Model-Based Estimates of Right Whale Habitat Use in the Gulf of Maine

Balancing human uses of the marine environment with the recovery of protected species requires accurate information on when and where species of interest are likely to be present. Here, we describe a system that can produce useful estimates of right whale Eubalaena glacialis presence and abundance on their feeding grounds in the Gulf of Maine. The foundation of our system is a coupled physical-biological model of the copepod Calan us finmarchicus, the preferred prey of right whales. From the modeled prey densities, we can estimate when whales will appear in the Great South Channel feeding ground. Based on our experience with the system, we consider how the relationship between right whales and copepods changes across spatial scales. The scale-dependent relationship between whales and copepods provides insight into how to improve future estimates of the distribution of right whales and other pelagic predators.

More Than Charged Base Loss — Revisiting the Fragmentation of Highly Charged Oligonucleotides

Tandem mass spectrometry is a well-established analytical tool for rapid and reliable characterization of oligonucleotides (ONs) and their gas-phase dissociation channels. The fragmentation mechanisms of native and modified nucleic acids upon different mass spectrometric activation techniques have been studied extensively, resulting in a comprehensive catalogue of backbone fragments. In this study, the fragmentation behavior of highly charged oligodeoxynucleotides (ODNs) comprising up to 15 nucleobases was investigated. It was found that ODNs exhibiting a charge level (ratio of the actual to the total possible charge) of 100% follow significantly altered dissociation pathways compared with low or medium charge levels if a terminal pyrimidine base (3' or 5') is present. The corresponding product ion spectra gave evidence for the extensive loss of a cyanate anion (NCO–), which frequently coincided with the abstraction of water from the 3'- and 5'-end in the presence of a 3'- and 5'-terminal pyrimidine nucleobase, respectively. Subsequent fragmentation of the MNCO– ion by MS3 revealed a so far unreported consecutive excision of a metaphosphate (PO3–)-ion for the investigated sequences. Introduction of a phosphorothioate group allowed pinpointing of PO3– loss to the ultimate phosphate group. Several dissociation mechanisms for the release of NCO– and a metaphosphate ion were proposed and the validity of each mechanism was evaluated by the analysis of backbone- or sugar modified ONs.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Sustainability principles put into practice: case studies of network analysis in Swiss climate change adaptation

Climate adaptation policies increasingly incorporate sustainability principles into their design and implementation. Since successful adaptation by means of adaptive capacity is recognized as being dependent upon progress toward sustainable development, policy design is increasingly characterized by the inclusion of state and non-state actors (horizontal actor integration), cross-sectoral collaboration, and inter-generational planning perspectives. Comparing four case studies in Swiss mountain regions, three located in the Upper Rhone region and one case from western Switzerland, we investigate how sustainability is put into practice. We argue that collaboration networks and sustainability perceptions matter when assessing the implementation of sustainability in local climate change adaptation. In other words, we suggest that adaptation is successful where sustainability perceptions translate into cross-sectoral integration and collaboration on the ground. Data about perceptions and network relations are assessed through surveys and treated via cluster and social network analysis.

Conservation of threatened habitat types under future climate change – Lessons from plant-distribution models and current extinction trends in southern Germany

A higher risk of future range losses as a result of climate change is expected to be one of the main drivers of extinction trends in vascular plants occurring in habitat types of high conservation value. Nevertheless, the impact of the climate changes of the last 60 years on the current distribution and extinction patterns of plants is still largely unclear. We applied species distribution models to study the impact of environmental variables (climate, soil conditions, land cover, topography), on the current distribution of 18 vascular plant species characteristic of three threatened habitat types in southern Germany: (i) xero-thermophilous vegetation, (ii) mesophilous mountain grasslands (mountain hay meadows and matgrass communities), and (iii) wetland habitats (bogs, fens, and wet meadows). Climate and soil variables were the most important variables affecting plant distributions at a spatial level of 10 × 10 km. Extinction trends in our study area revealed that plant species which occur in wetland habitats faced higher extinction risks than those in xero-thermophilous vegetation, with the risk for species in mesophilous mountain grasslands being intermediary. For three plant species characteristic either of mesophilous mountain grasslands or wetland habitats we showed exemplarily that extinctions from 1950 to the present day have occurred at the edge of the species’ current climatic niche, indicating that climate change has likely been the main driver of extinction. This is largely consistent with current extinction trends reported in other studies. Our study indicates that the analysis of past extinctions is an appropriate means to assess the impact of climate change on species and that vulnerability to climate change is both species- and habitat-specific.

