Forest Fires Across Italian Regions and Implications for Climate Change: A Panel Data Analysis

In this paper, we analyze the determinants of monthly variations in forest fire frequency and on the size of the area burnt for Italian regions between 2000 and 2011. We employ panel data techniques, which allow capturing the dynamics of fire danger due to changes in past climatic conditions, after accounting for regional fixed effects to control region-specific unobserved and time-invariant factors. Results highlight a significant heterogeneity of the effects of driving factors across the Italian peninsula and weather seasons. Climatic conditions also show lasting effects within the year. Using climate change projections for 2016–2035, we then obtain the projected forest fire frequency and total area burnt across the Italian peninsula for the same period. Climate change is expected to increase the number of forest fires across the whole peninsula, which is more evident for the central part of Italy. Even though most of annual increases in fire events relate to the summer period, intensifications in frequency during autumn become more evident in the southern Italy. We extend finally our analysis to investigate the contribution of socio-economic factors to fire regime and the role of education and the containment of fraudulent activity is also highlighted.</p

Warming and earlier spring increase western U.S. forest wildfire activity

Western United States forest wildfire activity is widely thought to have increased in recent decades, yet neither the extent of recent changes nor the degree to which climate may be driving regional changes in wildfire has been systematically documented. Much of the public and scientific discussion of changes in western United States wildfire has focused instead on the effects of 19thand 20th-century land-use history. We compiled a comprehensive database of large wildfires in western United States forests since 1970 and compared it with hydroclimatic and land-surface data. Here, we show that large wildfire activity increased suddenly and markedly in the mid-1980s, with higher large-wildfire frequency, longer wildfire durations, and longer wildfire seasons. The greatest increases occurred in mid-elevation, Northern Rockies forests, where land-use histories have relatively little effect on fire risks and are strongly associated with increased spring and summer temperatures and an earlier spring snowmelt

Warming and earlier spring increase western U.S. forest wildfire activity

Western United States forest wildfire activity is widely thought to have increased in recent decades, yet neither the extent of recent changes nor the degree to which climate may be driving regional changes in wildfire has been systematically documented. Much of the public and scientific discussion of changes in western United States wildfire has focused instead on the effects of 19th- and 20th-century land-use history. We compiled a comprehensive database of large wildfires in western United States forests since 1970 and compared it with hydroclimatic and land-surface data. Here, we show that large wildfire activity increased suddenly and markedly in the mid-1980s, with higher large-wildfire frequency, longer wildfire durations, and longer wildfire seasons. The greatest increases occurred in mid-elevation, Northern Rockies forests, where land-use histories have relatively little effect on fire risks and are strongly associated with increased spring and summer temperatures and an earlier spring snowmelt

Behavioral adaptation to climate change in wildfireâ prone forests

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146375/1/wcc553.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146375/2/wcc553_am.pd

Fatal inanition in reindeer (Rangifer tarandus tarandus): Pathological findings in completely emaciated carcasses

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A Global Meta-Analysis of Forest Bioenergy Greenhouse Gas Emission Accounting Studies

The potential greenhouse gas benefits of displacing fossil energy with biofuels are driving policy development in the absence of complete information. The potential carbon neutrality of forest biomass is a source of considerable scientific debate because of the complexity of dynamic forest ecosystems, varied feedstock types, and multiple energy production pathways. The lack of scientific consensus leaves decision makers struggling with contradicting technical advice. Analyzing previously published studies, our goal was to identify and prioritize those attributes of bioenergy greenhouse gas (GHG) emissions analysis that are most influential on length of carbon payback period. We investigated outcomes of 59 previously published forest biomass greenhouse gas emissions research studies published between 1991 and 2014. We identified attributes for each study and classified study cases by attributes. Using classification and regression tree analysis, we identified those attributes that are strong predictors of carbon payback period (e.g. the time required by the forest to recover through sequestration the carbon dioxide from biomass combusted for energy). The inclusion of wildfire dynamics proved to be the most influential in determining carbon payback period length compared to other factors such as feedstock type, baseline choice, and the incorporation of leakage calculations. Additionally, we demonstrate that evaluation criteria consistency is required to facilitate equitable comparison between projects. For carbon payback period calculations to provide operational insights to decision makers, future research should focus on creating common accounting principles for the most influential fac

Cause-specific mortality time series analysis: a general method to detect and correct for abrupt data production changes

<p>Abstract</p> <p>Background</p> <p>Monitoring the time course of mortality by cause is a key public health issue. However, several mortality data production changes may affect cause-specific time trends, thus altering the interpretation. This paper proposes a statistical method that detects abrupt changes ("jumps") and estimates correction factors that may be used for further analysis.</p> <p>Methods</p> <p>The method was applied to a subset of the AMIEHS (Avoidable Mortality in the European Union, toward better Indicators for the Effectiveness of Health Systems) project mortality database and considered for six European countries and 13 selected causes of deaths. For each country and cause of death, an automated jump detection method called Polydect was applied to the log mortality rate time series. The plausibility of a data production change associated with each detected jump was evaluated through literature search or feedback obtained from the national data producers.</p> <p>For each plausible jump position, the statistical significance of the between-age and between-gender jump amplitude heterogeneity was evaluated by means of a generalized additive regression model, and correction factors were deduced from the results.</p> <p>Results</p> <p>Forty-nine jumps were detected by the Polydect method from 1970 to 2005. Most of the detected jumps were found to be plausible. The age- and gender-specific amplitudes of the jumps were estimated when they were statistically heterogeneous, and they showed greater by-age heterogeneity than by-gender heterogeneity.</p> <p>Conclusion</p> <p>The method presented in this paper was successfully applied to a large set of causes of death and countries. The method appears to be an alternative to bridge coding methods when the latter are not systematically implemented because they are time- and resource-consuming.</p

Pervasive Growth Reduction in Norway Spruce Forests following Wind Disturbance

Background: In recent decades the frequency and severity of natural disturbances by e.g., strong winds and insect outbreaks has increased considerably in many forest ecosystems around the world. Future climate change is expected to further intensify disturbance regimes, which makes addressing disturbances in ecosystem management a top priority. As a prerequisite a broader understanding of disturbance impacts and ecosystem responses is needed. With regard to the effects of strong winds – the most detrimental disturbance agent in Europe – monitoring and management has focused on structural damage, i.e., tree mortality from uprooting and stem breakage. Effects on the functioning of trees surviving the storm (e.g., their productivity and allocation) have been rarely accounted for to date. Methodology/Principal Findings: Here we show that growth reduction was significant and pervasive in a 6.79?million hectare forest landscape in southern Sweden following the storm Gudrun (January 2005). Wind-related growth reduction in Norway spruce (Picea abies (L.) Karst.) forests surviving the storm exceeded 10 % in the worst hit regions, and was closely related to maximum gust wind speed (R 2 = 0.849) and structural wind damage (R 2 = 0.782). At the landscape scale, windrelated growth reduction amounted to 3.0 million m 3 in the three years following Gudrun. It thus exceeds secondary damage from bark beetles after Gudrun as well as the long-term average storm damage from uprooting and stem breakage in Sweden

Housing Arrangement and Location Determine the Likelihood of Housing Loss Due to Wildfire

Surging wildfires across the globe are contributing to escalating residential losses and have major social, economic, and ecological consequences. The highest losses in the U.S. occur in southern California, where nearly 1000 homes per year have been destroyed by wildfires since 2000. Wildfire risk reduction efforts focus primarily on fuel reduction and, to a lesser degree, on house characteristics and homeowner responsibility. However, the extent to which land use planning could alleviate wildfire risk has been largely missing from the debate despite large numbers of homes being placed in the most hazardous parts of the landscape. Our goal was to examine how housing location and arrangement affects the likelihood that a home will be lost when a wildfire occurs. We developed an extensive geographic dataset of structure locations, including more than 5500 structures that were destroyed or damaged by wildfire since 2001, and identified the main contributors to property loss in two extensive, fire-prone regions in southern California. The arrangement and location of structures strongly affected their susceptibility to wildfire, with property loss most likely at low to intermediate structure densities and in areas with a history of frequent fire. Rates of structure loss were higher when structures were surrounded by wildland vegetation, but were generally higher in herbaceous fuel types than in higher fuel-volume woody types. Empirically based maps developed using housing pattern and location performed better in distinguishing hazardous from non-hazardous areas than maps based on fuel distribution. The strong importance of housing arrangement and location indicate that land use planning may be a critical tool for reducing fire risk, but it will require reliable delineations of the most hazardous locations