care, seasonal climate changes, environmental issues affecting quality of public health have been holding the leading place while a life standard elevates, and epidemic situation becomes improved. However, the magnitude of specific population density-related TB risk factors in the Russian regions has not been examined yet. The study aim was to assess structured TB risk factors in the Russian regions with high and low population densities decreasing public health quality. Materials and methods. There was conducted a study using sociological, cluster-quota approaches, with respondent-based sample and a face-to-face distribution questionnaire provided by 2500 subjects, of which 1497 were from the North Ossetia-Alania Republic with a high population density, 1003 — from the Republic of Karelia with a low population density. A significance of differences was assessed by using exact criterion Fisher using a contingency table. Results. In the Republic of Karelia, compared with North Ossetia-Alania Republic, despite a higher gross regional product (527.8 thousand rubles vs 293.4 thousand rubles, p 0.000), social and behavioral TB risk factors were significantly elevated: fewer respondents with high education (18.4% vs 33.6%, p 0.000), higher divorced (18.7% vs 26.9%, p 0.022), higher number of those living in apartment buildings (65.0% vs 39.5%, p 0.000), more hired and seasonal workers, unemployed, pensioners due to age and disability (55.0% vs 32.3%, p 0.000), more alcohol abusers (67.4% vs 34.3%, p 0.000), “heavy” smokers (20.8% vs 7.2%, p 0.000), more subjects with chronic diseases (43.7% vs 32.1%, p 0.02); more issues related to accessibility to medical care: municipal policlinics are less available (42.7% vs 85.6%, p 0.000), the distant location of medical facilities (21.4% vs 2.7%, p 0.000), lack of transport links (15.7% vs 8.5%, p 0.000), poor roads (5.9% vs 16.9%, p 0.000) and few medical specialists (60.9% vs 16,8%, p 0.000) are more often noted. In the North Ossetia-Alania Republic vs the Republic of Karelia, respondents had more frequent social contact with TB patients (66.9% vs 34.8%, p 0.000). Conclusion. The epidemiological TB factors in the Russian regions with high population density hold a lead place; in regions with low population density, social, behavioral and accessibility to medical care factors remain relevant, which should be taken into account while developing measures for efficient management of epidemic process.

Functional data analysis to investigate controls on and changes in the seasonality of UK baseflow

ABSTRACT Continuous streamflow is critical for sustaining ecological systems and ensuring water resource security. Understanding controls on and changes in flows, including the seasonality of baseflow, is therefore an important task. Baseflow seasons have typically been investigated separately, potentially missing hydroecologically important timing changes. Instead, we apply a functional data analysis clustering approach to seasonal patterns of baseflow hydrographs for 671 catchments across Great Britain (GB). The baseflow clusters are characterized as early-, mid-, and late-season peaks. The spatial distribution of the baseflow seasonality clusters is closely connected to the baseflow index and a partition tree shows the influence of catchment topological, hydrogeological and soil factors. Changes in timing of baseflow seasonality are compared to climate seasonality. In GB there appears to be a small but systematic influence of a warming climate on baseflow seasonality via effective rainfall with a tendency for earlier seasonal baseflow peaks, with greater timing changes in snow-influenced catchments.

How well do climate modes explain precipitation variability?

Large-scale modes of climate variability, such as the El Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, show significant regional correlations with seasonal weather conditions, and are routinely forecast by meteorological agencies attempting to anticipate seasonal precipitation patterns. Here, we use machine learning together with more traditional approaches to quantify how much precipitation variability can be explained by large-scale modes of variability, and to understand the degree to which these modes interact non-linearly. We find that the relationship between climate modes and precipitation is predominantly non-linear. In some regions and seasons climate modes can explain up to 80% of precipitation variability. However, variability explained is below 10% for more than half of the land surface, and only 1% of the land shows values above 50%. This outcome provides a clear rationale to limit expectations of predictability from modes of variability in all but a few select regions and seasons.

