Lake surface temperatures in a changing climate: a global sensitivity analysis

We estimate the effects of climatic changes, as predicted by six climate models, on lake surface temperatures on a global scale, using the lake surface equilibrium temperature as a proxy. We evaluate interactions between different forcing variables, the sensitivity of lake surface temperatures to these variables, as well as differences between climate zones. Lake surface equilibrium temperatures are predicted to increase by 70 to 85 % of the increase in air temperatures. On average, air temperature is the main driver for changes in lake surface temperatures, and its effect is reduced by ~10 % by changes in other meteorological variables. However, the contribution of these other variables to the variance is ~40 % of that of air temperature, and their effects can be important at specific locations. The warming increases the importance of longwave radiation and evaporation for the lake surface heat balance compared to shortwave radiation and convective heat fluxes. We discuss the consequences of our findings for the design and evaluation of different types of studies on climate change effects on lakes.

Assessment of a real-time PCR test to diagnose syphilis from diverse biological samples

OBJECTIVES: To investigate the contribution of a real-time PCR assay for the detection of Treponema pallidum in various biological specimens with the secondary objective of comparing its value according to HIV status. METHODS: Prospective cohort of incident syphilis cases from three Swiss hospitals (Geneva and Bern University Hospitals, Outpatient Clinic for Dermatology of Triemli, Zurich) diagnosed between January 2006 and September 2008. A case-control study was nested into the cohort. Biological specimens (blood, lesion swab or urine) were taken at diagnosis (as clinical information) and analysed by real-time PCR using the T pallidum 47 kDa gene. RESULTS: 126 specimens were collected from 74 patients with primary (n = 26), secondary (n = 40) and latent (n = 8) syphilis. Among primary syphilis, sensitivity was 80% in lesion swabs, 28% in whole blood, 55% in serum and 29% in urine, whereas among secondary syphilis, it was 20%, 36%, 47% and 44%, respectively. Among secondary syphilis, plasma and cerebrospinal fluid were also tested and provided a sensitivity of 100% and 50%, respectively. The global sensitivity of T pallidum by PCR (irrespective of the compartment tested) was 65% during primary, 53% during secondary and null during latent syphilis. No difference regarding serology or PCR results was observed among HIV-infected patients. Specificity was 100%. CONCLUSIONS: Syphilis PCR provides better sensitivity in lesion swabs from primary syphilis and displays only moderate sensitivity in blood from primary and secondary syphilis. HIV status did not modify the internal validity of PCR for the diagnosis of primary or secondary syphilis.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.

Sensitivity of atmospheric CO2 and climate to explosive volcanic eruptions

Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric aerosol optical depth changes. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initial weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields a small additional radiative forcing that amplifies the cooling and perturbs the Earth System on longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different magnitudes of stratospheric aerosol optical depth changes and from global warming simulations show that the carbon cycle-climate sensitivity γ, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the magnitude and temporal evolution of the perturbation, and time scale of interest. On decadal time scales, modeled γ is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario.

Sensitivity of Nd isotopic composition in seawater to changes in Nd sources and paleoceanographic implications

It has been argued that past changes in the sources of Nd could hamper the use of the Nd isotopic composition (ϵNd) as a proxy for past changes in the overturning of deep water masses. Here we reconsider uncertainties associated with ϵNd in seawater due to potential regional to global scale changes in the sources of Nd by applying a modeling approach. For illustrative purposes we describe rather extreme changes in the magnitude of source fluxes, their isotopic composition or both. We find that the largest effects on ϵNd result from changes in the boundary source. Considerable changes also result from variations in the magnitude or ϵNd of dust and rivers but are largely constrained to depths shallower than 1 km, except if they occur in or upstream of regions where deep water masses are formed. From these results we conclude that changes in Nd sources have the potential to affect ϵNd. However, substantial changes are required to generate large-scale changes inϵNd in deep water that are similar in magnitude to those that have been reconstructed from sediment cores or result from changes in meridional overturning circulation in model experiments. Hence, it appears that a shift in ϵNdcomparable to glacial-interglacial variations is difficult to obtain by changes in Nd sources alone, but that more subtle variations can be caused by such changes and must be interpreted with caution.

