Sensitivity of simulated soil water content, evapotranspiration, gross primary production and biomass to climate change factors in Euro-Mediterranean grasslands

Grassland models often yield more uncertain outputs than arable crop models due to more complex interactions and the largely undocumented sensitivity of grassland models to environmental factors. The aim of the present study was to assess the impact of single-factor changes in temperature, precipitation, and atmospheric [CO2] on simulated soil water content (SWC), actual evapotranspiration (ET), gross primary production (GPP) and yield biomass, and also to link the sensitivity analysis with experimental results. We employed an unprecedented multi-model framework consisting of seven grassland models at nine sites with different environmental characteristics in Europe and Israel, with two management options at three sites. For warming/cooling and wetting/drying, models showed general consistency in the direction of SWC and ET changes, but less agreement regarding GPP and biomass changes. The simulated responses consistently revealed an overall positive effect of CO2 enrichment on GPP and biomass, while the direction of change differed for SWC and ET. Comparing with single-factor experimental manipulations, SWC simulations slightly underestimated the observed effect of warming, while the overall mean model sensitivity for biomass (+7.5%) closely matched the mean response observed with 1–2 °C warming (+6.6%). The models exhibited lower sensitivity of SWC to wetting or drying compared to the experiments. The overall mean sensitivity of biomass to drying was -4.3%, contrasting with the mean experimental effect size of -9.6%, which proved to be more realistic than the mean wetting effect (+3.2%, against +38.9% in the field trials). The simulated sensitivity of SWC to CO2 enrichment was markedly underestimated, while the biomass response (+12.0%) closely matched the observations (+17.5%). Although the multi-model averaging did not manifestly improve the realism of the simulations, it ensured a realistic response in the direction of change to varying conditions. The results suggest a paradigm shift in grassland modelling meaning that the usual practice of model optimisation/validation needs to be complemented by a sensitivity analysis following the approach presented. The results also highlight the importance of model improvements, especially in terms of soil hydrology representation, a key environmental driver of grassland functioning

The grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub

peer reviewe

The degradation of cell cycle regulators by SKP2/CKS1 ubiquitin ligase is genetically controlled in rodent liver cancer and contributes to determine the susceptibility to the disease.

Previous work showed a genetic control of cell cycle deregulation during hepatocarcinogenesis. We now evaluated in preneoplastic lesions, dysplastic nodules and hepatocellular carcinoma (HCC), chemically induced in genetically susceptible F344 and resistant Brown Norway (BN) rats, the role of cell cycle regulating proteins in the determination of a phenotype susceptible to HCC development. p21(WAF1), p27(KIP1), p57(KIP2) and p130 mRNA levels increased in fast growing lesions of F344 rats. Lower/no increases occurred in slowly growing lesions of BN rats. A similar behavior of RassF1A mRNA was previously found in the 2 rat strains. However, p21(WAF1), p27(KIP1), p57(KIP), p130 and RassF1A proteins exhibited no change/low increase in the lesions of F344 rats and consistent rise in dysplastic nodules and HCC of BN rats. Increase in Cks1-Skp2 ligase and ubiquitination of cell cycle regulators occurred in F344 but not in BN rat lesions, indicating that posttranslational modifications of cell cycle regulators are under genetic control and contribute to determine a phenotype susceptible to HCC. Moreover, proliferation index of 60 human HCCs was inversely correlated with protein levels but not with mRNA levels of P21(WAF1), P27(KIP1), P57(KIP2) and P130, indicating a control of human HCC proliferation by posttranslational modifications of cell cycle regulators

SKP2 and CKS1 promote degradation of cell cycle regulators and are associated with hepatocellular carcinoma prognosis.

