Synoptic-Scale Atmospheric Circulation and Boreal Canada Summer Drought Variability of the Past Three Centuries

Five independent multicentury reconstructions of the July Canadian Drought Code and one reconstruction of the mean July-August temperature were developed using a network of 120 well-replicated tree-ring chronologies covering the area of the eastern Boreal Plains to the eastern Boreal Shield of Canada. The reconstructions were performed using 54 time-varying reconstruction submodels that explained up to 50% of the regional drought variance during the period of 1919-84. Spatial correlation fields on the six reconstructions revealed that the meridional component of the climate system from central to eastern Canada increased since the mid-nineteenth century. The most obvious change was observed in the decadal scale of variability. Using 500-hPa geopotential height and wind composites, this zonal to meridional transition was interpreted as a response to an amplification of long waves flowing over the eastern North Pacific into boreal Canada, from approximately 1851 to 1940. Composites with NOAA Extended Reconstructed SSTs indicated a coupling between the meridional component and tropical and North Pacific SST for a period covering at least the past 150 yr, supporting previous findings of a summertime global ocean-atmospherel-and surface coupling. This change in the global atmospheric circulation could be a key element toward understanding the observed temporal changes in the Canadian boreal forest fire regimes over the past 150 yr

Effects of climate on occurence and size of large fires in a northern hardwood landscape: historical trends, forecasts, and implications for climate change in Témiscamingue, Québec

Questions: What climate variables best explain fire occurrence and area burned in the Great Lakes-St Lawrence forest of Canada? How will climate change influence these climate variables and thereby affect the occurrence of fire and area burned in a deciduous forest landscape in Témiscamingue, Québec, Canada?\ud Location: West central Québec and the Great Lakes-St Lawrence forest of Canada.\ud Methods: We first used an information-theoretic framework to evaluate the relative role of different weather variables in explaining occurrence and area burned of large fires (4200 ha, 1959-1999) across the Great Lakes- St Lawrence forest region. Second, we examined how these weather variables varied historically in Témiscamingue and, third, how they may change between the present and 2100 according to different scenarios of climate change based on two Global Circulation Models.\ud Results: Mean monthly temperature maxima during the fire season (Apr-Oct) and weighted sequences of dry spells best explained fire occurrence and area burned. Between 1910 and 2004, mean monthly temperature maxima in Témiscamingue showed no apparent temporal trend, while dry spell sequences decreased in frequency and length. All future scenarios show an increase in mean monthly temperature maxima, and one model scenario forecasts an increase in dry spell sequences, resulting in a slight increase in forecasted annual area burned.\ud Conclusion: Despite the forecasted increase in fire activity, effects of climate change on fire will not likely affect forest structure and composition as much as natural succession or harvesting and other disturbances, principally because of the large relative difference in area affected by these processes

A review of machine learning applications in wildfire science and management

Artificial intelligence has been applied in wildfire science and management since the 1990s, with early applications including neural networks and expert systems. Since then the field has rapidly progressed congruently with the wide adoption of machine learning (ML) in the environmental sciences. Here, we present a scoping review of ML in wildfire science and management. Our objective is to improve awareness of ML among wildfire scientists and managers, as well as illustrate the challenging range of problems in wildfire science available to data scientists. We first present an overview of popular ML approaches used in wildfire science to date, and then review their use in wildfire science within six problem domains: 1) fuels characterization, fire detection, and mapping; 2) fire weather and climate change; 3) fire occurrence, susceptibility, and risk; 4) fire behavior prediction; 5) fire effects; and 6) fire management. We also discuss the advantages and limitations of various ML approaches and identify opportunities for future advances in wildfire science and management within a data science context. We identified 298 relevant publications, where the most frequently used ML methods included random forests, MaxEnt, artificial neural networks, decision trees, support vector machines, and genetic algorithms. There exists opportunities to apply more current ML methods (e.g., deep learning and agent based learning) in wildfire science. However, despite the ability of ML models to learn on their own, expertise in wildfire science is necessary to ensure realistic modelling of fire processes across multiple scales, while the complexity of some ML methods requires sophisticated knowledge for their application. Finally, we stress that the wildfire research and management community plays an active role in providing relevant, high quality data for use by practitioners of ML methods.Comment: 83 pages, 4 figures, 3 table

Electrical studies of Barkhausen switching noise in ferroelectric PZT : critical exponents and temperature dependence

This work at St Andrews was supported by EPSRC grant EP/P024637/1. EKHS thanks EPSRC for support.Crackling noise of ferroelectric lead zirconate titanate samples during ferroelectric switching is demonstrated to be compatible with avalanche statistics. The peaks of the slew rate (time derivative of current dI/dt squared), defined as "jerks," were statistically analyzed and shown to obey power laws. The critical exponent obtained is 1.64 ± 0.15, in agreement with predictions from avalanche theory. The exponent is independent of temperature within experimental error margins.PostprintPeer reviewe

Fire and the relative roles of weather, climate and landscape characteristics in the Great Lakes-St. Lawrence forest of Canada

