Research

1170 KiB

Open AccessArticle

Assessing Climate Change Impacts on Wildfire Risk in the United States

by Hyunjin An, Jianbang Gan and Sung Ju Cho

Forests 2015, 6(9), 3197-3211; https://doi.org/10.3390/f6093197 - 15 Sep 2015

Cited by 15 | Viewed by 11358

This study examines the statistical association of wildfire risk with climatic conditions and non-climate variables in 48 continental US states. Because the response variable “wildfire risk” is a fractional variable bounded between zero and one, we use a non-linear panel data model to [...] Read more.

This study examines the statistical association of wildfire risk with climatic conditions and non-climate variables in 48 continental US states. Because the response variable “wildfire risk” is a fractional variable bounded between zero and one, we use a non-linear panel data model to recognize the bounded nature of the response variable. We estimate the non-linear panel data model (fractional probit) using the Generalized Estimating Equation (GEE) approach to ensure that the parameter estimation is efficient. The statistical model, coupled with the future climates projected by Global Climate Models (GCMs), is then employed to assess the impact of global climate change on wildfire risk. Our regression results show that wildfire risk is positively related to spring, summer, and winter temperatures and human population density whereas it is negatively associated with precipitation. The simulation results based on GCMs and the regression model indicate that climate change will intensify wildfire risk throughout the entire US, especially in the South Central region, posing an increasing wildfire threat and thus calling for more effective wildfire management strategies. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

12517 KiB

Open AccessArticle

Effect of Climate Change Projections on Forest Fire Behavior and Values-at-Risk in Southwestern Greece

by Kostas Kalabokidis, Palaiologos Palaiologou, Evangelos Gerasopoulos, Christos Giannakopoulos, Effie Kostopoulou and Christos Zerefos

Forests 2015, 6(6), 2214-2240; https://doi.org/10.3390/f6062214 - 19 Jun 2015

Cited by 49 | Viewed by 9997

Abstract

Climate change has the potential to influence many aspects of wildfire behavior and risk. During the last decade, Greece has experienced large-scale wildfire phenomena with unprecedented fire behavior and impacts. In this study, thousands of wildfire events were simulated with the Minimum Travel [...] Read more.

Climate change has the potential to influence many aspects of wildfire behavior and risk. During the last decade, Greece has experienced large-scale wildfire phenomena with unprecedented fire behavior and impacts. In this study, thousands of wildfire events were simulated with the Minimum Travel Time (MTT) fire growth algorithm (called Randig) and resulted in spatial data that describe conditional burn probabilities, potential fire spread and intensity in Messinia, Greece. Present (1961–1990) and future (2071–2100) climate projections were derived from simulations of the KNMI regional climate model RACMO2, under the SRES A1B emission scenario. Data regarding fuel moisture content, wind speed and direction were modified for the different projection time periods to be used as inputs in Randig. Results were used to assess the vulnerability changes for certain values-at-risk of the natural and human-made environment. Differences in wildfire risk were calculated and results revealed that larger wildfires that resist initial control are to be expected in the future, with higher conditional burn probabilities and intensities for extensive parts of the study area. The degree of change in the modeled Canadian Forest Fire Weather Index for the two time periods also revealed an increasing trend in frequencies of higher values for the future. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Graphical abstract

13669 KiB

Open AccessArticle

A Stochastic Programming Model for Fuel Treatment Management

by Mohannad Kabli, Jianbang Gan and Lewis Ntaimo

Forests 2015, 6(6), 2148-2162; https://doi.org/10.3390/f6062148 - 15 Jun 2015

Cited by 11 | Viewed by 4884

Abstract

This work considers a two-stage stochastic integer programming (SIP) approach for optimizing fuel treatment planning under uncertainty in weather and fire occurrence for rural forests. Given a set of areas for potentially performing fuel treatment, the problem is to decide the best treatment [...] Read more.