Differences in phenology between non‐native C4 grasses and native C3 and C4 grasses in a seasonally dry ecosystem

AbstractPlant species phenology is an important driver of invasions in seasonal climates. The phenology of non‐natives is generally uncoupled from that of native species. Grasses cover a large proportion of the land surface and are important invaders around the world. Interestingly, the phenology of native and non‐native grasses could be modulated by the different metabolic pathways. We aimed to compare the vegetative and reproductive phenology of invasive C₄ grasses with that of coexisting native C₃ and C₄ grasses and to explore the relationship between phenology and climate. We recorded the onset, duration and synchronicity of vegetative and reproductive phenology (flowering and fruiting) during 1 year. Native C₃ grasses had 50% of their above‐ground biomass green earlier and remained in that state for a longer period than non‐native and native C₄ grasses. Flowering and fruiting occurred earlier in non‐native C₄ grasses than in native C₄ grasses. The flowering period was longer in non‐native C₄ than in native C₃ and C₄, with the non‐native Melinis repens (Poaceae), a highly invasive species worldwide, accounting for most of the difference. Non‐native C₄ tended to exhibit a lower flowering and fruiting synchrony than both native C₃ and C₄ species. Finally, reproductive and vegetative phenology was positively associated with temperature, while precipitation was mostly associated with C₄ species. The uncoupled vegetative phenology observed could be related to differences in metabolism among the studied species, while the uncoupled reproduction between non‐native and native C₄ grasses could be due to an advantage in resource use by non‐native species. Our work provides the first insight into the possible role of the species origin and metabolic pathways in the vegetative and reproductive phenology of invasive non‐native C₄ and native C₃ and C₄ grasses. Finally, we suggest future directions to elucidate these processes.

Climate and soil explain contrasting intraspecific trait variability of widespread species over a large environmental gradient

Both climatic and edaphic conditions are currently undergoing significant changes on a global scale. Early studies have suggested that climate and soil together shape plant performance. However, establishing a precise theoretical framework to describe trait-environment relationships has proven challenging. Understanding and identifying the patterns and drivers of intraspecific trait variation is crucial for anticipating changes in plant distributions. This study aimed to examine the relative importance of various environmental drivers in explaining intraspecific trait variation for two widespread species, Sophora japonica and Robinia pseudoacacia, across a broad environmental scale spanning from the southeast to the northwest of China. Intraspecific variation in fourteen functional traits accounted for 23.4 % of S. japonica and 28.4 % of R. pseudoacacia, indicating that these species exhibit a degree of plasticity in response to changing environmental conditions. There were differences in the influence of climatic and edaphic factors on intraspecific trait variation. For both species, hydraulic trait variations were primarily driven by climate during the growth season and climatic seasonality. In comparison, soil chemical properties accounted for a substantial proportion of the variability in leaf economic traits. Our results show that S. japonica and R. pseudoacacia responded differently to variations in climatic factors. In contrast, the impact of soil factors on traits was more consistently observed between these two species. We conclude that soil conditions, like climate, are crucial factors in investigating geographic variation in functional traits and species distributions. Our analysis also highlights that species specificity must be considered when discussing plant adaptability to climate change. These findings provide valuable insights into how and to what extent climatic and edaphic factors influence species distributions by driving the intraspecific trait variability.

On the Use of Hindcast Skill for Merging NMME Seasonal Forecasts across the Western United States

Abstract Multimodel ensemble forecasts have gained widespread use over the past decade. A yet unresolved issue is whether forecast skill benefits from the use of prior skill from each model in providing a weighted combination. Here, we use the available seasonal ensemble forecasts of six models from the North American Multi-Model Ensemble (NMME) to study various aspects of prior skill–based weighting schemes and explore ways to merge multimodel forecasts. First, we postprocess each NMME model through quantile mapping and a simple spread error adjustment. Then, using an equal weighted combination as the baseline forecast, we test merging the models together through skill-based weights by varying the prior skill metric and varying how the metrics are aggregated across the different subbasins and time of year. Results confirm prior work that the combined forecasts do outperform individual models. When evaluating prior skill, equal weighting generally performed as well as or slightly better than all weighting schemes tried. The skill of the weighting scheme was not found to be strongly dependent on prior metric but did improve when aggregating all forecasted months and subbasins together to provide one overall weight to each model. Also, we found that including an offset to the prior metric that nudged the weights closer to equal weighting improves skill especially at longer leads where individual model skill is low. Results also show that the weighting schemes performed better than regression-based techniques including multiple linear regression and random forest. Significance Statement Here, we test how effective the past performance of seasonal climate models can be used for generating weights to merge multiple models together using the North American Multi-Model Ensemble (NMME) for forecasting temperature and precipitation across the western United States. Our results showed there was little benefit in using prior performance compared to weighting all six NMME models equally. The performance of the weighted forecasts was not strongly dependent on the choice of performance metric or over how many months or basins performance was pooled. An important finding is that when only one or two models were used for merging, performance was reduced relative to equal weighting; however, if three or more models were used, performance was nearly the same.

