Green growth and climate change: conceptual and empirical considerations

The feasibility of green growth is studied in the context of climate change. As carbon emissions are easier to quantify than many other types of environmental pressure, it will be possible to reach a more definite conclusion about the likelihood of green growth than has been possible in the long-standing historical debate on growth versus the environment. We calculate the rate of decoupling between gross domestic product (GDP) and GHG emissions needed to achieve internationally agreed climate targets. Next, eight arguments are considered that together suggest that fast decoupling will be very difficult. Subsequently, we examine the main lines of research used by proponents of green growth to support their viewpoint, including theoretical arguments, exercises with integrated assessment models, and studies of the environmental Kuznets curve hypothesis. It will be concluded that decoupling as a main or single strategy to combine economic and environmental aims should be judged as taking a very large risk with our common future. To minimize this risk we need to seriously consider reducing our dependence on growth. This requires a fundamental change of focus in both economic research and policy.

Policy relevance

Currently, green growth is the only strategy of mainstream economists and policy makers to address climate change. This article demonstrates that such an exclusive focus is very risky due to the scale of the challenge and the existence of various barriers to the fast decoupling of GHG emissions from economic output. It seems that the only option to combine environmental and economic objectives is reducing the dependence of our economies on growth. Finding strategies in line with this requires a fundamental change of focus in both economic research and policy.     

Vertical fault systems in the tectonosphere geoelectrical section in petroliferous domains of Sakhalin Island (Russia) and Gulf of Tonkin (Vietnam): Evidence from magnetotelluric sounding

The transverse current anomalies evident from magnetotelluric sounding (MTS) data in the transition zone from the Asian continent to the Pacific Ocean and a geoelectrical model suitable for explaining these effects are discussed. Using simulation results and new MTS data on Sakhalin and northern Vietnam, ultra-deep fluid–fault system (UDFFS) models are constructed, comprising steeply dipping low-resistivity and high-resistivity linear bodies which penetrate through the whole section of the lithosphere, continuing deep into the asthenosphere. The structure of these systems reflects the development of deep and ultra-deep fault zones, along which mantle-originated fluids may migrate through sediments to reach the surface. This allows the anisotropic–conductive fractured structures adjacent to these faults to be considered as being most favorable for hydrocarbon accumulations.     

Environmental heterogeneity predicts species richness of freshwater mollusks in sub-Saharan Africa

Species diversity and how it is structured on a continental scale is influenced by stochastic, ecological, and evolutionary driving forces, but hypotheses on determining factors have been mainly examined for terrestrial and marine organisms. The extant diversity of African freshwater mollusks is in general well assessed to facilitate conservation strategies and because of the medical importance of several taxa as intermediate hosts for tropical parasites. This historical accumulation of knowledge has, however, not resulted in substantial macroecological studies on the spatial distribution of freshwater mollusks. Here, we use continental distribution data and a recently developed method of random and cohesive allocation of species distribution ranges to test the relative importance of various factors in shaping species richness of Bivalvia and Gastropoda. We show that the mid-domain effect, that is, a hump-shaped richness gradient in a geographically bounded system despite the absence of environmental gradients, plays a minor role in determining species richness of freshwater mollusks in sub-Saharan Africa. The western branch of the East African Rift System was included as dispersal barrier in richness models, but these simulation results did not fit observed diversity patterns significantly better than models where this effect was not included, which suggests that the rift has played a more complex role in generating diversity patterns. Present-day precipitation and temperature explain richness patterns better than Eemian climatic condition. Therefore, the availability of water and energy for primary productivity during the past does not influence current species richness patterns much, and observed diversity patterns appear to be in equilibrium with contemporary climate. The availability of surface waters was the best predictor of bivalve and gastropod richness. Our data indicate that habitat diversity causes the observed species–area relationship, and hence, that environmental heterogeneity is a principal driver of freshwater mollusk richness on a continental scale.     

Rockfall trajectory modeling combined with heuristic analysis for assessing the rockfall hazard along the Maratea SS18 coastal road (Basilicata,Southern Italy)

In this paper, a study aimed to assess the rockfall hazard along a portion of the SS18 coastal road, located in the coastal area of Maratea (Basilicata Region, Southern Italy), is presented. The relevance of this study derives from the location of the study area, because the SS18 is a strategic roads in a touristic area, and, since the hazard assessment was performed in 2004 within a project financed by the Viability Regional Department of Autonomous National Company of Roads (ANAS), from the possibility to validate the results by using real rockfall events occurred after 2004. The procedure for assessing the rockfall hazard was composed of four sequential analyses: (i) geomechanical and kinematic characterization of rock mass, (ii) implementation of Romana’s (1985) Slope Mass Rating (SMR) method for identifying the potential boulder release areas (rockfall initiation areas), (iii) determination of rockfall trajectories by using a 3D numerical model (ROTOMAP), (iv) calculation and mapping of the hazard index by combining three factors, i.e., (a) lithological features of outcropping materials on rock faces, (b) kinematic compatibility defined by simulating the rockfall trajectories, and (c) spatial distribution of occurred rockfall events. Finally, the proposed methodology was validated by combining the distribution of the hazard levels along the road with the location on the SS18 of the rockfall events occurred from 2004 to 2014.     

Improving runoff prediction using agronomical information in a cropped,loess covered catchment

Predicting runoff hot spots and hot‐moments within a headwater crop‐catchment is of the utmost importance to reduce adverse effects on aquatic ecosystems by adapting land use management to control runoff. Reliable predictions of runoff patterns during a crop growing season remain challenging. This is mainly due to the large spatial and temporal variations of topsoil hydraulic properties controlled by complex interactions between weather, growing vegetation, and cropping operations. This interaction can significantly modify runoff patterns and few process‐based models can integrate this evolution of topsoil properties during a crop growing season at the catchment scale. Therefore, the purpose of this study was to better constrain the event‐based hydrological model Limburg Soil Erosion Model by incorporating temporal constraints for input topsoil properties during a crop growing season (LISEM). The results of the temporal constraint strategy (TCS) were compared with a classical event per event calibration strategy (EES) using multi‐scale runoff information (from plot to catchment). The EES and TCS approaches were applied in a loess catchment of 47 ha located 30 km northeast of Strasbourg (Alsace, France). A slight decrease of the Nash–Sutcliffe efficiency criterion on runoff discharge for TCS compared to EES was counterbalanced by a clear improvement of the spatial runoff patterns within the catchment. This study showed that limited agronomical and climatic information added during the calibration step improved the spatial runoff predictions of an event‐based model. Reliable prediction of runoff source, connectivity, and dynamics can then be derived and discussed with stakeholders to identify runoff hot spots and hot‐moments for subsequent land use and crop management modifications.