This work considers a two-stage stochastic integer programming (SIP) approach for optimizing fuel treatment planning under uncertainty in weather and fire occurrence for rural forests. Given a set of areas for potentially performing fuel treatment, the problem is to decide the best treatment option for each area under uncertainty in future weather and fire occurrence. A two-stage SIP model is devised whose objective is to minimize the here-and-now cost of fuel treatment in the first-stage, plus the expected future costs due to uncertain impact from potential fires in the second-stage calculated as ecosystem services losses. The model considers four fuel treatment options: no treatment, mechanical thinning, prescribed fire, and grazing. Several constraints such as budgetary and labor constraints are included in the model and a standard fire behavior model is used to estimate some of the parameters of the model such as fuel levels at the beginning of the fire season. The SIP model was applied to data for a study area in East Texas with 15 treatment areas under different weather scenarios. The results of the study show, for example, that unless the expected ecosystem services values for an area outweigh fuel treatment costs, no treatment is the best choice for the area. Thus the valuation of the area together with the probability of fire occurrence and behavior strongly drive fuel treatment choices. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

975 KiB

Open AccessArticle

Post-Fire Seedling Recruitment and Morpho-Ecophysiological Responses to Induced Drought and Salvage Logging in Pinus halepensis Mill. Stands

by Daniel Moya, Jorge De las Heras, Francisco R. López-Serrano and Pablo Ferrandis

Forests 2015, 6(6), 1858-1877; https://doi.org/10.3390/f6061858 - 29 May 2015

Cited by 22 | Viewed by 5725

Abstract

Salvage logging is the commonest post-fire emergency action, but has unclear ecological effects. In the Mediterranean Basin, drought periods and fire regimes are changing and forest management should be adapted. In summer 2009, a mid-high severity fire burned 968 ha of Aleppo pine [...] Read more.

Salvage logging is the commonest post-fire emergency action, but has unclear ecological effects. In the Mediterranean Basin, drought periods and fire regimes are changing and forest management should be adapted. In summer 2009, a mid-high severity fire burned 968 ha of Aleppo pine (Pinus halepensis Mill.) forest in southeast Spain, which was submitted to salvage logging six months later. In spring 2010, plots were set in untreated and logged areas to monitor the recruitment and survival of the main tree species and three companion species: Stipa tenacissima L. (resprouter), Cistus clusii Dunal and Rosmarinus officinalis L. (obligate seeders). We evaluated responses to different scenarios in relation to intensification of summer droughts and forest management to obtain differences in water stress, growth, and gas exchange to cope with summer drought. Drought was induced by using rain-exclusion shelters and recorded ecophysiological characteristics were obtained with a portable gas exchange system. The main tree species recruitment was poor, but companion species showed a high survival ratio. Lower water stress was found for obligate seeder seedlings, which was higher in logged areas with induced drought. The initial post-fire stage was similar for the studied areas. However, after two drought periods (2010 and 2011), significant differences were found in the morphological and ecophysiological responses. In the unmanaged area, the biggest size of individuals due to the most marked increases in height and coverage were observed mainly in resprouter S. tenacissima. In the area submitted to salvage logging, the growth ratios in plots with induced drought were lower, mainly for seeders. Greater productivity was related to higher transpiration, stomatal conductance, and net photosynthetic ratio, but lower water use efficiency was found in obligate seeders with no drought induction, and S. tenacissima obtained higher values in untreated areas. Our results confirm that both forest management and intensification of summer droughts influenced the resilience and productivity of the ecosystems in the short term. Adaptive forest management after fire can imply successful survival and recovery of plant communities in the mid to long term. This study provide a scientific basis to develop tools for the post-fire restoration of serotinous pine forests occurring in low-altitudinal areas of the Mediterranean Basin, prone to summer droughts and fire events. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

881 KiB

Open AccessArticle

Modeling Forest Lightning Fire Occurrence in the Daxinganling Mountains of Northeastern China with MAXENT

by Feng Chen, Yongsheng Du, Shukui Niu and Jinlong Zhao

Forests 2015, 6(5), 1422-1438; https://doi.org/10.3390/f6051422 - 24 Apr 2015

Cited by 63 | Viewed by 7857

Abstract

Forest lightning fire is a recurrent and serious problem in the Daxinganling Mountains of northeastern China. Information on the spatial distribution of fire danger is needed to improve local fire prevention actions. The Maxent (Maximun Entropy Models), which is prevalent in modeling habitat [...] Read more.

