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Item Interaction between Rumen Epithelial miRNAs-Microbiota-Metabolites in Response to Cold-Season Nutritional Stress in Tibetan Sheep.(MDPI (Basel, Switzerland), 2023-09-23) Lv W; Sha Y; Liu X; He Y; Hu J; Wang J; Li S; Guo X; Shao P; Zhao F; Li M; Freking BTibetan sheep are already well adapted to cold season nutrient stress on the Tibetan Plateau. Rumen, an important nutrient for metabolism and as an absorption organ in ruminants, plays a vital role in the cold stress adaptations of Tibetan sheep. Ruminal microbiota also plays an indispensable role in rumen function. In this study, combined multiomics data were utilized to comprehensively analyze the interaction mechanism between rumen epithelial miRNAs and microbiota and their metabolites in Tibetan sheep under nutrient stress in the cold season. A total of 949 miRNAs were identified in the rumen epithelium of both cold and warm seasons. A total of 62 differentially expressed (DE) miRNAs were screened using FC > 1.5 and p value < 0.01, and a total of 20,206 targeted genes were predicted by DE miRNAs. KEGG enrichment analysis revealed that DE miRNA-targeted genes were mainly enriched in axon guidance(ko04360), tight junction(ko04530), inflammatory mediator regulation of TRP channels(ko04750) and metabolism-related pathways. Correlation analysis revealed that rumen microbiota, rumen VFAs and DE miRNAs were all correlated. Further study revealed that the targeted genes of cold and warm season rumen epithelial DE miRNAs were coenriched with differential metabolites of microbiota in glycerophospholipid metabolism (ko00564), apoptosis (ko04210), inflammatory mediator regulation of TRP channels (ko04750), small cell lung cancer (ko05222), and choline metabolism in cancer (ko05231) pathways. There are several interactions between Tibetan sheep rumen epithelial miRNAs, rumen microbiota, and microbial metabolites, mainly through maintaining rumen epithelial barrier function and host homeostasis of choline and cholesterol, improving host immunity, and promoting energy metabolism pathways, thus enabling Tibetan sheep to effectively respond to cold season nutrient stress. The results also suggest that rumen microbiota have coevolved with their hosts to improve the adaptive capacity of Tibetan sheep to cold season nutrient stress, providing a new perspective for the study of cold season nutritional stress adaptation in Tibetan sheep.Item Global fine-resolution data on springtail abundance and community structure(Springer Nature Limited, 2024-01-03) Potapov AM; Chen T-W; Striuchkova AV; Alatalo JM; Alexandre D; Arbea J; Ashton T; Ashwood F; Babenko AB; Bandyopadhyaya I; Baretta CRDM; Baretta D; Barnes AD; Bellini BC; Bendjaballah M; Berg MP; Bernava V; Bokhorst S; Bokova AI; Bolger T; Bouchard M; Brito RA; Buchori D; Castaño-Meneses G; Chauvat M; Chomel M; Chow Y; Chown SL; Classen AT; Cortet J; Čuchta P; de la Pedrosa AM; De Lima ECA; Deharveng LE; Doblas Miranda E; Drescher J; Eisenhauer N; Ellers J; Ferlian O; Ferreira SSD; Ferreira AS; Fiera C; Filser J; Franken O; Fujii S; Koudji EG; Gao M; Gendreau-Berthiaume B; Gers C; Greve M; Hamra-Kroua S; Handa IT; Hasegawa M; Heiniger C; Hishi T; Holmstrup M; Homet P; Høye TT; Ivask M; Jacques B; Janion-Scheepers C; Jochum M; Joimel S; Jorge BCS; Juceviča E; Kapinga EM; Kováč Ľ; Krab EJ; Krogh PH; Kuu A; Kuznetsova N; Lam WN; Lin D; Lindo Z; Liu AWP; Lu J-Z; Luciáñez MJ; Marx MT; Mawan A; McCary MA; Minor MA; Mitchell GI; Moreno D; Nakamori T; Negri I; Nielsen UN; Ochoa-Hueso R; Oliveira Filho LCI; Palacios-Vargas JG; Pollierer MM; Ponge J-F; Potapov MB; Querner P; Rai B; Raschmanová N; Rashid MI; Raymond-Léonard LJ; Reis AS; Ross GM; Rousseau L; Russell DJ; Saifutdinov RA; Salmon S; Santonja M; Saraeva AK; Sayer EJ; Scheunemann N; Scholz C; Seeber J; Shaw P; Shveenkova YB; Slade EM; Stebaeva S; Sterzynska M; Sun X; Susanti WI; Taskaeva AA; Tay LS; Thakur MP; Treasure AM; Tsiafouli M; Twala MN; Uvarov AV; Venier LA; Widenfalk LA; Widyastuti R; Winck B; Winkler D; Wu D; Xie Z; Yin R; Zampaulo RA; Zeppelini D; Zhang B; Zoughailech A; Ashford O; Klauberg-Filho O; Scheu SSpringtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.Item Heritabilities and genetic and phenotypic correlations for milk production and fertility traits of spring-calved once-daily or twice-daily milking cows in New Zealand(Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association, 2023-03) Jayawardana JMDR; Lopez-Villalobos N; McNaughton