The evolution of scarab beetles tracks the sequential rise of angiosperms and mammals

Extant terrestrial biodiversity arguably is driven by the evolutionary success of angiosperm plants, but the evolutionary mechanisms and timescales of angiosperm-dependent radiations remain poorly understood. The Scarabaeoidea is a diverse lineage of predominantly plant- and dung-feeding beetles. Here, we present a phylogenetic analysis of Scarabaeoidea based on four DNA markers for a taxonomically comprehensive set of specimens and link it to recently described fossil evidence. The phylogeny strongly supports multiple origins of coprophagy, phytophagy and anthophagy. The ingroup-based fossil calibration of the tree widely confirmed a Jurassic origin of the Scarabaeoidea crown group. The crown groups of phytophagous lineages began to radiate first (Pleurostict scarabs: 108 Ma; Glaphyridae between 101 Ma), followed by the later diversification of coprophagous lineages (crown-group age Scarabaeinae: 76 Ma; Aphodiinae: 50 Ma). Pollen feeding arose even later, at maximally 62 Ma in the oldest anthophagous lineage. The clear time lag between the origins of herbivores and coprophages suggests an evolutionary path driven by the angiosperms that first favoured the herbivore fauna (mammals and insects) followed by the secondary radiation of the dung feeders. This finding makes it less likely that extant dung beetle lineages initially fed on dinosaur excrements, as often hypothesized.

GROMOS-C, a novel ground-based microwave radiometer for ozone measurement campaigns

Stratospheric ozone is of major interest as it absorbs most harmful UV radiation from the sun, allowing life on Earth. Ground-based microwave remote sensing is the only method that allows for the measurement of ozone profiles up to the mesopause, over 24 hours and under different weather conditions with high time resolution. In this paper a novel ground-based microwave radiometer is presented. It is called GROMOS-C (GRound based Ozone MOnitoring System for Campaigns), and it has been designed to measure the vertical profile of ozone distribution in the middle atmosphere by observing ozone emission spectra at a frequency of 110.836 GHz. The instrument is designed in a compact way which makes it transportable and suitable for outdoor use in campaigns, an advantageous feature that is lacking in present day ozone radiometers. It is operated through remote control. GROMOS-C is a total power radiometer which uses a pre-amplified heterodyne receiver, and a digital fast Fourier transform spectrometer for the spectral analysis. Among its main new features, the incorporation of different calibration loads stands out; this includes a noise diode and a new type of blackbody target specifically designed for this instrument, based on Peltier elements. The calibration scheme does not depend on the use of liquid nitrogen; therefore GROMOS-C can be operated at remote places with no maintenance requirements. In addition, the instrument can be switched in frequency to observe the CO line at 115 GHz. A description of the main characteristics of GROMOS-C is included in this paper, as well as the results of a first campaign at the High Altitude Research Station at Jungfraujoch (HFSJ), Switzerland. The validation is performed by comparison of the retrieved profiles against equivalent profiles from MLS (Microwave Limb Sounding) satellite data, ECMWF (European Centre for Medium-Range Weather Forecast) model data, as well as our nearby NDACC (Network for the Detection of Atmospheric Composition Change) ozone radiometer measuring at Bern.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

First continuous ground-based observations of long period oscillations in strato-/mesospheric wind profiles

Direct measurements of middle-atmospheric wind oscillations with periods between 5 and 50 days in the altitude range between mid-stratosphere (5 hPa) and upper mesosphere (0.02 hPa) have been made using a novel ground-based Doppler wind radiometer. The oscillations were not inferred from measurements of tracers, as the radiometer offers the unique capability of near-continuous horizontal wind profile measurements. Observations from four campaigns at high, mid and low latitudes with an average duration of 10 months have been analyzed. The dominant oscillation has mostly been found to lie in the extra-long period range (20–40 days), while the well-known atmospheric normal modes around 5, 10 and 16 days have also been observed. Comparisons of our results with ECMWF operational analysis model data revealed remarkably good agreement below 0.3 hPa but discrepancies above.

Tandem Mass Spectrometric Analysis of Metallocene Adducts with Short Oligonucleotides

Metallocene dichlorides constitute a remarkable class of antineoplastic agents that are highly effective against several cancer cell lines. They were shown to accumulate in the DNA-rich region, which suggests DNA as the primary target. These compounds exhibit two cyclopentadienyl ligands and two labile halide ligands, resulting in a bent sandwich structure. The cis-dihalide motif is structurally related to the cis-chloro configuration of cisplatin and similar modes of action can thus be assumed. Cisplatin binds to two neighboring guanine nucleobases in DNA and consequently, distorts the double-helix, thereby inhibiting DNA replication and transcription. Platinum is classified as a soft Lewis acid and binds preferentially to the nitrogen atoms within the nucleobases. The metallocene dichlorides investigated in this study comprise the metal centers Ti, V, Nb, Mo, Hf, and W, which are classified as hard or intermediate Lewis acids, and thus, favor binding to the phosphate oxygen. Although several studies reported adduct formation of metallocene dichlorides with nucleic acids, substantial information about the adduct composition, the binding pattern, and the nucleobase selectivity has not been provided yet. ESI-MS analyses gave evidence for the formation of metallocene adducts (M = Ti, V, Mo, and W) with single-stranded DNA homologues at pH 7. No adducts were formed with Nb and Hf at neutral pH, albeit adducts with Nb were observed at a low pH. MS2 data revealed considerable differences of the adduct compositions. The product ion spectra of DNA adducts with hard Lewis acids (Ti, V) gave evidence for the loss of metallocene ligands and only moderate backbone fragmentation was observed. By contrast, adducts with intermediate Lewis acids (Mo, W) retained the hydroxy ligands. Preliminary results are in good agreement with the Pearson concept and DFT calculations. Since the metallodrugs were not lost upon CID, the nucleobase selectivity, stoichiometry, and binding patterns can be elucidated by means of tandem mass spectrometry.

