Self-reported reasons for on-duty sleepiness among commercial airline pilots

Experimental and epidemiological research has shown that human sleepiness is determined especially by the circadian and homeostatic processes. The present field study examined which work-related factors airline pilots perceive as causing on-duty sleepiness during short-haul and long-haul flights. In addition, the association between the perceived reasons for sleepiness and actual sleepiness levels was examined, as well as the association between reporting inadequate sleep causing sleepiness and actual sleep-wake history. The study sample consisted of 29 long-haul (LH) pilots, 28 short-haul (SH) pilots, and 29 mixed fleet pilots (flying both SH and LH flights), each of whom participated in a 2-month field measurement period, yielding a total of 765 SH and 494 LH flight duty periods (FDPs) for analyses (FDP, a period between the start of a duty and the end of the last flight of that duty). The self-reports of sleepiness inducers were collected at the end of each FDP by an electronic select menu. On-duty sleepiness was rated at each flight phase by the Karolinska Sleepiness Scale (KSS). The sleep-wake data was collected by a diary and actigraph. The results showed that "FDP timing" and "inadequate sleep" were the most frequently reported reasons for on-duty sleepiness out of the seven options provided, regardless of FDP type (SH, LH). Reporting these reasons significantly increased the odds of increased on-duty sleepiness (KSS >= 7), except for reporting "inadequate sleep" during LH FDPs. Reporting "inadequate sleep" was also associated with increased odds of a reduced sleep-wake ratio (total sleep time/amount of wakefulnessPeer reviewe

High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra

Arctic terrestrial greenhouse gas (GHG) fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) play an important role in the global GHG budget. However, these GHG fluxes are rarely studied simultaneously, and our understanding of the conditions controlling them across spatial gradients is limited. Here, we explore the magnitudes and drivers of GHG fluxes across fine-scale terrestrial gradients during the peak growing season (July) in sub-Arctic Finland. We measured chamber-derived GHG fluxes and soil temperature, soil moisture, soil organic carbon and nitrogen stocks, soil pH, soil carbon-to-nitrogen (C/N) ratio, soil dissolved organic carbon content, vascular plant biomass, and vegetation type from 101 plots scattered across a heterogeneous tundra landscape (5 km2). We used these field data together with high-resolution remote sensing data to develop machine learning models for predicting (i.e., upscaling) daytime GHG fluxes across the landscape at 2 m resolution. Our results show that this region was on average a daytime net GHG sink during the growing season. Although our results suggest that this sink was driven by CO2 uptake, it also revealed small but widespread CH4 uptake in upland vegetation types, almost surpassing the high wetland CH4 emissions at the landscape scale. Average N2O fluxes were negligible. CO2 fluxes were controlled primarily by annual average soil temperature and biomass (both increase net sink) and vegetation type, CH4 fluxes by soil moisture (increases net emissions) and vegetation type, and N2O fluxes by soil C/N (lower C/N increases net source). These results demonstrate the potential of high spatial resolution modeling of GHG fluxes in the Arctic. They also reveal the dominant role of CO2 fluxes across the tundra landscape but suggest that CH4 uptake in dry upland soils might play a significant role in the regional GHG budget.</p

How generalist are these forest specialists? What Sweden's avian indicators indicate

Monitoring of forest biodiversity and habitats is an important part of forest conservation, but due to the impossible task of monitoring all species, indicator species are frequently used. However, reliance on an incorrect indicator of valuable habitat can reduce the efficiency of conservation efforts. Birds are often used as indicators as they are charismatic, relatively easy to survey, and because we often have knowledge of their habitat and resource requirements. In the Swedish government's environmental quality goals, there are a number of bird species identified as being associated with 'older' and 'high natural value' forests. Here we evaluate the occurrence of four of these indicator species using data from 91 production forest stands and 10 forest reserves in southern Sweden. The bird species assessed are willow tit Poecile montanus, coal tit Periparus ater, European crested tit Lophophanes cristatus and Eurasian treecreeper Certhia familiaris. For the production stands assessed, these indicator species exhibited no significant preferences regarding forest composition and structure, indicating a wider range of habitat associations than expected. These species frequently showed territorial behavior in forest stands &lt;60 and even 40 years of age; much younger than the 120-year threshold for 'older forest' as defined by governmental environmental goals. As almost 80% of the production stands >= 10 years old included at least one of the four indicator species, this raises questions regarding the suitability of these species as indictors of forests of high conservational value in southern Sweden. Notably, besides the four species assessed here, none of the additional indicator taxa identified by the government, were recorded in the 10 reserves. This outcome may reflect the difficulties involved in finding bird indicator species indicative of high natural values in this region. Our results highlight the importance of coupling bird surveys with quantified assessments of proximate vegetation cover

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Quantifying the Detrimental Impacts of Land-Use and Management Change on European Forest Bird Populations

The ecological impacts of changing forest management practices in Europe are poorly understood despite European forests being highly managed. Furthermore, the effects of potential drivers of forest biodiversity decline are rarely considered in concert, thus limiting effective conservation or sustainable forest management. We present a trait-based framework that we use to assess the detrimental impact of multiple land-use and management changes in forests on bird populations across Europe. Major changes to forest habitats occurring in recent decades, and their impact on resource availability for birds were identified. Risk associated with these changes for 52 species of forest birds, defined as the proportion of each species' key resources detrimentally affected through changes in abundance and/or availability, was quantified and compared to their pan-European population growth rates between 1980 and 2009. Relationships between risk and population growth were found to be significantly negative, indicating that resource loss in European forests is an important driver of decline for both resident and migrant birds. Our results demonstrate that coarse quantification of resource use and ecological change can be valuable in understanding causes of biodiversity decline, and thus in informing conservation strategy and policy. Such an approach has good potential to be extended for predictive use in assessing the impact of possible future changes to forest management and to develop more precise indicators of forest health

Effects of climate and atmospheric nitrogen deposition on early to mid-term stage litter decomposition across biomes

Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1-3.5% and of the more stable substrates by 3.8-10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4-2.2% and that of low-quality litter by 0.9-1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km(2)) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m(-2) yr(-1), respectively) compared to tundra (average annual NEE +10 and -2 g C m(-2) yr(-1)). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high