Submitted by Deyse Queiroz (deysequeirozz@hotmail.com) on 2018-06-14T14:16:39Z No. of bitstreams: 1 JOAQUIM PEREIRA RODRIGUES - DISSERTAÇÃO PPGEA 2003..pdf: 14449699 bytes, checksum: 7cf16212a6472107d11953d967cd33fa (MD5) / Made available in DSpace on 2018-06-14T14:16:39Z (GMT). No. of bitstreams: 1 JOAQUIM PEREIRA RODRIGUES - DISSERTAÇÃO PPGEA 2003..pdf: 14449699 bytes, checksum: 7cf16212a6472107d11953d967cd33fa (MD5) Previous issue date: 2003-07 / As espécies de Eucalyptus e Pinus brasileiros apresentam um alto nível de resistência aos incêndios florestais, sendo consideradas, por alguns, como plantas pirófitas ativas. E, por isto se pergunta: O comportamento das sementes dessas espécies evoluíram exclusivamente em relação às perturbações produzidas pelo fogo ou, pelo contrário, outras causas influenciaram nesse processo e ainda se essas espécies desenvolveram respostas adaptativas similares? Para responder estas perguntas, sementes de cinco espécies de Eucalyptus e três de Pinus foram submetidas a diferentes intensidades térmicas e tempo de exposição, para simular resposta aos diferentes regimes de fogo, avaliando os efeitos provocados pelas elevadas temperaturas a que foram submetidas às sementes, assim como o efeito das cinzas, tido como elemento mais notável do micro-ambiente em que há de se desenvolver posteriormente os propágulos. O material vegetal empregado foi produzido e adquirido pelo IPEF (Instituto de Pesquisas e Estudos Florestais) em Piracicaba, SP. Para avaliar a resposta das sementes ao efeito das temperaturas, fez-se uso do delineamento estatístico inteiramente casualisado com arranjo fatorial. Na ausência de tratamentos térmicos, as sementes de Eucalyptus e Pinus registraram altas taxas de germinação e forte redução já a partir de temperaturas igual ou superiores a 70 °C sugerindo que realmente não são plantas pirófitas ativas. Os valores da germinação obtidos com os tratamentos de temperatura igual a 50 °C diferiram estatisticamente da testemunha. No entanto, a redução da germinação, em termo médios, foi de 5% (87 para 92% da testemunha), sendo muito similares para todas as espécies de Eucalyptus e Pinus estudadas. Quando os valores da temperatura são iguais ou superiores a 110 °C se observa uma importante redução da germinação das sementes em todos os tratamentos. A avaliação simultânea do calor e das cinzas mostrou a existência de interação entre ambos os fatores, com inibição total da germinação em alguns tratamentos. / The Brazilians species of Eucalyptus and Pinus present a high resistance levei to the forest fires, being considered, for some, as plants active pyrofits. And, for this reason it wonders: Did the behavior of the seeds of those species develop exclusively in relationship the disturbances produced by the fire or for the thwart, do other causes influence in that process and if, those species developed answers similar adapted? To answer these questions, seeds of five species of Eucalyptuses and three of Pinus were submitted at different thermal intensities and time of exhibition, for similar answer to the different fire regimes, evaluating the effects provoked by high temperatures were submitted the one , as well as the effect of the ashes, had as the element more notable of the environment in that must grow the plants later. The material employed vegetable was produced and acquired by 1PEF (Researches and Forest Studies Institute) in Piracicaba; SP. To evaluate the answer of the seeds to the effect of the temperatures, it was made use of the statistical lineation entirely casualty with factorial arrangement. In the absence of thermal treatments, the of Eucalyptus and Pinus seeds already registered discharges germination rates and strong reduction starting from temperatures equal or superior to 70 °C suggesting that are not really plants active pyrofits. The values of the germination obtained with the temperature treatments same to 50 °C they differed statisticiality of control, however the reduction of the germination, in médium terms, was of 5% (87 for 92% of control), being very similar for ali the species of Eucalyptus and Pinus seeds studied. When the values of the temperature are same or superior to 110 °C an important reduction of the germination of the seeds of ali the treatments it is observed. The simultaneous evaluation of the heat and of the ashes, it showed the interaction existence between both the factors, with total inhibition of the germination in some treatments.

