Long-term changes to the frequency of occurrence of British moths are consistent with opposing and synergistic effects of climate and land-use changes

1. Species’ distributions are likely to be affected by a combination of environmental drivers. We used a data set of 11 million species occurrence records over the period 1970–2010 to assess changes in the frequency of occurrence of 673 macro-moth species in Great Britain. Groups of species with different predicted sensitivities showed divergent trends, which we interpret in the context of land-use and climatic changes. 2. A diversity of responses was revealed: 260 moth species declined significantly, whereas 160 increased significantly. Overall, frequencies of occurrence declined, mirroring trends in less species-rich, yet more intensively studied taxa. 3. Geographically widespread species, which were predicted to be more sensitive to land use than to climate change, declined significantly in southern Britain, where the cover of urban and arable land has increased. 4. Moths associated with low nitrogen and open environments (based on their larval host plant characteristics) declined most strongly, which is also consistent with a land-use change explanation. 5. Some moths that reach their northern (leading edge) range limit in southern Britain increased, whereas species restricted to northern Britain (trailing edge) declined significantly, consistent with a climate change explanation. 6. Not all species of a given type behaved similarly, suggesting that complex interactions between species’ attributes and different combinations of environmental drivers determine frequency of occurrence changes. 7. Synthesis and applications. Our findings are consistent with large-scale responses to climatic and land-use changes, with some species increasing and others decreasing. We suggest that land-use change (e.g. habitat loss, nitrogen deposition) and climate change are both major drivers of moth biodiversity change, acting independently and in combination. Importantly, the diverse responses revealed in this species-rich taxon show that multifaceted conservation strategies are needed to minimize negative biodiversity impacts of multiple environmental changes. We suggest that habitat protection, management and ecological restoration can mitigate combined impacts of land-use change and climate change by providing environments that are suitable for existing populations and also enable species to shift their ranges.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

Increased temperature sensitivity of net DOC production from ombrotrophic peat due to water table draw-down.

The production and release of dissolved organic carbon (DOC) from peat soils is thought to be sensitive to changes in climate, specifically changes in temperature and rainfall. However, little is known about the actual rates of net DOC production in response to temperature and water table draw-down, particularly in comparison to carbon dioxide (CO2) fluxes. To explore these relationships, we carried out a laboratory experiment on intact peat soil cores under controlled temperature and water table conditions to determine the impact and interaction of each of these climatic factors on net DOC production. We found a significant interaction (P < 0.001) between temperature, water table draw-down and net DOC production across the whole soil core (0 to −55 cm depth). This corresponded to an increase in the Q10 (i.e. rise in the rate of net DOC production over a 10 °C range) from 1.84 under high water tables and anaerobic conditions to 3.53 under water table draw-down and aerobic conditions between −10 and − 40 cm depth. However, increases in net DOC production were only seen after water tables recovered to the surface as secondary changes in soil water chemistry driven by sulphur redox reactions decreased DOC solubility, and therefore DOC concentrations, during periods of water table draw-down. Furthermore, net microbial consumption of DOC was also apparent at − 1 cm depth and was an additional cause of declining DOC concentrations during dry periods. Therefore, although increased temperature and decreased rainfall could have a significant effect on net DOC release from peatlands, these climatic effects could be masked by other factors controlling the biological consumption of DOC in addition to soil water chemistry and DOC solubility. These findings highlight both the sensitivity of DOC release from ombrotrophic peat to episodic changes in water table draw-down, and the need to disentangle complex and interacting controls on DOC dynamics to fully understand the impact of environmental change on this system.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Sulforaphane protects cortical neurons against 5-S-cysteinyl-dopamine-induced toxicity through the activation of ERK1/2, Nrf-2 and the upregulation of detoxification enzymes

The degeneration of dopaminergic neurons in the substantia nigra has been linked to the formation of the endogenous neurotoxin 5-S-cysteinyl-dopamine. Sulforaphane (SFN), an isothiocyanate derived from the corresponding precursor glucosinolate found in cruciferous vegetables has been observed to exert a range of biological activities in various cell populations. In this study, we show that SFN protects primary cortical neurons against 5-S-cysteinyl-dopamine induced neuronal injury. Pre-treatment of cortical neurons with SFN (0.01-1 microM) resulted in protection against 5-S-cysteinyl-dopamine-induced neurotoxicity, which peaked at 100 nM. This protection was observed to be mediated by the ability of SFN to modulate the extracellular signal-regulated kinase 1 and 2 and the activation of Kelch-like ECH-associated protein 1/NF-E2-related factor-2 leading to the increased expression and activity of glutathione-S-transferase (M1, M3 and M5), glutathione reductase, thioredoxin reductase and NAD(P)H oxidoreductase 1. These data suggest that SFN stimulates the NF-E2-related factor-2 pathway of antioxidant gene expression in neurons and may protect against neuronal injury relevant to the aetiology of Parkinson's disease.

