21 research outputs found

    A Trait-based approach for forest ecology and management: tools for theoretical and applied ecology

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    Global change threats affecting forests require better understanding of mechanisms driving species environmental responses, but also species effects on ecosystems, to identify optimal management strategies for safeguarding the services they provide. Thus, this thesis serves on trait ecology and tools as Species Distribution Modelling, Remote Sensing, and Climate Change Modelling to explore ecological concepts that prove useful for determining specific management actions. Specifically we hypothesised about three main aspects: 1) the capacity of several traits to explain the characteristics of species niche in the Mediterranean; 2) the influence of trait diversity on the temporal stability of forest productivity in Temperate and Boreal zones; and 3) current and future effects of climate on the mean traits of Mediterranean forest communities. Forest inventories from Spain and Quebec (eastern Canada) were used to obtain species distribution and community composition whereas species traits values were retrieved from the literature. Main results showed that: 1) Specific Leaf Area (SLA) can be used to accurately represent species aridity limits in the Mediterranean; 2) trait diversity provides stability in Temperate forests; and 3) climate change may reduce SLA values of forest communities suggesting notable impacts on ecosystem functioning in the Mediterranean. The thesis suggests that management strategies should be based on trait ecology in order to best adapt to global change

    Co-design of sectoral climate services based on seasonal prediction information in the Mediterranean

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    We present in this contribution the varied experiences gathered in the co-design of a sectoral climate services collection, developed in the framework of the MEDSCOPE project, which have in common the application of seasonal predictions for the Mediterranean geographical and climatic region. Although the region is affected by low seasonal predictability limiting the skill of seasonal forecasting systems, which historically has hindered the development of downstream services, the project was originally conceived to exploit windows of opportunity with enhanced skill for developing and evaluating climate services in various sectors with high societal impact in the region: renewable energy, hydrology, and agriculture and forestry. The project also served as the scientific branch of the WMO-led Mediterranean Climate Outlook Forum (MedCOF) that had as objective -among others- partnership strengthening on climate services between providers and users within the Mediterranean region. The diversity of the MEDSCOPE experiences in co-designing shows the wide range of involvement and engagement of users in this process across the Mediterranean region, which benefits from the existing solid and organized MedCOF community of climate services providers and users. A common issue among the services described here -and also among other prototypes developed in the project- was related with the communication of forecasts uncertainty and skill for efficiently informing decision-making in practice. All MEDSCOPE project prototypes make use of an internally developed software package containing process-based methods for synthesising seasonal forecast data, as well as basic and advanced tools for obtaining tailored products. Another challenge assumed by the project refers to the demonstration of the economic, social, and environmental value of predictions provided by these MEDSCOPE prototypes.The work described in this paper has received funding from the MEDSCOPE project co-funded by the European Commission as part of ERA4CS, an ERA-NET initiated by JPI Climate, grant agreement 690462

    Towards a Muon Collider

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    A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.Comment: 118 pages, 103 figure

    Towards a muon collider

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    A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work

    Erratum:Towards a muon collider

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    Towards a muon collider

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    A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work

    Erratum: Towards a muon collider

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    The original online version of this article was revised: The additional reference [139] has been added. Tao Han’s ORICD ID has been incorrectly assigned to Chengcheng Han and Chengcheng Han’s ORCID ID to Tao Han. Yang Ma’s ORCID ID has been incorrectly assigned to Lianliang Ma, and Lianliang Ma’s ORCID ID to Yang Ma. The original article has been corrected

    Predicting and Mapping Potential Fire Severity for Risk Analysis at Regional Level Using Google Earth Engine

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    Despite being a natural ecological process, wildfires are dramatic events that, accelerated by global change, could negatively affect ecosystem services depending on their severity level. However, because of data processing constraints, fire severity has been mostly neglected in risk analysis (especially at regional levels). Indeed, previous studies addressing fire severity focused mainly on analyzing single fire events, preventing the projection of the results over large areas. Although, building and projecting robust models of fire severity to integrate into risk analysis is of main importance to best anticipate decisions. Here, taking advantage of free data-processing platforms, such as Google Earth Engine, we use more than 1000 fire records from Western Italy and Southern France in the years 2004–2017, to assess the performance of random forest models predicting the relativized delta normalized burn ratio (rdNBR) used as proxy of fire severity. Furthermore, we explore the explanatory capacity and meaning of several variables related to topography, vegetation, and burning conditions. To show the potentialities of this approach for operational purposes, we projected the model for one of the regions (Sardinia) within the study area. Results showed that machine learning algorithms explain up to 75% of the variability in rdNBR, with variables related to vegetation amount and topography being the most important. These results highlight the potential usefulness of these tools for mapping fire severity in risk assessments

    Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

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    International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora
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