Classification of grassland successional stages using airborne hyperspectral imagery

Plant communities differ in their species composition, and, thus, also in their functional trait composition, at different stages in the succession from arable fields to grazed grassland. We examine whether aerial hyperspectral (414–2501 nm) remote sensing can be used to discriminate between grazed vegetation belonging to different grassland successional stages. Vascular plant species were recorded in 104.1 m2 plots on the island of Öland (Sweden) and the functional properties of the plant species recorded in the plots were characterized in terms of the ground-cover of grasses, specific leaf area and Ellenberg indicator values. Plots were assigned to three different grassland age-classes, representing 5–15, 16–50 and >50 years of grazing management. Partial least squares discriminant analysis models were used to compare classifications based on aerial hyperspectral data with the age-class classification. The remote sensing data successfully classified the plots into age-classes: the overall classification accuracy was higher for a model based on a pre-selected set of wavebands (85%, Kappa statistic value = 0.77) than one using the full set of wavebands (77%, Kappa statistic value = 0.65). Our results show that nutrient availability and grass cover differences between grassland age-classes are detectable by spectral imaging. These techniques may potentially be used for mapping the spatial distribution of grassland habitats at different successional stages

Development and validation of an automated liquid-liquid extraction GC/MS method for the determination of THC, 11-OH-THC, and free THC-carboxylic acid (THC-COOH) from blood serum

The analysis of Δ9-tetrahydrocannabinol (THC) and its metabolites 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) from blood serum is a routine task in forensic toxicology laboratories. For examination of consumption habits, the concentration of the phase I metabolite THC-COOH is used. Recommendations for interpretation of analysis values in medical-psychological assessments (regranting of driver’s licenses, Germany) include threshold values for the free, unconjugated THC-COOH. Using a fully automated two-step liquid-liquid extraction, THC, 11-OH-THC, and free, unconjugated THC-COOH were extracted from blood serum, silylated with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and analyzed by GC/MS. The automation was carried out by an x-y-z sample robot equipped with modules for shaking, centrifugation, and solvent evaporation. This method was based on a previously developed manual sample preparation method. Validation guidelines of the Society of Toxicological and Forensic Chemistry (GTFCh) were fulfilled for both methods, at which the focus of this article is the automated one. Limits of detection and quantification for THC were 0.3 and 0.6 μg/L, for 11-OH-THC were 0.1 and 0.8 μg/L, and for THC-COOH were 0.3 and 1.1 μg/L, when extracting only 0.5 mL of blood serum. Therefore, the required limit of quantification for THC of 1 μg/L in driving under the influence of cannabis cases in Germany (and other countries) can be reached and the method can be employed in that context. Real and external control samples were analyzed, and a round robin test was passed successfully. To date, the method is employed in the Institute of Legal Medicine in Giessen, Germany, in daily routine. Automation helps in avoiding errors during sample preparation and reduces the workload of the laboratory personnel. Due to its flexibility, the analysis system can be employed for other liquid-liquid extractions as well. To the best of our knowledge, this is the first publication on a comprehensively automated classical liquid-liquid extraction workflow in the field of forensic toxicological analysis

Tree species traits but not diversity mitigate stem breakage in a subtropical forest following a rare and extreme ice storm

Peer reviewedPublisher PD

Measurement of Biodiversity (MoB): A method to separate the scale-dependent effects of species abundance distribution, density, and aggregation on diversity change

Little consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance and temperature may affect species richness and other aspects of biodiversity. Part of the confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale. We provide an approach for the measurement of biodiversity that decomposes changes in species rarefaction curves into proximate components attributed to: (a) the species abundance distribution, (b) density of individuals and (c) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample- and individual-based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change. We tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new r package (mobr). The metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale toward a dissection of the proximate components that determine species richness across scales

Mental health in Germany in the first weeks of the Russo-Ukrainian war

Background In the connected world, although societies are not directly involved in a military conflict, they are exposed to media reports of violence. Aims We assessed the effects of such exposures on mental health in Germany during the military conflict in Ukraine. Method We used the German population-based cohort for digital health research, DigiHero, launching a survey on the eighth day of the Russo-Ukrainian war. Of the 27 509 cohort participants from the general population, 19 444 (70.7%) responded within 17 days. We measured mental health and fear of the impact of war compared with other fears (natural disasters or health-related). Results In a subsample of 4441 participants assessed twice, anxiety in the population (measured by the Generalised Anxiety Disorder-7 screener) was higher in the first weeks of war than during the strongest COVID-19 restrictions. Anxiety was elevated across the whole age spectrum, and the mean was above the cut-off for mild anxiety. Over 95% of participants expressed various degrees of fear of the impact of war, whereas the percentage for other investigated fears was 0.47–0.82. A one-point difference in the fear of the impact of war was associated with a 2.5 point (95% CI 2.42–2.58) increase in anxiety (11.9% of the maximum anxiety score). For emotional distress, the increase was 0.67 points (0.66–0.68) (16.75% of the maximum score). Conclusions The population in Germany reacted to the Russo-Ukrainian war with substantial distress, exceeding reactions during the strongest restrictions in the COVID-19 pandemic. Fear of the impact of war was associated with worse mental health

