Linking farm management and ecosystem service provision: Challenges and opportunities for soil erosion prevention in Mediterranean silvo-pastoral systems

At both local and landscape levels, farm management is the main driver of land cover change influencing ecosystem functions, processes and traits. In Mediterranean large-scale silvo-pastoral systems these changes can have serious implications in the provision of valuable ecosystem services (ES). Current ES assessment, mapping and valuation are still focused in representing the state and trends of ES provision, often missing the link to actual farm management and farm management systems. We propose an approach that, at the farm level, combines the classification of farm management systems with indicators of ES provision. This is illustrated for soil erosion prevention, a key ES in mitigating current and future impacts in Mediterranean regions and the proposed approach is tested in Southern Portugal. We characterize thirty-eight large-scale farm management units (FMU) regarding their management system and environmental traits. Each FMU was then classified according to their management system and a set of ES indicators was calculated. To classify the FMU, data on livestock composition and grazing density, pastures, and soil mobilization practices were object of a cluster analysis and the result was tested against a set of ES indicators. The results highlight the implications and challenges for the provision of soil erosion prevention under different farm management systems and draw a clear relation between more intensive management practices and the degradation of service provision. Our results can also be used to support land management and policy design through the definition of intensity thresholds that consider the local environmental and ecological condition

Policy impacts on regulating ecosystem services: looking at the implications of 60 years of landscape change on soil erosion prevention in a Mediterranean silvo-pastoral system

Context: Policy decisions form a major driver of land use change, with important implications for socially and environmentally susceptible regions. It is well known that there can be major unintended consequences, especially where policies are not tailored to regionally specific contexts. Objectives: In this paper we assess the implications of 60 years of agricultural policies on soil erosion prevention (SEP) by vegetation, an essential regulating ecosystem service in Mediterranean Europe. Methods: To assess these implications we produced and analysed a time series of land cover/use and environmental conditions datasets (from 1951 to 2012) in relation to changing agricultural policies for a specific region in the southern Portugal. A set of indicators related to SEP allowed us to identify that land use intensification as increased soil erosion in the last 60 years. Results: Particularly in the last 35 years, as a consequence of headage payments for cattle, the agricultural policy had a significant effect in the density and renewal of the tree cover, resulting in drastic effects for the provision of the SEP service. These are more significant after 1986, coinciding with the implementation of several Common Agricultural Policy instruments focused on increasing the modernization and productivity capacity of farm systems. Conclusions: The results show some unintended effects of agricultural policy mechanisms on ecosystem service provision and highlight the need for context-based policies, tailored to the environmental constrains and potentials of each region

Assessing the ability of rural areas to fulfill multiple societal demands

Rural areas are changing through a process of multifunctional transition. New societal expectations, including countryside consumption and protection, increasingly determine the way rural space is used. There is a pressing need to grasp the new relative balance between these drivers of the rural space, in each particular area, in order to target public intervention. Tackling differentiation within rural space will definitely contribute to developing the potential and vocation of each area while supporting territorial cohesion. In this context, sound analytical knowledge that reveals and characterizes this differentiation is required and novel analytical approaches are needed for this knowledge to be obtained. Based on the conceptual framework proposed by Holmes (2006, 2012), this paper presents two methodological pathways for defining a typology of European regions that considers the multifunctionality of rural areas today and the relative weight of the dimensions of production, protection and consumption. The classification is produced at Nomenclature Territorial Unit NUTS 2 level, using information derived from European statistical datasets compiling different cartographic sources. One of the methods used to develop a typology was a clustering approach while the other method used was an expert-based analytical procedure. Even when the limitations stemming from the data available for the whole of Europe are considered, the results are encouraging. The results show two different regional distributions in Europe. These distributions, which have some similarities but also certain differences, both reveal the general characteristics of NUTS 2 regions and shed new light on the ways in which societal expectations for production, protection and consumption might be spatially reconciled. The expert-based approach seems to produce a more faithful classification. Both typologies result in most regions being classified as pluri-active, or complex or multifunctional, which may indicate that multiple modes of rural occupancy are widely found in each region and therefore that a more detailed scale of analysis would be more likely to enable evidence-based decisions to be made

Biomass allometry and carbon factors for a Mediterranean pine (Pinus pinea L.) in Portugal

Forests play an important role in the global carbon balance because they offset a large portion of the carbon dioxide emitted through human activities. Accurate estimates are necessary for national reporting of greenhouse gas inventories, carbon credit trading and forest carbon management but in Portugal reliable and accessible forest carbon measurement methodologies are still lacking for some species. The objective of this study was to provide forest managers with a comprehensive database of carbon factors and equations that allows estimating stand-level carbon stocks in Pinus pinea L. (P. pinea), regardless of the tree inventory information available. We produced aboveground biomass and stem volume equations, biomass expansion factors (BEF) by component as well as wood basic density (WBD) and component carbon fraction in biomass. A root-to-shoot ratio is also presented using data from trees in which the root system was completely excavated. We harvested 53 trees in centre and south Portugal covering different sizes (6.5 to 56.3 cm), ages (10 to 45 years) and stand densities (20 to 580 trees ha–1). The results indicate that aboveground allometry in P. pinea is not comparable with other pines and varies considerably with stand characteristics, highlighting the need to develop stand-dependent factors and equations for local or regional carbon calculations. BEFaboveground decreases from open (1.33 ± 0.03 Mg m–3) to closed stands (1.07 ± 0.01 Mg m–3) due to a change in biomass allocation pattern from stem to branches. Average WBD was 0.50 ± 0.01 Mg m–3 but varies with tree dimensions and the root-to-shoot ratio found was 0.30 ± 0.03. The carbon fraction was statistically different from the commonly used 0.5 factor for some biomass components. The equations and factors produced allow evaluating carbon stocks in P. pinea stands in Portugal, contributing to a more accurate estimation of carbon sequestered by this forest type

