Klaus Steenberg Larsen

Simple additive effects are rare: a quantitative review of plant biomass and soil process responses to combined manipulations of CO2 and temperature

In recent years, increased awareness of the potential interactions between rising atmospheric CO2 concentrations ([ CO2 ]) and temperature has illustrated the importance of multifactorial ecosystem manipulation experiments for validating Earth System models. To address the urgent need for increased understanding of responses in multifactorial experiments, this article synthesizes how ecosystem productivity and soil processes respond to combined warming and [ CO2 ] manipulation, and compares it with those obtained in single factor [ CO2 ] and temperature manipulation experiments. Across all combined elevated [ CO2 ] and warming experiments, biomass production and soil respiration were typically enhanced. Responses to the combined treatment were more similar to those in the [ CO2 ]-only treatment than to those in the warming-only treatment. In contrast to warming-only experiments, both the combined and the [ CO2 ]-only treatments elicited larger stimulation of fine root biomass than of aboveground biomass, consistently stimulated soil respiration, and decreased foliar nitrogen (N) concentration. Nonetheless, mineral N availability declined less in the combined treatment than in the [ CO2 ]-only treatment, possibly due to the warming-induced acceleration of decomposition, implying that progressive nitrogen limitation (PNL) may not occur as commonly as anticipated from single factor [ CO2 ] treatment studies. Responses of total plant biomass, especially of aboveground biomass, revealed antagonistic interactions between elevated [ CO2 ] and warming, i.e. the response to the combined treatment was usually less-than-additive. This implies that productivity projections might be overestimated when models are parameterized based on single factor responses. Our results highlight the need for more (and especially more long-term) multifactor manipulation experiments. Because single factor CO2 responses often dominated over warming responses in the combined treatments, our results also suggest that projected responses to future global warming in Earth System models should not be parameterized using single factor warming experiments.

Quantifying global soil carbon losses in response to warming

The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

Final results of a long-term, clinical follow-up in fatty liver patients

Objective. There is increasing focus on non-alcoholic fatty liver disease (NAFLD). The aim of the present study was to conduct a long-term clinical follow-up of patients with biopsy-confirmed fatty liver without inflammation or significant fibrosis (pure fatty liver), to analyse for potential risk factors at the time of index liver biopsy important for survival and the development of cirrhosis and to describe the causes of death. Material and methods. Patients were linked through their personal identification number to the Danish National Registry of Patients and the Register of Causes of Death. All admissions, discharge diagnoses and causes of death during follow-up were collected. All surviving patients were invited to a clinical follow-up. Results. The follow-up period was 20.4 and 21.0 years, respectively, for the NAFLD and alcoholic fatty liver disease (AFLD) groups. Two NAFLD patients (1.2%) developed cirrhosis during the follow-up period versus 54 (22%) AFLD patients. Sixty-four percent of 178 surviving patients out of an original cohort of 417 patients attended the clinical follow-up. In NAFLD patients, none of the risk factors studied was significant in relation to the risk of death. Patients with AFLD died primarily from cirrhosis and other alcohol-related disorders, whereas in patients with NAFLD the main causes of death were cardiovascular disease and cancer. Conclusions. For patients with pure non-alcoholic fatty liver, survival was good and independent of the histological, clinical and biochemical characteristics at the time of biopsy; the main causes of death were cardiovascular disease and cancer.

Respiration and Microbial Dynamics in Two Subarctic Ecosystems during Winter and Spring Thaw: Effects of Increased Snow Depth

