Morphology, Anatomy, Cytogenetic and Behavior Surveys
Higher Phylogeny, Classification and Biogeography
Aims of the
Global Survey and
Inventory of Solifugae
HIGHER PHYLOGENY, CLASSIFICATION AND
Taxon Sampling: Exemplars from the
sister-group, Pseudoscorpiones, other Dromopoda, and more distantly related
arachnid orders (Coddington,
Harvey, Prendini and Walter 2004;
Giribet, Edgecombe, Wheeler,
and Babbitt 2002; Giribet and Ribera 2000; Shultz 1990; Weygoldt and Paulus
1979; Wheeler, Cartwright and Hayashi 1993; Wheeler and Hayashi 1998),
available from the AToL: Spider
Phylogeny and REVSYS: Vaejovidae
projects, will be included as outgroups. The ingroup sample will comprise
exemplars from all solifuge families, subfamilies, and as many genera as it is
possible to obtain fresh material for DNA isolation (ca. 450 samples
representing 10 families and at least 26 genera are already available from prior
collections by Prendini). We will attempt to sequence DNA from museum
material for crucial taxa of which no fresh samples are available. Taxa of
systematic and biogeographical significance will be targeted. Sampling key
genera in southern Africa and South America will facilitate assessment of
relationships by providing rare material for morphological and molecular
analyses. Sampling typical daesiids, as well as ammotrechids, ceromids,
gylippids, melanoblossids, and mummuciids in both regions will be essential for
placing them in a wider phylogenetic context, and illuminating putative Gondwana
connections. Sampling from the Palearctic region is crucial for fresh
material of Galeodidae, Karschiidae and Rhagodidae, not found in southern Africa
or the New World. Collections from the Palearctic will establish whether
the disjunct distribution of Gylippidae is real or artifactual. It will be
impossible to sample all enigmatic taxa. Dinorhax, for example,
known only from Vietnam and Indonesia, is placed in Melanoblossidae (Roewer
1934), but distribution and morphology suggest Karschiidae or Gylippidae.
Nevertheless, the sampling outlined will provide a foundation for family-level
classification that facilitates eventual placement of such genera when more
material is available.
Organismal Data Acquisition, Documentation and Storage: All
exemplar species from which DNA is sequenced will be scored in the organismal
matrix (a compilation of data from the morphological, anatomical, cytogenetic
and behavioral surveys) by
Cushings team. Available characters from the literature will be
included, along with those newly discovered and documented through original
observation. To ensure consistent treatment and repeatability, characters
will be critically examined in specimens, described using standard terminology
agreed upon by senior personnel, and documented with illustrations.
Matrices will be compiled and edited using
Nexus Data Editor
and WinClada (Nixon
2002). Digital images documenting character states and voucher specimen
data will be databased.
DNA Sequencing: The
AMNH Molecular Systematics Lab, where sequencing will be conducted by a
technician under Prendinis
direction, contains two ABI PrismTM
3730xl automated DNA sequencers, a
Biomek NX sequencing robot for automated PCR and sequence purification,
Eppendorf Mastercyclers, two MJ Research Tetrad 4-head and two Dyad MJ
Research Thermocyclers for PCR. Standard protocols are used for DNA
isolation, amplification and double-stranded sequencing (Prendini, Crowe and
Wheeler 2003). Sequence editing is conducted using
SequencherTM 4.6 (Gene Codes Co.,
Ann Arbor, MI). At least six gene loci (genome samples of 5001000+
base-pairs that can be sequenced as single pieces in both directions), summing
to ca. 5.6 kilobases, will be sequenced for all solifuge species for which fresh
material is obtained: 18S rDNA, 28S rDNA, Histone 3 (nuclear genome); 12S rDNA,
16S rDNA, Cytochrome Oxidase I (mitochondrial genome). These loci were
chosen due to availability of primers that consistently amplify large,
phylogenetically informative fragments in diverse arachnids and because they
evolve at different rates, providing resolution at overlapping taxonomic levels
(Prendini, Crowe and Wheeler 2003; Prendini, Weygoldt and Wheeler 2005).
