Three billion new trees in the EU’s biodiversity strategy: low ambition, but better environmental outcomes?

The EU Biodiversity strategy aims to plant 3 billion trees by 2030, in order to improve ecosystem restoration and biodiversity. Here, we compute the land area that would be required to support this number of newly planted trees by taking account of different tree species and planting regimes across the EU member states. We find that 3 billion trees would require a total land area of between 0.81 and 1.37 Mha (avg. 1.02 Mha). The historic forest expansion in the EU since 2010 was 2.44 Mha, meaning that despite 3 billion trees sounding like a large number this target is considerably lower than historic afforestation rates within the EU, i.e. only 40% of the past trend. Abandoned agricultural land is often proposed as providing capacity for afforestation. We estimate agricultural abandoned land areas from the HIstoric Land Dynamics Assessment+ database using two time thresholds (abandonment since 2009 or 2014) to identify potential areas for tree planting. The area of agricultural abandoned land was 2.6 Mha (potentially accommodating 7.2 billion trees) since 2009 and 0.2 Mha (potentially accommodating 741 million trees) since 2014. Our study highlights that sufficient space could be available to meet the 3 billion tree planting target from abandoned land. However, large-scale afforestation beyond abandoned land could have displacement effects elsewhere in the world because of the embodied deforestation in the import of agricultural crops and livestock. This would negate the expected benefits of EU afforestation. Hence, the EU\u27s relatively low ambition on tree planting may actually be better in terms of avoiding such displacement effects. We suggest that tree planting targets should be set at a level that considers physical ecosystem dynamics as well as socio-economic conditions

U and Th content in the Central Apennines continental crust: a contribution to the determination of the geo-neutrinos flux at LNGS

The regional contribution to the geo-neutrino signal at Gran Sasso National Laboratory (LNGS) was determined based on a detailed geological, geochemical and geophysical study of the region. U and Th abundances of more than 50 samples representative of the main lithotypes belonging to the Mesozoic and Cenozoic sedimentary cover were analyzed. Sedimentary rocks were grouped into four main "Reservoirs" based on similar paleogeographic conditions and mineralogy. Basement rocks do not outcrop in the area. Thus U and Th in the Upper and Lower Crust of Valsugana and Ivrea-Verbano areas were analyzed. Based on geological and geophysical properties, relative abundances of the various reservoirs were calculated and used to obtain the weighted U and Th abundances for each of the three geological layers (Sedimentary Cover, Upper and Lower Crust). Using the available seismic profile as well as the stratigraphic records from a number of exploration wells, a 3D modelling was developed over an area of 2^{\circ}x2^{\circ} down to the Moho depth, for a total volume of about 1.2x10^6 km^3. This model allowed us to determine the volume of the various geological layers and eventually integrate the Th and U contents of the whole crust beneath LNGS. On this base the local contribution to the geo-neutrino flux (S) was calculated and added to the contribution given by the rest of the world, yielding a Refined Reference Model prediction for the geo-neutrino signal in the Borexino detector at LNGS: S(U) = (28.7 \pm 3.9) TNU and S(Th) = (7.5 \pm 1.0) TNU. An excess over the total flux of about 4 TNU was previously obtained by Mantovani et al. (2004) who calculated, based on general worldwide assumptions, a signal of 40.5 TNU. The considerable thickness of the sedimentary rocks, almost predominantly represented by U- and Th- poor carbonatic rocks in the area near LNGS, is responsible for this difference.Comment: 45 pages, 5 figures, 12 tables; accepted for publication in GC

