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The harvested biomass of switchgrass (Panicum virgatum L.) is generally much lower than its potential; this may be due to several factors including not recovering all the biomass at harvest, weed competition, pests, disease and spatial variation of soil features. The objective of this research was to quantify the yield spatial variation of switchgrass and relate it to soil parameters, in a field of about 5 ha, in 2004 and 2005. Several thematic maps of soil parameters and biomass yield were produced using GIS and geostatistical methods. Soil parameters changed consistently within very short distances and biomass yield varied from 3 to more than 20 Mg ha-1. This remarkable variation indicates that the potential for increasing switchgrass productivity is a real prospect. Furthermore, spatial variation of yield showed similar patterns in the 2 years (r = 0.38**), and therefore a major influence of site characteristics on switchgrass yield can be assumed to occur. Significant correlations were found between biomass yield and soil N, P, moisture and pH as well as between soil parameters. Some soil parameters such as sand content showed patchy spatial distribution. Conversely, a reliable spatial dependence could not be identified for other parameters such as P. Further research is needed.

The transition to a low carbon future is starting to affect landscapes around the world. In order for this landscape transformation to be sustainable, renewable energy technologies should not cause critical trade-offs between the provision of energy and that of other ecosystem services such as food production. This literature review advances the body of knowledge on sustainable energy transition with special focus on ecosystem services-based approaches and methods. Two key issues emerge from this review: only one sixth of the published applications on the relation between renewable energy and landscape make use of the ecosystem service framework. Secondly, the applications that do address ecosystem services for landscape planning and design lack efficient methods and spatial reference systems that accommodate both cultural and regulating ecosystem services. Future research efforts should be directed to further advancing the spatial reference systems, the use of participatory mapping and landscape visualizations tools for cultural ecosystem services and the elaboration of landscape design principles.

Abstract The Mediterranean region is one of the most vulnerable regions to climate change. The majority of climate models forecast a rise in temperatures and less rainfall, which have been observed in recent decades. These changes will affect several vegetation properties, especially phenological dynamics and traits, by increasing drought intensity and recurrence. In this climate change context, the present study aims to assess the evolution of vegetation state and its relation with the climate dynamics in the Mediterranean forest region of northeast Tunisia using Land Surface Phenology (LSP) metrics and the vegetation index (NDVI) analysis from 2000 to 2017. To conduct this work, we used precipitation and temperature data from the two closest weather stations and 16-day NDVI composite images from the MODIS satellite source, with 250-m spatial resolution. Three phenological metrics— start of season (SOS), end of season (EOS), and length of season (LOS) — were obtained and compared for different vegetation types. The LSP variation in response to climatic metrics was also analyzed. The results showed that the LSP in our study area changed significantly during the 2000–2017 period, which includes an average 7.8 days delay in the SOS, an average advance in the EOS by 5 days, and LOS shortened by an average 12.8 days. Autumn (Pr_9) and spring (Pr_3 and P3_4) precipitations, as well as maximum temperature (Tx9+10), represent the best climate parameters to explain the changes in LSP. Both the NDVI and SPEI showed a significant high correlation (p

It is recognised that several constraints such as the lack of knowledge and expertise of farmers, land users and policy makers concerning agroforestry systems establishment and management hamper the adoption of agroforestry systems (Camilli et al. 2017). AFINET project acts at EU level in order to direct research results into practice and promote innovative ideas to face challenges and solve practitioners' problems. AFINET proposes an innovative methodology based on the creation of a European Interregional Network, linking different Regional Agroforestry Innovation Networks (RAINs). RAINs represent different climatic, geographical, social and cultural conditions and enclose a balanced representation of the key actors with complementary types of expertise (farmers, policy makers, advisory services, extension services, etc.). The Italian RAIN is focused on the Extra-Virgin Olive Oil (EVOO) value chain, with the main aim to promote agroforestry management of local olive orchards. Olive trees are still managed traditionally, often in marginal sites, with minimal mechanization and relatively low external inputs such as chemical treatments in comparison to other crops. The presence of permanent crops (olive trees) guarantees a partially tree cover reducing hydrogeological risk. Soil management usually keeps natural grassing reducing soil carbon emission and increasing soil fertility (Bateni et al. 2017). Intercropping with cereals and/or fodder legumes and livestock can also be practiced in olive orchards, increasing the complexity of the olive tree multifunctional system. Moreover, olive orchards can be managed as agroforestry systems since they can be intercropped with arable crops (cereals, legumes) and/or combined with livestock (sheep, poultry). The RAIN process, involving local stakeholders, highlighted the main bottlenecks of the EVOO value chain related to communication and dissemination of knowledge, technical and management aspects, market and policy. In order to contrast bottlenecks and exploit opportunities of the olive oil supply chain, the identified innovations are: i) adoption of best practices: testing and experimenting innovative agroforestry systems introducing different crop/animals species and varieties; ii) improve the management of the olive orchards: encouraging and increasing the organic production; iii) valorisation of olive processing residues: identifying and testing innovative products (bio-materials, olive paste as example); iv) arise the awareness among consumers: educating people about the benefits of olive oil consumption, creating networks among stakeholders, improving marketing and commercialization. Creating a Bio-district, defined as a geographical area where farmers, citizens, tourist operators, associations and public authorities enter into an agreement for the sustainable management of local resources, emerged a powerful tool to implement the innovation in the local EVOO value chain.

