Feasibility Study: Potential Enhancements for the LLNL Renewables Website

This feasibility study investigates additional improvements/extensions to the LLNL Renewables Website. Currently, the Renewables Website focuses on wind energy in California. Future enhancements will include other renewable energy sources. The extensions described below are focused along two separate yet related avenues: (1) Forecasting wildfire risk in the regions of California where new development may occur, as a part of the 'Million Solar Roofs' program. (2) Gaining a better understanding of the ecological components and potential of biofuels from forests in California. These two avenues are further described in the report. Following is a technical description of the Center for Fire Research and Outreach computing and web service capabilities

Contributions of Fire Refugia to Resilient Ponderosa Pine and Dry Mixed‐Conifer Forest Landscapes

Altered fire regimes can drive major and enduring compositional shifts or losses of forest ecosystems. In western North America, ponderosa pine and dry mixed‐conifer forest types appear increasingly vulnerable to uncharacteristically extensive, high‐severity wildfire. However, unburned or only lightly impacted forest stands that persist within burn mosaics—termed fire refugia—may serve as tree seed sources and promote landscape recovery. We sampled tree regeneration along gradients of fire refugia proximity and density at 686 sites within the perimeters of 12 large wildfires that occurred between 2000 and 2005 in the interior western United States. We used generalized linear mixed‐effects models to elucidate statistical relationships between tree regeneration and refugia pattern, including a new metric that incorporates patch proximity and proportional abundance. These relationships were then used to develop a spatially explicit landscape simulation model. We found that regeneration by ponderosa pine and obligate‐seeding mixed‐conifer tree species assemblages was strongly and positively predicted by refugia proximity and density. Simulation models revealed that for any given proportion of the landscape occupied by refugia, small patches produced greater landscape recovery than large patches. These results highlight the disproportionate importance of small, isolated islands of surviving trees, which may not be detectable with coarse‐scale satellite imagery. Findings also illustrate the interplay between patch‐scale resistance and landscape‐scale resilience: Disturbance‐resistant settings (fire refugia) can entrain resilience (forest regeneration) across the burn matrix. Implications and applications for land managers and conservation practitioners include strategies for the promotion and maintenance of fire refugia as components of resilient forest landscapes

Contemporary visions of progress in ecology and thoughts for the future

Although ecological research is progressing rapidly, the answers to certain key questions continue to elude us. This paper considers several of the contemporary challenges facing ecology. (1) Terminology is voluminous and often poorly defined, resulting in inefficient communication. (2) The concept of scale affects our inferences about system structure and function, requiring us to continue an almost heuristic investigation of breaks, domains, and integration. New tools that more explicitly incorporate scalar issues will need to be developed for progress to take place in the field of ecology. (3) Increasingly, it is expected that applied questions will be solved in less than a year. This demand for solutions from ecologists often produces short-term and inadequate responses. (4) How can ecologists improve communication between subdisciplines, with undergraduate students, and with the public? How will ecology be done in the future, and by whom? We provide some background to these observations and questions, and offer some potential solutions from the viewpoint of young practicing ecologists

Forest fire management, climate change, and the risk of catastrophic carbon losses

Approaches to management of fireprone forests are undergoing rapid change, driven by recognition that technological attempts to subdue fire at large scales (fire suppression) are ecologically and economically unsustainable. However, our current framework for intervention excludes the full scope of the fire management problem within the broader context of fire−vegetation−climate interactions. Climate change may already be causing unprecedented fire activity, and even if current fires are within the historical range of variability, models predict that current fire management problems will be compounded by more frequent extreme fire-conducive weather conditions (eg Fried et al. 2004)

How contemporary bioclimatic and human controls change global fire regimes

Anthropogenically driven declines in tropical savannah burnt area have recently received attention due to their effect on trends in global burnt area. Large-scale trends in ecosystems where vegetation has adapted to infrequent fire, especially in cooler and wetter forested areas, are less well understood. Here, small changes in fire regimes can have a substantial impact on local biogeochemistry. To investigate trends in fire across a wide range of ecosystems, we used Bayesian inference to quantify four primary controls on burnt area: fuel continuity, fuel moisture, ignitions and anthropogenic suppression. We found that fuel continuity and moisture are the dominant limiting factors of burnt area globally. Suppression is most important in cropland areas, whereas savannahs and boreal forests are most sensitive to ignitions. We quantify fire regime shifts in areas with more than one, and often counteracting, trends in these controls. Forests are of particular concern, where we show average shifts in controls of 2.3–2.6% of their potential maximum per year, mainly driven by trends in fuel continuity and moisture. This study gives added importance to understanding long-term future changes in the controls on fire and the effect of fire trends on ecosystem function

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

The implications of the United Nations Paris Agreement on climate change for globally significant biodiversity areas

