Filipe X. Catry

Modeling and mapping wildfire ignition risk in Portugal

Portugal has the highest density of wildfire ignitions among southern European countries. The ability to predict the spatial patterns of ignitions constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and firefighting resources allocation. In this study, we analyzed 127 490 ignitions that occurred in Portugal during a 5-year period. We used logistic regression models to predict the likelihood of ignition occurrence, using a set of potentially explanatory variables, and produced an ignition risk map for the Portuguese mainland. Results show that population density, human accessibility, land cover and elevation are important determinants of spatial distribution of fire ignitions. In this paper, we demonstrate that it is possible to predict the spatial patterns of ignitions at the national level with good accuracy and using a small number of easily obtainable variables, which can be useful in decision-making for wildfire management.

Regional variations in wildfire susceptibility of land-cover types in Portugal: implications for landscape management to minimize fire hazard

Patterns of wildfire occurrence at the landscape level were characterised during the period 1990–94 in Portugal. Based on land-cover information within 5591 burned patches (larger than 5 ha) and in the surrounding landscape, selection ratio functions were used to measure fire preference or avoidance for different land-cover types in 12 regions of the country. Shrublands were the most fire-prone land cover, whereas annual crops, permanent crops and agro-forestry systems were the most avoided by fire. In terms of forest types, conifer plantations were more susceptible to fire than eucalyptus, and broadleaved forests were the least fire-prone. There were regional variations in land-cover susceptibility to fire, which may be explained by differences in climate, management, ignition patterns, firefighting strategies, and regional availability. A cluster analysis of regional variations in selection ratios for all land covers allowed the identification of three main geographical areas with similar fire selection patterns. These results can be used for planning landscape-scale fuel management in order to create landscapes with a lower fire hazard.

A conceptual model of sprouting responses in relation to fire damage: an example with cork oak (Quercus suber L.) trees in Southern Portugal

The sprouting response types of 1,151 cork oak (Quercus suber) trees one and half years after a wildfire in southern Portugal were characterised. It was hypothesised that different response types should occur according to the following conceptual model: an increased level of damage (fire severity) on a sprouting tree that suffered a crown fire was expected to be reflected in a sequence of four alternative events, namely (a) resprouting exclusively from crown, (b) simultaneous resprouting from crown and base, (c) resprouting exclusively from base and (d) plant death. To assess whether the level of expected damage was influenced by the level of protection from disturbance, we explored the relationships between response types and tree size, bark thickness and cork stripping, using an information-theoretic approach. The more common response type was crown resprouting (68.8% of the trees), followed by plant death (15.8%), simultaneous resprouting from crown and base (10.1%) and basal resprouting (5.3%). In agreement with the conceptual model, trees which probably suffered a higher level of damage by fire (larger trees with thinner bark; exploited for cork) died or resprouted exclusively from base. On the other hand, trees that were well protected (smaller trees with thicker bark not exploited for cork) were able to rebuild their canopy through crown resprouting. Simultaneous resprouting from the crown and base was determined mainly by tree size, and it was more common in smaller trees.

Assessing the relative fire proneness of different forest types in Portugal

Abstract We have assessed the fire proneness of the main forest types in Portugal classified according to the main species, using three different approaches: the use of resource selection ratios applied to burned patches, the proportion of randomly located plots that were burned and the proportion of burned National Forest Inventory plots. The results allowed ranking fire proneness according to the following decreasing order: maritime pine forests, eucalyptus forests, unspecified broadleaf forests, unspecified conifer forests, cork oak forests, chestnut forests, holm oak forests and stone pine forests. In order to understand the obtained results we have assessed the structure of the different forest types using the percent cover of seven vegetation layers (C1–C7), a Tree Dominance Index, a Height Index and a Cover Index (IC). Structural variables and stand composition were used to predict fire probability according to binary logistic modelling. Only four structural variables and stand composition provided significant results, the latter being the most important variable for explaining fire probability. These models were used to predict fire probability for different stand types as a function of IC.

Forest fires in cork oak (Quercus suber L.) stands in Portugal

Fire and cork can be considered both the most serious problem and the most valuable resource of Portuguese forests. The existence of important areas of burned cork oak stands resulting from severe fire seasons in recent years is an environmental problem which deserves special attention. This paper makes a multidisciplinary survey of the problem of burned cork oak stands focusing on: the dimensions of the problem in Portugal, the remarkable resistance of cork oak to fire, the post‐fire management of cork oak stands, and the economic and ecological effects of fire in cork oak stands. Particular emphasis is given to knowledge gaps in this context.