Forest lightning fire is a recurrent and serious problem in the Daxinganling Mountains of northeastern China. Information on the spatial distribution of fire danger is needed to improve local fire prevention actions. The Maxent (Maximun Entropy Models), which is prevalent in modeling habitat distribution, was used to predict the possibility of lightning fire occurrence in a 1 × 1 km grid based on history fire data and environment variables in Daxinganling Mountains during the period 2005–2010.We used a jack-knife test to assess the independent contributions of lightning characteristics, meteorological factors, topography and vegetation to the goodness-of-fit of models and evaluated the prediction accuracy with the kappa statistic and AUC (receiver operating characteristic curve) analysis. The results showed that rainfall, number of strikes and lightning current intensity were major factors, and vegetation and geographic variable were secondary, in affecting lightning fire occurrence. The predicted model performs well in terms of accuracy, with an average AUC and maximum kappa value of 0.866 and 0.782, respectively, for the validation sample. The prediction accuracy also increased with the sample size. Our study demonstrated that the Maxent model can be used to predict lightning fire occurrence in the Daxinganling Mountains. This model can provide guidance to forest managers in spatial assessment of daily fire danger. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

2514 KiB

Open AccessArticle

An Exploratory Spatial Analysis of Social Vulnerability and Smoke Plume Dispersion in the U.S. South

by Cassandra Johnson Gaither, Scott Goodrick, Bryn Elise Murphy and Neelam Poudyal

Forests 2015, 6(5), 1397-1421; https://doi.org/10.3390/f6051397 - 24 Apr 2015

Cited by 18 | Viewed by 6343

Abstract

This study explores the spatial association between social vulnerability and smoke plume dispersion at the census block group level for the 13 southern states in the USDA Forest Service’s Region 8. Using environmental justice as a conceptual basis, we use Exploratory Spatial Data [...] Read more.

This study explores the spatial association between social vulnerability and smoke plume dispersion at the census block group level for the 13 southern states in the USDA Forest Service’s Region 8. Using environmental justice as a conceptual basis, we use Exploratory Spatial Data Analysis to identify clusters or “hot spots” for the incidence of both higher than average socially marginal populations and plume dispersion. The larger health disparities and environmental justice literature suggests that lower income and minority populations in the U.S. face greater exposure than middle/upper income, non-minority populations to environmental pollutants; however, we are aware of only a few studies examining this relationship in the context of population exposure to wildfires or prescribed fires in the U.S. South, despite the high occurrence of wildfires in the region. Analyses were conducted across five ecoregions in the South and for winter and spring/summer seasons. Results by ecoregion show significant spatial clustering of high social vulnerability block groups in the vicinity of block groups with a high number of smoke plumes (i.e., “hot spots”). Overall, however, socially vulnerable communities are not exposed to more smoke than non-socially vulnerable communities. Data limitations and suggestions for further research are discussed. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

352 KiB

Open AccessArticle

Source Material and Concentration of Wildfire-Produced Pyrogenic Carbon Influence Post-Fire Soil Nutrient Dynamics

by Lucas A. Michelotti and Jessica R. Miesel

Forests 2015, 6(4), 1325-1342; https://doi.org/10.3390/f6041325 - 21 Apr 2015

Cited by 20 | Viewed by 7013 | Correction

Abstract

Pyrogenic carbon (PyC) is produced by the thermal decomposition of organic matter in the absence of oxygen (O). PyC affects nutrient availability, may enhance post-fire nitrogen (N) mineralization rates, and can be a significant carbon (C) pool in fire-prone ecosystems. Our objectives were [...] Read more.

Pyrogenic carbon (PyC) is produced by the thermal decomposition of organic matter in the absence of oxygen (O). PyC affects nutrient availability, may enhance post-fire nitrogen (N) mineralization rates, and can be a significant carbon (C) pool in fire-prone ecosystems. Our objectives were to characterize PyC produced by wildfires and examine the influence that contrasting types of PyC have on C and N mineralization rates. We determined C, N, O, and hydrogen (H) concentrations and atomic ratios of charred bark (BK), charred pine cones (PC), and charred woody debris (WD) using elemental analysis. We also incubated soil amended with BK, PC, and WD at two concentrations for 60 days to measure C and N mineralization rates. PC had greater H/C and O/C ratios than BK and WD, suggesting that PC may have a lesser aromatic component than BK and WD. C and N mineralization rates decreased with increasing PyC concentrations, and control samples produced more CO₂ than soils amended with PyC. Soils with PC produced greater CO₂ and had lower N mineralization rates than soils with BK or WD. These results demonstrate that PyC type and concentration have potential to impact nutrient dynamics and C flux to the atmosphere in post-fire forest soils. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

264 KiB

Open AccessCommunication

Anomalies of the Austrian Forest Fire Regime in Comparison with Other Alpine Countries: A Research Note

by Mortimer M. Müller, Harald Vacik and Eva Valese

Forests 2015, 6(4), 903-913; https://doi.org/10.3390/f6040903 - 24 Mar 2015

Cited by 15 | Viewed by 7147

Abstract

In recent years, Austria has experienced highly variable forest fire activity with new record values regarding the number of fires and sizes of burned areas. Single seasons in 2011, 2012 and 2013 showed 20-year-peaks and significant differences regarding fire activity. A statistical overview [...] Read more.

