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Data from: An integrated occupancy and space-use model to predict abundance of imperfectly detected, territorial vertebrates
负责人:
关键词:
Density population size wildlife habitat model Bayesian home range Black- backed Woodpecker
DOI:
doi:10.5061/dryad.4ff53
摘要:
comes from a telemetry study of variation in territory size. A Bayesian framework is used to combine independent occupancy and home-range size models
Data from: Hide and seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence
负责人:
关键词:
biodiversity monitoring false absence observer effect site-occupancy models survey effort
DOI:
doi:10.5061/dryad.v2c17
摘要:
, however, can be corrected for by estimation of detectability. In traditional occupancy models, this requires repeat or multi-observer surveys. Recent
Data from: Identifying drivers of spatial variation in occupancy with limited replication camera trap data
负责人:
关键词:
occupancy model;Bayesian modeling;Serengeti;camera trap
DOI:
doi:10.5061/dryad.34kb373
摘要:
Occupancy models are widely used in camera trap studies to analyze species presence, abundance, and geographic distribution, among other importa
Data from: Estimating occupancy using spatially and temporally replicated snow surveys
负责人:
关键词:
lynx multi-scale occupancy snow survey spatial replication temporal replication wolverine
DOI:
doi:10.5061/dryad.v4p20
摘要:
Occupancy modelling is increasingly used to monitor changes in the spatial distribution of rare and threatened species. Occupancy methods hav
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
负责人:
Hall, Laurie
关键词:
Black rail Connectivity Dispersal Metapopulation Occupancy modeling Parentage analysis
DOI:
doi:10.5061/dryad.3bb81dv
摘要:
scales (1–10, 15, 20, 25, and 30 km). Connectivity measures were then fit as colonization covariates in occupancy models to estimate a model-averaged
Data from: Penalized likelihood methods improve parameter estimates in occupancy models
负责人:
关键词:
penalized likelihood;boundary estimates;maximum likelihood;summer 2011;occupancy modeling;detection probability;parameter estimation
DOI:
doi:10.5061/dryad.t40f2
摘要:
1. Occupancy models are employed in species distribution modelling to account for imperfect detection during field surveys. While this approach
Data from: Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within loc
负责人:
关键词:
metapopulation ecology;landscape ecology;habitat quality;occupancy-abundance relationship;analysis of variance;species distribution modeling;Melitaea cinxia
DOI:
doi:10.5061/dryad.ksn02v707
摘要:
and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy
Data from: Occupancy models for data with false positive and false negative errors and heterogeneity across sites and surveys
负责人:
关键词:
informative prior;imperfect detection;occupancy model;scenario;observation;phantom species;Mniotilta varia;detection probability;confirmed detection;hierarchical Bayesian model;Monte Carlo simulation
DOI:
doi:10.5061/dryad.t68v8
摘要:
and false negative processes while modeling realistic levels of heterogeneity in occupancy and detection probabilities without restrictive assumptions
Data from: Simultaneous estimation of occupancy and detection probabilities an illustration using Cincinnatian brachiopods
负责人:
关键词:
Paleozoic;preservation;occupancy modeling;Brachiopoda;AIC;mark-recapture;facies
DOI:
doi:10.5061/dryad.s4h53
摘要:
absences and those that imply non-detection of taxa that were actually present in the space and time of interest. Occupancy modeling, an approach fir
Data from: Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication
负责人:
关键词:
absence;detection probability;vultures;presence
DOI:
doi:10.5061/dryad.72j20
摘要:
modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model

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