Germination of Medicago sativa is inhibited by soluble compounds in cement dust

Deposition of cement dust on soils and plant surfaces is known to affect plant growth and the species composition of plant communities, but little is known about its effects (and those of its pH and constituents) on germination. Therefore, the aim of this study was to assess the toxicity of an aqueous cement extract, constituents of the extract and pH on the germination of seeds of a selected species, Medicago sativa. First, the effects of the extract were tested in assays with concentrations and exposure durations ranging from 0 to 1.0 g/mL and 4 to 96 h, respectively. At 0.8 g/mL, the extract strongly inhibited germination; a 4-h exposure reduced the germination rate, from 77?±?1.8 to 50?±?2.6 % (mean ± SE), while 8-h exposure completely inhibited it. Further, treatment at this concentration killed the non-germinating seeds, thus the inhibition was due to toxic effects. Neither the pH of the extract nor the concentration of its main soluble elements separately (K, Ca, S, Na, or Cr) caused the toxicity since germination rates were not significantly reduced when these variables were tested individually. However, a mixture of the elements in solution reduced germination rates, suggesting that they have adverse synergistic effects.     

The concept of the Portuguese National Ecological Reserve: constraints and impossibilities in the Azores Archipelago

The biophysical features of small islands (SI) distinguish them from other territories; isolation, small size and several anthropogenic pressures reduce the resilience of ecosystems and increase their vulnerability to global changes. Many SI have a shortage of infrastructures, institutions and technical/financial resources that hinder planning and require different integrated solutions. In Portugal, the National Ecological Reserve (NER) is legally binding for spatial planning instruments. It aims to defend natural values and areas of ecological value, or sensibility, or susceptible to natural hazards. However, the criteria for the design of NER are strictly set for mainland territory, not taking into account specific features of small islands. A case study of the Azores Archipelago is used to demonstrate that spatial planning instruments should be adapted to island contexts. Such adaptation will increase the effectiveness of their implementation in relation to the protection of natural resources, stability of biophysical structures and prevention of natural hazards. Observing the main differences between mainland and the Azores Archipelago it is possible to define a methodological transposition of the NER aims and goals into an island context. This approach is an answer to the constraints in effective adaptation of spatial planning instruments for islands.     

A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.     

Climate change adaptation,mitigation and livelihood benefits in coffee production: where are the synergies?

There are worldwide approximately 4.3 million coffee (Coffea arabica) producing smallholders generating a large share of tropical developing countries’ gross domestic product, notably in Central America. Their livelihoods and coffee production are facing major challenges due to projected climate change, requiring adaptation decisions that may range from changes in management practices to changes in crops or migration. Since management practices such as shade use and reforestation influence both climate vulnerability and carbon stocks in coffee, there may be synergies between climate change adaptation and mitigation that could make it advantageous to jointly pursue both objectives. In some cases, carbon accounting for mitigation actions might even be used to incentivize and subsidize adaptation actions. To assess potential synergies between climate change mitigation and adaptation in smallholder coffee production systems, we quantified (i) the potential of changes in coffee production and processing practices as well as other livelihood activities to reduce net greenhouse gas emissions, (ii) coffee farmers’ climate change vulnerability and need for adaptation, including the possibility of carbon markets subsidizing adaptation. We worked with smallholder organic coffee farmers in Northern Nicaragua, using workshops, interviews, farm visits and the Cool Farm Tool software to calculate greenhouse gas balances of coffee farms. From the 12 activities found to be relevant for adaptation, two showed strong and five showed modest synergies with mitigation. Afforestation of degraded areas with coffee agroforestry systems and boundary tree plantings resulted in the highest synergies between adaptation and mitigation. Financing possibilities for joint adaptation-mitigation activities could arise through carbon offsetting, carbon insetting, and carbon footprint reductions. Non-monetary benefits such as technical assistance and capacity building could be effective in promoting such synergies at low transaction costs.     

The determinants of support levels for wind energy in the European Union. An econometric study

The aim of this paper is to identify the factors that drive support levels for wind on-shore electricity in the Member States of the European Union (EU) with the help of econometric techniques. The econometric analysis is based on cross-section linear regressions with ordinary least squares. Four alternative specifications of the model have been estimated. The estimates comply with the basic hypotheses of the lineal model, i.e., absence of multicollinearity, accurate functional form, homokedasticity and normality in the distribution of errors. Thus, the estimations are unbiased, efficient and consistent. The results show that countries with higher wind energy generation costs have higher support levels. The higher support levels in countries with higher carbon intensities suggest that wind energy deployment is regarded as effective to mitigate carbon emissions. The type of support scheme also influences support levels, with feed-in tariffs leading to lower levels of support than other instruments. In addition, a general good investment climate in the country makes higher support levels less necessary, stressing the importance of lowering risks in order to reduce support levels and, thus, financial transfers from consumers to producers. Thus, providing stable regulatory frameworks should be a priority of policy-makers. The rest of variables (renewable energy resource potentials, administrative barriers, energy import dependency, interest rates, share of wind energy in total electricity generation as a proxy of lobbying pressures and electricity demand) are not statistically significant in most specifications and some of them do not have the expected sign.