Measurement of salivary cortisol has been used extensively as a non-invasive alternative to blood sampling to assess adrenal activity in ruminants. However, there is evidence suggesting a considerable delay in the transfer of cortisol from plasma into saliva. Previous studies in cattle have used long sampling intervals making it difficult to characterise the relationship between plasma and salivary cortisol (PLCort and SACort, respectively) concentrations at different time points and determine whether or not such a time lag exist in large ruminants. Therefore, the objective of this study was to characterise the relationship between plasma and salivary cortisol and determine if there is a significant time lag between reaching peak cortisol concentrations in plasma and saliva across a 4.25 h time-period, using short sampling intervals of 10-15 min, following social separation in dairy cattle. Five cows were separated from their calves at 4 days after calving, and six calves were separated from a group of four peers at 8 weeks of age. Following separation, the animals were moved to an unfamiliar surrounding where they could not see their calves or pen mates. The animals were catheterised with indwelling jugular catheters 1 day before sampling. Blood and saliva samples were obtained simultaneously before and after separation. In response to the stressors, PLCort and SACort increased reaching peak concentrations 10 and 20 min after separation, respectively. This suggested a 10 min time lag between peak cortisol concentrations in plasma and saliva, which was further confirmed with a time-series analysis. Considering the 10 min time lag, SACort was strongly correlated with PLCort (P < 0.0001). Salivary cortisol correlates well with plasma cortisol and is a good indicator of the time-dependent variations in cortisol concentrations in plasma following acute stress. However, there is a time lag to reach peak cortisol concentrations in saliva compared to those in plasma, which should be considered when saliva samples are used as the only measure of hypothalamic-pituitary-adrenal axis response to stress in cattle.

Some of the climate-sensitive infections (CSIs) affecting humans are zoonotic vector-borne diseases, such as Lyme borreliosis (BOR) and tick-borne encephalitis (TBE), mostly linked to various species of ticks as vectors. Due to climate change, the geographical distribution of tick species, their hosts, and the prevalence of pathogens are likely to change. A recent increase in human incidences of these CSIs in the Nordic regions might indicate an expansion of the range of ticks and hosts, with vegetation changes acting as potential predictors linked to habitat suitability. In this paper, we study districts in Fennoscandia and Russia where incidences of BOR and TBE have steadily increased over the 1995–2015 period (defined as ’Well Increasing districts’). This selection is taken as a proxy for increasing the prevalence of tick-borne pathogens due to increased habitat suitability for ticks and hosts, thus simplifying the multiple factors that explain incidence variations. This approach allows vegetation types and strengths of correlation specific to the WI districts to be differentiated and compared with associations found over all districts. Land cover types and their changes found to be associated with increasing human disease incidence are described, indicating zones with potential future higher risk of these diseases. Combining vegetation cover and climate variables in regression models shows the interplay of biotic and abiotic factors linked to CSI incidences and identifies some differences between BOR and TBE. Regression model projections up until 2070 under different climate scenarios depict possible CSI progressions within the studied area and are consistent with the observed changes over the past 20 years.

Throughout history, humans have experienced epidemics. The balance of living in nature encircled by microorganisms is delicate. More than 70% of today’s emerging infections are zoonotic, i.e., those in which microorganisms transmitted from animals infect humans. Species are on the move at speeds never previously recorded, among ongoing climate change which is especially rapid at high latitudes. This calls for intensified international surveillance of Northern infectious diseases. Russia holds the largest area of thawing permafrost among Northern nations, a process which threatens to rapidly disrupt the balance of nature. In this paper, we provide details regarding Russian health infrastructure in order to take the first steps toward a collaborative international survey of Northern infections and international harmonization of the procured data.

Using hydrological models with a high temporal resolution to predict risk for rutting may be a possible method to improve planning of forwarder trails or to schedule logging operations in sites with low bearing capacity to periods when soil moisture content is at a minimum. We have studied whether descriptions of rut variations, collected in 27 logging sites, can be improved by using hydrological data, modeled by Swedish HYdrological Prediction for Environment (S-HYPE). Other explanatory variables, such as field-surveyed data and spatial data, were also used to describe rut variations within and across logging sites. The results indicated that inclusion of S-HYPE data led to only marginal improvement in explaining the observed variations of the ruts in terms of both “rut depths” within the logging sites and “proportion of forwarder trails with ruts” across the logging sites. However, application of S-HYPE data for adapting depth-to-water (DTW) maps to temporal changes of soil moisture content may be a way to develop more dynamic soil moisture maps for forestry applications.

As the terrestrial realms of the Arctic thaw with climate change, populations of relative southern infectious diseases carried by vector organisms such as ticks and mosquitoes may migrate, expand and/or in other ways respond to the resulting landscape transitions, and transmit onto humans and animals of the far North. The OneHealth effects of potentially expanding climate sensitive infections (CSI’s) constitute a serious global threat. To identify potential CSI’s, data concerning a selection of human infections were procured from national health reporting systems to cover the current thirty-year climate reference period (onto 2016) from western Greenland to the pacific coast of Russia, from approximately 55 to 80 degrees north. The diseases chosen to represent different transmission processes, e.g. via vector organisms bound to water, air, and/or soil environments, were borreliosis, brucellosis, cryptosporidiosis, leptospirosis, Puumala haemorrhagic fever, Q-fever, tick-borne encephalitis, and tularaemia. Inferential results indicate that 88% (7/8) of these infections are changing systematically with respect to incidence levels and/or geographic distribution, at local or regional scales within the study area, and that they therefore should be considered as being potentially climate sensitive. It is hence likely that many northern societies will experience changing CSI exposure. In addition, for each of the selected infections, the geographic distribution of their respective thirty-year average incidences was used to define “diseases climates” for future reference. Inconsistencies across national health reporting systems, as well as the current (late 2023) exclusion of Russian observatory networks, are seriously constraining the possibilities to infer international climate-related epidemiological trends.