Synthesis, chemical, electrochemical characterization of oxomolybdenum(V) complexes of 2-(3,5-dimethyl pyrazol-1-yl) benzothiazole ligand: crystal structure of ligand and oxomolybdenum(VI) complex and density functional theory (DFT) calculation

This work reports the ligational behavior of the neutral bidentate chelating molecule 2-(3,5-dimethyl pyrazol-1-yl) benzothiazole towards the oxomolybdenum(V) center. Both mononuclear complexes of the type (MoOX3L)-O-V and binuclear complexes of the formula (Mo2O4X2L2)-O-V (where X = Cl, Br) are isolated in the solid state. The complexes are characterized by elemental analyses, various spectroscopic techniques (UV-Vis IR), magnetic susceptibility measurement at room temperature, and cyclic voltammetry for their redox behavior at a platinum electrode in CH3CN. The mononuclear complexes (MoOX3L)-O-V are found to be paramagnetic while the binuclear complexes Mo2O4X2L2 are diamagnetic. Crystal and molecular structure of the ligand and the dioxomolybdenum complex (MoO2Br2L)-O-VI (obtained from the complex MoOBr3L during crystallization) have been solved by single crystal X-ray diffraction technique. Relevant DFT calculations of the ligand and the complex (MoO2Br2L)-O-VI are also carried out.

Classification of cortical microcircuits based on micro-electrode-array data from slices of rat barrel cortex

The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitary of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.

Quantifying errors due to frequency changes and target location uncertainty for radar refractivity retrievals

Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron- and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 20°C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (ΔfTx) or the refractivity (ΔN). Observations at C band with a 2-μs pulse show an additional 66° of phase change noise for a ΔfTx of 190 kHz (34 ppm); this allows the effect due to ΔN to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large ΔN develops relative to the reference period [e.g., ~55° when ΔN = 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual–pulse repetition frequency (PRF) operation of a magnetron transmitter.

A unified approach to the recognition of complex actions from sequences of zone-crossings

We present a method for the recognition of complex actions. Our method combines automatic learning of simple actions and manual definition of complex actions in a single grammar. Contrary to the general trend in complex action recognition that consists in dividing recognition into two stages, our method performs recognition of simple and complex actions in a unified way. This is performed by encoding simple action HMMs within the stochastic grammar that models complex actions. This unified approach enables a more effective influence of the higher activity layers into the recognition of simple actions which leads to a substantial improvement in the classification of complex actions. We consider the recognition of complex actions based on person transits between areas in the scene. As input, our method receives crossings of tracks along a set of zones which are derived using unsupervised learning of the movement patterns of the objects in the scene. We evaluate our method on a large dataset showing normal, suspicious and threat behaviour on a parking lot. Experiments show an improvement of ~ 30% in the recognition of both high-level scenarios and their composing simple actions with respect to a two-stage approach. Experiments with synthetic noise simulating the most common tracking failures show that our method only experiences a limited decrease in performance when moderate amounts of noise are added.

The neurotoxicity of 5-S-cysteinyldopamine is mediated by the early activation of ERK1/2 followed by the subsequent activation of ASK1/JNK1/2 pro-apoptotic signalling

Parkinson's disease is characterized by the progressive and selective loss of dopaminergic neurons in the substantia nigra. It has been postulated that endogenously formed CysDA (5-S-cysteinyldopamine) and its metabolites may be, in part, responsible for this selective neuronal loss, although the mechanisms by which they contribute to such neurotoxicity are not understood. Exposure of neurons in culture to CysDA caused cell injury, apparent 12-48 h post-exposure. A portion of the neuronal death induced by CysDA was preceded by a rapid uptake and intracellular oxidation of CysDA, leading to an acute and transient activation of ERK2 (extracellular-signal-regulated kinase 2) and caspase 8. The oxidation of CysDA also induced the activation of apoptosis signal-regulating kinase 1 via its de-phosphorylation at Ser967, the phosphorylation of JNK (c-Jun N-terminal kinase) and c-Jun (Ser73) as well as the activation of p38, caspase 3, caspase 8, caspase 7 and caspase 9. Concurrently, the inhibition of complex I by the dihydrobenzothiazine DHBT-1 [7-(2-aminoethyl)-3,4-dihydro-5-hydroxy-2H-1,4-benzothiazine-3-carboxylic acid], formed from the intracellular oxidation of CysDA, induces complex I inhibition and the subsequent release of cytochrome c which further potentiates pro-apoptotic mechanisms. Our data suggest a novel comprehensive mechanism for CysDA that may hold relevance for the selective neuronal loss observed in Parkinson's disease.