GEOGRAPHICAL ANALYSIS OF THE FACTORS AFFECTING THERMAL COMFORT IN AL-MASHKHAB DISTRICT

The climate is one of the most important environmental factors that affect human comfort and health, as the human body responds to climatic elements involuntarily due to their effect on the heat exchange process between the human body and the thermal environment in which it lives. Several thermal comfort indicators were applied to determine the limits of thermal comfort in the study area (Ghom indicator and wind cooling indicator k), which depended on the most stable climate elements in the study area (temperature, relative humidity, and wind). As a result, the climatic seasons of the year were determined based on the cold winter months (December, January, and February). The spring season is represented by the months of (March and April), which are moderate, while the summer season represents The hot months (May, June, July, August, and September). The months (October and November) represent the fall season. The study concluded after comparing the results of the monthly distribution of climate indicators with the classification limits of human thermal comfort that the state of thermal extremism did not appear, represented by the great stress that threatens health during the months of the year, while the state of severe thermal discomfort appeared clearly, especially during the day of the summer months (severe hot discomfort) and the nights of the winter months (severe cold discomfort), so these two seasons are the least suitable for practicing most types of activities in open places, while the most suitable times for practicing various activities were represented by the spring and fall seasons, as the degree of influence of climate elements on the human feeling of comfort varied during the months of the year as in Tables (3, 5), and the study recommends the necessity of linking various human activities and events to human thermal comfort and linking vacations to the months of thermal discomfort.

Pleistocene pedogenic carbonates from alluvial paleosols in eastern Sudan reveal a semi-arid and seasonal climate, similar to today

Pedogenic carbonates can provide important information regarding paleoclimatic conditions. Compared with East Africa, Pleistocene pedogenic carbonates in Sudan, particularly calcretes, have received very little attention, particularly with regard to local paleoclimatic reconstructions. Pleistocene alluvial sediments aged from ∼230 to <17 ka were deposited along the middle Atbara River in eastern Sudan. Intercalated in these alluvial deposits are paleosols in which different types of pedogenic carbonates occur. Petrographic, mineralogical and isotopic analyses were performed to reconstruct the regional paleoenvironmental conditions. The investigated pedogenic carbonates are appropriate for paleoclimatic reconstruction because they are free of inherited carbonate and diagenetic modification. The paleosols identified in a previous study as Aridisols/Calcisols contain calcrete horizons that consist of an orthic nodular horizon, sometimes overlain by a laminar horizon. Paleosols identified as Vertisols contain slickensides, and disorthic and septaric nodules. The paleosols show stable carbon and oxygen isotope values ranging between −9.12 and −5.12 ‰, and between −7.25 and −4.09 ‰, respectively. Supporting the previous study, the inferred climatic conditions were arid to semi‐arid, with a mixture of C3 and C4 vegetation cover, and paleoprecipitation greater than 350 mm/yr, similar to that of the present-day, with likely higher rainfall during the formation of Vertisols than Aridisols/Calcisols. The thickness and morphology of Pleistocene calcretes in eastern Sudan are similar to those in East Africa, suggesting similar climatic conditions during their formation. Well-and weakly-developed calcretes in Aridisols formed in distal and proximal floodplains, respectively, whereas well-developed vertic horizon in Vertisols formed in distal floodplains.

Forward modelling of white spruce radial growth at trailing edge demonstrates high plasticity

Climate conditions throughout the 21st century across much of western Canada's boreal forest have been drier than normal leading to significant impacts on forest productivity and tree growth. Determining the limiting factors of radial growth in common boreal tree species under current and future conditions is crucial to reconcile how they will continue to respond to climate change. In this study, we used a network of 26 white spruce tree-ring chronologies south of its natural range as an artificially constructed trailing edge to assess climate-growth relationships and limiting factors by identifying seasonal climate relationships and using the Vaganov-Shashkin Lite (VS-Lite) model, respectively. Analysis revealed that white spruce in the study region is positively correlated to precipitation and negatively associated with temperature from the current and previous growing seasons. VS-Lite showed that moisture was the primary limiting factor in growth across the entire study area. The modelled radial growth from the VS-Lite model showed moderate success (14 of 26 site models were significant) and was more variable than measured tree-ring index values. The model systematically overestimated drought-related impacts on radial growth, especially during the middle portion of the growth season (June–August) indicating white spruce likely employs a conservative approach to carbohydrate storage as the region is much more susceptible to moisture deficits. The outcome of our research illustrates that white spruce may be resilient to hotter, drier conditions through environmental plasticity in the Boreal Plains.