LR; Hickson REThe objectives of this study were to estimate the genetic and phenotypic correlations and heritabilities for milk production and fertility traits in spring-calved once-daily (OAD) milking cows for the whole season in New Zealand and compare those estimates with twice-daily (TAD) milking cows. Data used in the study consisted of 69,252 first parity cows from the calving seasons 2015-2016 to 2017-2018 in 113 OAD and 531 TAD milking herds. Heritability estimates for production and fertility traits were obtained through single-trait animal models, and estimates of genetic and phenotypic correlations were obtained through bivariate animal models. Heritability estimates of production traits varied from 0.26 to 0.61 in OAD and from 0.13 to 0.63 in TAD. Heritability estimates for fertility traits were low in both OAD and TAD milking cow populations, and estimates were consistent (OAD: 0.01 to 0.10 and TAD: 0.01 to 0.08) across milking regimens. Estimates of phenotypic and genetic correlations among production traits were consistent across populations. In both populations, phenotypic correlations between milk production and fertility traits were close to zero, and most of the genetic correlations were antagonistic. In OAD milking cows, genetic correlations of milk and lactose yields with the start of mating to conception, 6-wk in-calf, not-in-calf, and 6-wk calving rate were close to zero. Interval from first service to conception was negatively genetically correlated with milk and lactose yields in OAD milking cows. Protein percentage was positively genetically correlated with 3-wk and 6-wk submission, 3-wk in-calf, 6-wk in-calf, first service to conception, 3-wk calving, and 6-wk calving rate in the TAD milking cow population, but these correlations were low in the OAD milking cow population. Further studies are needed to understand the relationship of protein percentage and fertility traits in the OAD milking system. The phenotypic correlations between fertility traits were similar in OAD and TAD milking populations. Genetic correlations between fertility traits were strong (≥0.70) in cows milked TAD, but genetic correlations varied from weak to strong in cows milked OAD. Further research is required to evaluate the interaction between genotype by milking regimen for fertility traits in terms of sire selection in the OAD milking cow population.Item Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa.(Springer Nature Limited, 2020-08-28) Smith MW; Willis T; Alfieri L; James WHM; Trigg MA; Yamazaki D; Hardy AJ; Bisselink B; De Roo A; Macklin MG; Thomas CJContinental-scale models of malaria climate suitability typically couple well-established temperature-response models with basic estimates of vector habitat availability using rainfall as a proxy. Here we show that across continental Africa, the estimated geographic range of climatic suitability for malaria transmission is more sensitive to the precipitation threshold than the thermal response curve applied. To address this problem we use downscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a process-based representation of mosquito breeding habitat availability. A more complex pattern of malaria suitability emerges as water is routed through drainage networks and river corridors serve as year-round transmission foci. The estimated hydro-climatically suitable area for stable malaria transmission is smaller than previous models suggest and shows only a very small increase in state-of-the-art future climate scenarios. However, bigger geographical shifts are observed than with most rainfall threshold models and the pattern of that shift is very different when using a hydrological model to estimate surface water availability for vector breeding.Item A new season for climate change science and praxis?(Walter de Gruyter GmbH, 2024-01-29) Glavovic B; Bremer S; Wardekker AI write these reflections at the end of the 27th Conference of Parties meeting of governments (COP27), held in Egypt in November 2022, at which governments sought to progress climate action. COP27 was informed by the Sixth Assessment Report (AR6) by the Intergovernmental Panel on Climate Change (IPCC). Established in 1988, the IPCC provides UN member nations with comprehensive assessments of the state of climate change science and its implications. I spent much of 2017–2022 devoted to AR6. I was a Coordinating Lead Author of the chapter on sea-level rise in the IPCC’s Special Report on the Ocean and Cryosphere in a Changing