Effect of scavenging on predation in a food web

The fasting endurance hypothesis (FEH) predicts strong selection for large body size in mammals living in environments where food supply is interrupted over prolonged periods of time. The Arctic is a highly seasonal and food-restricted environment, but contrary to predictions from the FEH, empirical evidence shows that Arctic mammals are often smaller than their temperate conspecifics. Intraspecific studies integrating physiology and behaviour of different-sized individuals may shed light on this paradox. We tested the FEH in free-living Svalbard reindeer Rangifer tarandus platyrhynchus. We measured daily energy expenditure (DEE), subcutaneous body temperature (Tsc) and activity levels during the late winter in 14 adult females with body masses ranging from 46.3 to 57.8 kg. Winter energy expenditure (WEE) and fasting endurance (FE) were modelled dynamically by combining these data with body composition measurements of culled individuals at the onset of winter (14 years, n = 140) and variation in activity level throughout winter (10 years, n = 70). Mean DEE was 6.3 ± 0.7 MJ/day. Lean mass, Tsc and activity had significantly positive effects on DEE. Across all 140 individuals, mean FE was 85 ± 17 days (range 48–137 days). In contrast to the predictions of the FEH, the dominant factor affecting FE was initial fat mass, while body mass and FE were not correlated. Furthermore, lean mass and fat mass were not correlated. FE was on average 80% (45 days) longer in fat than lean individuals of the same size. Reducing activity levels by ~16% or Tsc by ~5% increased FE by 7% and 4% respectively. Our results fail to support the FEH. Rather, we demonstrate that (a) the size of fat reserves can be independent of lean mass and body size within a species, (b) ecological and environmental variation influence FE via their effects on body composition and (c) physiological and behavioural adjustments can improve FE within individuals. Altogether, our results suggest that there is a selection in Svalbard reindeer to accumulate body fat, rather than to grow structurally large. </ol

Iterative model predictions for wildlife populations impacted by rapid climate change

To improve understanding and management of the consequences of current rapid environmental change, ecologists advocate using long-term monitoring data series to generate iterative near-term predictions of ecosystem responses. This approach allows scientific evidence to increase rapidly and management strategies to be tailored simultaneously. Iterative near-term forecasting may therefore be particularly useful for adaptive monitoring of ecosystems subjected to rapid climate change. Here, we show how to implement near-term forecasting in the case of a harvested population of rock ptarmigan in high-arctic Svalbard, a region subjected to the largest and most rapid climate change on Earth. We fitted state-space models to ptarmigan counts from point transect distance sampling during 2005–2019 and developed two types of predictions: (1) explanatory predictions to quantify the effect of potential drivers of ptarmigan population dynamics, and (2) anticipatory predictions to assess the ability of candidate models of increasing complexity to forecast next-year population density. Based on the explanatory predictions, we found that a recent increasing trend in the Svalbard rock ptarmigan population can be attributed to major changes in winter climate. Currently, a strong positive effect of increasing average winter temperature on ptarmigan population growth outweighs the negative impacts of other manifestations of climate change such as rain-on-snow events. Moreover, the ptarmigan population may compensate for current harvest levels. Based on the anticipatory predictions, the near-term forecasting ability of the models improved nonlinearly with the length of the time series, but yielded good forecasts even based on a short time series. The inclusion of ecological predictors improved forecasts of sharp changes in next-year population density, demonstrating the value of ecosystem-based monitoring. Overall, our study illustrates the power of integrating near-term forecasting in monitoring systems to aid understanding and management of wildlife populations exposed to rapid climate change. We provide recommendations for how to improve this approach

Direct and indirect effects of environmental drivers on reindeer reproduction

The impact of climate change on the dynamics of populations has been well documented and is widespread. However, weather variability influences populations both directly and indirectly, and is mediated by species interactions. This complexity may impede proper climate impact assessments. Hence, predicting the consequences of climate change may require including processes that occur both with time lags and across trophic levels. Based on our current understanding of the mechanisms linking local climate and trophic interactions in tundra ecosystems, we used a state-space formulation of a mediation model that allowed for assessing the relative contribution of direct and indirect environmental (weather and trophic) effects on reindeer Rangifer tarandus reproductive success. Our study showed that the mediator effect of body condition caused delayed but predictable effects of weather, plant productivity, and reindeer densities on reproductive success. Furthermore, these predictors also affected reproductive success directly and with the same sign, suggesting that direct and indirect effects pulled in the same direction with respect to their combined total effect on reproductive success. Hence, poor weather conditions not only affect calf production negatively the same year, but also increase the likelihood of poor reproductive success the subsequent year. The results support the expectation that calf slaughter mass (as a proxy for herd body condition) is an important indicator of the state of reindeer herds with respect to their production potential and resilience to weather events and climate change. Finally, the model framework employed in the present study can be further developed as a potential vehicle for near-term forecasting, and thereby constitutes a useful tool for adaptive management