ABSTRACT Recent evidence suggests that biogeochemical processes in the Arctic during late winter and spring-thaw strongly affect the annual cycling of carbon and nutrients, indicating high susceptibility to climate change. We therefore examined the carbon and nutrient dynamics in a sub-arctic heath and a birch forest with high temporal resolution from March until snowmelt at both ambient and experimentally increased snow depths. Ecosystem respiration (ER) from mid-March to snowmelt at ambient snow was high, reaching 99 ± 19 (birch) and 67 ± 1.4 g C m−2 (heath). Enhanced snow depth by about 20–30 cm increased ER by 77–157% during late winter but had no effects during spring-thaw. ER rates at the birch site were poorly described by classic first-order exponential models (R2 = 0.06–0.10) with temperature as a single variable, but model fit improved considerably by including the supply of dissolved organic carbon (DOC) or nitrogen (DON) in the model (R2 = 0.40–0.47). At the heath, model fit with temperature as the single variable was better (R2 = 0.38–0.52), yet it improved when the supply of DOC or DON was included (R2 = 0.65–0.72). Microbial carbon decreased by 43% within a few days after the first soil freeze-thaw event, while microbial nitrogen and phosphorus decreased more slowly. Because soil inorganic nitrogen and phosphorus concentrations were low, nutrients released from lysed microbial cells may have been sequestered by surviving microbes or by plants resuming growth. The fast change in microbial biomass and the dependence of ER on substrate availability stress the need for high temporal resolution in future research on ecosystem carbon and nutrient dynamics at snowmelt in order to make robust models of their turnover.

Temperature response of soil respiration largely unaltered with experimental warming

Significance One of the greatest challenges in projecting future shifts in the global climate is understanding how soil respiration rates will change with warming. Multiple experimental warming studies have explored this response, but no consensus has been reached. Based on a global synthesis of 27 experimental warming studies spanning nine biomes, we find that although warming increases soil respiration rates, there is limited evidence for a shifting respiration response with experimental warming. We also note a universal decline in the temperature sensitivity of respiration at soil temperatures >25 °C. Together, our data indicate that future respiration rates are likely to follow the current temperature response function, but higher latitudes will be more responsive to warmer temperatures. The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of ∼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.

Increased sensitivity to climate change in disturbed ecosystems

Human domination of the biosphere includes changes to disturbance regimes, which push many ecosystems towards early-successional states. Ecological theory predicts that early-successional ecosystems are more sensitive to perturbations than mature systems, but little evidence supports this relationship for the perturbation of climate change. Here we show that vegetation (abundance, species richness and species composition) across seven European shrublands is quite resistant to moderate experimental warming and drought, and responsiveness is associated with the dynamic state of the ecosystem, with recently disturbed sites responding to treatments. Furthermore, most of these responses are not rapid (2-5 years) but emerge over a longer term (7-14 years). These results suggest that successional state influences the sensitivity of ecosystems to climate change, and that ecosystems recovering from disturbances may be sensitive to even modest climatic changes. A research bias towards undisturbed ecosystems might thus lead to an underestimation of the impacts of climate change.

Multi-factor climate change effects on insect herbivore performance

The impact of climate change on herbivorous insects can have far-reaching consequences for ecosystem processes. However, experiments investigating the combined effects of multiple climate change drivers on herbivorous insects are scarce. We independently manipulated three climate change drivers (CO2, warming, drought) in a Danish heathland ecosystem. The experiment was established in 2005 as a full factorial split-plot with 6 blocks × 2 levels of CO2 × 2 levels of warming × 2 levels of drought = 48 plots. In 2008, we exposed 432 larvae (n = 9 per plot) of the heather beetle (Lochmaea suturalis Thomson), an important herbivore on heather, to ambient versus elevated drought, temperature, and CO2 (plus all combinations) for 5 weeks. Larval weight and survival were highest under ambient conditions and decreased significantly with the number of climate change drivers. Weight was lowest under the drought treatment, and there was a three-way interaction between time, CO2, and drought. Survival was lowest when drought, warming, and elevated CO2 were combined. Effects of climate change drivers depended on other co-acting factors and were mediated by changes in plant secondary compounds, nitrogen, and water content. Overall, drought was the most important factor for this insect herbivore. Our study shows that weight and survival of insect herbivores may decline under future climate. The complexity of insect herbivore responses increases with the number of combined climate change drivers.

Diagnostic value of soluble CD163 serum levels in patients suspected of meningitis: comparison with CRP and procalcitonin.

