Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community- weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.

Flooding tolerance in four 'Garrigue' landscape plants: implications for their future use in the urban landscapes of north-west Europe?

Within a changing climate, Mediterranean ‘Garrigue’ xerophytes are increasingly recommended as suitable urban landscape plants in north-west Europe, based on their capacity to tolerate high temperature and reduced water availability during summer. Such species, however, have a poor reputation for tolerating waterlogged soils; paradoxically a phenomenon that may also increase in north-west Europe due to predictions for both higher volumes of winter precipitation, and short, but intensive periods of summer rainfall. This study investigated flooding tolerance in four landscape ‘Garrigue’ species, Stachys byzantina, Cistus × hybridus, Lavandula angustifolia and Salvia officinalis. Despite evolving in a dry habitat, the four species tested proved remarkably resilient to flooding. All species survived 17 days flooding in winter, with Stachys and Lavandula also surviving equivalent flooding duration during summer. Photosynthesis and biomass production, however, were strongly inhibited by flooding although the most tolerant species, Stachys quickly restored its photosynthetic capacity on termination of flooding. Overall, survival rates were comparable to previous studies on other terrestrial (including wetland) species. Subsequent experiments using Salvia (a species we identified as ‘intermediate’ in tolerance) clearly demonstrated adaptations to waterlogging, e.g. acclimation against anoxia when pre-treated with hypoxia. Despite anecdotal information to the contrary, we found no evidence to suggest that these xerophytic species are particularly intolerant of waterlogging. Other climatic and biotic factors may restrict the viability and distribution of these species within the urban conurbations of north-west Europe, but we believe increased incidence of flooding per se should not preclude their consideration.

Statins and selective inhibition of Rho kinase protect small conductance calcium-activated potassium channel function (KCa2.3) in cerebral arteries

Background: In rat middle cerebral and mesenteric arteries the KCa2.3 component of endothelium-dependent hyperpolarization (EDH) is lost following stimulation of thromboxane (TP) receptors, an effect that may contribute to the endothelial dysfunction associated with cardiovascular disease. In cerebral arteries, KCa2.3 loss is associated with NO synthase inhibition, but is restored if TP receptors are blocked. The Rho/Rho kinase pathway is central for TP signalling and statins indirectly inhibit this pathway. The possibility that Rho kinase inhibition and statins sustain KCa2.3 hyperpolarization was investigated in rat middle cerebral arteries (MCA). Methods: MCAs were mounted in a wire myograph. The PAR2 agonist, SLIGRL was used to stimulate EDH responses, assessed by simultaneous measurement of smooth muscle membrane potential and tension. TP expression was assessed with rt-PCR and immunofluorescence. Results: Immunofluorescence detected TP in the endothelial cell layer of MCA. Vasoconstriction to the TP agonist, U46619 was reduced by Rho kinase inhibition. TP receptor stimulation lead to loss of KCa2.3 mediated hyperpolarization, an effect that was reversed by Rho kinase inhibitors or simvastatin. KCa2.3 activity was lost in L-NAME-treated arteries, but was restored by Rho kinase inhibition or statin treatment. The restorative effect of simvastatin was blocked after incubation with geranylgeranyl-pyrophosphate to circumvent loss of isoprenylation. Conclusions: Rho/Rho kinase signalling following TP stimulation and L-NAME regulates endothelial cell KCa2.3 function. The ability of statins to prevent isoprenylation and perhaps inhibit of Rho restores/protects the input of KCa2.3 to EDH in the MCA, and represents a beneficial pleiotropic effect of statin treatment.

Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties

Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.

Risk assessment of UK skylark populations using life-history and individual-based landscape models

Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

Conductance and relaxations of gelatin films in the glassy and rubbery states

The dielectric constant, epsilon', and the dielectric loss, epsilon'', for gelatin films were measured in the glassy and rubbery states over a frequency range from 20 Hz to 10 MHz; epsilon' and epsilon'' were transformed into M* formalism (M* = 1/(epsilon' - i epsilon'') = M' + iM''; i, the imaginary unit). The peak of epsilon'' was masked probably due to dc conduction, but the peak of M'', e.g. the conductivity relaxation, for the gelatin used was observed. By fitting the M'' data to the Havriliak-Negami type equation, the relaxation time, tauHN, was evaluated. The value of the activation energy, Etau, evaluated from an Arrhenius plot of 1/tauHN, agreed well with that of Esigma evaluated from the DC conductivity sigma0 both in the glassy and rubbery states, indicating that the conductivity relaxation observed for the gelatin films was ascribed to ionic conduction. The value of the activation energy in the glassy state was larger than that in the rubbery state.

The influence of anthropogenic landscape changes on weather in south Florida

Using identical observed meteorology for lateral boundary conditions, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida. Three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state. Over the 2-month period, there was a 9% decrease in rainfall averaged over south Florida with the 1973 landscape and an 11% decrease with the 1993 landscape, as compared with the model results when the 1900 landscape is used. The limited available observations of trends in summer rainfall over this region are consistent with these trends.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

A global quantitative synthesis of local and landscape effects on wild bee pollinators in agroecosystems

Bees provide essential pollination services that are potentially affected both by local farm management and the surrounding landscape. To better understand these different factors, we modelled the relative effects of landscape composition (nesting and floral resources within foraging distances), landscape configuration (patch shape, interpatch connectivity and habitat aggregation) and farm management (organic vs. conventional and local-scale field diversity), and their interactions, on wild bee abundance and richness for 39 crop systems globally. Bee abundance and richness were higher in diversified and organic fields and in landscapes comprising more high-quality habitats; bee richness on conventional fields with low diversity benefited most from high-quality surrounding land cover. Landscape configuration effects were weak. Bee responses varied slightly by biome. Our synthesis reveals that pollinator persistence will depend on both the maintenance of high-quality habitats around farms and on local management practices that may offset impacts of intensive monoculture agriculture.