Species interactions and random dispersal rather than habitat filtering drive community assembly during early plant succession

Theory on plant succession predicts a temporal increase in the complexity of spatial community structure and of competitive interactions: initially random occurrences of early colonising species shift towards spatially and competitively structured plant associations in later successional stages. Here we use long-term data on early plant succession in a German post mining area to disentangle the importance of random colonisation, habitat filtering, and competition on the temporal and spatial development of plant community structure. We used species co-occurrence analysis and a recently developed method for assessing competitive strength and hierarchies (transitive versus intransitive competitive orders) in multispecies communities. We found that species turnover decreased through time within interaction neighbourhoods, but increased through time outside interaction neighbourhoods. Successional change did not lead to modular community structure. After accounting for species richness effects, the strength of competitive interactions and the proportion of transitive competitive hierarchies increased through time. Although effects of habitat filtering were weak, random colonization and subsequent competitive interactions had strong effects on community structure. Because competitive strength and transitivity were poorly correlated with soil characteristics, there was little evidence for context dependent competitive strength associated with intransitive competitive hierarchies.

Picea abies in Europe: distribution, habitat, usage and threats

Among the coniferous species, Norway spruce (Picea abies (L.) Karst.) is one of the most important trees in Europe both for economic and ecological aspects, with a long tradition of cultivation. It can be a big tree, reaching 50-60 m in height with a straight and regular trunk, particularly used for timber constructions, pulpwood for paper and furniture. This widespread species dominates the Boreal forests in Northern Europe and the subalpine areas of the Alps and Carpathian Mountains. Thanks to its high performances in different site conditions, it can also be found outside its natural distribution on lower elevations in more temperate forests. Norway spruce has been massively planted up to its niche limits, where it is particularly susceptible to heat and drought, due to its shallow root system. For this reason it is expected to be severely affected under global warming conditions. Disturbed and weakened plants can be easily attacked by rot fungi such as Heterobasidion annosum and Armillaria, or by the bark beetles Ips typographus, one of the most destructive spruce forest pests.

Improving the Quality of Life of spousal caregivers of stroke survivors: A cost effectiveness analysis

Back ground and Purpose. There is a growing consensus among health care researchers that Quality of Life (QoL) is an important outcome and, within the field of family caregiving, cost effectiveness research is needed to determine which programs have the greatest benefit for family members. This study uses a multidimensional approach to measure the cost effectiveness of a multicomponent intervention designed to improve the quality of life of spousal caregivers of stroke survivors. Methods. The CAReS study (Committed to Assisting with Recovery after Stroke) was a 5-year prospective, longitudinal intervention study for 159 stroke survivors and their spousal caregivers upon discharge of the stroke survivor from inpatient rehabilitation to their home. CAReS cost data were analyzed to determine the incremental cost of the intervention per caregiver. The mean values of the quality-of-life predictor variables of the intervention group of caregivers were compared to the mean values of usual care groups found in the literature. Significant differences were then divided into the cost of the intervention per caregiver to calculate the incremental cost effectiveness ratio for each predictor variable. Results. The cost of the intervention per caregiver was approximately $2,500. Statistically significant differences were found between the mean scores for the Perceived Stress and Satisfaction with Life scales. Statistically significant differences were not found between the mean scores for the Self Reported Health Status, Mutuality, and Preparedness scales. Conclusions. This study provides a prototype cost effectiveness analysis on which researchers can build. Using a multidimensional approach to measure QoL, as used in this analysis, incorporates both the subjective and objective components of QoL. Some of the QoL predictor variable scores were significantly different between the intervention and comparison groups, indicating a significant impact of the intervention. The estimated cost of the impact was also examined. In future studies, a scale that takes into account both the dimensions and the weighting each person places on the dimensions of QoL should be used to provide a single QoL score per participant. With participant level cost and outcome data, uncertainty around each cost-effectiveness ratio can be calculated using the bias-corrected percentile bootstrapping method and plotted to calculate the cost-effectiveness acceptability curves.^

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.