The aim of the study was to evaluate and compare the diagnostic value of sCD163 serum levels with CRP and PCT in meningitis and bacterial infection. An observational cohort study was conducted between February 2001 and February 2005. The study population comprised 55 patients suspected of meningitis on admission to a 27-bed infectious disease department at a Danish university hospital. Biomarker serum levels on admission were measured. Sensitivity and specificity were evaluated at pre-specified cut-off values and overall diagnostic accuracies were compared using receiver-operating characteristic AUCs (areas under curves). Patients were classified by 2 sets of diagnostic criteria into: A) purulent meningitis, serous meningitis or non-meningitis, and B) systemic bacterial infection, local bacterial infection or non-bacterial disease. An elevated serum level of sCD163 was the most specific marker for distinguishing bacterial infection from non-bacterial disease (specificity 0.91; sensitivity 0.47). However, the overall diagnostic accuracy of CRP (AUC =0.91) and PCT (AUC =0.87) were superior (p<0.02 and p<0.06) compared to that of sCD163 (AUC =0.72). For the diagnosis of systemic bacterial infection, the AUC of sCD163 (0.83) did not differ significantly from those of CRP or PCT. All markers had AUCs <0.75 for differentiating between purulent meningitis and other conditions. In conclusion, CRP and PCT had high diagnostic value and were superior as markers of bacterial infection compared to sCD163. However, sCD163 may be helpful in rapid identification of patients with systemic bacterial infection. If used as an adjunct to lumbar puncture, PCT and CRP had very high diagnostic accuracy for distinguishing between bacterial and viral infection in patients with spinal fluid pleocytosis. However, none of the markers was useful as an independent tool for the clinical diagnosis of patients with purulent meningitis.

Maximum likelihood inference for multivariate frailty models using an automated Monte Carlo EM algorithm.

We present a maximum likelihood estimation procedure for the multivariate frailty model. The estimation is based on a Monte Carlo EM algorithm. The expectation step is approximated by averaging over random samples drawn from the posterior distribution of the frailties using rejection sampling. The maximization step reduces to a standard partial likelihood maximization. We also propose a simple rule based on the relative change in the parameter estimates to decide on sample size in each iteration and a stopping time for the algorithm. An important new concept is acquiring absolute convergence of the algorithm through sample size determination and an efficient sampling technique. The method is illustrated using a rat carcinogenesis dataset and data on vase lifetimes of cut roses. The estimation results are compared with approximate inference based on penalized partial likelihood using these two examples. Unlike the penalized partial likelihood estimation, the proposed full maximum likelihood estimation method accounts for all the uncertainty while estimating standard errors for the parameters.

Few multiyear precipitation-reduction experiments find a shift in the productivity-precipitation relationship.

Well-defined productivity-precipitation relationships of ecosystems are needed as benchmarks for the validation of land models used for future projections. The productivity-precipitation relationship may be studied in two ways: the spatial approach relates differences in productivity to those in precipitation among sites along a precipitation gradient (the spatial fit, with a steeper slope); the temporal approach relates interannual productivity changes to variation in precipitation within sites (the temporal fits, with flatter slopes). Precipitation-reduction experiments in natural ecosystems represent a complement to the fits, because they can reduce precipitation below the natural range and are thus well suited to study potential effects of climate drying. Here, we analyse the effects of dry treatments in eleven multiyear precipitation-manipulation experiments, focusing on changes in the temporal fit. We expected that structural changes in the dry treatments would occur in some experiments, thereby reducing the intercept of the temporal fit and displacing the productivity-precipitation relationship downward the spatial fit. The majority of experiments (72%) showed that dry treatments did not alter the temporal fit. This implies that current temporal fits are to be preferred over the spatial fit to benchmark land-model projections of productivity under future climate within the precipitation ranges covered by the experiments. Moreover, in two experiments, the intercept of the temporal fit unexpectedly increased due to mechanisms that reduced either water loss or nutrient loss. The expected decrease of the intercept was observed in only one experiment, and only when distinguishing between the late and the early phases of the experiment. This implies that we currently do not know at which precipitation-reduction level or at which experimental duration structural changes will start to alter ecosystem productivity. Our study highlights the need for experiments with multiple, including more extreme, dry treatments, to identify the precipitation boundaries within which the current temporal fits remain valid.