Links between body mass index, total body fat, cholesterol, high-density lipoprotein, and insulin sensitivity in patients with obesity related to depression, anger, and anxiety

OBJECTIVE: Define links between psychosocial parameters and metabolic variables in obese females before and after a low-calorie diet. METHOD: Nine female obese patients (age 36.1 +/- 7.1 years, body mass index [BMI] > 30 kg/m2) were investigated before and after a 6-week low-calorie diet accompanied by behavior therapy. Blood lipids, insulin sensitivity (Bergman protocol), fat distribution (by dual-energy X-ray absorptiometry [DEXA]), as well as psychological parameters such as depression, anger, anxiety, symptom load, and well-being, were assessed before and after the dieting period. RESULTS: The females lost 9.6 +/- 2.8 kg (p < .0001) of body weight, their BMI was reduced by 3.5 +/- 0.3 kg/m2 (p < .0001), and insulin sensitivity increased from 3.0 +/- 1.8 to 4.3 +/- 1.5 mg/kg (p = .05). Their abdominal fat content decreased from 22.3 +/- 5.5 to 18.9 +/- 4.5 kg (p < .0001). In parallel, psychological parameters such as irritability (p < .05) and cognitive control (p < .0001) increased, whereas feelings of hunger (p < .05), externality (p < .05), interpersonal sensitivity (p < .01), paranoid ideation (p < .05), psychoticism (p < .01), and global severity index (p < .01) decreased. Prospectively, differences in body fat (percent) were correlated to nervousness (p < .05). Waist-to-hip ratio (WHR) differences were significantly correlated to sociability (p < .05) and inversely to emotional instability (p < .05), whereas emotional instability was inversely correlated to differences in insulin sensitivity (p < .01). DISCUSSION: Weight reduction may lead to better somatic risk factor control. Women with more nervousness and better sociability at the beginning of a diet period may lose more weight than others.

Haemonchus contortus acetylcholine receptors of the DEG-3 subfamily and their role in sensitivity to monepantel

Gastro-intestinal nematodes in ruminants, especially Haemonchus contortus, are a global threat to sheep and cattle farming. The emergence of drug resistance, and even multi-drug resistance to the currently available classes of broad spectrum anthelmintics, further stresses the need for new drugs active against gastro-intestinal nematodes. A novel chemical class of synthetic anthelmintics, the Amino-Acetonitrile Derivatives (AADs), was recently discovered and the drug candidate AAD-1566 (monepantel) was chosen for further development. Studies with Caenorhabditis elegans suggested that the AADs act via nicotinic acetylcholine receptors (nAChR) of the nematode-specific DEG-3 subfamily. Here we identify nAChR genes of the DEG-3 subfamily from H. contortus and investigate their role in AAD sensitivity. Using a novel in vitro selection procedure, mutant H. contortus populations of reduced sensitivity to AAD-1566 were obtained. Sequencing of full-length nAChR coding sequences from AAD-susceptible H. contortus and their AAD-1566-mutant progeny revealed 2 genes to be affected. In the gene monepantel-1 (Hco-mptl-1, formerly named Hc-acr-23H), a panel of mutations was observed exclusively in the AAD-mutant nematodes, including deletions at intron-exon boundaries that result in mis-spliced transcripts and premature stop codons. In the gene Hco-des-2H, the same 135 bp insertion in the 5' UTR created additional, out of frame start codons in 2 independent H. contortus AAD-mutants. Furthermore, the AAD mutants exhibited altered expression levels of the DEG-3 subfamily nAChR genes Hco-mptl-1, Hco-des-2H and Hco-deg-3H as quantified by real-time PCR. These results indicate that Hco-MPTL-1 and other nAChR subunits of the DEG-3 subfamily constitute a target for AAD action against H. contortus and that loss-of-function mutations in the corresponding genes may reduce the sensitivity to AADs.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.

Regional climate model simulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 and ~0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.

Plant and arthropod community sensitivity to rainfall manipulation but not nitrogen enrichment in a successional grassland ecosystem

Grasslands provide many ecosystem services including carbon storage, biodiversity preservation and livestock forage production. These ecosystem services will change in the future in response to multiple global environmental changes, including climate change and increased nitrogen inputs. We conducted an experimental study over 3 years in a mesotrophic grassland ecosystem in southern England. We aimed to expose plots to rainfall manipulation that simulated IPCC 4th Assessment projections for 2100 (+15 % winter rainfall and −30 % summer rainfall) or ambient climate, achieving +15 % winter rainfall and −39 % summer rainfall in rainfall-manipulated plots. Nitrogen (40 kg ha−1 year−1) was also added to half of the experimental plots in factorial combination. Plant species composition and above ground biomass were not affected by rainfall in the first 2 years and the plant community did not respond to nitrogen enrichment throughout the experiment. In the third year, above-ground plant biomass declined in rainfall-manipulated plots, driven by a decline in the abundances of grass species characteristic of moist soils. Declining plant biomass was also associated with changes to arthropod communities, with lower abundances of plant-feeding Auchenorrhyncha and carnivorous Araneae indicating multi-trophic responses to rainfall manipulation. Plant and arthropod community composition and plant biomass responses to rainfall manipulation were not modified by nitrogen enrichment, which was not expected, but may have resulted from prior nitrogen saturation and/or phosphorus limitation. Overall, our study demonstrates that climate change may in future influence plant productivity and induce multi-trophic responses in grasslands.