Synaptic Transmission: Looking for Clues to Autism Spectrum Disorders (ASD) Etiology in Copy Number Variants Containing Synaptic Genes

Copy Number Variants (CNVs) play an important role in susceptibility to ASD, often mediated by the deletion or duplication of genes involved in synaptic structure and function. Increasing evidence suggests a central role for defects in synaptic structure and function in the pathogenesis of non-syndromic ASD. In this study we tested the hypothesis of an enrichment in CNVs encompassing synaptic transmission genes in ASDThis work was supported by the fellowships SFRH/BD/79081/2011 to BO, SFRH/BPD/74739/2010 to ICC and SFRH/BPD/64281/2009 to CC from Fundação para a Ciência e a Tecnologia (FCT; Portugal)

Copy number variants involving components of the glutamatergic synaptic pathway in ASD patients

This work was supported by the fellowships SFRH/BD/79081/2011 to BO, SFRH/BPD/74739/2010 to ICC and SFRH/BPD/64281/2009 to CC from Fundação para a Ciência e a Tecnologia (FCT; Portugal).Copy Number Variants (CNVs) play an important role in susceptibility to Autism Spectrum Disorders (ASD), in particular when deleting or duplicating genes involved in synaptic structure and function such as glutamatergic synapse genes. Identifying CNVs of etiologic relevance for ASD that include glutamatergic genes may contribute to the understanding of glutamate-related pathogenic mechanisms in this disorder

UV spectrophotometry method for the monitoring of galacto-oligosaccharides production

Monitoring the industrial production of galacto-oligosaccharides (GOS) requires a fast and accurate methodology able to quantify, in real time, the substrate level and the product yield. In this work, a simple, fast and inexpensive UV spectrophotometric method, together with partial least squares regression (PLS) and artificial neural networks (ANN), was applied to simultaneously estimate the products (GOS) and the substrate (lactose) concentrations in fermentation samples. The selected multiple models were trained and their prediction abilities evaluated by cross-validation and external validation being the results obtained compared with HPLC measurements. ANN models, generated from absorbance spectra data of the fermentation samples, gave, in general, the best performance being able to accurately and precisely predict lactose and total GOS levels, with standard error of prediction lower than 13 g kg-1 and coefficient of determination for the external validation set of 0.93–0.94, showing residual predictive deviations higher than five, whereas lower precision was obtained with the multiple model generated with PLS. The results obtained show that UV spectrophotometry allowed an accurate and non-destructive determination of sugars in fermentation samples and could be used as a fast alternative method for monitoring GOS production

Learning difficulties : a portuguese perspective of a universal issue

In this article we present findings of a study that was conducted with the purpose of deepening the knowledge about the field of learning difficulties in Portugal. Therefore, within these findings we will discuss across several cultural boundaries, themes related with the existence of learning difficulties as a construct, the terminology, the political, social and scientific influences on the field, and the models of identification and of ongoing school support for students. While addressing the above-mentioned themes we will draw attention to the different, yet converging, international understandings of learning difficulties

UV spectrophotometry method for the monitoring of galacto-oligosaccharides production

Monitoring the industrial production of galacto-oligosaccharides (GOS) requires a fast and accurate methodology able to quantify, in real time, the substrate level and the product yield. In this work, a simple, fast and inexpensive UV spectrophotometric method, together with partial least squares regression (PLS) and artificial neural networks (ANN), was applied to simultaneously estimate the products (GOS) and the substrate (lactose) concentrations in fermentation samples. The selected multiple models were trained and their prediction abilities evaluated by cross-validation and external validation being the results obtained compared with HPLC measurements. ANN models, generated from absorbance spectra data of the fermentation samples, gave, in general, the best performance being able to accurately and precisely predict lactose and total GOS levels, with standard error of prediction lower than 13 g kg 1 and coefficient of determination for the external validation set of 0.93–0.94, showing residual predictive deviations higher than five, whereas lower precision was obtained with the multiple model generated with PLS. The results obtained show that UV spectrophotometry allowed an accurate and non-destructive determination of sugars in fermentation samples and could be used as a fast alternative method for monitoring GOS production.Fundação para a Ciência e a Tecnologia (FCT) - Bolsa de doutouramento SFRH/BDE/15510/2004Agência da Inovação – Programa IDEIA (Potugal

Practical procedure for discriminating monofloral honey with a broad pollen profile variability using an electronic tongue

Colour and floral origin are key parameters that may influence the honey market. Monofloral light honey are more demanded by consumers, mainly due to their flavour, being more valuable for producers due to their higher price when compared to darker honey. The latter usually have a high anti-oxidant content that increases their healthy potential. This work showed that it is possible to correctly classify monofloral honey with a high variability in floral origin with a potentiometric electronic tongue after making a preliminary selection of honey according their colours: white, amber and dark honey. The results showed that the device had a very satisfactory sensitivity towards floral origin (Castanea sp., Echium sp., Erica sp., Lavandula sp., Prunus sp. and Rubus sp.), allowing a leave-one-out cross validation correct classification of 100%. Therefore, the E-tongue shows potential to be used at analytical laboratory level for honey samples classification according to market and quality parameters, as a practical tool for ensuring monofloral honey authenticity