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Data from: Exploring variation in fitness surfaces over time or space
负责人:
关键词:
natural selection;projection pursuit regression;tensor decomposition
DOI:
doi:10.5061/dryad.f4r56j4c
摘要:
for understanding multivariate selection and evolution. However, rigorous statistical comparisons of multivariate selection surfaces over time or space hav
Data from: Robustness of the approximate likelihood of the protracted speciation model
负责人:
关键词:
Likelihood;Macroevolution;phylogeny;diversification;Birth-death model
DOI:
doi:10.5061/dryad.20g1d
摘要:
of its parameters (rate of initiation of speciation, rate of completion of speciation, and extinction rate) and statistical comparison of this model to other
Data from: The conservation status and population decline of the African penguin deconstructed in space and time
负责人:
关键词:
Spheniscus demersus;population declines;conservation
DOI:
doi:10.5061/dryad.vx0k6djp7
摘要:
rs of count data (1979–2019) and Bayesian state-space models to assess the African penguin Spheniscus demersus population under IUCN Red List Crite
Data from: Robust design for coalescent model inference
负责人:
关键词:
population genetic inference;structured coalescent;Experimental design;sequential Markovian coalescent;Coalescent Theory;skyline models
DOI:
doi:10.5061/dryad.n7rm21c
摘要:
l protocol, which controls variables such as the sampling of sequences through time and space, or the transformation of model parameters. While there is an exte
Data from: Use of continuous traits can improve morphological phylogenetics
负责人:
关键词:
morphology;Paleontology;Bayesian;phylogenetics;Quantitative Characters
DOI:
doi:10.5061/dryad.40b70
摘要:
in morphological datasets by preserving larger variation in state space compared to many discretisation schemes. I also suggest that the use of continuous trait models
Data from: Changes in spatial variance during a grassland to shrubland state transition
负责人:
关键词:
regime shifts;shrub encroachment;bush encroachment;Forecasting;Warning Signs;non-equilibrium;resilience;transient dynamics
DOI:
doi:10.5061/dryad.h45mr
摘要:
de of theoretical models, very little is known about slower state transitions and how they unfold in time and space. We quantified changes in spatial variance as a mesic
Data from: Study of morphological variation of northern Neotropical Ariidae reveals conservatism despite macrohabitat transitions
负责人:
关键词:
Sciades;Ariidae;Bagre;Ariopsis;disparity;Morphological Evolution;Fish;convevol;Cathorops;Holocene;Geometric morphometrics;Notarius
DOI:
doi:10.5061/dryad.m55m7
摘要:
h a broad spectrum of different habitats from sea to freshwater, the morphospace analysis and analyses of shape and co-variation with habitat in a phylogenetic conte
Data from: A global synthesis of survival estimates for microbats
负责人:
关键词:
Demography;mortality;state-space model;population viability;mark-recapture;Austronomus australis;Chalinolobus gouldii;Chiroptera
DOI:
doi:10.5061/dryad.78m34
摘要:
Accurate survival estimates are needed to construct robust population models, which are a powerful tool for understanding and predicting the fate
Data from: State-space modelling of geolocation data reveals sex differences in the use of management areas by breeding northern fulmars
负责人:
Edwards, Ewan W. J.
关键词:
double-tagging fisheries bycatch GLS geolocator validation Marine Strategy Framework Directive northern fulmar OSPAR spatial modelling tracking
DOI:
doi:10.5061/dryad.vb322
摘要:
tracking data from 11 double-tagged (GPS/geolocator) northern fulmars Fulmarus glacialis L. within a state-space modelling (SSM) framework to estimate errors
Data from: The seasonal climate niche predicts phenology and distribution of an ephemeral annual plant, Mollugo verticillata
负责人:
关键词:
climate change;germination phenology;herbarium;seasonal climate niche;MaxEnt;ecological niche model;flowering phenology;Mollugo verticillata;historical records;niche breadth;1896-2069
DOI:
doi:10.5061/dryad.0s9j3
摘要:
framework to construct a seasonal species distribution model (SDM) of the species’ climate niche within the total climate space available across all seasons

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