Hydromorphological features are crucial in structuring habitats for freshwater organisms. The quantification of these variables is often performed through accurate measuring or detailed estimation, but their assessment is not always feasible for river management purposes. Economic and time constraints often lead to difficulty in creating simple summaries of collected data for practical use. The Lentic-lotic River Descriptor (LRD) was developed to identify the character of a river site in terms of local hydraulic conditions. Information about the presence of flow types, channel substrates, in-stream vegetation, organic debris and artificial features is included in its calculation. The main aim of this paper is to investigate whether the lentic-lotic character of a river site, as summarized with the LRD descriptor, is relevant to aquatic invertebrate communities in nearly natural river sites. Invertebrate data were collected with multi-habitat, proportional sampling and hydromorphological information was gained by applying the CARAVAGGIO method (river habitat survey technique) in the field. The dataset was generated from High or Good ecological status river sites located in Mediterranean areas of Italy. Correspondence Analysis was performed to relate the invertebrate community structure to a set of catchment-scale, reach-scale and chemical environmental variables. The results of the multivariate analysis indicate that LRD provides a persuasive explanation of the most important axis of variation in benthic data. This paper also presents the optimal LRD range for a set of invertebrate taxa, accompanied by a short discussion of their potential use in conservation issues.

(Uploaded by Plazi for the Bat Literature Project) The evolutionary history of plant and animal species has been deeply influenced by both climate changes and human actions. Human actions have been particularly heavy during the Anthropocene, when over 250 mammal species became extinct, mostly on islands. Here, we shortly review the existing literature, and test whether the various mammalian orders are all equally prone to extinction risks. We concluded that species belonging to the orders Rodentia, Primates, and Artiodactyla were more prone to become extinct, whereas those belonging to the orders Chiroptera and Carnivora were less. Surprisingly, apparently IUCN red list placed higher conservation concerns for the species belonging to the mammalian orders which are globally least prone to become extinct during the Holocene.

Species distribution models (SDMs) provide realistic scenarios to explain the influence of bioclimatic variables on plant pathogen distribution. Diplodia sapinea is most harmful to plantations of both exotic and native pine species in Italy, causing economic consequences expecially to edible seed production. In this study, we developed maximum entropy models for D. sapinea in Italy to reach the following goals: (i) to carry out the pathogen's first geographical distribution analysis in Italy and determine which ecogeographical variables (EGVs) may influence its outbreaks; (ii) to detect the effect of climate change on the potential occurrence of disease outbreaks by 2050 and 2070. We used Maxent ver. 3.4.0 to develop SDMs. We used six global climate models (BCC-CSM1-1, CCSM4, GISS-E2-R, MIROC5, HadGEM2-ES and MPI-ESM-LR) for two representative concentration pathways (4.5 and 8.5) and two time projections (2050 and 2070) to detect future climate projections of D. sapinea. The most important EGVs influencing outbreaks were land cover, altitude, mean temperature of driest and wettest quarter, precipitation of wettest quarter, precipitation seasonality and minimum temperature of coldest month. The distribution of D. sapinea mostly expanded in central and southern Italy and shifted in altitude upwards on average by ca. 93m a.s.l. Moreover the fungus expanded the range where disease outbreaks may be recorded in response to an increase in the mean temperature of wettest and driest quarter by ca. 1.9 C and 5.8 C, respectively in all climate change scenarios. Precipitation of wettest quarter did not differ between current and any of future models. Under different climate change scenarios D. sapinea's disease outbreaks will be likely to affect larger areas of pine forests in the country, probably causing heavy effects on the dynamics and evolution of these stands or perhaps constraining their survival.

Glacial extent and mass balance are sensitive climate proxies providing solid information on past climatic conditions. However, series of annual mass-balance measurements of more than 60 years are scarce. To our knowledge, this is the first time the latewood density data (MXD) of the Swiss stone pine (Pinus cembra L.) have been used to reconstruct the summer mass balance (B s ) of an Alpine glacier. The MXD-based B s well correlates with a B s reconstruction based on the May to September temperature. Winter precipitation has been used as an independent proxy to infer the winter mass balance and to obtain an annual mass-balance (B n ) estimate dating back to the gla- ciological year 1811/12. The reconstructed MXD/precipitation-based B n well correlates with the data both of the Careser and of other Alpine glaciers measured by the glaciological method. A number of critical issues should be considered in both proxies, including non-linear response of glacial mass balance to temperature, bedrock topography, ice thinning and fragmentation, MXD acquisition and standardization methods, and finally the 'divergence problem' responsible for the recently reduced sensitivity of the dendrochronological data. Nevertheless, our results highlight the possibility of performing MXD-based dendroglaciological reconstructions using this stable and reliable proxy.