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Following earlier studies, we present forward and inverse simulations of heat and fluid transport of the upper crust using a local 3-D model of the Kola area. We provide best estimates for palaeotemperatures and permeabilities, their errors and their dependencies. Our results allow discriminating between the two mentioned processes to a certain extent, partly resolving the non-uniqueness of the problem. We find clear indications for a significant contribution of advective heat transport, which, in turn, imply only slightly lower ground surface temperatures during the last glacial maximum relative to the present value. These findings are consistent with the general background knowledge of (i) the fracture zones and the corresponding fluid movements in the bedrock and (ii) the glacial history of the Kola area.
Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining post-processing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.
In Valais, Switzerland, Scots pines (Pinus sylvestris L.) are declining, mainly following drought. To assess the impact of drought on tree growth and survival, an irrigation experiment was initiated in 2003 in a mature pine forest, approximately doubling the annual precipitation. Tree crown transparency (lack of foliage) and leaf area index (LAI) were annually assessed. Seven irrigated and six control trees were felled in 2006, and needles, stem discs and branches were taken for growth analysis. Irrigation in 2004 and 2005, both with below-average precipitation, increased needle size, area and mass, stem growth and, with a 1-year delay, shoot length. This led to a relative decrease in tree crown transparency (−14%) and to an increase in stand LAI (+20%). Irrigation increased needle length by 70%, shoot length by 100% and ring width by 120%, regardless of crown transparency. Crown transparency correlated positively with mean needle size, shoot length and ring width and negatively with specific leaf area. Trees with high crown transparency (low growth, short needles) experienced similar increases in needle mass and growth with irrigation than trees with low transparency (high growth, long needles), indicating that seemingly declining trees were able to ‘recover’ when water supply became sufficient. A simple drought index before and during the irrigation explained most of the variation found in the parameters for both irrigated and control trees.
Increasing Scots pine (Pinus sylvestris L.) mortality has been recently observed in the dry inner valleys of the European Alps. Besides drought, infection with pine mistletoe (Viscum album ssp. austriacum) seems to play an important role in the mortality dynamics of Scots pines, but how mistletoes promote pine decline remains unclear. To verify whether pine mistletoe infection weakens the host via crown degradation, as observed for dwarf mistletoes, we studied the negative effects of pine mistletoe infestation on the photosynthetic tissues and branch growth of pairs of infested and non-infested branches. Pine mistletoe infection leads to crown degradation in its host by reducing the length, the radial increment, the ramification, the needle length and the number of needle years of the infested branches. This massive loss in photosynthetic tissue results in a reduction in primary production and a subsequent decrease in carbohydrate availability. The significant reduction in needle length due to mistletoe infection is an indication for a lower water and nutrient availability in infested branches. Thus, mistletoe infection might lead to a decrease in the availability of water and carbohydrates, the two most important growth factors, which are already shortened due to the chronic drought situation in the area. Therefore, pine mistletoe increases the risk of drought-induced mortality of its host when growing in a xeric environment.
Climate change is challenging forestry management and practices. Among other things, tree species with the ability to cope with more extreme climate conditions have to be identified. However, while environmental factors may severely limit tree growth or even cause tree death, assessing a tree species' potential for surviving future aggravated environmental conditions is rather demanding. The aim of this study was to find a tree-ring-based method suitable for identifying very drought-tolerant species, particularly potential substitute species for Scots pine (Pinus sylvestris L.) in Valais. In this inner-Alpine valley, Scots pine used to be the dominating species for dry forests, but today it suffers from high drought-induced mortality. We investigate the growth response of two native tree species, Scots pine and European larch (Larix decidua Mill.), and two non-native species, black pine (Pinus nigra Arnold) and Douglas fir (Pseudotsuga menziesii Mirb. var. menziesii), to drought. This involved analysing how the radial increment of these species responded to increasing water shortage (abandonment of irrigation) and to increasingly frequent drought years. Black pine and Douglas fir are able to cope with drought better than Scots pine and larch, as they show relatively high radial growth even after irrigation has been stopped and a plastic growth response to drought years. European larch does not seem to be able to cope with these dry conditions as it lacks the ability to recover from drought years. The analysis of trees' short-term response to extreme climate events seems to be the most promising and suitable method for detecting how tolerant a tree species is towards drought. However, combining all the methods used in this study provides a complete picture of how water shortage could limit species.
Knowledge-based productivity in “low-tech” industries: evidence from firms in developing countries
(2014)
Using firm-level data from five developing countries—Brazil, Ecuador, South Africa, Tanzania, and Bangladesh—and three industries—food processing, textiles, and the garments and leather products—this article examines the importance of various sources of knowledge for explaining productivity and formally tests whether sector- or country-specific characteristics dominate these relationships. Knowledge sources driving productivity appear mainly sector specific. Also differences in the level of development affect the effectiveness of knowledge sources. In the food processing sector, firms with higher educated managers are more productive, and in least-developed countries, additionally those with technology licenses and imported machinery and equipment. In the capital-intensive textiles sector, productivity is higher in firms that conduct R&D. In the garments and leather products sector, higher education of the managers, licensing, and R&D raise productivity.