Question: In deciduous-dominated forest landscapes, what are the relative roles of fire weather, climate, human and biophysical landscape characteristics for explaining variation in large fire occurrence and area burned? Location: The Great Lakes-St. Lawrence forest of Canada. Methods: We characterized the recent (1959-1999) regime of large (≥ 200 ha) fires in 26 deciduous-dominated landscapes and analysed these data in an information-theoretic framework to compare six hypotheses that related fire occurrence and area burned to fire weather severity, climate normals, population and road densities, and enduring landscape characteristics such as surficial deposits and large lakes. Results: 392 large fires burned 833 698 ha during the study period, annually burning on average 0.07% ± 0.42% of forested area in each landscape. Fire activity was strongly seasonal, with most fires and area burned occurring in May and June. A combination of antecedent-winter precipitation, fire season precipitation deficit/surplus and percent of landscape covered by well-drained surficial deposits best explained fire occurrence and area burned. Fire occurrence varied only as a function of fire weather and climate variables, whereas area burned was also explained by percent cover of aspen and pine stands, human population density and two enduring characteristics: percent cover of large water bodies and glaciofluvial deposits. Conclusion: Understanding the relative role of these variables may help design adaptation strategies for forecasted increases in fire weather severity by allowing (1) prioritization of landscapes according to enduring characteristics and (2) management of their composition so that substantially increased fire activity would be necessary to transform landscape structure and composition

On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90th percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we were interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the spatial pattern and magnitude of their respective instantaneous versions, leading to inconsistent results when projected into the future. As a result, we advocate caution when using daily mean data and strongly recommend the application of the standard definition for its calculation as closely as possible. Threshold-dependent indices derived from FWI are not reliably represented by the daily mean version and thus can neither be applied for the estimation of future fire danger season length and severity, nor for the estimation of future extreme events.The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 243888 (FUME Project). J.F. acknowledges nancial support from the Spanish R&D&I programme through grant CGL2010-22158-C02 (CORWES project). The ESCENA project (200800050084265) of the Spanish \Strategic action on energy and climate change" provided the WRF RCM simulation used in this study. We acknowledge three anonymous referees for their useful comments that helped to improve the original manuscript

Smartphone and medical related App use among medical students and junior doctors in the United Kingdom (UK): a regional survey

Background: Smartphone usage has spread to many settings including that of healthcare with numerous potential and realised benefits. The ability to download custom-built software applications (apps) has created a new wealth of clinical resources available to healthcare staff, providing evidence-based decisional tools to reduce medical errors. Previous literature has examined how smartphones can be utilised by both medical student and doctor populations, to enhance educational and workplace activities, with the potential to improve overall patient care. However, this literature has not examined smartphone acceptance and patterns of medical app usage within the student and junior doctor populations. Methods: An online survey of medical student and foundation level junior doctor cohorts was undertaken within one United Kingdom healthcare region. Participants were asked whether they owned a Smartphone and if they used apps on their Smartphones to support their education and practice activities. Frequency of use and type of app used was also investigated. Open response questions explored participants’ views on apps that were desired or recommended and the characteristics of apps that were useful. Results: 257 medical students and 131 junior doctors responded, equating to a response rate of 15.0% and 21.8% respectively. 79.0% (n=203/257) of medical students and 74.8% (n=98/131) of junior doctors owned a smartphone, with 56.6% (n=115/203) of students and 68.4% (n=67/98) of doctors owning an iPhone. The majority of students and doctors owned 1–5 medical related applications, with very few owning more than 10, and iPhone owners significantly more likely to own apps (Chi sq, p<0.001). Both populations showed similar trends of app usage of several times a day. Over 24hours apps were used for between 1–30 minutes for students and 1–20 minutes for doctors, students used disease diagnosis/management and drug reference apps, with doctors favouring clinical score/calculator apps. Conclusions: This study found a high level of smartphone ownership and usage among medical students and junior doctors. Both groups endorse the development of more apps to support their education and clinical practice

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

The role of historical fire disturbance in the carbon dynamics of the pan-boreal region : a process-based analysis

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): G02029, doi:10.1029/2006JG000380.Wildfire is a common occurrence in ecosystems of northern high latitudes, and changes in the fire regime of this region have consequences for carbon feedbacks to the climate system. To improve our understanding of how wildfire influences carbon dynamics of this region, we used the process-based Terrestrial Ecosystem Model to simulate fire emissions and changes in carbon storage north of 45°N from the start of spatially explicit historically recorded fire records in the twentieth century through 2002, and evaluated the role of fire in the carbon dynamics of the region within the context of ecosystem responses to changes in atmospheric CO2 concentration and climate. Our analysis indicates that fire plays an important role in interannual and decadal scale variation of source/sink relationships of northern terrestrial ecosystems and also suggests that atmospheric CO2 may be important to consider in addition to changes in climate and fire disturbance. There are substantial uncertainties in the effects of fire on carbon storage in our simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. To improve the ability to better predict how fire will influence carbon storage of this region in the future, new analyses of the retrospective role of fire in the carbon dynamics of northern high latitudes should address these uncertainties.Funding for this study was provided by grants from the National Science Foundation Biocomplexity Program (ATM-0120468) and Office of Polar Programs (OPP-0531047 and OPP- 0327664); the National Aeronautics and Space Administration Land Cover Land Use Change Program (NAF-11142) and North America Carbon Program (NNG05GD25G); the Bonanza Creek LTER (Long-Term Ecological Research) Program (funded jointly by NSF grant DEB-0423442 and USDA Forest Service, Pacific Northwest Research Station grant PNW01- JV11261952-231); and the U.S. Geological Survey