Spatial distribution of vectors of Ross River virus and Barmah Forest virus on Russell Island, Moreton Bay, Queensland

We used a network of 20 carbon dioxide- and octenol-supplemented light traps to sample adult mosquitoes throughout Russell Island in southern Moreton Bay, south-east Queensland. Between February and April 2001, an estimated 1365 564 adult female mosquitoes were collected. In contrast to an average catch of 9754 female mosquitoes per trap night on Russell Island, reference traps set on Macleay Island and on the mainland returned average catches of 3172 and 222, respectively. On Russell Island, Ochlerotatus vigilax (Skuse), Coquillettidia linealis (Skuse), Culex annulirostris Skuse and Verrallina funerea (Theobald), known or suspected vectors of Ross River (RR) and/or Barmah Forest (BF) viruses, comprised 89.6% of the 25 taxa collected. When the spatial distributions of the above species were mapped and analysed using local spatial statistics, all were found to be present in highest numbers towards the southern end of the island during most of the 7 weeks. This indicated the presence of more suitable adult harbourage sites and/or suboptimal larval control efficacy. As immature stages and the breeding habitat of Cq. linealis are as yet undescribed, this species in particular presents a considerable impediment to proposed development scenarios. The method presented here of mapping the numbers of mosquitoes throughout a local government area allows specific areas that have high vector numbers to be defined.

Field hydraulic properties of an Alfisol under various fallow systems in southwestern Nigeria

The effects of various fallow management systems and cropping intensities on water infiltration were measured on an Alfisol at Ibadan in southwestern Nigeria. The objective was to determine the influence of the land use systems (a combination of crop-fallow sequences and intercropping types) on soil hydraulic properties obtained by disc permeameter and double-ring infiltration measurements. The experiment was established in 1989 as a split-plot design with four replications. The main plots were natural fallow, planted Pueraria phaseoloides and planted Leucaena leucocephala. The subplots were 1 year of maize/cassava intercrop followed by 3-year fallow (25% cropping intensity), or 2-year fallow (33% cropping intensity), or 1-year fallow (50% cropping intensity), or no fallow period (100% cropping intensity). Water infiltration rates and sorptivities were measured under saturated and unsaturated flow. Irrespective of land use, infiltration rates at the soil surface (121-324 cm h(-1)) were greater than those measured at 30 cm depth (55-144 cm h(-1)). This indicated that fewer large pores were present below 30 cm depth compared with 0-30 cm, depth. Despite some temporal variation, sorptivities with the highest mean value of 93.5 cm h(-1/2) increased as the cropping intensity decreased, suggesting a more continuous macropore system under less intensive land use systems. This was most likely due to continuous biopores created by perennial vegetation under long fallow systems. Intercropped maize and cassava yields also increased as cropping intensity decreased. The weak relationship between crop yields and hydraulic conductivity/infiltration rates suggests that the rates were not limiting.

Prescribed burning impact on forest soil properties – a fuzzy boolean nets approach

The Portuguese northern forests are often and severely affected by wildfires during the Summer season. These occurrences significantly affect and negatively impact all ecosystems, namely soil, fauna and flora. In order to reduce the occurrences of natural wildfires, some measures to control the availability of fuel mass are regularly implemented. Those preventive actions concern mainly prescribed burnings and vegetation pruning. This work reports on the impact of a prescribed burning on several forest soil properties, namely pH, soil moisture, organic matter content and iron content, by monitoring the soil self-recovery capabilities during a one year span. The experiments were carried out in soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, Portugal, which was kept intact from prescribed burnings during a period of four years. Soil samples were collected from five plots at three different layers (0–3, 3–6 and 6–18) 1 day before prescribed fire and at regular intervals after the prescribed fire. This paper presents an approach where Fuzzy Boolean Nets (FBN) and Fuzzy reasoning are used to extract qualitative knowledge regarding the effect of prescribed fire burning on soil properties. FBN were chosen due to the scarcity on available quantitative data. The results showed that soil properties were affected by prescribed burning practice and were unable to recover their initial values after one year.