Made available in DSpace on 2016-12-12T20:12:30Z (GMT). No. of bitstreams: 1 PGEF14MA031.pdf: 2003307 bytes, checksum: a7a54a3a2ae662326ba3aa09c5407e0f (MD5) Previous issue date: 2014-07-25 / Forest fires have caused damage, especially to the environment, and prevention is still the most economical and efficient way to avoid such damage. The present study aimed to draw a profile of fires in five years, 2009-2013, in Lages-SC and to verify the efficiency of the Fórmula de Monte Alegre (FMA) and Fórmula de Monte Alegre Alterada (FMA+) in predicting the degree of danger during the period of observation. Records of fires from the Fire Brigade of Santa Catarina (CBMSC) as well as meteorological data from the Center for Hydrometeorology and Environmental Information Resources Enterprise for Agricultural Research (EPAGRI / CIRAM) and National Institute of Meteorology (INMET) were used in the period from 01 January 2009 to December 31, 2013. These data were organized and analyzed, and the results showed that 386 fires were seen, and 58.81% were in native forest and 41.19% occurred in reforestation areas. The fires occurred mainly between the months of August and September, with 144 occurrences (37.3% of total), a time when greater attention, especially in the readiness of combat teams is required. There was a need for adjustments to the parameters that measure the degree of danger to FMA and FMA+, so that the number of days provided for each hazard class possess an inverse relationship to the degree of danger as well as the number of fire observe a direct relationship with the hazard class. After adjustment, the values obtained for the skill score and percentage of success of FMA were 0.2146 and 67.41% and FMA+ were 0.1883 and 63.53% / Os incêndios florestais têm causado grandes prejuízos, principalmente ao meio ambiente, sendo que a prevenção ainda é a forma mais econômica e eficiente para se evitar tais danos. O presente trabalho teve como objetivo traçar um perfil dos incêndios ocorridos durante 5 anos, de 2009 a 2013, no município de Lages-SC, além de verificar a eficiência da Fórmula de Monte Alegre (FMA) e da Fórmula de Monte Alegre Alterada (FMA+) na previsão do grau de perigo durante o período de observação. Foram utilizados os registros de incêndios do Corpo de Bombeiros Militar de Santa Catarina (CBMSC), bem como os dados meteorológicos do Centro de Informações de Recursos Ambientais e Hidrometeorologia da Empresa de Pesquisa Agropecuária de Santa Catarina (EPAGRI/CIRAM) e do Instituto Nacional de Meteorologia (INMET), no período de 01 de janeiro de 2009 a 31 de dezembro de 2013. Essas informações foram padronizadas e analisadas, sendo que os resultados mostraram que foram atendidos 386 incêndios, sendo que 58,81% ocorreram em floresta nativa e 41,19% ocorreram em áreas de reflorestamento. Os incêndios ocorreram principalmente nos meses de agosto e setembro, com 144 ocorrências (37,3% do total), época em que é necessária maior atenção, sobretudo na prontidão das equipes de combate. Observou-se a necessidade de ajustes nos parâmetros que medem o grau de perigo para FMA e para FMA+, de forma que o número de dias previsto em cada classe de perigo possuísse uma relação inversa com o grau de perigo, bem como para que o número de incêndios observasse uma relação direta com a classe de perigo. Após os ajustes, os valores obtidos para o skill score e percentual de sucesso da FMA foram: 0,2146 e 67,41% e para FMA+ foram: 0,1883 e 63,53%

