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Data from: Next generation lineage discovery: a case study of tuberous Claytonia L.
负责人:
关键词:
New species;edaphic;SVD quartets;Reticulation;Claytonia crawfordii;Elliptical Fourier Analysis;ddRAD;statistical ordination;Next Generation Sequencing;genome skimming;Montiaceae
DOI:
doi:10.5061/dryad.m99v4
摘要:
heless, species complexes are ubiquitous and their classification is essential for understanding how diversity influences ecosystem function. METHODS
Data from: Systematics of the cosmopolitan aquatic genus Elatine
负责人:
关键词:
Elatine;reticulate evolution;morphology;trnK\/matK;Elatinaceae;Waterworts;ITS;nuclear and plastid DNA;hybridization;taxonomy;rbcL;hybridization
DOI:
doi:10.5061/dryad.69f22
摘要:
explained as a consequence of adaptation to their aquatic life. These phylogenetic analyses also have helped to clarify the infrageneric classification
Data from: Legume phylogeny and classification in the 21st century: progress, prospects and lessons for other species-rich clades
负责人:
关键词:
Leguminosae;Legumes;phylogeny;classification
DOI:
doi:10.5061/dryad.r5k63
摘要:
ues in comparative biology and classification. Our goal is to stimulate the research needed to improve our knowledge of legume phylogeny and evolution; the approaches tha
Data from: Flow-ecology relationships are spatially structured and differ among flow regimes
负责人:
关键词:
environmental flows;Traits;hydrology;life history strategies;streams;Fish;spatial autocorrelation
DOI:
doi:10.5061/dryad.2f7h7t6
摘要:
h as autocorrelation due to spatial design, flow regime classification, and other environmental or ecological sources of spatial bias. 3. We used mixed moving-average
MPM Herpetology
负责人:
Spencer, Carol;;Bloom, David;;Bloom, David;;Wieczorek, John;;Henderson, Robert;;Colby, Julia
关键词:
DOI:
doi:10.15468/ef6frs
摘要:
of animal life on our planet. Today, the MPM vertebrate zoologists center their research on the classification, evolution, natural history and ecology
Data from: Phylogeny of Salix subgenus Salix s.l. (Salicaceae): delimitation biogeography and reticulate evolution
负责人:
关键词:
Salix;reticulate evolution;Biogeography;Salix subgenus Salix;phylogeny;character evolution;Cenozoic;Salicaceae
DOI:
doi:10.5061/dryad.qr2vv
摘要:
nt morphological characters (number of stamens, and morphology of bud scales) used in subgeneric classification within Salix remain untested, and a disjunct Old–New World
Data from: Island woodiness underpins accelerated disparification in plant radiations
负责人:
关键词:
Insular woodiness;Tarweeds;Hypericum;sky islands;diversification rate shifts;Miocene to present;Silverswords;Macaronesia;adaptive radiation;Echium;ecological opportunity;Lupinus;Madiinae;secondary woodiness;disparification
DOI:
doi:10.5061/dryad.rt530k9
摘要:
saturation for the classical oceanic island plant radiations – the Hawaiian silverswords and Macaronesian Echium ? and the well?studied sky island radiati
Data from: DNA variation in the phenotypically-diverse brown alga Saccharina japonica
负责人:
关键词:
Saccharina japonica;Saccharina cichorioides;DNA polymorphism;Phenotypic Plasticity;Saccharina japonica morphological forms;brown algae;kelp;Saccharina
DOI:
doi:10.5061/dryad.h32m962j
摘要:
t the TYP and LON forms are very similar genetically in spite of drastic differences in morphology, life history traits, and ecological preferences. Bot
Data from: Recent ecological selection on regulatory divergence is shaping clinal variation in Senecio on Mount Etna
负责人:
关键词:
Senecio aethnensis;gene flow;population genetics;Selection - Natural;hybridization;Adaptation;Senecio chrysanthemifolius
DOI:
doi:10.5061/dryad.677v3
摘要:
nct species) is a classic example of an altitudinal cline. Hybridization at intermediate altitudes and gradients in phenotypic and life-history traits occur al
Data from: Machine learning biogeographic processes from biotic patterns: a new trait-dependent dispersal and diversification model with model choic
负责人:
关键词:
Biogeography;Macroevolution;model choice;phylogenetics;Machine Learning;island radiation;taxon cycle
DOI:
doi:10.5061/dryad.4cj58
摘要:
enies, with the discriminant functions trained on data generated by simulations under our model. This approach of model selection by classification of empirical data with respect to data

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