The economic value of seasonal weather and climate services for maize farmers in Manicaland Province of Zimbabwe

Most rural areas in Zimbabwe are extremely vulnerable to changing climatic conditions, particularly droughts, which threaten smallholder farmers' livelihoods. Seasonal weather forecast services can help farmers adapt, optimise production, and implement risk reduction strategies. To support increased investment in these services, this study seeks to provide quantitative evidence on the economic value of locality-specific seasonal weather forecasts by eliciting maize producers' willingness to pay (WTP) through the contingent valuation approach. The results of the study show that among 502 farmers, 68 % would pay for seasonal weather forecasts, highlighting their perceived economic value and practical utility in agricultural decision-making. On average, farmers were willing to pay one (1) United States dollar (US$1) per month for seasonal weather forecast services. Extrapolating this demand nationally, we estimate an annual economic value of around US$ 53.2 million for these services. This valuation underscores the substantial economic benefits that weather and climate services could offer to Zimbabwe's agriculture sector, justifying the case for increased resource allocation towards the delivery of location-specific weather forecasts. Using the Heckman selection model, the study further identified that maize producers' climate change perceptions, radio ownership, and prior participation in agricultural policy development significantly increased their likelihood of paying for seasonal weather forecasts. These factors highlight the role of both access to information and engagement in policy processes in shaping farmers' valuation of seasonal weather forecasts. Establishing district-level climate change dialogue platforms can significantly enhance maize producers' awareness of climate change, deepen their understanding of the value of weather forecasts, and encourage their participation in policy-making processes. By creating spaces for knowledge exchange and farmer engagement, these platforms not only support informed farm decision-making but also help tailor climate services to farmers' needs. Nevertheless, farmers from the Ndau ethnic group and those in remote areas showed reluctance to pay for seasonal weather forecasts, indicating that factors like ethnicity and remoteness affect WTP. This reluctance highlights how social marginalisation and inadequate infrastructure in remote areas limit access to weather information, thereby reducing farmers' perceived value of these services. Enhanced telecommunication infrastructure and radio signals in rural areas, especially community radios, could help to expand the access and tailoring of forecast messages in local languages, making it understandable and thus supporting informed decision-making across diverse farming communities.

Effects of seasonal climate forecasts on livelihood outcomes: a case of smallholder farmers in rural Zambia

In as much as seasonal climate forecasts are an essential tool for supporting livelihoods in rainfed agriculture production, the effects of seasonal climate forecasts on income and yield at the agro ecological zone and wealth quartile levels are not sufficiently researched in Zambia. In order to close this gap, we focused on investigating the impacts of using climate information on productivity and income, while using an endogenous switching regression on a representative subnational and national level data from 7241 agricultural households. Using STATA 17 for analysis, the study found that smallholder farmers who integrated seasonal climate forecasts outperformed those who did not have the information, achieving higher yields (421.54 kg/ha). The localized effects of seasonal forecasting by agro ecological zone indicated that low rainfall areas had significant yield gains than other zones, and wealth results for wealth quartiles showed that farmers in higher quartiles had better yield (126.14 kg/ha) and income (1509.44 kg/ha) gains.. This study therefore recommends that policymakers develop policies and strategies that are region-specific to foster climate awareness to and integration of adaptation techniques by farmers. Additionally, the study also recommends the provision of social safety net to less-endowed farmers as well as investing in better early warning systems to enhance participation in using forecasted information for a sustainable future.

Climatic seasonality and dominant species drive the temporal dynamics in a lizard assemblage in the Arid Chaco - Monte ecotone

Lizard assemblages are dynamic, influenced by both seasonal climatic changes and intrinsic population shifts. Climate plays a crucial role in shaping lizard phenology, or the timing of their biological events, which critically affects the spatiotemporal structure of sympatric populations. Understanding how species richness and abundance fluctuate over time, and how these changes are influences by temporal factors, is essential for distinguishing between variations caused by unpredictable external factors and underlying natural changes. This study aimed to characterize lizard assemblage structure and dynamics, as well as species demographics, over three consecutive years within an Arid Chaco - Monte ecotone in central-western Argentina. We also sought to assess the effects of environmental drivers (e.g., temperature, precipitation) on assemblage and population dynamics. Monthly samples were taken using pitfall traps from October 2015 to May 2018 within the protected area of the Valle Fértil Multiple Use Reserve. We captured 1446 lizards, representing 12 species. Liolaemus chacoensis was dominant in the assemblage, followed by Teius teyou and Aurivela longicauda. Species richness and diversity varied seasonally, peaking during summer and autumn. The lizard assemblage exhibited activity throughout all seasons, with significant temporal niche overlap between species. Reproduction and activity in lizards were highly seasonal, primarily occurring in spring and summer, likely due to low winter temperatures and highly seasonal rainfall. Our study shows that climate seasonality and the demographics of the dominant species significantly influence the temporal dynamics of lizard assemblages in the Arid Chaco-Monte ecotone of Argentina.

