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functions and services for human societies. Temperatures are increasing most rapidly in high northern latitudes, altering tree growth and competition dynamics, and modifying disturbance regimes. The effect of these cumulative changes on the ecosystem functions provided by boreal forests is difficult to predict. We used the process-based LANDIS-II forest landscape model to evaluate how climate change and timber harvesting will interact to alter the production of ecosystem functions and services in boreal forests on three study areas across a large latitudinal gradient (11°) in central Siberia. We found that the relative importance of wood harvesting as a disturbance type varied depending on latitude and its impact was always far less than that of fire. Moderate climate change increased the availability of wood for harvest in the northern landscape, but wood availability declined in the southern landscapes under any amount of climate change likely because of an increase in the frequency of fire that kept forests too young for harvest. Modest climate change (RCP6.0) increased productivity and the storage of carbon in all landscapes but severe climate change (RCP8.5) reduced both in the southernmost landscape. Harvesting as a specific driver of change in these boreal forests is likely to be relatively minor except as a forest fragmentation process. Our results provide compelling evidence that status quo forest management in these landscapes is likely not sustainable, suggesting that climate-smart forestry will be needed. 

Boreal forests form the largest terrestrial biome globally. Climate change is expected to induce large changes in vegetation of high latitude ecosystems, but there is considerable uncertainty about where, when, and how those changes will occur. Such vegetation change produces major feedback to the climate system, including by modifying albedo (reflectivity). Our study used the LANDIS-II forest landscape model to project forest dynamics on four representative landscapes (1 M ha) for 280 years into the future under a range of climate scenarios across a broad latitudinal gradient in Siberia. The model estimated the albedo of the vegetation and any snow on each landscape grid-cell through time to quantify surface albedo change in response to climate change and disturbances. We found that the shortening of the snow-covered season (winter) decreased annual average albedo dramatically, and climate change facilitated the invasion of tundra by boreal trees in the northernmost landscape (reducing albedo in all seasons). However, in other landscapes, albedo increased in summer due to disturbances (fire, wind, insects, harvest), eliminating or reducing leaf area in the short-term, and in the mid-term by promoting more reflective forest types deciduous, light conifers). This increased albedo was somewhat ephemeral and under climate change was overwhelmed by the shortening of the snow-covered season that greatly reduced albedo. We conclude that the primary driver of the overall reflectivity of boreal ecosystems is not vegetation, but rather, the length of the snow-covered season. Because climate change is likely to dramatically shorten the snow season, the concurrent reduction of albedo has the potential to act as a powerful positive feedback for climate change. Managing natural and anthropogenic disturbances may be the only tool with potential to mitigate the reduction of albedo by climate change in boreal ecosystems because management to encourage more reflective forest types has relatively small effect. 

Abstract BackgroundClimate change is expected to increase fire activity across the circumboreal zone, including central Siberia. However, few studies have quantitatively assessed potential changes in fire regime characteristics, or considered possible spatial variation in the magnitude of change. Moreover, while simulations indicate that changes in climate are likely to drive major shifts in Siberian vegetation, knowledge of future forest dynamics under the joint influence of changes in climate and fire regimes remains largely theoretical. We used the forest landscape model, LANDIS-II, with PnET-Succession and the BFOLDS fire extension to simulate changes in vegetation and fire regime characteristics under four alternative climate scenarios in three 10,000-km²study landscapes distributed across a large latitudinal gradient in lowland central Siberia. We evaluated vegetation change using the fire life history strategies adopted by forest tree species: fire resisters, fire avoiders, and fire endurers. ResultsAnnual burned area, the number of fires per year, fire size, and fire intensity all increased under climate change. The relative increase in fire activity was greatest in the northernmost study landscape, leading to a reduction in the difference in fire rotation period between study landscapes. Although the number of fires per year increased progressively with the magnitude of climate change, mean fire size peaked under mild or moderate climate warming in each of our study landscapes, suggesting that fuel limitations and past fire perimeters will feed back to reduce individual fire extent under extreme warming, relative to less extreme warming scenarios. In the Southern and Mid-taiga landscapes, we observed a major shift from fire resister-dominated forests to forests dominated by broadleaved deciduous fire endurers (BetulaandPopulusgenera) under moderate and extreme climate warming scenarios, likely associated with the substantial increase in fire activity. These changes were accompanied by a major decrease in average cohort age and total vegetation biomass across the simulation landscapes. ConclusionsOur results imply that climate change will greatly increase fire activity and reduce spatial heterogeneity in fire regime characteristics across central Siberia. Potential ecological consequences include a widespread shift toward forests dominated by broadleaved deciduous species that employ a fire endurer strategy to persist in an increasingly fire-prone environment. 