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

A Review on the Characterization of Signals and Systems by Power Law Distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Forest fire detection with a small fixed wing autonomous aerial vehicle

In this work a forest fire detection solution using small autonomous aerial vehicles is proposed. The FALCOS unmanned aerial vehicle developed for remote-monitoring purposes is described. This is a small size UAV with onboard vision processing and autonomous flight capabilities. A set of custom developed navigation sensors was developed for the vehicle. Fire detection is performed through the use of low cost digital cameras and near-infrared sensors. Test results for navigation and ignition detection in real scenario are presented.

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.

FireSpotter a VGI-Based Forest Fire Reporting System

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Geospatial assessment of pest-induced forest damage through the use of UAV-bases NIR imaging and Gi-technology

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Predicting the impacts of climate change on the distribution and conservation of endemic forest land snails of Madeira Island

Climate change is emerging as one of the major threats to natural communities of the world’s ecosystems; and biodiversity hotspots, such as Madeira Island, might face a challenging future in the conservation of endangered land snails’ species. With this thesis, progresses have been made in order to properly understand the impact of climate on these vulnerable taxa; and species distribution models coupled with GIS and climate change scenarios have become crucial to understand the relations between species distribution and environmental conditions, identifying threats and determining biodiversity vulnerability. With the use of MaxEnt, important changes in the species suitable areas were obtained. Laurel forest species, highly dependent on precipitation and relative humidity, may face major losses on their future suitable areas, leading to the possible extinction of several endangered species, such as Leiostyla heterodon. Despite the complexity of the biological systems, the intrinsic uncertainty of species distribution models and the lack of information about land snails’ functional traits, this analysis contributed to a pioneer study on the impacts of climate change on endemic species of Madeira Island. The future inclusion of predictions of the effect of climate change on species distribution as part of IUCN assessments could contribute to species prioritizing, promoting specific management actions and maximizing conservation investment.

Growth rate of a terra firme rain forest in Brazilian Amazonia over an eight-year period in response to logging

This paper deals with growth rates of trees > 5cm dbh over an eight-year period from 257 species at the Tapajós National Forest. The discussion is centred on the behaviour of the forest after logging. Permanent sample plots were established in 1981 and measured at the first time. The area was logged in 1982. Measurements after logging occurred in 1983, 1987 and 1989. Considering all species together, diameter increment was similar for both intensities of logging until five years after logging. Light-demanding species showed significantly higher growth rates than shade-tolerant species in the logged forest, with greater increment in the heavier treatment intensity. Commercial species also had higher growth rates in the heavier logged area, although those were significantly different only in the period from one to five years after logging. In the undisturbed forest, growth rates increased with increasing dbh size. At species level, growth rate varied between and within treatments, as well as between trees within species, depending mainly on degree of canopy opening. The logging favoured the growth of commercial species, chiefly the light-demanders. Therefore, if the same growth conditions continue being given, for example by silvicultural treatments, to those species of commercial interest, the forest would reach a stock available for harvesting around year 30 after logging. However, the high variation in increment rates indicates that an eight-year period is not sufficient to allow predictions on cutting cycles or polycyclic management systems for the study forest.

Aproximación al diseño de sistemas de bio-reactores para la delignificación de materiales lignocelulósicos y para la decontaminación de suelos y efluentes. Approximation to the design of bio-reactors systems for the delignificación of lignocellulosic materials and for the decontamination of soil and effluents