Results are presented from the 2021 test run of active fire detection using the Visual Infrared Imaging Radiometer Suite (VIIRS) instrument, that is currently onboard the polar satellites Suomi-NPP and NOAA-20. The test is performed by the Swedish Civil Contingencies Agency and the Swedish Meteorological and Hydrological Institute, in cooperation with local fire departments in Sweden. The aim of this report was to study the impact of clouds on the ability of active fire detection, as well as to identify objects that potentially can cause commission errors in the VIIRS 375 m active fire algorithm (false positive notifications). Also, the study aimed to investigate what may cause omission errors in the algorithm, and to show to what extent the detections can be used to represent the true time development of the wildfire front and burned area. Using a cloudmask and a cloudtype classification product from Nowcasting Satellite Application Facilities (NWC SAF), the impact of clouds was anlalyzed by comparing the cloud data with the obtained fire notifications from the satellites. Active fires and newly burned areas were also studied using Sentinel-2 imagery, specifically the False Color Urban and the Short Wave Infrared (SWIR) RGB composites, as well as images from the 842 nm band, making use of the relatively high spatial resolution as well as the spectral signatures of fire and newly burned vegetation. Detection of active fires occurred in both cloud free and completely cloud covered conditions. How-ever, roughly 70% of the detected vegetation fire pixels were obtained in conditions with 20% clouds or less. / I rapporten presenteras resultat från 2021 års test av satellitdetektering av skogs- och vegetationsbränder, ett test som genomförs av MSB och SMHI i samverkan med kommunala räddningstjänster. De två satelliter som ingår i testet (Suomi-NPP och NOAA-20) går i polära omloppsbanor och är utrustade med instrumentet Visible Infrared Imaging Radiometer Suite (VIIRS). Detta projekt syftade till att undersöka hur molnighet påverkar möjligheten till detektion med satellit, vilka objekt som potentiellt kan ge upphov till falska detektioner samt vad som kan orsaka uteblivna satellitdetektioner. Ytterligare ett mål med rapporten var att genom fallstudier av större bränder undersöka i vilken utsträckning satellitdetektionerna kan användas för att representera brandfrontens utveckling med tiden och brandens faktiska utbredning. Vid studierna av molnighet analyserades en molnmask och en molnklassificeringsprodukt från Nowcasting Satellite Application Facilities (NWC SAF). I utvärderingen användes även data från Sentinel-2 för att studera pågående bränder och avbränd yta, som syns tydligt i RGB-kompositerna False Color Urban och Short Wave Infrared (SWIR) och i 842 nm-bandet, tack vare den relativt höga bildupplösningen och den nyligen avbrända ytans spektralsignatur. Brand detekterades i både molnfria och helt molntäckta förhållanden. Drygt 70 % av detektionerna vid vegetationsbrand kom emellertid i förhållanden med 20 % moln eller mindre.

This qualitative study examines how emergency people are framed in Swedish evening-, and local newspapers during the forest fire in Västmanland, Sweden 2014. The study also includes if there is any difference between the framing due to the location of the newspaper. The study is based on qualitative text analysis. The theoretical basis is representation, framing theory, media image, media logic and a few conceptions from crisis communication theory. An overall result is that critique of emergency people never are answered. An other is that critique often is directed to people who haven’t been able to affect the critique situations.

The ability to gather and process information regarding the condition of forest fires is essential to cost-effective, safe, and efficient fire fighting. Advances in sensory and autopilot technology have made miniature unmanned aerial systems (UASs) an important tool in the acquisition of information. This thesis addresses some of the challenges faced when employing UASs for forest-fire perimeter surveillance; namely, perimeter tracking, cooperative perimeter surveillance, and path planning. Solutions to the first two issues are presented and a method for understanding path planning within the context of a forest-fire environment is demonstrated. Both simulation and hardware results are provided for each solution.

