Teaching Planning of Forestry Engineering in Spain : origins and evolution

This paper addresses the historical evolution of, from its inception, to the present day, within the changing context of EHEA and linked to professional competences. The research methodology, although it is mainly a historical document review, expert opinions on university educational planning of university education of forestry engineering in Spain are also included. The results show the evolution of centralized planning, based on technical knowledge transmission to an approach based on competences (technical, contextual and behavioral) focusing on learning for improving employability.

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.

First 20 years of DNDC: Model evolution and GRAMP.

The DNDC (DeNitrification and DeComposition) model was first developed by Li et al. (1992) as a rain event-driven process-orientated simulation model for nitrous oxide, carbon dioxide and nitrogen gas emissions from the agricultural soils in the U.S. Over the last 20 years, the model has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. The Global Research Alliance Modelling Platform (GRAMP) is a UK-led initiative for the establishment of a purposeful and credible web-based platform initially aimed at users of the DNDC model. With the aim of improving the predictions of soil C and N cycling in the context of climate change the objectives of GRAMP are to: 1) to document the existing versions of the DNDC model; 2) to create a family tree of the individual DNDC versions; 3) to provide information on model use and development; and 4) to identify strengths, weaknesses and potential improvements for the model.