Changes in CO 2 concentration and climate are likely to alter disturbance regimes and competitive outcomes among tree species, which ultimately can result in shifts of species and biome boundaries. Such changes are already evident in high latitude forests, where waterlogged soils produced by topography, surficial geology, and permafrost are an important driver of forest dynamics. Predicting such effects under the novel conditions of the future requires models with direct and mechanistic links of abiotic drivers to growth and competition. We enhanced such a forest landscape model (PnET-Succession in LANDIS-II) to allow simulation of waterlogged soils and their effects on tree growth and competition. We formally tested how these modifications alter water balance on wetland and permafrost sites, and their effect on tree growth and competition. We applied the model to evaluate its promise for mechanistically simulating species range expansion and contraction under climate change across a latitudinal gradient in Siberian Russia. We found that higher emissions scenarios permitted range expansions that were quicker and allowed a greater diversity of invading species, especially at the highest latitudes, and that disturbance hastened range shifts by overcoming the natural inertia of established ecological communities. The primary driver of range advances to the north was altered hydrology related to thawing permafrost, followed by temperature effects on growth. Range contractions from the south (extirpations) were slower and less tied to emissions or latitude, and were driven by inability to compete with invaders, or disturbance. An important non-intuitive result was that some extant species were killed off by extreme cold events projected under climate change as greater weather extremes occurred over the next 30 years, and this had important effects on subsequent successional trajectories. The mechanistic linkages between climate and soil water dynamics in this forest landscape model produced tight links between climate inputs, physiology of vegetation, and soils at a monthly time step. The updated modeling system can produce high quality projections of climate impacts on forest species range shifts by accounting for the interacting effects of CO 2 concentration, climate (including longer growing seasons), seed dispersal, disturbance, and soil hydrologic properties. 

The advanced LIGO gravitational wave detectors need high power laser sources with excellent beam quality and low-noise behavior. We present a pre-stabilized laser system with 70 W of output power that was used in the third observing run of the advanced LIGO detectors. Furthermore, the prototype of a 140 W pre-stabilized laser system for future use in the LIGO observatories is described and characterized. 

Amorphous tantala ( ${\mathrm{T}\mathrm{a}}_2{\mathrm{O}}_5$) thin films were deposited by reactive ion beam sputtering with simultaneous low energy assist ${\mathrm{A}\mathrm{r}}^{+}$or ${\mathrm{A}\mathrm{r}}^{+}/{\mathrm{O}}_2^{+}$bombardment. Under the conditions of the experiment, the as-deposited thin films are amorphous and stoichiometric. The refractive index and optical band gap of thin films remain unchanged by ion bombardment. Around 20% improvement in room temperature mechanical loss and 60% decrease in absorption loss are found in samples bombarded with 100-eV ${\mathrm{A}\mathrm{r}}^{+}$. A detrimental influence from low energy ${\mathrm{O}}_2^{+}$bombardment on absorption loss and mechanical loss is observed. Low energy ${\mathrm{A}\mathrm{r}}^{+}$bombardment removes excess oxygen point defects, while ${\mathrm{O}}_2^{+}$bombardment introduces defects into the tantala films. 

Binary static analysis has seen a recent surge in interest, due to a rise in analysis targets for which no other method is appropriate, such as, embedded firmware. This has led to the proposal of a number of binary static analysis tools and techniques, handling various kinds of programs, and answering different research questions. While static analysis tools that focus on binaries inherit the undecidability of static analysis, they bring with them other challenges, particularly in dealing with the aliasing of code and data pointers. These tools may tackle these challenges in different ways, but unfortunately, there is currently no concrete means of comparing their effectiveness at solving these central, problem-independent aspects of static analysis. In this paper, we propose a new method for creating a dataset of real-world programs, paired with the ground truth for static analysis. Our approach involves the injection of synthetic “facts” into a set of open-source programs, consisting of new variables and their possible values. The analyses’ goal is then to evaluate the possible values of these facts at certain program points. As the facts are injected randomly within an arbitrarily-large set of programs, the kinds of data flows that can be measured are widely-varied in size and complexity. We implemented this idea as a prototype system, AUTOFACTS, and used it to create a ground truth dataset of 29 programs, with various types and number of facts, resulting in a total of 2,088 binaries (with 72 versions for each program). To our knowledge, this is the first dataset aimed at the problem-independent evaluation of static analysis tools, and we contribute all code and the dataset itself to the community as open-source.