Tesis por compendio / [ES] La proliferación de sistemas autónomos y su creciente integración en la vida humana cotidiana han abierto nuevas fronteras de investigación y desarrollo. Dentro de este ámbito, la presente tesis se adentra en las aplicaciones multifacéticas de los LLMs (Large Language Models), técnicas de DL (Deep Learning) y algoritmos de optimización en el ámbito de estos sistemas autónomos. A partir de los principios de los métodos potenciados por la Inteligencia Artificial (IA), los estudios englobados en este trabajo convergen en la exploración y mejora de distintos sistemas autónomos que van desde sistemas de platooning de camiones en sistemas de comunicaciones Beyond 5G (B5G), Sistemas Multi-Agente (SMA), Vehículos Aéreos No Tripulados (UAV), estimación del área de incendios forestales, hasta la detección temprana de enfermedades como el glaucoma. Un enfoque de investigación clave, perseguido en este trabajo, gira en torno a la implementación innovadora de controladores PID adaptativos en el platooning de vehículos, facilitada a través de la integración de los LLMs. Estos controladores PID, cuando se infunden con capacidades de IA, ofrecen nuevas posibilidades en términos de eficiencia, fiabilidad y seguridad de los sistemas de platooning. Desarrollamos un modelo de DL que emula un controlador PID adaptativo, mostrando así su potencial en las redes y radios habilitadas para IA. Simultáneamente, nuestra exploración se extiende a los sistemas multi-agente, proponiendo una Teoría Coevolutiva Extendida (TCE) que amalgama elementos de la dinámica coevolutiva, el aprendizaje adaptativo y las recomendaciones de estrategias basadas en LLMs. Esto permite una comprensión más matizada y dinámica de las interacciones estratégicas entre agentes heterogéneos en los SMA. Además, nos adentramos en el ámbito de los vehículos aéreos no tripulados (UAVs), proponiendo un sistema para la comprensión de vídeos que crea una log de la historia basada en la descripción semántica de eventos y objetos presentes en una escena capturada por un UAV. El uso de los LLMs aquí permite razonamientos complejos como la predicción de eventos con mínima intervención humana. Además, se aplica una metodología alternativa de DL para la estimación del área afectada durante los incendios forestales. Este enfoque aprovecha una nueva arquitectura llamada TabNet, integrada con Transformers, proporcionando así una estimación precisa y eficiente del área. En el campo de la salud, nuestra investigación esboza una metodología exitosa de detección temprana del glaucoma. Utilizando un enfoque de entrenamiento de tres etapas con EfficientNet en imágenes de retina, logramos una alta precisión en la detección de los primeros signos de esta enfermedad. A través de estas diversas aplicaciones, el foco central sigue siendo la exploración de metodologías avanzadas de IA dentro de los sistemas autónomos. Los estudios dentro de esta tesis buscan demostrar el poder y el potencial de las técnicas potenciadas por la IA para abordar problemas complejos dentro de estos sistemas. Estas investigaciones en profundidad, análisis experimentales y soluciones desarrolladas arrojan luz sobre el potencial transformador de las metodologías de IA en la mejora de la eficiencia, fiabilidad y seguridad de los sistemas autónomos, contribuyendo en última instancia a la futura investigación y desarrollo en este amplio campo. / [CA] La proliferació de sistemes autònoms i la seua creixent integració en la vida humana quotidiana han obert noves fronteres de recerca i desenvolupament. Dins d'aquest àmbit, la present tesi s'endinsa en les aplicacions multifacètiques dels LLMs (Large Language Models), tècniques de DL (Deep Learning) i algoritmes d'optimització en l'àmbit d'aquests sistemes autònoms. A partir dels principis dels mètodes potenciats per la Intel·ligència Artificial (IA), els estudis englobats en aquest treball convergeixen en l'exploració i millora de diferents sistemes autònoms que van des de sistemes de platooning de camions en sistemes de comunicacions Beyond 5G (B5G), Sistemes Multi-Agent (SMA), Vehicles Aeris No Tripulats (UAV), estimació de l'àrea d'incendis forestals, fins a la detecció precoç de malalties com el glaucoma. Un enfocament de recerca clau, perseguit en aquest treball, gira entorn de la implementació innovadora de controladors PID adaptatius en el platooning de vehicles, facilitada a través de la integració dels LLMs. Aquests controladors PID, quan s'infonen amb capacitats d'IA, ofereixen noves possibilitats en termes d'eficiència, fiabilitat i seguretat dels sistemes de platooning. Desenvolupem un model de DL que emula un controlador PID adaptatiu, mostrant així el seu potencial en les xarxes i ràdios habilitades per a IA. Simultàniament, la nostra exploració s'estén als sistemes multi-agent, proposant una Teoria Coevolutiva Estesa (TCE) que amalgama elements de la dinàmica coevolutiva, l'aprenentatge adaptatiu i les recomanacions d'estratègies basades en LLMs. Això permet una comprensió més matissada i dinàmica de les interaccions estratègiques entre agents heterogenis en els SMA. A més, ens endinsem en l'àmbit dels Vehicles Aeris No Tripulats (UAVs), proposant un sistema per a la comprensió de vídeos que crea un registre de la història basat en la descripció semàntica d'esdeveniments i objectes presents en una escena capturada per un UAV. L'ús dels LLMs aquí permet raonaments complexos com la predicció d'esdeveniments amb mínima intervenció humana. A més, s'aplica una metodologia alternativa de DL per a l'estimació de l'àrea afectada durant els incendis forestals. Aquest enfocament aprofita una nova arquitectura anomenada TabNet, integrada amb Transformers, proporcionant així una estimació precisa i eficient de l'àrea. En el camp de la salut, la nostra recerca esbossa una metodologia exitosa de detecció precoç del glaucoma. Utilitzant un enfocament d'entrenament de tres etapes amb EfficientNet en imatges de retina, aconseguim una alta precisió en la detecció dels primers signes d'aquesta malaltia. A través d'aquestes diverses aplicacions, el focus central continua sent l'exploració de metodologies avançades d'IA dins dels sistemes autònoms. Els estudis dins d'aquesta tesi busquen demostrar el poder i el potencial de les tècniques potenciades per la IA per a abordar problemes complexos dins d'aquests sistemes. Aquestes investigacions en profunditat, anàlisis experimentals i solucions desenvolupades llançen llum sobre el potencial transformador de les metodologies d'IA en la millora de l'eficiència, fiabilitat i seguretat dels sistemes autònoms, contribuint en última instància a la futura recerca i desenvolupament en aquest ampli camp. / [EN] The proliferation of autonomous systems, and their increasing integration with day-to-day human life, have opened new frontiers of research and development. Within this scope, the current thesis dives into the multifaceted applications of Large Language Models (LLMs), Deep Learning (DL) techniques, and Optimization Algorithms within the realm of these autonomous systems. Drawing from the principles of AI-enhanced methods, the studies encapsulated within this work converge on the exploration and enhancement of different autonomous systems ranging from B5G Truck Platooning Systems, Multi-Agent Systems (MASs), Unmanned Aerial Vehicles, Forest Fire Area Estimation, to the early detection of diseases like Glaucoma. A key research focus, pursued in this work, revolves around the innovative deployment of adaptive PID controllers in vehicle platooning, facilitated through the integration of LLMs. These PID controllers, when infused with AI capabilities, offer new possibilities in terms of efficiency, reliability, and security of platooning systems. We developed a DL model that emulates an adaptive PID controller, thereby showcasing its potential in AI-enabled radio and networks. Simultaneously, our exploration extends to multi-agent systems, proposing an Extended Coevolutionary (EC) Theory that amalgamates elements of coevolutionary dynamics, adaptive learning, and LLM-based strategy recommendations. This allows for a more nuanced and dynamic understanding of the strategic interactions among heterogeneous agents in MASs. Moreover, we delve into the realm of Unmanned Aerial Vehicles (UAVs), proposing a system for video understanding that employs a language-based world-state history of events and objects present in a scene captured by a UAV. The use of LLMs here enables open-ended reasoning such as event forecasting with minimal human intervention. Furthermore, an alternative DL methodology is applied for the estimation of the affected area during forest fires. This approach leverages a novel architecture called TabNet, integrated with Transformers, thus providing accurate and efficient area estimation. In the field of healthcare, our research outlines a successful early detection methodology for glaucoma. Using a three-stage training approach with EfficientNet on retinal images, we achieved high accuracy in detecting early signs of this disease. Across these diverse applications, the core focus remains: the exploration of advanced AI methodologies within autonomous systems. The studies within this thesis seek to demonstrate the power and potential of AI-enhanced techniques in tackling complex problems within these systems. These in-depth investigations, experimental analyses, and developed solutions shed light on the transformative potential of AI methodologies in improving the efficiency, reliability, and security of autonomous systems, ultimately contributing to future research and development in this expansive field. / De Zarzà I Cubero, I. (2023). AI-Enhanced Methods in Autonomous Systems: Large Language Models, DL Techniques, and Optimization Algorithms [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202201 / Compendio

Artificial Neural Networks (ANNs) have been comprehensively researched, both from a computer scientific perspective and with regard to their use for predictive modelling in a wide variety of applications including hydrology and the environment. Yet their adoption for live, real-time systems remains on the whole sporadic and experimental. A plausible hypothesis is that this may be at least in part due to their treatment heretofore as “black boxes” that implicitly contain something that is unknown, or even unknowable. It is understandable that many of those responsible for delivering Early Warning Systems (EWS) might not wish to take the risk of implementing solutions perceived as containing unknown elements, despite the computational advantages that ANNs offer. This thesis therefore builds on existing efforts to open the box and develop tools and techniques that visualise, analyse and use ANN weights and biases especially from the viewpoint of neural pathways from inputs to outputs of feedforward networks. In so doing, it aims to demonstrate novel approaches to self-improving predictive model construction for both regression and classification problems. This includes Neural Pathway Strength Feature Selection (NPSFS), which uses ensembles of ANNs trained on differing subsets of data and analysis of the learnt weights to infer degrees of relevance of the input features and so build simplified models with reduced input feature sets. Case studies are carried out for prediction of flooding at multiple nodes in urban drainage networks located in three urban catchments in the UK, which demonstrate rapid, accurate prediction of flooding both for regression and classification. Predictive skill is shown to reduce beyond the time of concentration of each sewer node, when actual rainfall is used as input to the models. Further case studies model and predict statutory bacteria count exceedances for bathing water quality compliance at 5 beaches in Southwest England. An illustrative case study using a forest fires dataset from the UCI machine learning repository is also included. Results from these model ensembles generally exhibit improved performance, when compared with single ANN models. Also ensembles with reduced input feature sets, using NPSFS, demonstrate as good or improved performance when compared with the full feature set models. Conclusions are drawn about a new set of tools and techniques, including NPSFS and visualisation techniques for inspection of ANN weights, the adoption of which it is hoped may lead to improved confidence in the use of ANN for live real-time EWS applications.

No description available.

In this study, the immediate and short term (three months) effects of conservation burning have been investigated in coniferous forests in southeastern Sweden. Five tree species were investigated Picea abies (Norway spruce), Pinus sylvestris (Scots pine), Populus tremula (aspen), Betula pendula (silver birch) and Betula pubescens (downy birch), as well as ground vegetation of mosses, dwarf shrubs and ground lichens. Burning increased the proportion of live deciduous tree shoots from 51 % to 81 % and the live tree shoot size distribution of four tree species was significantly changed by fire. Fire affected the tree species differently. Three months after burning deciduous tree species exhibited strong sprouting, while P. sylvestris had established many seedlings, significantly increasing its share of the tree stand. P. abies lacked any visible positive response to burning and its number of live shoots decreased by 83 %. Mineral soil was exposed on only the moss vegetation and covered just 4 % of the studied plot area. The initial vegetation response to fire was negative, but significant dwarf shrub recovery was detected three months after burning.

Thesis (MScBosb)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: The characteristics and total fuel load of the forest floor (FF) and harvest residue (HR) are needed to develop tools that can be used for fuel load management, fire risk analysis and fire behaviour prediction for P. patula grown in the summer rainfall area of South Africa (SA). Forest floor depth, mass and ash-free mass were measured and there was generally a greater range in depth under sawtimber (ST) stands than under pulpwood (PLP) stands. Forest floor loads, prior to ashing, ranged from 21 - 168 t ha-1 and 27 - 72 t ha-1, for ST and PLP stands, respectively and loads increased linearly with stand age. Sawtimber and PLP stands were analysed together, which resulted in a significant correlation between depth and mass (r2 = 0.78, n = 31). A loss on ignition procedure carried out on sub-samples of the FF improved the relationship between the FF depth and the ash-free mass for the different stands, and provided a more accurate model for the prediction of mass from depth. A multiple regression analysis revealed that age, altitude and mean annual precipitation (MAP) provided the best subset and accounted for 72% of the variation in the FF mass observed. The effect of increasing FF load and increasing moisture content on the fireline intensity (FLI) was examined using the fire behaviour prediction programme, BehavePlus. Harvest residue was quantified and characterised in terms of fuel size classes, under current silvicultural regimes for ST and PLP, for the development of fuel models for this species over its planted range in SA. An investigation into the proportion (by mass) of the 1- (0.0 - 0.6 cm), 10- (0.6 – 2.5 cm), 100- (2.5 – 7.6 cm) and 1000-hr (> 7.6 cm diameter) fuel classes of the total HR mass indicated that there was a significant difference between the mass of the 1-, 10- and 1000-hr fuel classes of the two silvicultural regimes, and no significant difference for the 100-hr fuel class. Two fuel models for P. patula HR and two models for standing timber were developed using the new model (NEWMDL) programme of BEHAVE and tested in BehavePlus. Nutrient concentrations were used with FF layer and HR size class load data to estimate the quantities of nutrients held in the fuel and to describe nutrient distributions in the fuel complex. Significant differences in the nutrient concentration of the FF layers and fuel components were observed which has important implications for fuel management. The concentration of N determined in this study, relative to that determined in other similar studies on P. patula was low. Forest floor loads were predicted and nutrient pools calculated for typical ST and PLP stands at both low and high altitude to provide insight into the nutrient distributions within the fuel complex. / AFRIKAANSE OPSOMMING: Die karaktereienskappe en totale brandstoflading van die bosvloer (FF) en kaalkap oorskot (HR) word benodig om instrumente te ontwikkel wat gebruik kan word vir brandstoflading bestuur, brandgevaar ontleding en brandgedrag voorspelling vir P. patula, wat in die somer reënvalgebied van Suid-Afrika groei. Die bosvloer diepte, massa en asvrye massa is gemeet en daar was oor die algemeen ‘n groter variasie in diepte onder saaghout (ST) opstande as onder pulphout (PLP) opstande. Die bosvloerladings, voor verassing, het varieer van 21 – 168 t ha-1 en 27 – 72 t ha-1 vir ST en PLP opstande respektiwelik. Ladings het linieêr vermeerder met opstand ouderdom. Saaghout en PLP opstande is saam geanaliseer en het tot ‘n betekenisvolle korrelasie gelei tussen diepte en massa (r2 = 0.78, n = 31). ‘n Verliestydens- ontbranding prosedure is uitgevoer op die FF monsters en het die verhouding tussen FF diepte en die asvrye massa van die verskillende opstande verbeter. Dit het ook gelei tot akkurater model vir die voorspelling van massa vanaf diepte. ‘n Veelvoudige regressie analise het aan die lig gebring dat ouderdom, hoogte en gemiddelde jaarlikse reënval (MAP) die beste sub-groep verskaf, en het 72% van die variasie in die FF massa verklaar. Ondersoek is ingestel op die effek van toenemende FF lading en toenemende voginhoud op die brandlyn intensiteit (FLI) deur die brandgedrag program, BehavePlus, toe te pas. Die kaalkap oorskot is gekwantifiseer en gekarakteriseer volgens brandstof grootteklasse, onder die huidige boskultuurstelsels vir ST en PLP, vir die ontwikkeling van brandstofmodelle vir hierdie spesie oor die betrokke groeistreek in SA. ‘n Ondersoek in die verhouding (volgens massa) van die 1- (0.0 – 0.6 cm), 10- (0.6 – 2.5 cm), 100- (2.5 – 7.6 cm) en 1000-uur (> 7.6 cm deursnee) brandstofklasse van die totale HR massa het aangedui dat daar ‘n betekenisvolle verskil is tussen die massas van die 1-, 10- en 1000-uur brandstofklasse van die twee boskultuurstelsels, en geen betekenisvolle verskil vir die 100- uur brandstofklas nie. Twee brandstofmodelle is ontwikkel vir P. patula HR en twee modelle vir staande hout deur gebruik te maak van die nuwe model (NEWMDL) program van BEHAVE en getoets in BehavePlus. Voedingstof konsentrasies is gebruik, tesame met die FF laag en HR klasgrootte ladingdata, om die voedingstof inhoud van die brandstof te skat en om die voedingstof verspreiding te beskryf in die brandstofkompleks. Betekenisvolle verskille is waargeneem in die voedingstof konsentrasies van die FF lae en brandstof komponente wat belangrike implikasies inhou vir brandstofbestuur. Die konsentrasie wat vir N in hierdie studie bepaal is, was laag relatief tot ander soortgelyke studies vir P. patula. Die bosvloer ladings is voorspel en voedingstofpoele bereken vir tipiese ST en PLP opstande vir beide lae en hoë hoogtes om insig te verkry, sodat insig verkry kon word in die voedingstof verspreidings binne die brandstofkompleks.