Loss and reappearance of transferrin receptors in human leukemic cell lines

Serum transferrin (the iron binding protein) exerts its iron carrier function at the cell surface after binding to the appropriate receptor (TrR). In this work it is demonstrated that differentiating agents induce loss of TrR from the surface of three leukemic cell lines (Molt-3, HL-60 and K-562). Loss of TrR correlates with change in morphology and induction of phenotypic markers of the differentiated cells. Removal of the differentiating agent from the culture is followed by reexpression of TrR on the cell surface. The data presented in this paper suggest that TrR may play a regulatory role in cell differentiation and malignant transformation.     

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha^?1 year^?1 km^?1 for P. abies and 0.93 ± 0.010 Mg C ha^?1 year^?1 km^?1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.     

Unbiased sex-specific survival in Alpine chamois

Many polygynous ungulates show higher mortality of males than of females, because of the intense male–male competition during the rut and the costs associated with the development of sexual-size dimorphism. In the weakly dimorphic Alpine chamois Rupicapra rupicapra the occurrence of differential sex-specific survival strategies is controversial. To date, only two studies investigated the survivorship of males and females in this species, producing conflicting results: these works, based on the use of life tables, require confirmation from researches carried out on living populations. We assessed the survival pattern of a protected Alpine chamois population in the Swiss National Park, where 116 individuals were marked and monitored over 13 years (1996–2008). We tested for sex-, age- and year-dependence of survival by means of capture-mark-resight models. Resighting probabilities were sex-dependent, and survival rates were time-dependent. Females had higher resighting probabilities (0.84) than males (0.74). All over the time periods, sex had a weak influence on survival probability (males = 0.91; females = 0.92) and survival rates remained surprisingly high until late age (1 year = 0.90; 2–7 years = 0.91; 8+ years = 0.92). The growing evidence for a high adult survival and a weak differential mortality of the two sexes, together with the highly seasonal sexual-size dimorphism observed for Alpine chamois, might indicate the occurrence of a unique conservative survival strategy in both sexes and a low-risk mating strategy by males.     

The influence of sampling design on tree‐ring‐based quantification of forest growth

Tree‐rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree‐ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and‐climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long‐term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree‐ring‐based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short‐term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree‐ring‐based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.     

Effects of climate extremes on the terrestrial carbon cycle: concepts,processes and potential future impacts

Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance‐induced mechanisms and processes to also operate in an extreme context. The paucity of well‐defined studies currently renders a quantitative meta‐analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land‐cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground‐based observational case studies reveals that many regions in the (sub‐)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon–climate feedbacks.     

Estimating density dependence from population time series using demographic theory and life-history data

For populations with a density-dependent life history reproducing at discrete annual intervals, we analyze small or moderate fluctuations in population size around a stable equilibrium, which is applicable to many vertebrate populations. Using a life history having age at maturity alpha, with stochasticity and density dependence in adult recruitment and mortality, we derive a linearized autoregressive equation with time lags from 1 to alpha yr. Contrary to current interpretations, the coefficients corresponding to different time lags in the autoregressive dynamics are not simply measures of delayed density dependence but also depend on life-history parameters. The theory indicates that the total density dependence in a life history, D, should be defined as the negative elasticity of population growth rate per generation with respect to change in population size, [Formula: see text], where lambda is the asymptotic multiplicative growth rate per year, T is the generation time, and N is adult population size. The total density dependence in the life history, D, can be estimated from the sum of the autoregression coefficients. We estimate D in populations of seven vertebrate species for which life-history studies and unusually long time series of complete population censuses are available. Estimates of D were statistically significant and large, on the order of 1 or higher, indicating strong density dependence in five of the seven species. We also show that life history can explain the qualitative features of population autocorrelation functions and power spectra and observations of increasing empirical variance in population size with increasing length of time series.