A global database for metacommunity ecology, integrating species, traits, environment and space

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology

Anxiety, depressive symptoms, and distress over the course of the war in Ukraine in three federal states in Germany

IntroductionThe Russian invasion of Ukraine and the resulting consequences are in the center of political discussions, media, and likely individual thinking of the population in Germany. Yet, the impact of this prolonged exposure on mental health is not known hitherto.MethodsUsing the population based cohort study DigiHero from three federal states (Saxony-Anhalt, Saxony, and Bavaria), we assessed anxiety levels (GAD-7), depressive symptoms (PHQ-9), and distress (modified PDI) in the first weeks of war and 6 months later.ResultsOf those 19,432, who responded in the first weeks of war, 13,934 (71.1%) responded also 6 months later. While anxiety and emotional distress decreased during the 6 months, their average scores were still elevated, and a substantial fraction of respondents displayed clinically relevant sequelae. Persons from low-income households were especially affected, specifically by fears related to the personal financial situation. Those who reacted with a particularly strong fear in the beginning of war were more likely to have persistent clinically relevant symptoms of depression and anxiety also 6 months later.DiscussionThe Russian invasion of Ukraine is accompanied by continuing impairment of mental health in the German population. Fears surrounding the personal financial situation are a strong determinant

Plant community assembly and biodiversity: a spatio-temporal perspective

Biodiversity, the variety of life at all organisational levels from genes to ecosystems, affects ecosystem processes and therefore the goods and services ecosystems provide. More research is needed to provide new insights into biodiversity changes and the processes that drive these changes, in order to formulate effective policy and conservation measures to stop the ongoing biodiversity loss. In this thesis, I focus on spatial and temporal changes in different aspects of plant biodiversity and examine the driving forces that generate and maintain observed biodiversity patterns. Multiple facets of biodiversity (taxonomic, phylogenetic, functional) were characterized in semi-natural grasslands (in plots of 0.5 × 0.5 and 2 × 2 m, and whole grassland polygons). The extent to which the present-day and historical characteristics of the sites and their surrounding landscape explain the current diversity patterns was quantified. Temporal changes in the multiple facets of diversity, and assembly processes that drive these changes, were investigated along a more than 300 year long chronosequence representing an arable to semi-natural grassland succession. Both grassland plant species richness and functional trait diversity in grassland sites were to a large extent explained by the land use history of the sites and the availability of grassland habitat in the surrounding historical landscape. It appears that not only is there a delayed loss of species diversity in response to landscape fragmentation ("extinction debt") but that there is also a delayed decline of functional diversity in response to ongoing habitat destruction (i.e. a "functioning debt") that will potentially generate a time lag in the changes in ecosystem attributes. Quantification of the linkages between the distribution and diversity of dispersal and persistence traits and current and historical properties of the grassland sites and their surrounding landscape revealed that long-distance dispersal potential as well as the diversity of different dispersal and persistence strategies within present-day grassland communities was mainly determined by the local management history and landscape history. Long-distance dispersal by wind and animals no longer appears to be contributing to the colonization of the remaining fragments of habitat within the increasingly fragmented modern landscape, and long-term persistent species are likely to dominate the grassland communities in the future. Whereas many long-distance dispersed species can still persist locally in the presence of grazing disturbance, grazing management may also promote the diversity of different dispersal and persistence strategies, but only in sites that were well connected to grassland areas in the past. The extent to which grassland management strategies can maintain a high diversity of dispersal and persistence strategies, and thereby the capacity of a plant community to buffer environmental change, will depend on the context of the site within the historical surrounding landscape. Comparative analysis of taxonomic, phylogenetic and functional diversity at different stages of arable-to-semi-natural grassland succession demonstrated that community assembly during secondary grassland succession was deterministic with respect to species traits, suggesting that it may be possible to predict changes in biodiversity, and associated alterations in ecosystems functioning in future environments, on the basis of species functional traits. Taxonomic, phylogenetic and functional diversity showed contrasting patterns of change over time. Short-term grazing management (5-50 years) promoted species richness, but did not enhance phylogenetic or functional diversity. Only long-term grazing management, over more than 270 years, promoted phylogenetic and functional diversity without further increases in species richness. I conclude that (a) multiple facets of biodiversity should be considered in order to more realistically assess the full dimensions of biodiversity loss resulting from human-driven environmental changes, (b) history is a major determinant of biodiversity, and (c) the simultaneous consideration of multiple facets of biodiversity can provide new insights into the processes that shape communities