In recent years, Austria has experienced highly variable forest fire activity with new record values regarding the number of fires and sizes of burned areas. Single seasons in 2011, 2012 and 2013 showed 20-year-peaks and significant differences regarding fire activity. A statistical overview of datasets from Austria, Switzerland, Italy and Slovenia is given, allowing a preliminary comparison between the Alpine countries. Higher temperatures in combination with local dry weather conditions are hypothesized as reasons for the observed anomalies. Further analysis will be done with new climatic data in high spatial resolution from the “AgroDroughtAustria” project to confirm these preliminary findings. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Graphical abstract

378 KiB

Open AccessArticle

Simulation of Quaking Aspen Potential Fire Behavior in Northern Utah, USA

by R. Justin DeRose and A. Joshua Leffler

Forests 2014, 5(12), 3241-3256; https://doi.org/10.3390/f5123241 - 15 Dec 2014

Cited by 6 | Viewed by 6113

Abstract

Current understanding of aspen fire ecology in western North America includes the paradoxical characterization that aspen-dominated stands, although often regenerated following fire, are “fire-proof”. We tested this idea by predicting potential fire behavior across a gradient of aspen dominance in northern Utah using [...] Read more.

Current understanding of aspen fire ecology in western North America includes the paradoxical characterization that aspen-dominated stands, although often regenerated following fire, are “fire-proof”. We tested this idea by predicting potential fire behavior across a gradient of aspen dominance in northern Utah using the Forest Vegetation Simulator and the Fire and Fuels Extension. The wind speeds necessary for crowning (crown-to-crown fire spread) and torching (surface to crown fire spread) were evaluated to test the hypothesis that predicted fire behavior is influenced by the proportion of aspen in the stand. Results showed a strong effect of species composition on crowning, but only under moderate fire weather, where aspen-dominated stands were unlikely to crown or torch. Although rarely observed in actual fires, conifer-dominated stands were likely to crown but not to torch, an example of “hysteresis” in crown fire behavior. Results support the hypothesis that potential crown fire behavior varies across a gradient of aspen dominance and fire weather, where it was likely under extreme and severe fire weather, and unlikely under moderate and high fire weather. Furthermore, the “fire-proof” nature of aspen stands broke down across the gradient of aspen dominance and fire weather. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

4446 KiB

Open AccessArticle

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

by Christopher S. R. Neigh, Douglas K. Bolton, Jennifer J. Williams and Mouhamad Diabate

Forests 2014, 5(12), 3169-3198; https://doi.org/10.3390/f5123169 - 12 Dec 2014

Cited by 16 | Viewed by 7375

Abstract

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, [...] Read more.

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration’s (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer’s and user’s accuracies of 0.21 ± 0.06 to 0.38 ± 0.05 for insect disturbance, 0.23 ± 0.07 to 1 ± 0 for burned area and 0.74 ± 0.03 to 0.76 ± 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer’s and user’s accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Graphical abstract

338 KiB

Open AccessArticle

Effects of a Wildfire on Selected Physical, Chemical and Biochemical Soil Properties in a Pinus massoniana Forest in South China

by Li Xue, Qiujing Li and Hongyue Chen

Forests 2014, 5(12), 2947-2966; https://doi.org/10.3390/f5122947 - 25 Nov 2014

Cited by 66 | Viewed by 9601

Abstract

Pinus massoniana forests bordering South China are often affected by wildfires. Fires cause major changes in soil properties in many forest types but little is known about the effects of fire on soil properties in these P. massoniana forests. Such knowledge is important [...] Read more.

