Marc Gracia

ENVIRONMENTAL AND HUMAN FACTORS INFLUENCING FIRE TRENDS IN ENSO AND NON-ENSO YEARS IN TROPICAL MEXICO

Tropical and subtropical areas present the vast majority of contemporary global fires. Despite the human origin of most of these fires, little is known of how environmental and socioeconomic variables contribute to the spatial patterns of fire incidence and burned areas. The tropical Mexican State of Chiapas represents a good case study to analyze these interactions, due to the availability of official data, and its similarities to other tropical countries, in terms of environmental and socioeconomic characteristics. This study evaluates the relative importance of human-related and environmental variables in determining the distribution of the number of fires and area burned in the tropical State of Chiapas in years of normal and extreme climatic conditions (non-El Nino vs. El Nino). We have searched for causal relationships among fire, environmental, and socioeconomic variables in Chiapas using path analysis. Results of this study show a major importance of environmental variables in non-El Nino years, s...

Factors influencing the pattern of fire severities in a large wildfire under extreme meteorological conditions in the Mediterranean basin.

In Mediterranean ecosystems, large fires frequently burn under extreme meteorological conditions, but they are usually characterized by a spatial heterogeneity of burn severities. The way in which such mixed-severity fires are a result of fuels, topography and weather remains poorly understood. We computed fire severity of a large wildfire that occurred in Catalonia, Spain, as the difference between the post- and pre-fire Normalized Difference Vegetation Index (NDVI) values obtained through Landsat images. Fuel and topographic variables were derived from remote sensing, and fire behavior variables were obtained from an exhaustive reconstruction of the fire. Results showed that fire severity had a negative relationship with percentage of canopy cover, i.e. green surviving plots were mainly those with more forested conditions. Of the topographic variables, only aspect had a significant effect on fire severity, with higher values in southern than in northern slopes. Fire severity was higher in head than in flank and back fires. The interaction of these two variables was significant, with differences between southern and northern aspects being small for head fires, but increasing in flank and back fires. The role of these variables in determining the pattern of fire severities is of primary importance for interpreting the current landscapes and for establishing effective fire prevention and extinction policies.

Fuel types and crown fire potential in Pinus halepensis forests

There is a lack of knowledge to identify and classify forest structures according to the risk of crown fires, especially in Mediterranean regions. In this study, for the first time, we use real information, obtained after a wildfire that burnt under extreme meteorological conditions, to classify forest structures of Pinus halepensis into fuel types as a function of crown fire potential. We identified fourteen forest structures which characterize many forest types in Western Mediterranean areas depending on canopy closure, number of tree layers, percent of each tree layer and overall tree density. By using the pattern of fire types that burnt the most numerous forest structures, we have identified four fire hazard groups of forest structures which are considered different fuel types. The first two had the lowest risk of active crown fires and they differed in the proportion of surface fires and passive crown fires. The third fuel type was the threshold between structures with low and high extreme fire behavior; while the fourth had a high risk of active crown fires. Firefighters and forest managers who are demanding this kind of schema, will test and upgrade this classification of fuel types in function of crown fire potential during future wildfires.

A quantitative comparison of methods for classifying burned areas with LISS¿III imagery

Environmental agencies frequently require tools for quick assessments of areas affected by large fires. Remote sensing techniques have been reported as efficient tools to evaluate the effects of fire. However, there exist few quantitative comparisons about the performance of the diverse methods. This study quantitatively evaluated the accuracy of five different techniques, a field survey and four satellite‐based techniques, in order to quickly classify a large forest fire that occurred in 1998 in Solsonès (north‐east Spain) by means of an IRS LISS‐III image. Three pure classes were determined: burned area, unburned vegetation, and bare soil; along with a non‐pure class that we called mixed area. These selected techniques were included into a tree classifier to investigate their partial contribution to the final classification. The most accurate methods when focusing on pure classes were those directly related to the spectral characteristics of the pixel: Reflectance Data and Spectral Unmixing (82% of overall accuracy), versus the poorer performances of Vegetation Indices (70%), Textural measures (72%) and the field survey (68.6%). Since no image processing technique was applied to the Raw Reflectance Data, it can be considered the most cost‐effective method, and the tree classifier reinforces its importance. The results of this study reveal that time consuming and expensive methods are not necessarily the most accurate, especially when potentially easily distinguishable classes are involved.

Habitat determinants of abundance, structure and composition of flying Hymenoptera communities in mountain old-growth forests

1. Old‐growth forests have features that endow them with an extraordinary ecological value. These forests are sources of habitat diversity and, consequently, biodiversity, which makes them a basic objective of conservation programs. Insects have been traditionally used as indicators of forest condition.

Composition and habitat use of small mammals in old-growth mountain forests

Old-growth mountain forests in the Pyrenees have natural gap dynamics, a well-developed shrub layer and a large amount of dead wood. Small mammal communities in two types of old-growth forests, silver fir and mountain pine, were studied in July and September in 2006 and 2007. Four species were trapped: bank vole (Myodes glareolus), wood mouse (Apodemus sylvaticus), garden dormouse (Eliomys quercinus) and common shrew (Sorex araneus). Bank voles and wood mice were most commonly trapped (78% of all captures). There were no differences in community composition in the two forest types, although the bank vole was more often captured in the silver fir than in the mountain pine forest. Mammals were more frequently captured at trap stations with high shrub cover, high tree regeneration cover and low herbaceous cover. Our results show that forest structure and, to a lesser extent, forest type determine small mammal community structure, and specifically fine-scale occurrence patterns, in these old-growth forests.