Exploring parameter sensitivities of the land surface using a locally coupled land-atmosphere model

This paper presents a multicriteria analysis that explores the sensitivity of the land surface to changes in both land and atmospheric parameters, in terms of reproducing surface heat fluxes and ground temperature; for the land parameters, offline sensitivity analyses were also conducted for comparison to infer the influence of land-atmosphere interactions. A simple "one-at-a-time" sensitivity analysis was conducted first to filter out some insensitive parameters, followed by a multicriteria sensitivity analysis using the multiobjective generalized sensitivity analysis algorithm. The models used were the locally coupled National Center for Atmospheric Research (NCAR) single-column community climate model and the offline NCAR land surface model, driven and evaluated by a summer intensive operational periods (IOP) data set from the southern Great Plains. As expected, the results show that land-atmosphere interactions (with or without land-atmosphere parameter interactions) can have significant influences on the sensitivity of the land surface to changes in the land parameters, and the single-criterion sensitivities can be significantly different from the multicriteria sensitivity. These findings are mostly model and data independent and can be generally useful, regardless of the model/data dependence of the sensitivities of individual parameters. The exceptionally high sensitivities of the selected atmospheric parameters in a multicriteria sense (and in particular for latent heat) appeal for adequate attention to the specification of effective values of these parameters in an atmospheric model. Overall, this study proposes an effective framework of multicriteria sensitivity analysis beneficial to future studies in the development and parameter estimation of other complex (offline or coupled) land surface models. Copyright 2004 by the American Geophysical Union

Parameter sensitivity analysis for different complexity land surface models using multicriteria methods

A multicriteria algorithm, the MultiObjective Generalized Sensitivity Analysis (MOGSA), was used to investigate the parameter sensitivity of five different land surface models with increasing levels of complexity in the physical representation of the vegetation (BUCKET, CHASM, BATS 1, Noah, and BATS 2) at five different sites representing crop land/ pasture, grassland, rain forest, cropland, and semidesert areas. The methodology allows for the inclusion of parameter interaction and does not require assumptions of independence between parameters, while at the same time allowing for the ranking of several single-criterion and a global multicriteria sensitivity indices. The analysis required on the order of 50 thousand model runs. The results confirm that parameters with similar "physical meaning" across different model structures behave in different ways depending on the model and the locations. It is also shown that after a certain level an increase in model structure complexity does not necessarily lead to better parameter identifiability, i.e., higher sensitivity, and that a certain level of overparameterization is observed. For the case of the BATS 1 and BATS 2 models, with essentially the same model structure but a more sophisticated vegetation model, paradoxically, the effect on parameter sensitivity is mainly reflected in the sensitivity of the soil-related parameter. Copyright 2006 by the American Geophysical Union

Parameter estimation of a land surface scheme using multicriteria methods

Attempts to create models of surface-atmosphere interactions with greater physical realism have resulted in land surface schemes (LSS) with large numbers of parameters. The hope has been that these parameters can be assigned typical values by inspecting the literature. The potential for using the various observational data sets that are now available to extract plot-scale estimates for the parameters of a complex LSS via advanced parameter estimation methods developed for hydrological models is explored in this paper. Results are reported for two case studies using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The traditional single-criterion methods were found to be of limited value. However, a multicriteria approach was found to be effective in constraining the parameter estimates into physically plausible ranges when observations on at least one appropriate heat flux and one properly selected state variable are available. Copyright 1999 by the American Geophysical Union

Sensitivity analysis of a land surface scheme using multicriteria methods

Attempts to model surface-atmosphere interactions with greater physical realism have resulted in complex land surface schemes (LSS) with large numbers of parameters. A companion paper describes a multicriteria calibration procedure for extracting plot-scale estimates of the preferred ranges of these parameters from the various observational data sets that are now available. A complementary procedure is presented in this paper that provides an objective determination of the multicriteria sensitivity of the modeled variables to the parameters, thereby allowing the number of calibration parameters and hence the computational effort to be reduced. Two case studies are reported for the BATS model using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The sensitivity results were found to be consistent with the physical properties of the different environments, thereby supporting the reasonableness of the model formulation. Further, when the insensitive parameters are omitted from the calibration process, there is little degradation in the quality of the model description and little change in the preferred range of the remaining parameters. Copyright 1999 by the American Geophysical Union

Tidal and groundwater fluxes to a shallow, microtidal estuary : constraining inputs through field observations and hydrodynamic modeling