Pinus massoniana forests bordering South China are often affected by wildfires. Fires cause major changes in soil properties in many forest types but little is known about the effects of fire on soil properties in these P. massoniana forests. Such knowledge is important for providing a comprehensive understanding of wildfire effects on soil patterns and for planning appropriate long-term forest management in these forests. Changes in soil physical properties, carbon, nutrients, and enzymes were investigated in a P. massoniana forest along a wildfire-induced time span consisting of an unburned soil, and soils 0, one, four, and seven years post-fire. Soil (0–10 cm) was collected from burned and unburned sites immediately and one, four, and seven years after a wildfire. The wildfire effects on soil physical and chemical properties and enzyme activities were significantly different among treatment variation, time variation, and treatment-by-time interaction. Significant short-term effects on soil physical, chemical, and biological properties were found, which resulted in a deterioration of soil physical properties by increasing soil bulk density and decreasing macropores and capillary moisture. Soil pH increased significantly in the soil one-year post-fire. Carbon, total nitrogen (N) and phosphorus (P), and available N and P increased significantly immediately and one year after the wildfire and decreased progressively to concentrations lower than in the unburned soil. Total potassium (K) and exchangeable K increased immediately after the wildfire and then continuously decreased along the burned time-span. Urease, acid phosphatase, and catalase activities significantly decreased compared to those in the unburned soil. In fire-prone P. massoniana forests, wildfires may significantly influence soil physical properties, carbon, nutrients, and enzyme activity. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Figure 1

1145 KiB

Open AccessArticle

Microclimate and Modeled Fire Behavior Differ Between Adjacent Forest Types in Northern Portugal

by Anita Pinto and Paulo M. Fernandes

Forests 2014, 5(10), 2490-2504; https://doi.org/10.3390/f5102490 - 17 Oct 2014

Cited by 11 | Viewed by 7744

Abstract

Fire severity varies with forest composition and structure, reflecting micrometeorology and the fuel complex, but their respective influences are difficult to untangle from observation alone. We quantify the differences in fire weather between different forest types and the resulting differences in modeled fire [...] Read more.

Fire severity varies with forest composition and structure, reflecting micrometeorology and the fuel complex, but their respective influences are difficult to untangle from observation alone. We quantify the differences in fire weather between different forest types and the resulting differences in modeled fire behavior. Collection of in-stand weather data proceeded during two summer periods in three adjacent stands in northern Portugal, respectively Pinus pinaster (PP), Betula alba (BA), and Chamaecyparis lawsoniana (CL). Air temperature, relative humidity and wind speed varied respectively as CL < PP < BA, PP < CL < BA, and CL < BA < PP. Differences between PP and the other types were greatest during the warmest and driest hours of the day in a sequence of 10 days with high fire danger. Estimates of daytime moisture content of fine dead fuels and fire behavior characteristics for this period, respectively, from Behave and BehavePlus, indicate a CL < BA < PP gradient in fire potential. High stand density in CL and BA ensured lower wind speed and higher fuel moisture content than in PP, limiting the likelihood of an extreme fire environment. However, regression tree analysis revealed that the fire behavior distinction between the three forest types was primarily a function of the surface fuel complex, and more so during extreme fire weather conditions. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures

Graphical abstract

Review

Jump to: Research, Other

537 KiB

Open AccessReview

Tools for Assessing the Impacts of Climate Variability and Change on Wildfire Regimes in Forests

by Hety Herawati, José Ramón González-Olabarria, Arief Wijaya, Christopher Martius, Herry Purnomo and Rubeta Andriani

Forests 2015, 6(5), 1476-1499; https://doi.org/10.3390/f6051476 - 30 Apr 2015

Cited by 11 | Viewed by 9937

Abstract

Fire is an intrinsic element of many forest ecosystems; it shapes their ecological processes, determines species composition and influences landscape structure. However, wildfires may: have undesirable effects on biodiversity and vegetation coverage; produce carbon emissions to the atmosphere; release smoke affecting human health; [...] Read more.

Fire is an intrinsic element of many forest ecosystems; it shapes their ecological processes, determines species composition and influences landscape structure. However, wildfires may: have undesirable effects on biodiversity and vegetation coverage; produce carbon emissions to the atmosphere; release smoke affecting human health; and cause loss of lives and property. There have been increasing concerns about the potential impacts of climate variability and change on forest fires. Climate change can alter factors that influence the occurrence of fire ignitions, fuel availability and fuel flammability. This review paper aims to identify tools and methods used for gathering information about the impacts of climate variability and change on forest fires, forest fuels and the probability of fires. Tools to assess the impacts of climate variability and change on forest fires include: remote sensing, dynamic global vegetation and landscape models, integrated fire-vegetation models, fire danger rating systems, empirical models and fire behavior models. This review outlines each tool in terms of its characteristics, spatial and temporal resolution, limitations and applicability of the results. To enhance and improve tool performance, each must be continuously tested in all types of forest ecosystems. Full article

(This article belongs to the Special Issue Climate Change and Forest Fire)

► Show Figures