Los materiales lignocelulósicos residuales de las actividades agroindustriales pueden ser aprovechados como fuente de lignina, hemicelulosa y celulosa. El tratamiento químico del material lignocelulósico se debe enfrentar al hecho de que dicho material es bastante recalcitrante a tal ataque, fundamentalmente debido a la presencia del polímero lignina. Esto se puede lograr también utilizando hongos de la podredumbre blanca de la madera. Estos producen enzimas lignolíticas extracelulares fundamentalmente Lacasa, que oxida la lignina a CO2. Tambien oxida un amplio rango de sustratos ( fenoles, polifenoles, anilinas, aril-diaminas, fenoles metoxi-sustituídos, y otros), lo cual es una buena razón de su atracción para aplicaciones biotecnológicas. La enzima tiene potencial aplicación en procesos tales como en la delignificación de materiales lignocelulósicos y en el bioblanqueado de pulpas para papel, en el tratamiento de aguas residuales de plantas industriales, en la modificación de fibras y decoloración en industrias textiles y de colorantes, en el mejoramiento de alimentos para animales, en la detoxificación de polutantes y en bioremediación de suelos contaminados. También se la ha utilizado en Q.Orgánica para la oxidación de grupos funcionales, en la formación de enlaces carbono- nitrógeno y en la síntesis de productos naturales complejos. HIPOTESIS: Los hongos de podredumbre blanca, y en condiciones óptimas de cultivo producen distintos tipos de enzimas oxidasas, siendo las lacasas las más adecuadas para explorarlas como catalizadores en los siguientes procesos:  Delignificación de residuos de la industria forestal con el fin de aprovechar tales desechos en la alimentación animal.  Decontaminación/remediación de suelos y/o efluentes industriales. Se realizarán los estudios para el diseño de bio-reactores que permitan responder a las dos cuestiones planteadas en la hipótesis. Para el proceso de delignificación de material lignocelulósico se proponen dos estrategias: 1- tratar el material con el micelio del hongo adecuando la provisión de nutrientes para un desarrollo sostenido y favorecer la liberación de la enzima. 2- Utilizar la enzima lacasa parcialmente purificada acoplada a un sistema mediador para oxidar los compuestos polifenólicos. Para el proceso de decontaminación/remediación de suelos y/o efluentes industriales se trabajará también en dos frentes: 3) por un lado, se ha descripto que existe una correlación positiva entre la actividad de algunas enzimas presentes en el suelo y la fertilidad. En este sentido se conoce que un sistema enzimático, tentativamente identificado como una lacasa de origen microbiano es responsable de la transformación de compuestos orgánicos en el suelo. La enzima protege al suelo de la acumulación de compuestos orgánicos peligrosos catalizando reacciones que involucran degradación, polimerización e incorporación a complejos del ácido húmico. Se utilizarán suelos incorporados con distintos polutantes(por ej. policlorofenoles ó cloroanilinas.) 4) Se trabajará con efluentes industriales contaminantes (alpechínes y/o el efluente líquido del proceso de desamargado de las aceitunas). The lignocellulosic raw materials of the agroindustrial activities can be taken advantage as source of lignin, hemicellulose and cellulose. The chemical treatment of this material is not easy because the above mentioned material is recalcitrant enough to such an assault, due to the presence of the lignin. This can be achieved also using the white-rot fungi of the wood. It produces extracellular ligninolitic enzymes, fundamentally Laccase, which oxidizes the lignin to CO2. The enzyme has application in such processes as in the delignification of lignocellulosic materials and in the biobleaching of fibers for paper industry, in the treatment of waste water of industrial plants, in the discoloration in textile industries, in the improvement of food for ruminants, in the detoxification of polutants and in bioremediation of contaminated soils. HYPOTHESIS: The white-rot fungi produce different types of enzymes, being the laccases the most adapted to explore them as catalysts in the following processes:  Delignification of residues of the forest industry in order to take advantage of such waste in the animal feed.  Decontamination of soils and / or waste waters. The studies will be conducted for the design of bio reactors that allow to answer to both questions raised in the hypothesis. For the delignification process of lignocellulosic material they propose two strategies: 1- to treat the material with the fungi 2-to use the partially purified enzyme to oxidize the polyphenolic compounds. For the soil and/or waste water decontamination process, we have: 3- Is know that the enzyme protects to the soil of the accumulation of organic dangerous compounds catalyzing reactions that involve degradation, polymerization and incorporation to complexes of the humic acid. There will be use soils incorporated into different pollutants. 4- We will work with waste waters (alpechins or the green olive debittering effluents.