This paper is not subject to U.S. copyright. The definitive version was published in Estuaries and Coasts 35 (2012): 1285-1298, doi:10.1007/s12237-012-9515-x.Increased nutrient loading to estuaries has led to eutrophication, degraded water quality, and ecological transformations. Quantifying nutrient loads in systems with significant groundwater input can be difficult due to the challenge of measuring groundwater fluxes. We quantified tidal and freshwater fluxes over an 8-week period at the entrance of West Falmouth Harbor, Massachusetts, a eutrophic, groundwater-fed estuary. Fluxes were estimated from velocity and salinity measurements and a total exchange flow (TEF) methodology. Intermittent cross-sectional measurements of velocity and salinity were used to convert point measurements to cross-sectionally averaged values over the entire deployment (index relationships). The estimated mean freshwater flux (0.19 m3/s) for the 8-week period was mainly due to groundwater input (0.21 m3/s) with contributions from precipitation to the estuary surface (0.026 m3/s) and removal by evaporation (0.048 m3/s). Spring–neap variations in freshwater export that appeared in shorter-term averages were mostly artifacts of the index relationships. Hydrodynamic modeling with steady groundwater input demonstrated that while the TEF methodology resolves the freshwater flux signal, calibration of the index– salinity relationships during spring tide conditions only was responsible for most of the spring–neap signal. The mean freshwater flux over the entire period estimated from the combination of the index-velocity, index–salinity, and TEF calculations were consistent with the model, suggesting that this methodology is a reliable way of estimating freshwater fluxes in the estuary over timescales greater than the spring– neap cycle. Combining this type of field campaign with hydrodynamic modeling provides guidance for estimating both magnitude of groundwater input and estuarine storage of freshwater and sets the stage for robust estimation of the nutrient load in groundwater.Funding was provided by the USGS Coastal and Marine Geology Program and by National Science Foundation Award #0420575 from the Biocomplexity/Coupled Biogeochemical Cycles Program

Multiple molecular mechanisms form a positive feedback loop driving amyloid β42 peptide-induced neurotoxicity via activation of the TRPM2 channel in hippocampal neurons

Emerging evidence supports an important role for the ROS-sensitive TRPM2 channel in mediating age-related cognitive impairment in Alzheimer’s disease (AD), particularly neurotoxicity resulting from generation of excessive neurotoxic Aβ peptides. Here we examined the elusive mechanisms by which Aβ₄₂ activates the TRPM2 channel to induce neurotoxicity in mouse hippocampal neurons. Aβ₄₂-induced neurotoxicity was ablated by genetic knockout (TRPM2-KO) and attenuated by inhibition of the TRPM2 channel activity or activation through PARP-1. Aβ₄₂-induced neurotoxicity was also inhibited by treatment with TPEN used as a Zn²⁺-specific chelator. Cell imaging revealed that Aβ₄₂-induced lysosomal dysfunction, cytosolic Zn²⁺ increase, mitochondrial Zn²⁺ accumulation, loss of mitochondrial function, and mitochondrial generation of ROS. These effects were suppressed by TRPM2-KO, inhibition of TRPM2 or PARP-1, or treatment with TPEN. Bafilomycin-induced lysosomal dysfunction also resulted in TRPM2-dependent cytosolic Zn²⁺ increase, mitochondrial Zn²⁺ accumulation, and mitochondrial generation of ROS, supporting that lysosomal dysfunction and accompanying Zn²⁺ release trigger mitochondrial Zn²⁺ accumulation and generation of ROS. Aβ₄₂-induced effects on lysosomal and mitochondrial functions besides neurotoxicity were also suppressed by inhibition of PKC and NOX. Furthermore, Aβ₄₂-induced neurotoxicity was prevented by inhibition of MEK/ERK. Therefore, our study reveals multiple molecular mechanisms, including PKC/NOX-mediated generation of ROS, activation of MEK/ERK and PARP-1, lysosomal dysfunction and Zn²⁺ release, mitochondrial Zn²⁺ accumulation, loss of mitochondrial function, and mitochondrial generation of ROS, are critically engaged in forming a positive feedback loop that drives Aβ₄₂-induced activation of the TRPM2 channel and neurotoxicity in hippocampal neurons. These findings shed novel and mechanistic insights into AD pathogenesis

Gene probing reveals the widespread distribution, diversity and abundance of isoprene-degrading bacteria in the environment

Background: Approximately 500 Tg of isoprene are emitted to the atmosphere annually, an amount similar to that of methane, and despite its significant effects on the climate, very little is known about the biological degradation of isoprene in the environment. Isolation and characterisation of isoprene degraders at the molecular level has allowed the development of probes targeting isoA encoding the α-subunit of the isoprene monooxygenase. This enzyme belongs to the soluble diiron centre monooxygenase family and catalyses the first step in the isoprene degradation pathway. The use of probes targeting key metabolic genes is a successful approach in molecular ecology to study specific groups of bacteria in complex environments. Here, we developed and tested a novel isoA PCR primer set to study the distribution, abundance, and diversity of isoprene degraders in a wide range of environments. Results: The new isoA probes specifically amplified isoA genes from taxonomically diverse isoprene-degrading bacteria including members of the genera Rhodococcus, Variovorax, and Sphingopyxis. There was no cross-reactivity with genes encoding related oxygenases from non-isoprene degraders. Sequencing of isoA amplicons from DNA extracted from environmental samples enriched with isoprene revealed that most environments tested harboured a considerable variety of isoA sequences, with poplar leaf enrichments containing more phylogenetically diverse isoA genes. Quantification by qPCR using these isoA probes revealed that isoprene degraders are widespread in the phyllosphere, terrestrial, freshwater and marine environments. Specifically, soils in the vicinity of high isoprene-emitting trees contained the highest number of isoprene-degrading bacteria. Conclusion: This study provides the molecular ecology tools to broaden our knowledge of the distribution, abundance and diversity of isoprene degraders in the environment, which is a fundamental step necessary to assess the impact that microbes have in mitigating the effects of this important climate-active gas