Spatial point process modeling applied to the assessment of risk factors associated to forest wildfires incidence in Castellón, Spain

During the last decades the Mediterranean zone in Europe has experienced an increment in the incidence of forest wildfires. This increase is partly explained by higher mean temperature and lower relative humidity, while socioeconomic change has lead to the abandonment of farms, resulting in an increase in an unusual accumulation of forest fuels, increasing the risk of wildfires. Mapping wildfire risk is highly important because wildfires are known to potentially lead to landscape changes and to modify fire regime by inducing potential changes in vegetation composition. Also, they pose a hazard to human property and life. Maps of wildfire risk based on statistical models provide a measure of uncertainty for the inferences derived from such risk maps, leaving a quantitative error margin for managers and decision takers. Further, some of the model parameters often have a physical or a biological interpretation which can give ecologists and forest engineers answers about scientific questions of interest. In this paper, we analyze the incidence of wildfires in the province of Castellón in Spain in order to identify risk factors associated with wildfire incidences during the years 2001–2006. We used the discrete nature of wildfire events to build such models using point process theory and methods and included information about elevation, slope, aspect, land use and distance to nearest road as covariates in our modeling process. Our results show that wildfire risk in Castellón is associated with all the covariates considered and that three land-use categories have the highest risk of wildfire incidence. Also, wildfire incidences are not independent and some degree of interaction exists, which indicates that the commonly used Poisson point process models are not applicable in this case, but instead area-interaction models should be considered

Landscape - wildfire interactions in southern Europe: implications for landscape management

ReviewEvery year approximately half a million hectares of land are burned by wildfires in southern Europe, causing large ecological and socio-economic impacts. Climate and land use changes in the last decades have increased fire risk and danger. In this paper we review the available scientific knowledge on the relationships between landscape and wildfires in the Mediterranean region, with a focus on its application for defining landscape management guidelines and policies that could be adopted in order to promote landscapes with lower fire hazard. The main findings are that (1) socio-economic drivers have favoured land cover changes contributing to increasing fire hazard in the last decades, (2) large wildfires are becoming more frequent, (3) increased fire frequency is promoting homogeneous landscapes covered by fire-prone shrublands; (4) landscape planning to reduce fuel loads may be successful only if fire weather conditions are not extreme. The challenges to address these problems and the policy and landscape management responses that should be adopted are discussed, along with major knowledge gapsinfo:eu-repo/semantics/publishedVersio

Modelling fire occurrence at regional scale. Does vegetation phenology matter?

Through its influence on biomass production, climate controls fuel availability affecting at the same time fuel moisture and flammability, which are the main determinants for fire ignition and propagation. Knowing the role of fuel phenology on fire ignition patterns is hence a key issue for fire prevention, detection, and development of mitigation strategies. The objective of this study is to quantify, at coarse scale, the role of the vegetation seasonal dynamics on fire ignition patterns of the National Park of Cilento, Vallo di Diano and Alburni (southern Italy) during 2000-2013. We applied a habitat suitability model to compare the multitemporal NDVI profiles at the locations of fire occurrence (the used habitat) with the NDVI profiles of the entire study area (the available habitat). Results demonstrated that, from May to October, wildfires occur preferentially at sites where the remotely-sensed NDVI observations have on average lower values than the available habitat. On the other hand, in the period November-April, wildfires tend to occur at sites where the corresponding NDVI observations have higher values than the available habitat. From a practical viewpoint, the proposed method can be implemented using many different ecogeographical variables simultaneously, thus integrating remotely sensed imagery with socioeconomic data, land cover, physiography or any landscape features that are thought to influence fire occurrence in the study area

Characterizing pyroregions in mainland Spain from spatial-temporal patterns of fire regime and their underlying drivers