Effect of Grazing on the Welfare of Dairy Cows Raised Under Different Housing Conditions in Compost Barns.

There is currently no established information for assessing the general welfare conditions and behavior of dairy cows housed in compost-bedded pack barns (CBPs) that allow access to pasture. Therefore, the objective of this study was to evaluate and classify the welfare and behavior of dairy cows in three different housing conditions within CBPs in southern Brazil. During both the cold and hot seasons, nine farms were divided into three groups: CONV (conventional, large, full-time barns), ADAP (conventionally adapted, full-time barns), and PART (part-time barns). The European Welfare Quality® (WQ®) protocol takes into account the characteristics of the animals, animal housing, and farm management to set an overall score to assess animal welfare, which is why WQ® was used in this study. Daytime behavior was monitored over a period of four consecutive hours on two days. The 29 WQ® measures were grouped into 11 criteria, then into four principles, and finally into the general welfare category. The experimental design employed was a randomized block design in a 2 × 3 factorial scheme (two climatic seasons and three groups), with the means of the measures, principles, and criteria for each group, season, and interaction (group × season) compared using the Tukey test. The diurnal behavior of the cows was described by the average absolute frequency of each observed behavioral measure. There were no differences among the groups in any of the measures assessed by the WQ® protocol. However, there was a significant increase in both the incidence of diarrhea and the duration of lying down during the cold season. Only the principle of appropriate behavior varied among the groups, with the PART group demonstrating superior scores. Regardless of the season, the welfare of dairy cows maintained in CBPs was classified as "improved". No abnormalities in behavior were observed among cows housed in the different groups or seasons. Cows in the PART group laid down less frequently during the hot season. Overall, the CBP system provided favorable welfare and behavioral conditions for cows in Brazil, and access to grazing further enhanced the welfare of animals housed in the PART group.

Is the ‘Year Without a Summer’ imprinted in continental varve thickness records?

The 1816 CE Year Without a Summer (YWS), following the 1815 CE Tambora eruption, is a classic example of a global cooling event caused by a volcanic eruption. It is well-documented in various historical sources and natural archives. In this study, we investigate whether imprints of this event can be detected in time series of varve and varve sublayer thickness (VT) derived from lake archives. To this end, we examine 43 published and globally distributed VT records covering the period 1766–1866 CE. We hypothesize that thickness anomalies in many VT records correspond to the YWS because it was one of the most prominent climatic events of recent centuries, and VT is a sensitive climate recorder. We evaluate site-specific temperature and precipitation anomalies for the YWS of each investigated lake using available climate model simulations that incorporate proxy and observational data. VT anomalies are identified based on individually selected threshold values for each record, following a robust estimation of trend and variability in the VT data. The climate variables and seasons most influential to VT are determined for each lake based on the related original publications. Our analysis documents that only five records reveal VT anomalies attributable to the YWS. The relationship between VT anomalies and the YWS is questionable in seven records, primarily due to uncertainty about the climatic influence on VT in these cases, and unlikely for the remaining 31 records. The 31 records lacking a YWS signature are divided into two groups. In the first group, the absence of VT anomalies is likely due to weak climate forcing, as temperature and precipitation changed only slightly at those locations. In the second group, while climate forcing was significant, the season during which the anomaly occurred or the specific climate variable that deviated from the long-term mean were not the primary drivers of VT identified in the original studies. We conclude that VT anomalies due to annual climate events are only recorded if a combination of favorable conditions coincides.

Seasonal Upwelling Forecasts in the California Current System

AbstractCoastal upwelling plays a vital role in the support and maintenance of productive marine ecosystems throughout the California Current System (CCS). Here, we evaluate upwelling forecast skill using ∼30 years of seasonal reforecasts from four global climate models contributing to the North American Mulitmodel Ensemble (NMME). The models skillfully predict upwelling intensity throughout much of the CCS in boreal winter, and in the South‐Central CCS in spring/summer. The models also skillfully predict various aspects of upwelling phenology, including the timing of the spring transition, as well as the total vertical transport integrated over the course of the upwelling season. Climatic sources of forecast skill vary with season, with contributions from the El Niño‐Southern Oscillation in winter‐spring, and the North Pacific Oscillation and the North Pacific Meridional Mode in the winter‐summer. Our results highlight the potential of seasonal climate forecasts to inform management of upwelling‐sensitive marine resources.