Elongation Factor 1-α and Polymerase II (nuclear genome) and NADH dehydrogenase
subunit I and Cytochrome Oxidase II (mitochondrial genome) may be added if
containing sufficient variation and easy to amplify.
Vouchering and Archiving Data: Specimens examined and illustrated
for morphological analysis will be labeled as vouchers in the database, as will
tissue samples stored in the Ambrose
Monell Cryo Collection. Morphological and genetic data will be
centralized on the project website, allowing data exchange between project
participants and dissemination of results. Sequences will be submitted to
morphological data and images to MorphBank
and MorphoBank, and trees to the
Tree of Life and
Missing Data: Although we will aim for complete organismal and
molecular matrices, missing or inapplicable data are unavoidable. We will
use reductive coding (Strong and Lipsomb 1999) or construct chimeras or
composite terminals when necessary. Chimeras will be limited to taxa the
monophyly of which is unlikely to affect results of the analysis, e.g., we might
combine morphology, karyotype and DNA from three different Chelypus species to
form a Chelypus terminal. The effects of missing data on analyses will
be assessed by removing taxa with missing data, reanalyzing, and comparing to
the original results.
Data Analysis: Analyses will involve heuristic searches and explore
varied optimality criteria, methods and programs. Besides desktop
computers, we will use the
cluster, allowing multiple analyses to address parameter sensitivity and
explore the analytical space. Searches for most parsimonious trees (Farris
1970, 1983; Kluge 1984) will use
and Wheeler 1996-), TNT (Goloboff, Farris, and Nixon 2002), and
PAUP* (Swofford 2002),
each with parallel versions. POY will be used for analysis of
molecular data, as it is the only program implementing direct optimization
(simultaneous alignment and tree-search), regarded as ideal in principle
(Wheeler 1994, 1996, 1998, 1999, 2000, 2001, 2001a; Slowinski 1998; Giribet and
Wheeler 1999; Giribet, Distel, Polz, Sterrer, and Wheeler 2000; Giribet,
Edgecombe and Wheeler 2001; Wahlberg and Zimmerman 2000), but computationally
demanding. Strategies for rapid tree search (Goloboff 1999; Nixon 1999)
will enhance searches throughout tree space. Maximum likelihood (Cavalli-Sforza
and Edwards 1967; Felsenstein 1979, 1981, 1981a, 1983[ Huelsenbeck and Crandall
1997) is also implemented in POY. Likelihood is more computationally
intensive than parsimony, so we will restrict these analyses to overlapping
subsets of taxa, combining results with supertree methods (Gordon 1986; Baum
1992; Ragan 1992; Bininda-Emonds and Bryant 1998; Steel, Dress, and Bocker 2000;
Semple and Steel 2000; Bininda-Emonds and Sanderson 2001). We will use
MrBayes (Huelsenbeck, Ronquist,
Larget, Van der Mark, and Simon 2000-) to analyze the entire dataset with
Bayesian methods (Rannala and Yang 1996; Mau and Newton 1997; Mau, Newton and
Larget 1999). Analyses of data partitions (morphology, different loci) will be
conducted separately and simultaneously. Simultaneous analysis (and all
analyses involving morphological data) will be restricted to parsimony because
the likelihood assumption of uniform stochastic behavior is problematic for
morphological data. Partitioned Bremer support (Baker and DeSalle 1997;
Baker, Yu and DeSalle 1998) will be used to address the relative contributions
of different loci and morphological character systems to the simultaneous
analysis. Relative support for nodes will be assessed with branch support
indices (Bremer 1988, 1994; Donoghue, Olmstead, Smith and Palmer 1992) and
bootstraps (Felsenstein 1985; Sanderson 1989). Adaptational and
biogeographical hypotheses will be tested by optimization on the tree obtained
by simultaneous analysis of all evidence, using
WinClada (Nixon 2002) and
MacClade (Maddison and
Maddison 1992). Ambiguous optimizations will be resolved with ACCTRAN,
maximizing homology by favoring reversals (Swofford and Maddison 1987, 1992).
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