Not only mosses: lemming winter diets as described by DNA metabarcoding

This is a post-peer-review, pre-copyedit version of an article published in Polar Biology. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00300-017-2114-3. The temporal dynamics of most tundra food webs are shaped by the cyclic population dynamics of lemmings. While processes during winter may be behind the recent disruptions of lemming cycles, lemming winter ecology is poorly known. We present here the first DNA metabarcoding data on the winter diet of Norwegian lemmings (Lemmus lemmus), based on feces collected after a winter of population increase. Prostrate willows, mosses, and graminoids dominated the species winter diet, indicating that the conventional idea of lemmings as moss‐specialists should be revised. The behavior of lemming‐plant models in theoretical studies is conditional on the assumptions of mosses being their main winter food item. As shrubs have been excluded from the framework of these models, incorporating them in future modeling studies should nuance our understanding on how plants affect lemmings. We also sampled diet of a few individuals found dead on top of the snow. These individuals had relatively empty stomachs and had, prior to death, relied heavily on mosses. This apparent lack of abundant good quality indicates spatial heterogeneity in local food availability during the population increase phase

Food web approach for managing Arctic wildlife populations in an era of rapid environmental change

Scientists and wildlife managers implementing adaptive monitoring and management schemes, are tasked with providing predictions of population responses to harvest and environmental changes. Such predictions are useful not only to forecast direct effects of climate, productivity, land use, or habitat degradation, but also changes in the food web, such as expanding/increasing species that are predators, prey, and competitors of populations of concern. Explicit consideration of food webs and their dynamics in more complex models could provide better predictions of future changes, and allow us to better assess the influence of management actions. Here, we present our perspective on what we have learned from conducting a number of case studies using such a food web approach with a focus on climate and harvest impacts and their implications for management. We found empirical support for many of our hypothesized food web effects, and were able in some cases to obtain short-term forecasts with slightly lower prediction error using models that account for food web dynamics compared with simpler models. Predictions are the foundation of adaptive management because they allow quantitative assessment of the effects of management actions; however, evaluating predictions requires adequate and high-quality monitoring data. Results from our case studies show that a combination of long-term monitoring and different types of study designs coupled with models of adequate complexity are likely required to better understand populations’ responses to environmental changes and harvest, as well as the consequences for food webs

A Dynamic Occupancy Model for Interacting Species with Two Spatial Scales

Occupancy models have been extended to account for either multiple spatial scales or species interactions in a dynamic setting. However, as interacting species (e.g., predators and prey) often operate at different spatial scales, including nested spatial structure might be especially relevant to models of interacting species. Here we bridge these two model frameworks by developing a multi-scale, two-species occupancy model. The model is dynamic, i.e. it estimates initial occupancy, colonization and extinction probabilities—including probabilities conditional to the other species’ presence. With a simulation study, we demonstrate that the model is able to estimate most parameters without marked bias under low, medium and high average occupancy probabilities, as well as low, medium and high detection probabilities, with only a small bias for some parameters in low-detection scenarios. We further evaluate the model’s ability to deal with sparse field data by applying it to a multi-scale camera trapping dataset on a mustelid-rodent predator–prey system. Most parameters are estimated with low uncertainty (i.e. narrow posterior distributions). More broadly, our model framework creates opportunities to explicitly account for the spatial structure found in many spatially nested study designs, and to study interacting species that have contrasting movement ranges with camera traps.Supplementary materials accompanying this paper appear online.publishedVersio

Integration of Placental Transfer in a Fetal–Maternal Physiologically Based Pharmacokinetic Model to Characterize Acetaminophen Exposure and Metabolic Clearance in the Fetus

Background and Objective: Although acetaminophen is frequently used during pregnancy, little is known about fetal acetaminophen pharmacokinetics. Acetaminophen safety evaluation has typically focused on hepatotoxicity, while other events (fetal ductal closure/constriction) are also relevant. We aimed to develop a fetal–maternal physiologically based pharmacokinetic (PBPK) model (f-m PBPK) to quantitatively predict placental acetaminophen transfer, characterize fetal acetaminophen exposure, and quantify the contributions of specific clearance pathways in the term fetus. Methods: An acetaminophen pregnancy PBPK model was extended with a compartment representing the fetal liver, which included maturation of relevant enzymes. Different approaches to describe placental transfer were evaluated (ex vivo cotyledon perfusion experiments, placental transfer prediction based on Caco-2 cell permeability or physicochemical properties [MoBi®]). Predicted maternal and fetal acetaminophen profiles were compared with in vivo observations. Results: Tested approaches to predict placental t