El fuego ha coexistido de forma intrínseca en diversos ecosistemas a nivel global. En el caso de los ambientes más humanizados la acción del hombre ha alterado esos regímenes de incendio naturales por uno fundamentalmente de carácter antrópico. En el contexto de la Europa Mediterránea, el número de incendios forestales y su área quemada observados han experimentado un descenso general durante el final del siglo XX. Esto ha supuesto un declive de la incidencia del fuego en la mayoría de los ecosistemas mediterráneos históricamente afectados por incendios recurrentes. Por tanto, es evidente la alteración de los regímenes de incendio pasados, debido principalmente a la intervención humana con una política de exclusión total del fuego muy exigente.No obstante, la evolución reciente de los regímenes de incendio presenta una alta variabilidad espacial y temporal. Por otro lado, las perspectivas de futuro vaticinan un impacto creciente del factor humano (abandono del campo, gestión de los bosques y mantenimiento de la supresión excluyente), lo que consecuentemente derivará una mayor actividad de incendios debido a una mayor cantidad de combustible disponible. Asimismo, se prevén unas condiciones climáticas cada vez más propensas a generar incendios de gran superficie (mayores valores de temperatura, mayor frecuencia de olas de calor y sequías), lo que sin duda afectará negativamente tanto a los ecosistemas como las sociedades futuras.Todos estos factores hacen necesaria una adecuada zonificación de los regímenes de incendio desde una perspectiva espacio-temporal, la cual permita conocer la relación existente entre el régimen de incendios alterado y los factores socio-económicos y ambientales asociados. Así como detectar tendencias en el tiempo en regiones que experimenten un descenso de la actividad, o, por el contrario, incremento de la incidencia de incendios. Por tanto, conociendo estas zonas se podrá mejorar la gestión y prevención contra incendios forestales.Esta tesis doctoral se enfoca en enriquecer el conocimiento sobre la identificación e interpretación de regiones homogéneas de regímenes de incendio. Para ello se recurre a un amplio abanico de métodos de análisis estadísticos y de modelado espacial. La tesis se estructura de acuerdo a los siguientes objetivos: el objetivo 1 se centra en analizar la distribución espacio-temporal de las principales métricas que definen el régimen de incendio durante el periodo reciente. El objetivo 2 pretende profundizar en la influencia del riesgo meteorológico en la evolución de la actividad de los incendios. El objetivo 3 evalúa el cambio de la contribución relativa de los factores antropogénicos en los incendios forestales. El objetivo 4 se enfoca en explicar la evolución y causas de los cambios o transiciones de los regímenes de incendios durante el periodo reciente (1974-2015) y futuro (2016-2036). Finalmente, el objetivo 5 pone la atención en la traslación de la zonificación de tipologías de regímenes de incendios hacia una cartografía integral de piroregiones.Los resultados indican que los regímenes de incendio en la España peninsular han experimentado diversos cambios, principalmente una disminución considerable de la actividad de incendios en la mayor parte del territorio, aunque todavía persiste una alta actividad en el extremo norte (especialmente en invierno). Los diversos métodos de aprendizaje automático empleados, especialmente Random Forest, han demostrado su potencial en términos de revelar los factores que impulsan la evolución del régimen de incendios. Además, la proyección ARIMA ha confirmado la tendencia actual hacia una menor incidencia de incendios. Todo apunta a que las medidas preventivas deben tomar más protagonismo en áreas con un abrupto descenso de la ocurrencia, ya que son significativamente más propensas a grandes incendios a corto y medio plazo.Fire has always been an intrinsic feature in various ecosystems around the world. In environments heavily populated by humans, their actions have altered these natural fire regimes for others that are fundamentally anthropogenic in nature. In the context of Mediterranean Europe, the number of forest fires and their observed burnt area fell into a general decline during the late twentieth century, which led to a reduced incidence of fire in most Mediterranean ecosystems historically affected by recurrent fires. Therefore, the change in past fire regimes is evident, mainly due to human intervention instigating a very demanding policy of total exclusion of fire. However, the recent evolution of fire regimes presents a high spatial and temporal variability. On the other hand, future scenarios predict a growing impact of the human factor (more land abandonment, poor management of forests and adhering exclusively to suppression methods), which will result in increased fire activity due to a greater amount of available fuel. In addition, climatic conditions are expected to cause increasingly larger burned areas (higher temperatures, more frequent heat waves and droughts), which will undoubtedly have a negative effect on both ecosystems and future societies. All these factors make an adequate zoning of fire regimes necessary from a spatial-temporal perspective, which allows the relationship between the altered fire regime and associated socio-economic and environmental factors to be determined, as well as detecting temporal trends in regions with decreasing activity, or on the contrary, an increase in the incidence of fires. Therefore, finding these areas will lead to improved management and prevention of forest fires. This doctoral thesis focuses on enriching knowledge for identifying and interpreting homogeneous regions of fire regimes. A wide range of methods of statistical analysis and spatial modeling are employed. The thesis is structured according to the following objectives: Objective 1 focuses on analyzing the spatial-temporal distribution of the main features defining the fire regime during the recent period. Objective 2 aims to further describe the influence of meteorological danger on the evolution of fire activity. Objective 3 evaluates the change in the relative contribution of anthropogenic factors on forest fires. Objective 4 focuses on explaining the evolution and causes of changes or transitions in fire regimes during the recent (1974-2015) and future (2016-2036) periods. Finally, Objective 5 centers on the transfer of the zoning of fire regime typologies into an integral mapping of pyroregions The results indicate that fire regimes in mainland Spain have undergone several changes, mainly a considerable decrease in fire activity in most of the territory, although it still remains high in the north (especially in winter). The diverse machine-learning methods employed, especially Random Forest, have demonstrated their potential in terms of revealing the fire drivers behind fire regime evolution. Moreover, forecasting by the ARIMA model has confirmed the ongoing tendency towards a lower incidence of fire. All indications are that preventive measures should take greater prominence in areas with an abrupt decrease in wildfires, as they are significantly more prone to large ones in the short and medium term.<br /

