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While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

AbstractGlobal impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

The conversion of renewable biomasses into biofuels and chemicals represents a strategic way to reduce the use of fossil feedstock, by contributing in switching to a more sustainable society. The use of agro-industrial wastes does not subtract resources destined for food consumption. In addition, waste utilization would result in a reduction of its accumulation, with a consequent decrease of environmental impact and financial losses due to the relevant disposal. In this context, a wide variety of exploitable agricultural resources can be used to support this sustainable growth. However, the characterization represents the first step towards a targeted and proficient exploitation of the chemical and energetic potential of a residual biomass. In this work, some representative residual (Mexican) biomasses were investigated: pepper residues (Hungarian yellow and red variety), coconut shells (Cocos nucifera), flamboyant pods (Delonix regia), seeds of avocado (Persea Americana), palm (Palma de Coroco) and nance (Byrsonima crassifolia) were chemically characterized and the relevant potential applications for the synthesis of biofuels and fine chemicals were specifically evaluated. Lipids, structural carbohydrates, and lignin were specifically valorized in a proficient cascade of technologies, which aim to exploit the correspondent potential, according to the principles of biorefinery and circular economy.

The objectives of this study were to examine the possibility of reducing the fuel consumption and CO2 emissions of harvesters during cut-to-length operations by applying various technical settings to the machine through the machine's own software package. The adjustment of machine settings had an effect on the fuel consumption per unit product (l m3) and can reduce the fuel consumption and CO2 emissions in cut-to-length harvesting operations. The main factor significantly affecting both fuel consumption and productivity was stem size. The study involved three cut-to-length machines operating in thinning with comparable stand environment and silvicultural prescriptions. The novelty of this work is in exploring the fuel saving potential of simple adjustments of machine settings in cut-to-length harvesting machines. Such adjustments have an impact on fuel efficiency and may reduce fuel consumption and CO2 emissions in cut-to-length harvesting operations. This work may result in a reduction of energy consumption and environmental pollution, thereby contributing to cleaner production. This study bridges the gaps between research, development and implementation: it offers practical solutions that may affect manufacturers as well as practitioners and entrepreneurs in the field. The outcome of this study may result in innovative technology development with less impact on the environment.

This study regards the estimate of olive oil pruning biomass. The objective is to increase the knowledge of pruning biomass availability to business purposes. Having recognized the importance of both uncertainty and dynamics, we first estimate the probability distribution of the yields in a small farms sample and then determine the related expected value of pruning olive oil yield. We use these estimates to draw microscenarios illustrating the dynamics of the pruning biomass yields based on the enlargement of the number of trees per hectare (intensification) and of the olive oil crop area (specialization). The results show how intensification and specialization determine a mosaic pattern of changes in the pruning yields probabilities. The resulting estimate of the pruning biomass availability is similar to those provided in literature for the Italian case. Across the Italian regions, the difference between the expected pruning yield and a theoretical yield index decreases as the specialization increases. Two validity boundaries of the model are presented.The study concludes noting that, unless they are associated, intensification and specification not systematically augment the average olive oil pruning biomass yield in a territory and that the yields increase appears to be more probable beyond intensification large values.

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.

Under arid conditions, where water availability is the limiting factor for plant survival, water balance models can be used to explain vegetation dynamics. [...]