Susete Marques

Characterization of wildfires in Portugal

Forest fires severity has increased in Portugal in the last decades. Climate change scenarios suggest the reinforcement of this severity. Forest ecosystem managers and policy-makers thus face the challenge of developing effective fire prevention policies. The characterization of forest fires is instrumental for meeting this challenge. An approach for characterizing fire occurrence in Portugal, combining the use of geographic information systems and statistical analysis techniques, is presented. Emphasis was on the relationships between ecological and socioeconomic features and fire occurrence. The number and sizes of wildfires in Portugal were assessed for three 5-year periods (1987–1991, 1990–1994, and 2000–2004). Features maps were overlaid with perimeters of forest fires, and the proportion of burned area for each period was modeled using weighted generalized linear models (WGLM). Descriptive statistics showed variations in the distribution of fire size over recent decades, with a significant increase in the number of very large fires. Modeling underlined the impact of the forest cover type on the proportion of area burned. The statistical analysis further showed that socioeconomic features such as the proximity to roads impact the probability of fires occurrence. Results suggest that this approach may provide insight needed to develop fire prevention policies.

A Bayesian Modelling of Wildfires in Portugal

In the last decade wildfires became a serious problem in Portugal due to socieconomic and climate change trends. In order to analyse wildfire data, we employ beta regression for modelling the proportion of burned wild area, under a Bayesian perspective. Our main goal is to find out fire risk factors that influence the proportion of area burned and what may make a wild area susceptible or resistant to fire. Then, we analyse wildfire data in Portugal during 1990–1994 through Bayesian normal and beta regression models that use Markov chain Monte Carlo methods for estimating quantities of interest.

decision support systems in Slovak forestry planning: a review Systémy na podporu rozhodovania v lesníckom plánovaní na Slovensku: prehľad

Abstract Project COST Action FP 0804 - FORSYS summarizes European experiences in developing and applying decision support systems for forest management. This paper introduces FORSYS methodology for the classification of current forest management problems and for the description of existing decision support systems. The paper identifies the general forestry planning problems that need to be solved in Slovakia, lists the DSS tools available in Slovakia and evaluate their ability for addressing the identified problems. Finally, the research needs and gaps in this field were identified. A comparison of the situation regarding decision support in Slovakia and both in Europe and neighbouring countries (Austria, Hungary) is introduced in order to justify the identified needs. The paper is focused on the overview of models, methods and knowledge management techniques which are available in Slovakia now. We found out that the Slovak decision support research follows the state in Europe with a significant time delay and a lack of adequate instruments for addressing the contemporary planning problems exists. Consequently, there is a strong need for the development and application of computer-based tools to support decision-making problems in forest management. Abstrakt Projekt Akcie COST FP 0804 - FORSYS zhŕňa európske skúsenosti v oblasti rozvoja a využívania systémov pre podporu rozhodovania v obhospodarovaní lesov. Predložený príspevok sa zaoberá metodikou FORSYS pre klasifikáciu súčasných problémov lesného hospodárstva a pre opis existujúcich systémov pre podporu rozhodovania. Identifikuje základné problémy lesníckeho plánovania, ktoré je potrebné riešiť na Slovensku, uvádza DSS nástroje ktoré sú k dispozícii a hodnotí ich schopnosť riešiť identifikované problémy. Na záver sú identifikované potreby výskumného riešenia a existujúce nedostatky v tejto oblasti. Na odôvodnenie zistených potrieb sa tiež uvádza porovnanie situácie v oblasti podpory rozhodovania na Slovensku so situáciou v Európe a susedných krajinách (Rakúsko, Maďarsko). Článok je zameraný na prehľad modelov a metód rozhodovania ako aj techník na manažment znalostí, ktoré sú aktuálne na Slovensku k dispozícii. Všeobecne možno konštatovať, že výskum v oblasti podpory rozhodovania na Slovensku síce sleduje stav v Európe, avšak so značným časovým oneskorením a výrazným nedostatkom vhodných nástrojov pre riešenie aktuálnych plánovacích problémov. V dôsledku toho existuje silná potreba pre vývoj a aplikácie počítačových nástrojov na podporu rozhodovania problémov hospodárenia v lesoch.

Strategic Management Scheduling

Strategic or long-term management planning plays a key role in the development of forest schedules as the temporal dimension is a determinant characteristic of all forestry production systems. In this chapter we address the representation of industrial forest strategic forest management problems as well as the interpretation of its solution. We start with a simple harvest scheduling model aiming at the maximization of economic returns while addressing concerns with the sustainability of a product flow. This policy scenario is expanded to reflect concerns with the volume in the ending inventory, with the average carbon stock, with the environmental impacts of clearcuts and with the integration of road building and maintenance decisions. Several modeling approaches are considered to represent and solve each problem. An example forest is used to illustrate all problems and how they may be addressed by each modeling approach. Several applications of the modeling approaches to strategic management planning of industrial plantations are briefly described in six Management Planning in Action boxes. A list of problems at the end of the chapter build from the same example forest to support model building, model solving and interpretation of results by readers.

Using INLA to Estimate a Highly Dimensional Spatial Model for Forest Fires in Portugal

Within the context of accessing the risk of forest fires, Amaral-Turkman et al. (Environ. Ecol. Stat. 18:601–617, 2011) have proposed a spatio-temporal hierarchical approach which jointly models the fire ignition probability and the fire’s size, in a Bayesian framework. This is recovered and applied to Portuguese forest fires data, with some necessary modifications in what concerns the format of the data (not available in a regular lattice over the territory) and also because of the estimation complications that arise due to the high dimensionality of the neighbouring structure involved. To address the latter, as it compromises the estimation via Markov Chain Monte Carlo (MCMC) methods, and having the model be recognized as a latent Gaussian model, it was chosen to do the Bayesian estimation also using an Integrated Nested Laplace Approximation approach, with real computational advantages. Corresponding methodologies and results are described and compared.