BACKGROUND &#38; AIMS: The cell cycle regulators P21(WAF1), P27(KIP1), P57(KIP2), P130, RASSF1A, and FOXO1 are down-regulated during hepatocellular carcinoma (HCC) pathogenesis. We investigated the role of the ubiquitin ligase subunits CKS1 and SKP2, which regulate proteasome degradation of cell cycle regulators, in HCC progression. METHODS: Human HCC tissues from patients with better (HCCB, >3 years survival) and poorer prognosis (HCCP, <3 years survival) and HCC cell lines were analyzed. RESULTS: The promoters of P21(WAF1), P27(KIP1), and P57(KIP2) were more frequently hypermethylated in HCCP than HCCB. Messenger RNA levels of these genes were up-regulated in samples in which these genes were not methylated; protein levels increased only in HCCB because of CKS1- and SKP2-dependent ubiquitination of these proteins in HCCP. The level of SKP2 expression correlated with rate of HCC cell proliferation and level of microvascularization of samples and was inversely correlated with apoptosis and survival. In HCCB, SKP2 activity was balanced by degradation by the ubiquitin ligase anaphase-promoting complex/cyclosome (APC/C)-CDH1 and up-regulation of SKP2 suppressor histidine triad nucleotide binding protein 1 (HINT1). In HCCP, however, SKP2 was not degraded because of down-regulation of the phosphatase CDC14B, CDK2-dependent serine phosphorylation (which inhibits interaction between CDH1 and SKP2), and HINT1 inactivation. In HCC cells, small interfering RNA knockdown of SKP2 reduced proliferation and ubiquitination of the cell cycle regulators, whereas SKP2 increased proliferation and reduced expression of cell cycle regulators. CONCLUSIONS: Ubiquitination and proteasome degradation of P21WAF1, P27KIP1, P57KIP2, P130, RASSF1A, and FOXO1 and mechanisms that prevent degradation of SKP2 by APC/C-CDH1 contribute to HCC progression. CKS1-SKP2 ligase might be developed as a therapeutic target or diagnostic marker

Sensitivity and uncertainty analysis of grassland models in Europe and Israel

Sensitivity and uncertainty analysis of grassland models in Europe and Israel. MACSUR Conference 201

Ras-driven proliferation and apoptosis signaling during rat liver carcinogenesis is under genetic control.

Fast growth and deregulation of G1 and S phases characterize preneoplastic and neoplastic liver lesions of genetically susceptible F344 rats, whereas a G1-S block in lesions of resistant BN rats explains their low progression capacity. However, signal transduction pathways responsible for the different propensity of lesions from the 2 rat strains to evolve to malignancy remain unknown. Here, we comparatively investigated the role of Ras/Erk pathway inhibitors, involved in growth restraint and cell death, in the acquisition of a phenotype resistant or susceptible to hepatocarcinogenesis. Moderate activation of Ras, Raf-1 and Mek proteins was paralleled in both rat models by strong induction of Dab2 and Rkip inhibitors. Levels of Dusp1, a specific ERK inhibitor, increased only in BN rat lesions, leading to modest ERK activation, whereas a progressive Dusp1 decline occurred in corresponding lesions from F344 rats and was accompanied by elevated ERK activation. Furthermore, a gradual increase of Rassf1A/Nore1A/Mst1-driven apoptosis was detected in both rat strains, with highest levels in BN hepatocellular carcinoma (HCC), whereas loss of Dab2IP, a protein implicated in ASK1-dependent cell death, occurred only in F344 rat HCC, resulting in significantly higher apoptosis in BN than F344 HCC. Taken together, our results indicate a control of the Ras/Erk pathway and the pro-apoptotic Rassf1A/Nore1A and Dab2IP/Ask1 pathways by HCC susceptibility genes. Dusp1 possesses a prominent role in the acquisition of the phenotype resistant to HCC by BN rats, whereas late activation of RassF1A/Nore1A and Dab2IP/Ask1 axes is implicated in the highest apoptosis characteristic of BN HCC

Sensitivity of a grassland model ensemble to climate change factors: the MACSUR approach

In grassland modelling, understanding feedbacks between grassland ecosystems and the atmosphere in the context of regional scale climatic changes is essential for the accurate quantification of ecosystem water and carbon (C) fluxes. Different grassland models respond differently to environmental conditions and climatic circumstances. To test the sensitivity of different models to changes in input variables, ensemble modelling approaches are used because they generate an expanded envelope of possible systemic outputs. Here, an ensemble modelling approach was applied to explore water and C fluxes from grasslands in Europe. Seven grassland models were run at nine long-term grassland sites representing a broad gradient of geographic and climatic conditions. It was assessed the sensitivity to climate change factors including precipitation (P), temperature (T) and atmospheric CO2 concentration [CO2]. Baseline weather series (including [CO2]=380 ppm) were modified by changing T and P by -25%, -10%, -5%, +5%, +10%, +25% of the observed standard deviation and [CO2] by +5%, +10%, +15%, +25%, +50%, +100%. The obtained multi-model responses for each driver showed different levels of sensitivity. Soil temperature and gross primary production (GPP) displayed strong sensitivity to air temperature and precipitation. Based on the multi-model median of model responses, altered scenarios of precipitation had an important effect on modelled evapotranspiration from grassland swards. In general, yield biomass and GPP increased with elevated levels of [CO2]. Rising T and [CO2] had a fundamental effect on the C cycling of terrestrial ecosystems. This study demonstrates the use of ensemble modelling to address critical issues of uncertainty associated with individual model predictions, and provides increased understanding of water and C fluxes in grasslands under climate change

Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance

This study presents results from a major grassland model intercomparison exercise, and highlights the main challenges faced in the implementation of a multi-model ensemble prediction system in grasslands. Nine, independently developed simulation models linking climate, soil, vegetation and management to grassland biogeochemical cycles and production were compared in a simulation of soil water content(SWC) and soil temperature (ST) in the topsoil, and of biomass production. The results were assessed against SWC and ST data from five observational grassland sites representing a range of conditions –Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland – and against yield measurements from the same sites and other experimental grassland sites in Europe and Israel. We present a comparison of model estimates from individual models to the multi-model ensemble (represented by multi-model median: MMM). Withcalibration (seven out of nine models), the performances were acceptable for weekly-aggregated ST(R2> 0.7 with individual models and >0.8–0.9 with MMM), but less satisfactory with SWC (R2< 0.6 with individual models and < ∼ 0.5 with MMM) and biomass (R2< ∼0.3 with both individual models and MMM).With individual models, maximum biases of about −5◦C for ST, −0.3 m3m−3for SWC and 360 g DM m−2for yield, as well as negative modelling efficiencies and some high relative root mean square errors indicate low model performance, especially for biomass. We also found substantial discrepancies across different models, indicating considerable uncertainties regarding the simulation of grassland processes. The multi-model approach allowed for improved performance, but further progress is strongly needed in the way models represent processes in managed grassland systems

The grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub

International audienceThe grassland model intercomparison of the FACCE MACSUR knowledge hub involves nine modelling approaches. Grassland-specific approaches (AnnuGrow, PaSim, SPACSYS) were compared to the approaches mainly conceived to simulate crops (ARMOSA, EPIC, STICS) and biomes (Biome-BGC MuSo, CARAIB, LPJmL). The model intercomparison exercise is run over nine grassland sites across Europe and peri-Mediterranean regions where data were collected from at least five up to 31 years, with focus on biomass production and carbon exchanges. The protocol for model intercomparison, derived from Agricultural Model Intercomparison and Improvement Project, includes sensitivity tests, as well as blind and calibrated simulations. A fuzzy logic-based indicator for model assessment was developed to provide insights into agreement between simulations and observations, complexity of model structure and robustness of simulation results over a variety of conditions. Some results are illustrated, which show the limitations of the models run with current parameterization to simulate grassland dry matter and C exchanges across the Euro-Mediterranean region. The study also suggests that the regional calibration can accommodate model discrepancies. However, areas in the model structures have been identified that require further improvements to reduce uncertainties and increase reliability of model results in impact studies

Dual-specificity phosphatase 1 ubiquitination in extracellular signal-regulated kinase-mediated control of growth in human hepatocellular carcinoma.

Sustained activation of extracellular signal-regulated kinase (ERK) has been detected previously in numerous tumors in the absence of RAS-activating mutations. However, the molecular mechanisms responsible for ERK-unrestrained activity independent of RAS mutations remain unknown. Here, we evaluated the effects of the functional interactions of ERK proteins with dual-specificity phosphatase 1 (DUSP1), a specific inhibitor of ERK, and S-phase kinase-associated protein 2 (SKP2)/ CDC28 protein kinase 1b (CKS1) ubiquitin ligase complex in human hepatocellular carcinoma (HCC). Levels of DUSP1, as assessed by real-time reverse transcription–PCR and Western blot analysis, were significantly higher in tumors with better prognosis (as defined by the length of patients’ survival) when compared with both normal and nontumorous surrounding livers, whereas DUSP1 protein expression sharply declined in all HCC with poorer prognosis. In the latter HCC subtype, DUSP1 inactivation was due to either ERK/SKP2/CKS1- dependent ubiquitination or promoter hypermethylation associated with loss of heterozygosity at the DUSP1 locus. Noticeably, expression levels of DUSP1 inversely correlated with those of activated ERK, as well as with proliferation index and microvessel density, and directly with apoptosis and survival rate. Subsequent functional studies revealed that DUSP1 reactivation led to suppression of ERK, CKS1, and SKP2 activity, inhibition of proliferation and induction of apoptosis in human hepatoma cell lines. Taken together, the present data indicate that ERK achieves unrestrained activity during HCC progression by triggering ubiquitin-mediated proteolysis of its specific inhibitor DUSP1. Thus, DUSP1 may represent a valuable prognostic marker and ERK, CKS1, or SKP2 potential therapeutic targets for human HC