Climate (1), Lead Author of the chapter on Climate Resilient Development, and co-lead for the Cross-Chapter Paper on Cities and Settlements by the Sea, in the Working Group II report (2). How can I convey the gravitas of the climate predicament outlined in AR6? Moreover, where do we stand now – after more than three decades of intensive climate change science-policy interactions? What does this portend for climate change scientists, policy advisors and elected politicians? What does it mean for you and I? And how might answers to these questions inform our understanding about seasons; and how we might navigate impending dangerous climate change?Item How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households(MDPI (Basel, Switzerland), 2024-04-19) Smit M; Corner-Thomas R; Draganova I; Andrews C; Thomas D; Friedrich CMSurprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.Item Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.(Cambridge University Press, 2024-04-15) Grout L; Hales S; Baker MG; French N; Wilson NOccurrence of cryptosporidiosis has been associated with weather conditions in many settings internationally. We explored statistical clusters of human cryptosporidiosis and their relationship with severe weather events in New Zealand (NZ). Notified cases of cryptosporidiosis from 1997 to 2015 were obtained from the national surveillance system. Retrospective space-time permutation was used to identify statistical clusters. Cluster data were compared to severe weather events in a national database. SaTScan analysis detected 38 statistically significant cryptosporidiosis clusters. Around a third (34.2%, 13/38) of these clusters showed temporal and spatial alignment with severe weather events. Of these, nearly half (46.2%, 6/13) occurred in the spring. Only five (38%, 5/13) of these clusters corresponded to a previously reported cryptosporidiosis outbreak. This study provides additional evidence that severe weather events may contribute to the development of some cryptosporidiosis clusters. Further research on this association is needed as rainfall intensity is projected to rise in NZ due to climate change. The findings also provide further arguments for upgrading the quality of drinking water sources to minimize contamination with pathogens from runoff from livestock agriculture.Item Time lag effect on malaria transmission dynamics in an Amazonian Colombian municipality and importance for early warning systems.(Springer Nature Limited, 2023-10-30) Gonzalez-Daza W; Vivero-Gómez RJ; Altamiranda-Saavedra M; Muylaert RL; Landeiro VLMalaria remains a significant public health problem worldwide, particularly in low-income regions with limited access to healthcare. Despite the use of antimalarial drugs, transmission remains an issue in Colombia, especially among indigenous populations in remote areas. In this study, we used an SIR Ross MacDonald model that considered land use change, temperature, and precipitation to analyze eco epidemiological parameters and the impact of time lags on malaria transmission in La Pedrera-Amazonas municipality. We found changes in land use between 2007 and 2020, with increases in forested areas, urban infrastructure and water edges resulting in a constant increase in mosquito carrying capacity. Temperature and precipitation variables exhibited a fluctuating pattern that corresponded to rainy and dry seasons, respectively and a marked influence of the El Niño climatic phenomenon. Our findings suggest that elevated precipitation and temperature increase malaria infection risk in the following 2 months. The risk is influenced by the secondary vegetation and urban infrastructure near primary forest formation or water body edges. These results may help public health officials and policymakers develop effective malaria control strategies by monitoring precipitation, temperature, and land use variables to flag high-risk areas and critical periods, considering the time lag effect.Item A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.(Public Library of Science (PLoS), 2024-01-18) Lo Iacono G; Cook AJC; Derks G; Fleming LE; French N; Gillingham EL; Gonzalez Villeta LC; Heaviside C; La Ragione RM; Leonardi G; Sarran CE; Vardoulakis S; Senyah F; van Vliet AHM; Nichols G; Vega NDisentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.Item How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space.(Springer, 2024-03-27) Roberts MG; Hickson RI; McCaw JMWe extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.