Cork oak vulnerability to fire: the role of bark harvesting, tree characteristics and abiotic factors

Forest ecosystems where periodical tree bark harvesting is a major economic activity may be particularly vulnerable to disturbances such as fire, since debarking usually reduces tree vigour and protection against external agents. In this paper we asked how cork oak Quercus suber trees respond after wildfires and, in particular, how bark harvesting affects post-fire tree survival and resprouting. We gathered data from 22 wildfires (4585 trees) that occurred in three southern European countries (Portugal, Spain and France), covering a wide range of conditions characteristic of Q. suber ecosystems. Post-fire tree responses (tree mortality, stem mortality and crown resprouting) were examined in relation to management and ecological factors using generalized linear mixed-effects models. Results showed that bark thickness and bark harvesting are major factors affecting resistance of Q. suber to fire. Fire vulnerability was higher for trees with thin bark (young or recently debarked individuals) and decreased with increasing bark thickness until cork was 3–4 cm thick. This bark thickness corresponds to the moment when exploited trees are debarked again, meaning that exploited trees are vulnerable to fire during a longer period. Exploited trees were also more likely to be top-killed than unexploited trees, even for the same bark thickness. Additionally, vulnerability to fire increased with burn severity and with tree diameter, and was higher in trees burned in early summer or located in drier south-facing aspects. We provided tree response models useful to help estimating the impact of fire and to support management decisions. The results suggested that an appropriate management of surface fuels and changes in the bark harvesting regime (e.g. debarking coexisting trees in different years or increasing the harvesting cycle) would decrease vulnerability to fire and contribute to the conservation of cork oak ecosystems.

Characterizing and modelling the spatial patterns of wildfire ignitions in Portugal: fire initiation and resulting burned area.

According to the statistics Portugal has the highest density of wildfire ignitions among southern European countries. The ability to predict ignition occurrence constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and fire fighting resources allocation. In this study we used a database with information about 127 490 fire ignitions that occurred in Portugal during a five year period. We performed frequency analysis to characterize the occurrence of wildfire ignitions in relation to both human and environmental variables and compared the spatial patterns of ignitions which originated fires larger or smaller than 500 ha. We also used logistic regression models to predict the relative probability of ignition occurrence, as a function of the resulting fire size. Results show that fire ignitions are strongly related to human presence and activity, and that the spatial patterns of ignitions are different for larger or smaller wildfires. Larger wildfires started in areas with lower population density, more distant from the main roads and at higher elevations, when compared to smaller fires, and also started more frequently in shrublands and forested areas. The results obtained can be useful in decision making for fire danger management.

A working prototype of a dynamic geographical information system

The objective of this work is to develop a dynamic geographical information system (DGIS) applicable for the simulation of spatio-temporal phenomena. DGIS is designed and implemented as a dynamic raster GIS in a fully integrated systems strategy using theory of modelling and simulation, discrete event systems specifications, and knowledge-based simulation methodologies. The approach accommodates the representations and operators of current GIS in a broader systems representation scheme that includes the constructs for handling continuous time, model base, multiple resolution, hierarchy, taxonomy, variable structure, and intelligent agents. DGIS is defined as an endomorphic system that can be transformed by the user into different, application-specific, spatial dynamic simulation environments depending on the models selected to fit the various aspects of its structure. In this paper we describe the theory, methods, and technologies upon which the system is designed and implemented and discuss how it can support complex spatial simulations. To probe operational applicability, an instance of DGIS is generated: a fire spread simulation environment, which is tested in the simulation of 15 real fire events.

Modelling the effects of distance on the probability of fire detection from lookouts

In the management of forest fires, early detection and fast response are known to be the two major actions that limit both fire loss and fire-associated costs. There are several inter-related factors that are crucial in producing an efficient fire detection system: the strategic placement and networking of lookout towers, the knowledge of the fire detection radius for lookout observers at a given location and the ability to produce visibility maps. This study proposes a new methodology in the field of forest fire management, using the widely accepted Fire Detection Function Model to evaluate the effect of distance and other variables on the probability that an object is detected by an observer. In spite of the known variability, the model seems robust when applied to a wide variety of situations, and the results obtained for the effective detection radius (13.4 km for poor conditions and 20.6 km for good conditions) are in general agreement with those proposed by other authors. We encourage the application of the new approach in the evaluation or planning of lookout networks, in addition to other integrated systems used in fire detection.

Landscape dynamics in Mediterranean oak forests under global change: understanding the role of anthropogenic and environmental drivers across forest types

The Mediterranean region is projected to be extremely vulnerable to global change, which will affect the distribution of typical forest types such as native oak forests. However, our understanding of Mediterranean oak forest responses to future conditions is still very limited by the lack of knowledge on oak forest dynamics and species-specific responses to multiple drivers. We compared the long-term (1966-2006) forest persistence and land cover change among evergreen (cork oak and holm oak) and deciduous oak forests and evaluated the importance of anthropogenic and environmental drivers on observed changes for Portugal. We used National Forest Inventories to quantify the changes in oak forests and explored the drivers of change using multinomial logistic regression analysis and an information theoretical approach. We found distinct trends among oak forest types, reflecting the differences in oak economic value, protection status and management schemes: cork oak forests were the most persistent (62%), changing mostly to pines and eucalypt; holm oak forests were less persistent (53.2%), changing mostly to agriculture; and deciduous oak forests were the least persistent (45.7%), changing mostly to shrublands. Drivers of change had distinct importance across oak forest types, but drivers from anthropogenic origin (wildfires, population density, and land accessibility) were always among the most important. Climatic extremes were also important predictors of oak forest changes, namely extreme temperatures for evergreen oak forests and deficit of precipitation for deciduous oak forests. Our results indicate that under increasing human pressure and forecasted climate change, evergreen oak forests will continue declining and deciduous oak forests will be replaced by forests dominated by more xeric species. In the long run, multiple disturbances may change competitive dominance from oak forests to pyrophytic shrublands. A better understanding of forest dynamics and the inclusion of anthropogenic drivers on models of vegetation change will improve predicting the future of Mediterranean oak forests.