Inefficient or just different? Effects of heterogeneity on bank efficiency scores

In this paper, we show the importance of accounting for heterogeneity among sample firms in stochastic frontier analysis. For a fairly homogenous sample of German savings and cooperative banks, we analyze how alternative theoretical assumptions regarding the nature of heterogeneity can be modeled and the extent to which the respective empirical specifications affect estimated efficiency levels and rankings. We find that the level of efficiency scores is affected in the case of both cost and profitmodels. On the cost side especially, level and rank correlations show that different specifications identify different banks as being best or worst performers. Our main conclusion is that efficiency studies in general and bank efficiency studies in particular should account for heterogeneity across sample firms. Especially when efficiency measures are employed for policy purposes, a careful choice of models and transparency regarding maximization methods are essential to be able to make inferences about managerial behavior. --Heterogeneity,X-efficiency,benchmarking,bank production

Spatial Modeling of Local-Scale Biogenic and Anthropogenic Carbon Dioxide Emissions in Helsinki

There is a growing need to simulate the effect of urban planning on both local climate and greenhouse gas emissions. Here, a new urban surface carbon dioxide (CO2) flux module for the Surface Urban Energy and Water Balance Scheme is described and evaluated using eddy covariance observations at two sites in Helsinki in 2012. The spatial variability and magnitude of local-scale anthropogenic and biogenic CO2 flux components at high spatial (250 m x 250 m) and temporal (hourly) resolution are examined by combining high-resolution (down to 2 m) airborne lidar-derived land use data and mobility data to account for people's movement. Urban effects are included in the biogenic components parameterized using urban eddy covariance and chamber observations. Surface Urban Energy and Water Balance Scheme reproduces the seasonal and diurnal variability of the CO2 flux well. Annual totals deviate 3% from observations in the city center and 2% in a suburban location. In the latter, traffic is the dominant CO2 source but summertime vegetation partly offsets traffic-related emissions. In the city center, emissions from traffic and human metabolism dominate and the vegetation effect is minor due to the low proportion of vegetation surface cover (22%). Within central Helsinki, human metabolism accounts for 39% of the net local-scale emissions and together with road traffic is to a large extent responsible for the spatial variability of the emissions. Annually, the biogenic emissions and sinks are in near balance and thus the effect of vegetation on the carbon balance is small in this high-latitude city.Peer reviewe

An artificial intelligence approach to remotely assess pale lichen biomass

Although generally given little attention in vegetation studies, ground-dwelling (terricolous) lichens are major contributors to overall carbon and nitrogen cycling, albedo, biodiversity and biomass in many high-latitude ecosystems. Changes in biomass of mat-forming pale lichens have the potential to affect vegetation, fauna, climate and human activities including reindeer husbandry. Lichens have a complex spectral signature and terricolous lichens have limited growth height, often growing in mixtures with taller vegetation. This has, so far, prevented the development of remote sensing techniques to accurately assess lichen biomass, which would be a powerful tool in ecosystem and ecological research and rangeland management. We present a Landsat based remote sensing model developed using deep neural networks, trained with 8914 field records of lichen volume collected for > 20 years. In contrast to earlier proposed machine learning and regression methods for lichens, our model exploited the ability of neural networks to handle mixed spatial resolution input. We trained candidate models using input of 1 x 1 (30 x 30 m) and 3 x 3 Landsat pixels based on 7 reflective bands and 3 indices, combined with a 10 m spatial resolution digital elevation model. We normalised elevation data locally for each plot to remove the region-specific variation, while maintaining informative local variation in topography. The final model predicted lichen volume in an evaluation set (n = 159) reaching an R2 of 0.57. NDVI and elevation were the most important predictors, followed by the green band. Even with moderate tree cover density, the model was efficient, offering a considerable improvement compared to earlier methods based on specific reflectance. The model was in principle trained on data from Scandinavia, but when applied to sites in North America and Russia, the predictions of the model corresponded well with our visual interpretations of lichen abundance. We also accurately quantified a recent historic (35 years) change in lichen abundance in northern Norway. This new method enables further spatial and temporal studies of variation and changes in lichen biomass related to multiple research questions as well as rangeland management and economic and cultural ecosystem services. Combined with information on changes in drivers such as climate, land use and management, and air pollution, our model can be used to provide accurate estimates of ecosystem changes and to improve vegetation-climate models by including pale lichens.Peer reviewe

Implementation of symptom protocols for nurses providing telephone-based cancer symptom management: a comparative case study

Background: The pan-Canadian Oncology Symptom Triage and Remote Support (COSTaRS) team developed 13 evidence-informed protocols for symptom management. Aim: To build an effective and sustainable approach for implementing the COSTaRS protocols for nurses providing telephone-based symptom support to cancer patients. Methods: A comparative case study was guided by the Knowledge to Action Framework. Three cases were created for three Canadian oncology programs that have nurses providing telephone support. Teams of researchers and knowledge users: (a) assessed barriers and facilitators influencing protocol use, (b) adapted protocols for local use, (c) intervened to address barriers, (d) monitored use, and (e) assessed barriers and facilitators influencing sustained use. Analysis was within and across cases. Results: At baseline, >85% nurses rated protocols positively but barriers were identified (64-80% needed training). Patients and families identified similar barriers and thought protocols would enhance consistency among nurses teaching self-management. Twenty-two COSTaRS workshops reached 85% to 97% of targeted nurses (N = 119). Nurses felt more confident with symptom management and using the COSTaRS protocols (p < .01). Protocol adaptations addressed barriers (e.g., health records approval, creating pocket versions, distributing with telephone messages). Chart audits revealed that protocols used were documented for 11% to 47% of patient calls. Sustained use requires organizational alignment and ongoing leadership support. Linking Evidence to Action: Protocol uptake was similar to trials that have evaluated tailored interventions to improve professional practice by overcoming identified barriers. Collaborating with knowledge users facilitated interpretation of findings, aided protocol adaptation, and supported implementation. Protocol implementation in nursing requires a tailored approach. A multifaceted intervention approach increased nurses' use of evidence-informed protocols during telephone calls with patients about symptoms. Training and other interventions improved nurses' confidence with using COSTaRS protocols and their uptake was evident in some documented telephone calls. Protocols could be adapted for use by patients and nurses globally.Dawn Stacey, Esther Green, Barbara Ballantyne, Joy Tarasuk, Myriam Skrutkowski, Meg Carley, Kim Chapman, Craig Kuziemsky, Erin Kolari, Brenda Sabo, Andréanne Saucier, Tara Shaw, Lucie Tardif, Tracy Truant, Greta G. Cummings, Doris Howel

Understanding Crowd-Powered Search Groups: A Social Network Perspective

Background: Crowd-powered search is a new form of search and problem solving scheme that involves collaboration among a potentially large number of voluntary Web users. Human flesh search (HFS), a particular form of crowd-powered search originated in China, has seen tremendous growth since its inception in 2001. HFS presents a valuable test-bed for scientists to validate existing and new theories in social computing, sociology, behavioral sciences, and so forth. Methodology: In this research, we construct an aggregated HFS group, consisting of the participants and their relationships in a comprehensive set of identified HFS episodes. We study the topological properties and the evolution of the aggregated network and different sub-groups in the network. We also identify the key HFS participants according to a variety of measures. Conclusions: We found that, as compared with other online social networks, HFS participant network shares the power-law degree distribution and small-world property, but with a looser and more distributed organizational structure, leading to the diversity, decentralization, and independence of HFS participants. In addition, the HFS group has been becoming increasingly decentralized. The comparisons of different HFS sub-groups reveal that HFS participants collaborated more often when they conducted the searches in local platforms or the searches requiring a certain level of professional knowledge background. On the contrary, HFS participants did not collaborate much when they performed the search tas

The ABCflux database : Arctic-boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic-boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic-boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June-August; 32 %), and fewer observations were available for autumn (September-October; 25 %), winter (December-February; 18 %), and spring (March-May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).Peer reviewe

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems : a review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.Peer reviewe

Deinococcus geothermalis: The Pool of Extreme Radiation Resistance Genes Shrinks

Bacteria of the genus Deinococcus are extremely resistant to ionizing radiation (IR), ultraviolet light (UV) and desiccation. The mesophile Deinococcus radiodurans was the first member of this group whose genome was completely sequenced. Analysis of the genome sequence of D. radiodurans, however, failed to identify unique DNA repair systems. To further delineate the genes underlying the resistance phenotypes, we report the whole-genome sequence of a second Deinococcus species, the thermophile Deinococcus geothermalis, which at its optimal growth temperature is as resistant to IR, UV and desiccation as D. radiodurans, and a comparative analysis of the two Deinococcus genomes. Many D. radiodurans genes previously implicated in resistance, but for which no sensitive phenotype was observed upon disruption, are absent in D. geothermalis. In contrast, most D. radiodurans genes whose mutants displayed a radiation-sensitive phenotype in D. radiodurans are conserved in D. geothermalis. Supporting the existence of a Deinococcus radiation response regulon, a common palindromic DNA motif was identified in a conserved set of genes associated with resistance, and a dedicated transcriptional regulator was predicted. We present the case that these two species evolved essentially the same diverse set of gene families, and that the extreme stress-resistance phenotypes of the Deinococcus lineage emerged progressively by amassing cell-cleaning systems from different sources, but not by acquisition of novel DNA repair systems. Our reconstruction of the genomic evolution of the Deinococcus-Thermus phylum indicates that the corresponding set of enzymes proliferated mainly in the common ancestor of Deinococcus. Results of the comparative analysis weaken the arguments for a role of higher-order chromosome alignment structures in resistance; more clearly define and substantially revise downward the number of uncharacterized genes that might participate in DNA repair and contribute to resistance; and strengthen the case for a role in survival of systems involved in manganese and iron homeostasis

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R-2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra-and interspecific trait variation on ecosystem functioning.Peer reviewe