A Cretaceous carbonate delta drift in the Montagna della Maiella, Italy

The Upper Cretaceous (Campanian\u2013Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is compared to newly discovered contourite drifts in the Maldives. Like the drift deposits in the Maldives, the Orfento Formation fills a channel and builds a Miocene delta-shaped and mounded sedimentary body in the basin that is similar in size to the approximately 350 km 2 large coarse-grained bioclastic Miocene delta drifts in the Maldives. The composition of the bioclastic wedge of the Orfento Formation is also exclusively bioclastic debris sourced from the shallow-water areas and reworked clasts of the Orfento Formation itself. In the near mud-free succession, age-diagnostic fossils are sparse. The depositional textures vary from wackestone to float-rudstone and breccia/conglomerates, but rocks with grainstone and rudstone textures are the most common facies. In the channel, lensoid convex-upward breccias, cross-cutting channelized beds and thick grainstone lobes with abundant scours indicate alternating erosion and deposition from a high-energy current. In the basin, the mounded sedimentary body contains lobes with a divergent progradational geometry. The lobes are built by decametre thick composite megabeds consisting of sigmoidal clinoforms that typically have a channelized topset, a grainy foreset and a fine-grained bottomset with abundant irregular angular clasts. Up to 30 m thick channels filled with intraformational breccias and coarse grainstones pinch out downslope between the megabeds. In the distal portion of the wedge, stacked grainstone beds with foresets and reworked intraclasts document continuous sediment reworking and migration. The bioclastic wedge of the Orfento Formation has been variously interpreted as a succession of sea-level controlled slope deposits, a shoaling shoreface complex, or a carbonate tidal delta. Current-controlled delta drifts in the Maldives, however, offer a new interpretation because of their similarity in architecture and composition. These similarities include: (i) a feeder channel opening into the basin; (ii) an excavation moat at the exit of the channel; (iii) an overall mounded geometry with an apex that is in shallower water depth than the source channel; (iv) progradation of stacked lobes; (v) channels that pinch out in a basinward direction; and (vi) smaller channelized intervals that are arranged in a radial pattern. As a result, the Upper Cretaceous (Campanian\u2013Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is here interpreted as a carbonate delta drift

Opportunity for pharmacogenomic testing in patients with cystic fibrosis

Background Patients with cystic fibrosis (CF) are exposed to many drugs in their lifetime and many of these drugs have Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines that are available to guide dosing. Contemporary CF treatments are targeted to specific mutations in the CF transmembrane conductance regulator (CFTR) gene, and thus, require patients to have genetic testing before initiation of modulator therapy. However, aside from CFTR genetic testing, pharmacogenomic testing is not standard of care for CF patients. Aim The aim of this study is to determine the number of non-CFTR modulator medications with CPIC guidelines that are prescribed to patients with CF. Materials & Methods We identified all patients with a diagnosis of CF and queried our hospital electronic medical records (EMR) for all orders, including inpatient and prescriptions, for all drugs or drug classes that have CPIC actionable guidelines for drug–gene pairs that can be used to guide therapy. Results We identified 576 patients with a diagnosis of CF that were treated at our institution during this 16-year period between June 2005 and May 2021. Of these patients, 504 patients (87.5%) received at least one drug that could have been dosed according to CPIC guidelines if pharmacogenomic results would have been available. Conclusions Patients with CF have high utilization of drugs with CPIC guidelines, therefore preemptive pharmacogenomic testing should be considered in CF patients at the time of CFTR genetic testing

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth’s surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The relationships between regional Quaternary uplift, deformation across active normal faults and historical seismicity in the upper plate of subduction zones: The Capo D’Orlando Fault, NE Sicily

In order to investigate deformation within the upper plate of the Calabrian subduction zone we have mapped and modelled a sequence of Late Quaternary palaeoshorelines tectonically-deformed by the Capo D’Orlando normal fault, NE Sicily, which forms part of the actively deforming Calabrian Arc. In addition to the 1908 Messina Strait earthquake (Mw 7.1), this region has experienced damaging earthquakes, possibly on the Capo D’Orlando Fault, however, it is not considered by some to be a potential seismogenic source. Uplifted Quaternary palaeoshorelines are preserved on the hangingwall of the Capo D’Orlando Fault, indicating that hangingwall subsidence is counteracted by regional uplift, likely because of deformation associated with subduction/collision. We attempt to constrain the relationship between regional uplift, crustal extensional processes and historical seismicity, and we quantify both the normal and regional deformation signals. We report uplift variations along the strike of the fault and use a synchronous correlation technique to assign ages to palaeoshorelines, facilitating calculation of uplift rates and the fault throw-rate. Uplift rates in the hangingwall increase from 0.4 mm/yr in the centre of the fault to 0.89 mm/yr beyond its SW fault tip, suggesting 0.5 mm/yr of fault related subsidence, which implies a throw-rate of 0.63 ± 0.02 mm/yr, and significant seismic hazard. Overall, we emphasise that upper plate extension and related vertical motions complicate the process of deriving information on the subduction/collision process, such as coupling and slip distribution on the subduction interface, parameters that are commonly inferred for other subduction zones without considering upper plate deformation

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives