Search results for "sademetsät"

showing 3 items of 3 documents

Polypore communities and their substrate characteristics in Atlantic forest fragments in southeast Brazil

2018

Anthropogenic environmental changes have resulted in biodiversity crisis. Although tropical rainforests are one of the global biodiversity hotspots, their biodiversity is still poorly known. Especially fungi are poorly represented in national Red Lists and conservation plans, despite their important role in ecosystem functioning. We studied wood-inhabiting fungi (polypores) in four areas within two Atlantic rainforest fragments in Southeast Brazil. Our aim was to investigate fungal substrate characteristics and community composition. Deadwood amount ranged from 27 to 82 m3/ha among the four study areas and altogether we recorded 53 polypore species. More species were observed in intermediat…

0106 biological sciencestropical forestBiodiversitysademetsätRainforest010603 evolutionary biology01 natural sciencesPolyporeEcosystemTransectNature and Landscape ConservationbiodiversitydeadwoodEcologybiologyCommunityEcologybiology.organism_classificationluonnon monimuotoisuuslahottajasienetbiodiversiteettiwood-decaying fungiGeographywood-inhabiting fungiNestednessta1181sienetrainforestcommunity ecology010606 plant biology & botanyGlobal biodiversityTropical Conservation Science
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Statistical models and inference for spatial point patterns with intensity-dependent marks

2009

MCMCGaussian excursion setbayesilainen menetelmätilastomenetelmätsademetsätBitterlich samplinglog Gaussian Cox processpine samplingsdensity-dependenceMonte Carlo -menetelmätmark-dependent thinningalgoritmitmarked point processrandom set marked Cox processtropical rainforestBayesian modelling
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Bayesian semiparametric long memory models for discretized event data

2020

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…

mallintaminenFOS: Computer and information sciencesStatistics and Probabilitylong range dependenceaikasarjatMarkovin ketjutfractional Brownian motionsademetsätekologinen mallinnusStatistics - ApplicationsArticleMethodology (stat.ME)fractalApplications (stat.AP)AmazonStatistics - Methodologylatent Gaussian process modelstodennäköisyyslaskentanonparametric Bayesbayesilainen menetelmägaussiset prosessitmatemaattinen tilastotiedeluonnonäänetlinnut -- äänetluonnon monimuotoisuusMonte Carlo -menetelmätComputer Science::SoundModeling and Simulationprobitfraktaalittime seriesStatistics Probability and UncertaintyThe Annals of Applied Statistics
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