Integration of Environmental Models in Spatial Data Infrastructures: A Use Case in Wildfire Risk Prediction

Achieving sustainable growth in our society implies monitoring our environment in order to measure human impact and detect relevant changes and detrimental driving factors such as wildfires and desertification. In order for experts to perform environmental modelling they need to be able to access data and models in an efficient and interoperable manner as well as share their findings to assist other professionals in decision making. In the current information society, distributed information systems are essential for sharing digital resources such as data and tools. Advances in Service-Oriented Architectures (SOA) allow for the distribution and accessibility of on-line resources such as data and tools, which served through standards-based services improve the sharing of data, models and models results. This research presents a service-oriented application that addresses the issues of interoperable access to environmental modelling capabilities as well as the mechanisms to share their results an efficiently throughout interoperable components. The aim is twofold, first we present different models for multi-scale forest fire risk prediction based on spatial point processes, and second we provide this functionality as a distributed application, that, based on international standards, such as those offered by the Open Geospatial Consortium (OGC), improves interoperable access to these models as well as the publication of the results to be shared with other interested stakeholders

How Fire History, Fire Suppression Practices and Climate Change Affect Wildfire Regimes in Mediterranean Landscapes

Available data show that future changes in global change drivers may lead to an increasing impact of fires on terrestrial ecosystems worldwide. Yet, fire regime changes in highly humanised fire-prone regions are difficult to predict because fire effects may be heavily mediated by human activities We investigated the role of fire suppression strategies in synergy with climate change on the resulting fire regimes in Catalonia (north-eastern Spain). We used a spatially-explicit fire-succession model at the landscape level to test whether the use of different firefighting opportunities related to observed reductions in fire spread rates and effective fire sizes, and hence changes in the fire regime. We calibrated this model with data from a period with weak firefighting and later assess the potential for suppression strategies to modify fire regimes expected under different levels of climate change. When comparing simulations with observed fire statistics from an eleven-year period with firefighting strategies in place, our results showed that, at least in two of the three sub-regions analysed, the observed fire regime could not be reproduced unless taking into account the effects of fire suppression. Fire regime descriptors were highly dependent on climate change scenarios, with a general trend, under baseline scenarios without fire suppression, to large-scale increases in area burnt. Fire suppression strategies had a strong capacity to compensate for climate change effects. However, strong active fire suppression was necessary to accomplish such compensation, while more opportunistic fire suppression strategies derived from recent fire history only had a variable, but generally weak, potential for compensation of enhanced fire impacts under climate change. The concept of fire regime in the Mediterranean is probably better interpreted as a highly dynamic process in which the main determinants of fire are rapidly modified by changes in landscape, climate and socioeconomic factors such as fire suppression strategies

Burned area prediction with semiparametric models

[Abstract] Wildfires are one of the main causes of forest destruction, especially in Galicia (north-west Spain), where the area burned by forest fires in spring and summer is quite high. This work uses two semiparametric time-series models to describe and predict the weekly burned area in a year: autoregressive moving average (ARMA) modelling after smoothing, and smoothing after ARMA modelling. These models can be described as a sum of a parametric component modelled by an autoregressive moving average process and a non-parametric one. To estimate the non-parametric component, local linear and kernel regression, B-splines and P-splines were considered. The methodology and software were applied to a real dataset of burned area in Galicia for the period 1999–2008. The burned area in Galicia increases strongly during summer periods. Forest managers are interested in predicting the burned area to manage resources more efficiently. The two semiparametric models are analysed and compared with a purely parametric model. In terms of error, the most successful results are provided by the first semiparametric time-series model.Ministerio del Medio Ambiente, Rural y Marino; PSE-310000-2009-4Ministerio de Economía y Competitividad; MTM2014-52876-RMinisterio de Economía y Competitividad; MTM2011-22392Ministerio de Economía y Competitividad; MTM2013-41383-PXunta de Galicia; CN2012/130Xunta de Galicia; 07MRU035291PRCOST Action/UE COST-OC-2008-1-2124