Iron deficiency and red cell indices in patients with heart failure

Aims To investigate the prevalence of iron deficiency (ID) in heart failure (HF) patients with normal vs. abnormal red cell indices (RCI), the associations between iron parameters and RCI, and prognostic consequences of ID independently of RCI. Methods and results We analysed clinical data of 1821 patients with HF [mean age 66 13 years; 71% men; New York Heart Association class I/II/III/IV (11%/39%/44%/6%); left ventricular ejection fraction >45%: 19%]. Iron deficiency (ferritin Conclusions Patients with HF should be routinely screened for ID irrespective of the presence of anaemia or abnormal RCI. The detrimental impact of ID on long-term survival in HF is partially independent of RCI

Physiologically Based Pharmacokinetic Modeling to Characterize Acetaminophen Pharmacokinetics and N-Acetyl-p-Benzoquinone Imine (NAPQI) Formation in Non-Pregnant and Pregnant Women

Background and Objective: Little is known about acetaminophen (paracetamol) pharmacokinetics during pregnancy. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict acetaminophen pharmacokinetics throughout pregnancy. Methods: PBPK models for acetaminophen and its metabolites were developed in non-pregnant and pregnant women. Physiological and enzymatic changes in pregnant women expected to impact acetaminophen pharmacokinetics were considered. Models were evaluated using goodness-of-fit plots and by comparing predicted pharmacokinetic profiles with in vivo pharmacokinetic data. Predictions were performed to illustrate the average concentration at steady state (Css,avg) values, used as an indicator for efficacy, of acetaminophen achieved following administration of 1000 mg every 6 h. Furthermore, as a measurement of potential hepatotoxicity, the molar dose fraction of acetaminophen converted to N-acetyl-p-benzoquinone imine (NAPQI) was estimated. Results: PBPK models successfully predicted the pharmacokinetics of acetaminophen and its metabolites in non-pregnant and pregnant women. Predictions resulted in the lowest Css,avg in the third trimester (median [interquartile range]: 4.5 [3.8–5.1] mg/L), while Css,avg was 6.7 [5.9–7.4], 5.6 [4.7–6.3], and 4.9 [4.1–5.5] mg/L in non-pregnant, first trimester, and second trimester populations, respectively. Assuming a constant raised cytochrome P450 2E1 activity throughout pregnancy, the molar dose fraction of acetaminophen converted to NAPQI was highest during the first trimester (median [interquartile range]: 11.0% [9.1–13.4%]), followed by the second (9.0% [7.5–11.0%]) and third trimester (8.2% [6.8–10.1%]), compared with non-pregnant women (7.7% [6.4–9.4%]). Conclusion: Acetaminophen exposure is lower in pregnant than in non-pregnant women, and is related to pregnancy duration. Despite these findings, higher dose adjustments cannot be advised yet as it is unknown whether pregnancy affects the toxicodynamics of NAPQI. Information on glutathione abundance during pregnancy and NAPQI in vivo data are required to further refine the presented model

Variability of protein level and phosphorylation status caused by biopsy protocol design in human skeletal muscle analyses

<p>Abstract</p> <p>Background</p> <p>Bergström needle biopsy is widely used to sample skeletal muscle in order to study cell signaling directly in human tissue. Consequences of the biopsy protocol design on muscle protein quantity and quality remain unclear. The aim of the present study was to assess the impact of different events surrounding biopsy protocol on the stability of the Western blot signal of eukaryotic translation initiation factor 4E binding protein 1 (4E-BP1), Akt, glycogen synthase kinase-3β (GSK-3β), muscle RING finger protein 1 (MuRF1) and p70 S6 kinase (p70 S6K). Six healthy subjects underwent four biopsies of the <it>vastus lateralis</it>, distributed into two distinct visits spaced by 48 hrs. At visit 1, a basal biopsy in the right leg was performed in the morning (R1) followed by a second in the left leg in the afternoon (AF). At visit 2, a second basal biopsy (R2) was collected from the right leg. Low intensity mobilization (3 × 20 right leg extensions) was performed and a final biopsy (Mob) was collected using the same incision site as R2.</p> <p>Results</p> <p>Akt and p70 S6K phosphorylation levels were increased by 83% when AF biopsy was compared to R1. Mob condition induced important phosphorylation of p70 S6K when compared to R2. Comparison of R1 and R2 biopsies revealed a relative stability of the signal for both total and phosphorylated proteins.</p> <p>Conclusions</p> <p>This study highlights the importance to standardize muscle biopsy protocols in order to minimize the method-induced variation when analyzing Western blot signals.</p