Climate change is already affecting species and their distributions. Distributional range changes have occurred and are projected to intensify for many widespread plants and animals, creating associated risks to many ecosystems. Here, we estimate the climate change-related risks to the species in globally significant biodiversity conservation areas over a range of climate scenarios, assessing their value as climate refugia. In particular, we quantify the aggregated benefit of countries’ emission reduction pledges (Intended Nationally Determined Contributions and Nationally Determined Contributions under the Paris Agreement), and also of further constraining global warming to 2 °C above pre-industrial levels, against an unmitigated scenario of 4.5 °C warming. We also quantify the contribution that can be made by using smart spatial conservation planning to facilitate some levels of autonomous (i.e. natural) adaptation to climate change by dispersal. We find that without mitigation, on average 33% of each conservation area can act as climate refugium (or 18% if species are unable to disperse), whereas if warming is constrained to 2 °C, the average area of climate refuges doubles to 67% of each conservation area (or, without dispersal, more than doubles to 56% of each area). If the country pledges are fulfilled, an intermediate estimate of 47–52% (or 31–38%, without dispersal) is obtained. We conclude that the Nationally Determined Contributions alone have important but limited benefits for biodiversity conservation, with larger benefits accruing if warming is constrained to 2 °C. Greater benefits would result if warming was constrained to well below 2 °C as set out in the Paris Agreement

Robust projections of Fire Weather Index in the Mediterranean using statistical downscaling

The effect of climate change on wildfires constitutes a serious concern in fire-prone regions with complex fire behavior such as the Mediterranean. The coarse resolution of future climate projections produced by General Circulation Models (GCMs) prevents their direct use in local climate change studies. Statistical downscaling techniques bridge this gap using empirical models that link the synoptic-scale variables from GCMs to the local variables of interest (using e.g. data from meteorological stations). In this paper, we investigate the application of statistical downscaling methods in the context of wildfire research, focusing in the Canadian Fire Weather Index (FWI), one of the most popular fire danger indices. We target on the Iberian Peninsula and Greece and use historical observations of the FWI meteorological drivers (temperature, humidity, wind and precipitation) in several local stations. In particular, we analyze the performance of the analog method, which is a convenient first choice for this problem since it guarantees physical and spatial consistency of the downscaled variables, regardless of their different statistical properties. First we validate the method in perfect model conditions using ERA-Interim reanalysis data. Overall, not all variables are downscaled with the same accuracy, with the poorest results (with spatially averaged daily correlations below 0.5) obtained for wind, followed by precipitation. Consequently, those FWI components mostly relying on those parameters exhibit the poorest results. However, those deficiencies are compensated in the resulting FWI values due to the overall high performance of temperature and relative humidity. Then, we check the suitability of the method to downscale control projections (20C3M scenario) from a single GCM (the ECHAM5 model) and compute the downscaled future fire danger projections for the transient A1B scenario. In order to detect problems due to non-stationarities related to climate change, we compare the results with those obtained with a Regional Climate Model (RCM) driven by the same GCM. Although both statistical and dynamical projections exhibit a similar pattern of risk increment in the first half of the 21st century, they diverge during the second half of the century. As a conclusion, we advocate caution in the use of projections for this last period, regardless of the regionalization technique applied.We are grateful to the Spanish Meteorological Agency (AEMET) and to the Hellenic National Meteorological Service (HNMS) for providing the observational data used in this study. We would also like to thank Erik van Meijgaard from the Royal Netherlands Meteorological Institute for making available ENSEMBLES RACMO2 climate model output verifying at 12:00 UTC and to the Max Planck Institute for providing the appropriate data for the ECHAM5 model used in this work. This work was partly funded by European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreements 243888 (FUME Project) and from Spanish Ministry MICINN under grant EXTREMBLES (CGL2010-21869). We thank tw

A Kinase-Independent Role for the Rad3ATR-Rad26ATRIP Complex in Recruitment of Tel1ATM to Telomeres in Fission Yeast

ATM and ATR are two redundant checkpoint kinases essential for the stable maintenance of telomeres in eukaryotes. Previous studies have established that MRN (Mre11-Rad50-Nbs1) and ATRIP (ATR Interacting Protein) interact with ATM and ATR, respectively, and recruit their partner kinases to sites of DNA damage. Here, we investigated how Tel1ATM and Rad3ATR recruitment to telomeres is regulated in fission yeast. Quantitative chromatin immunoprecipitation (ChIP) assays unexpectedly revealed that the MRN complex could also contribute to the recruitment of Tel1ATM to telomeres independently of the previously established Nbs1 C-terminal Tel1ATM interaction domain. Recruitment of Tel1ATM to telomeres in nbs1-c60Δ cells, which lack the C-terminal 60 amino acid Tel1ATM interaction domain of Nbs1, was dependent on Rad3ATR-Rad26ATRIP, but the kinase domain of Rad3ATR was dispensable. Thus, our results establish that the Rad3ATR-Rad26ATRIP complex contributes to the recruitment of Tel1ATM independently of Rad3ATR kinase activity, by a mechanism redundant with the Tel1ATM interaction domain of Nbs1. Furthermore, we found that the N-terminus of Nbs1 contributes to the recruitment of Rad3ATR-Rad26ATRIP to telomeres. In response to replication stress, mammalian ATR–ATRIP also contributes to ATM activation by a mechanism that is dependent on the MRN complex but independent of the C-terminal ATM interaction domain of Nbs1. Since telomere protection and DNA damage response mechanisms are very well conserved between fission yeast and mammalian cells, mammalian ATR–ATRIP may also contribute to the recruitment of ATM to telomeres and to sites of DNA damage independently of ATR kinase activity

Global Pyrogeography: the Current and Future Distribution of Wildfire

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning