The commonness of rarity: Global and future distribution of rarity across land plants

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

P. 1-15Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe.S

Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems

This is the final version. Available on open access from Wiley via the DOI in this recordData Availability Statement: The data collected for this publication, including aerial images, marker and plot coordinates and dry sample weights, as well as site and survey metadata, are available from the NERC Environmental Information Data Centre . Code for photogrammetric processing and statistical analysis is available at Zenodo Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1–10 ha−1. Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Vývoj mikrostruktury amorfních vrstev Hf–B–Si–C–N s vysokoteplotní odolností po vyžíhání do 1500 °C ve vzduchu

Amorfní povlaky Hf–B–Si–C–N vykazují velmi vysokou vysokoteplotní oxidační odolnost. V této práci je zkoumán vývoj mikrostruktury povlaků Hf7B23Si22C6N40 a Hf6B21Si19C4N47 vyžíhaných do 1500 °C s cílem pochopit jejich vysokou oxidační odolnost. Vyžíhané povlaky vykazují dvouvrstvou strukturu zahrnující původní nadeponovaný materiál s horní zoxidovanou vrstvou. Mikrostruktura zoxidované vrstvy je v obou případech tvořena nanokrystalky HfO2 rozptýlenými v amorfní matrici na bázi SiOx. V případě povlaku Hf7B23Si22C6N40 zůstává spodní vrstva amorfní, zatímco v případě povlaku Hf6B21Si19C4N47 částečně rekrystalizuje a tvoří nanokrystalky HfB2 a HfN, které jsou oddělené fázemi h-Si3N4 a h-BN. Fáze HfB2 a HfN vytváří sendvičovou koherentní nanostrukturu spojenou přes monovrstvu (111)-Hf. Navzdory rozdílnému složení původních povlaků vykazuje rozhraní dvouvrstvé struktury v obou případech podobnou mikrostrukturu s jemným rozmístěním nanokrystalků HfO2, které jsou obklopeny fází SiO2. Vysokoteplotní oxidační odolnost obou povlaků je přisuzována konkrétnímu vývoji mikrostruktury obsahující nanokrystalky HfO2 zabudované v husté matrici na bázi amorfního SiOx a krystalického SiO2 (křemen) na rozhraní dvouvrstvé struktury, které slouží jako bariéra pro difúzi kyslíku a přestup tepla.Recently, amorphous Hf–B–Si–C–N coatings found to demonstrate superior high-temperature oxidation resistance. The microstructure evolution of two coatings, Hf7B23Si22C6N40 and Hf6B21Si19C4N47, annealed to 1500 °C in air is investigated to understand their high oxidation resistance. The annealed coatings develop a two-layered structure comprising of the original as-deposited film followed by an oxidized layer. In both films, the oxidized layer possesses the same microstructure with HfO2 nanoparticles dispersed in an amorphous SiOx-based matrix. The bottom layer in the Hf6B21Si19C4N47 coating remains amorphous after annealing while Hf7B23Si22C6N40 recrystallized partially showing a nanocrystalline structure of HfB2 and HfN nanoparticles separated by h-Si3N4 and h-BN boundaries. The HfB2 and HfN nanostructures form a sandwich structure with a HfB2 strip being atomically coherent to HfN skins via (111)-Hf monolayers. In spite of the different bottom layer structure, the oxidized/bottom layer interface of both films was found to exhibit a similar microstructure with a fine distribution of HfO2 nanoparticles surrounded by SiO2 quartz boundaries. The high-temperature oxidation resistance of both films is attributed to the particular evolving microstructure consisting of HfO2 nanoparticles within a dense SiOx-based matrix and quartz SiO2 in front of the oxidized/bottom layer interface acting as a barrier for oxygen and thermal diffusion

The Spectral Species Concept in Living Color.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing