980 resultados para Forest Model
Resumo:
The recent history and current trends in the collection and archiving of forest information and models is reviewed. The question is posed as to whether the community of forest modellers ought to take some action in setting up a Forest Model Archive (FMA) as a means of conserving and sharing the heritage of forest models that have been developed over several decades. The paper discusses the various alternatives of what an FMA could be, and should be. It then goes on to formulate a conceptual model as the basis for the construction of a FMA. Finally the question of software architecture is considered. Again there are a number of possible solutions. We discuss the alternatives, some in considerable detail, but leave the final decisions on these issues to the forest modelling community. This paper has spawned the “Greenwich Initiative” on the FMA. An internet discussion group on the topic will be started and launched by the “Trafalar Group”, which will span both IUFRO 4.1 and 4.11, and further discussion is planned to take place at the Forest Modelling Conference in Portugal, June 2002.
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Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.
Resumo:
Adaptation potential of forests to rapid climatic changes can be assessed from vegetation dynamics during past climatic changes as preserved in fossil pollen data. However, pollen data reflect the integrated effects of climate and biotic processes, such as establishment, survival, competition, and migration. To disentangle these processes, we compared an annually laminated late Würm and Holocene pollen record from the Central Swiss Plateau with simulations of a dynamic forest patch model. All input data used in the simulations were largely independent from pollen data; i.e. the presented analysis is non-circular. Temperature and precipitation scenarios were based on reconstructions from pollen-independent sources. The earliest arrival times of the species at the study site after the last glacial were inferred from pollen maps. We ran a series of simulations under different combinations of climate and immigration scenarios. In addition, the sensitivity of the simulated presence/absence of four major species to changes in the climate scenario was examined. The pattern of the pollen record could partly be explained by the used climate scenario, mostly by temperature. However, some features, in particular the absence of most species during the late Würm could only be simulated if the winter temperature anomalies of the used scenario were decreased considerably. Consequently, we had to assume in the simulations, that most species immigrated during or after the Younger Dryas (12 000 years BP), Abies and Fagus even later. Given the timing of tree species immigration, the vegetation was in equilibrium with climate during long periods, but responded with lags at the time-scale of centuries to millennia caused by a secondary succession after rapid climatic changes such as at the end of Younger Dryas, or immigration of dominant taxa. Climate influenced the tree taxa both directly and indirectly by changing inter-specific competition. We concluded, that also during the present fast climatic change, species migration might be an important process, particularly if geographic barriers, such as the Alps are in the migrational path.
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In order to find out which factors influenced the forest dynamics in northern Italy during the Holocene, a palaeoecological approach involving pollen analysis was combined with ecosystem modelling. The dynamic and distribution based forest model DisCForm was run with different input scenarios for climate, species immigration, fire, and human impact and the similarity of the simulations with the original pollen record was assessed. From the comparisons of the model output and the pollen core, it appears that immigration was most important in the first part of the Holocene, and that fire and human activity had a major influence in the second half. Species not well represented in the simulation outputs are species with a higher abundance in the past than today (Corylus), with their habitat in riparian forests (Alnus) or with a strong response to human impact (Castanea).
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Despite its importance in social interactions, laughter remains little studied in affective computing. Intelligent virtual agents are often blind to users’ laughter and unable to produce convincing laughter themselves. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received less attention. The aim of this study is threefold. First, to probe human laughter perception by analyzing patterns of categorisations of natural laughter animated on a minimal avatar. Results reveal that a low dimensional space can describe perception of laughter “types”. Second, to investigate observers’ perception of laughter (hilarious, social, awkward, fake, and non-laughter) based on animated avatars generated from natural and acted motion-capture data. Significant differences in torso and limb movements are found between animations perceived as laughter and those perceived as non-laughter. Hilarious laughter also differs from social laughter. Different body movement features were indicative of laughter in sitting and standing avatar postures. Third, to investigate automatic recognition of laughter to the same level of certainty as observers’ perceptions. Results show recognition rates of the Random Forest model approach human rating levels. Classification comparisons and feature importance analyses indicate an improvement in recognition of social laughter when localized features and nonlinear models are used.
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O desmatamento na Amazônia brasileira já alterou cerca de 750 milhões de hectares e desse total, 20% encontra-se com algum nível de degradação. A reincorporação ao processo produtivo das áreas alteradas com o reflorestamento de espécies tropicais, de valor comercial, é uma alternativa para minimizar os impactos ambientais, com benefícios ecológicos, aumento da oferta de madeira e diminuição da pressão sobre as florestas naturais remanescentes. No entanto, um dos grandes empecilhos para o reflorestamento é a falta de conhecimentos científicos sobre o crescimento de espécies nativas e exóticas. Diante disto, este trabalho teve como objetivo avaliar a eficiência de diferentes sistemas de plantios com espécies florestais nativa e exótica para recuperação de áreas alteradas. O trabalho foi realizado no município de Dom Eliseu, estado do Pará, em três sistemas de uso da terra: plantio puro (Schizolobium parahyba var. amazonicum e Khaya ivorensis), consórcio de espécies florestais (S. parahyba var. amazonicum e Khaya ivorensis), sistema agroflorestal (S. parahyba var. amazonicum e Musa sp). Aos 40 meses de idade, em plantio homogêneo, Schizolobium parahyba var. amazonicum mostrou maior crescimento silvicultural (altura e diâmetro) no espaçamento 4 m x 3 m e Khaya ivorensis no espaçamento 4 m x 4 m. No entanto, o paricá apresentou melhor desempenho em sistema de consórcio e sistema agroflorestal. O melhor desempenho de K. ivorensis foi no consórcio de espécies. Entre os sistemas de plantio estudados (SAF e misto de espécies), a deposição de biomassa foi maior no sistema de consórcio de espécies com 3.737,5 kg ha-1, sendo que, a maior contribuição de material vegetal foi do paricá. Foi evidenciada correlação negativa entre a deposição de serapilheira e a precipitação pluviométrica para o paricá, e positiva para K. ivorensis. Os resultados obtidos mostraram que o modelo florestal de consórcio de espécies mostrou-se promissor e pode ser uma alternativa para recuperação de áreas alteradas, de modo a oferecer diferentes opções de madeira e ao mesmo tempo, agregar fatores positivos em relação a produção de biomassa e aspectos físico-químicos do solo.
Resumo:
Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.
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This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation.
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Paleoceanographic archives derived from 17 marine sediment cores reconstruct the response of the Southwest Pacific Ocean to the peak interglacial, Marine Isotope Stage (MIS) 5e (ca. 125?ka). Paleo-Sea Surface Temperature (SST) estimates were obtained from the Random Forest model-an ensemble decision tree tool-applied to core-top planktonic foraminiferal faunas calibrated to modern SSTs. The reconstructed geographic pattern of the SST anomaly (maximum SST between 120 and 132?ka minus mean modern SST) seems to indicate how MIS 5e conditions were generally warmer in the Southwest Pacific, especially in the western Tasman Sea where a strengthened East Australian Current (EAC) likely extended subtropical influence to ca. 45°S off Tasmania. In contrast, the eastern Tasman Sea may have had a modest cooling except around 45°S. The observed pattern resembles that developing under the present warming trend in the region. An increase in wind stress curl over the modern South Pacific is hypothesized to have spun-up the South Pacific Subtropical Gyre, with concurrent increase in subtropical flow in the western boundary currents that include the EAC. However, warmer temperatures along the Subtropical Front and Campbell Plateau to the south suggest that the relative influence of the boundary inflows to eastern New Zealand may have differed in MIS 5e, and these currents may have followed different paths compared to today.
Resumo:
Computer modelling promises to. be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The 'spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/- 50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations. (c) 2006 Published by Elsevier B.V.
Resumo:
Forest policy and forestry management in Tasmania have undergone a number of changes in the last thirty years, many explicitly aimed at improving industry sustainability, job security, and forest biodiversity conservation. Yet forestry remains a contentious issue in Tasmania, due to a number of interacting factors, most significant of which is the prevalence of a ‘command and control’ governance approach by policymakers and managers. New approaches such as multiple-stakeholder decision-making, adaptive management, and direct public participation in policymaking are needed. Such an approach has been attempted in Canada in the last decade, through the Canadian Model Forest Program, and may be suitable for Tasmania. This paper seeks to describe what the Canadian Model Forest approach is, how it may be implemented in Tasmania, and what role it may play in the shift to a new forestry paradigm. Until such a paradigm shift occurs contentions and confrontations are likely to continue.
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Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.
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In this study we analyze how the ion concentrations in forest soil solution are determined by hydrological and biogeochemical processes. A dynamic model ACIDIC was developed, including processes common to dynamic soil acidification models. The model treats up to eight interacting layers and simulates soil hydrology, transpiration, root water and nutrient uptake, cation exchange, dissolution and reactions of Al hydroxides in solution, and the formation of carbonic acid and its dissociation products. It includes also a possibility to a simultaneous use of preferential and matrix flow paths, enabling the throughfall water to enter the deeper soil layers in macropores without first reacting with the upper layers. Three different combinations of routing the throughfall water via macro- and micropores through the soil profile is presented. The large vertical gradient in the observed total charge was simulated succesfully. According to the simulations, gradient is mostly caused by differences in the intensity of water uptake, sulfate adsorption and organic anion retention at the various depths. The temporal variations in Ca and Mg concentrations were simulated fairly well in all soil layers. For H+, Al and K there were much more variation in the observed than in the simulated concentrations. Flow in macropores is a possible explanation for the apparent disequilibrium of the cation exchange for H+ and K, as the solution H+ and K concentrations have great vertical gradients in soil. The amount of exchangeable H+ increased in the O and E horizons and decreased in the Bs1 and Bs2 horizons, the net change in whole soil profile being a decrease. A large part of the decrease of the exchangeable H+ in the illuvial B horizon was caused by sulfate adsorption. The model produces soil water amounts and solution ion concentrations which are comparable to the measured values, and it can be used in both hydrological and chemical studies of soils.