Why should we care about biodiversity? Biodiversity is the basis for the necessary essentials to human existence: food, fiber, fuel, and shelter. Of the estimated more than 250,000 species of angiosperms, nearly 20,000 have been used at one time or another as food for humans. Advances in agriculture are dependent upon the interaction between sys- tematics and biodiversity. Since the 1960s, world crop yields have increased two- to four-fold. Part of this increase is due to the creation of improved crop varieties through breeding programs and more recently through genetic engineering. Locating and identifying relatives of crop species have been of critical importance to agricultural research in breeding for desirable characteristics. With the advent of genetic engi- neering, nearly any plant species is a potential source of genes for transfer to agricultural crops. Ironically, the conversion of native ecosystems to agricultural lands in an attempt to accommodate the food demands of an exponentially grow- ing human population may eliminate the very organisms on which agriculture depends for its future. Fertile soil, obvi- ously essential for the vitality of agricultural crops, is also a by-product of biodiversity because it is formed through the interactions of a number of soil organisms: fungi, earthworms, bacteria, plant roots, and burrowing mammals. Species loss could result in soils unable to support vegetation.
I am particularly grateful to the following members in the Kellogg lab, past and present, who have trained me in lab work or helped me in one way or another: Matt Estep, Sara Fuentes, John Hodge, Michael McKain, Rosa Ortiz, Renata Reinheimer, Jimmy Triplett, Dilys Vela and Yunjing Wang. I want to thank the biology faculty at the University of Missouri - St. Louis who have broadened my interests beyond molecular plantsystematics and evolution. I am also grateful to Maryann Hempen, Patricia Hinton and Kathy Burney-Miller at the Biology Department Office who always provided considerable assistance when needed. I am also very thankful to Mick Richardson and Peter Hoch, Manager of the Graduate Program at the Missouri Botanical Garden, for helping with various administrative matters pertaining to my research.
Plant Biology and computer science in one core Around the world, many biologists, as well as botanists today, are trying to counter the daunting agricultural and environmental challenges. From food to increasing human population or creation of renewable energy, trends in plant science aims at delivering comprehensive solutions to such problems. Authentic approaches to address likely challenges may be carried out through modern molecular techniques, understanding of the evolution of plant genetic attributes, and by predicting the impact of environment on plant life. The science of living organisms is a data-driven, data dependent as well as a data-intensive branch of science (Smith and Nair, 2005; Thuiller et al., 2011). Botanists and Zoologists both are overwhelmed with fresh data e.g. DNA sequencing to the complex appearance of traits, species phylogeny, environmental influences and outcomes, molecular phenotyping etc. (Yesson and Culham, 2006). Botanical data ranges from full genome sequences of different plant types to geographical distribution of plant species throughout the biosphere (Hughes, 2006). Such data differ largely from the results in published manuscripts to actual data entries in databases. Diverse Analytical methods for data analysis are developing at a considerable pace (Lyons et al., 2008). Contrarily, most data sets are not simple enough to put together and means to analyze such data are `not often accessible or poorly in access. These data integration problems are much difficult for any single lab to handle (Lyons et al., 2011). Solution to such problems demands Inter-disciplinary approach with knowledge from computer science, information technology, and the Biology. The development and up-gradation of already available analysis programs and datasets are very significant and must be enhanced for future activities (Altintas et al., 2006; Hirayama and Shinozaki, 2010; Perianayagam et al., 2010).
12 chromosomes, then the high turnover rates that prevent such sequences on the A chromosomes from accumulating and degrading would be absent and allow for sequence decay. Thus, the dynamic equilibrium between frequent integration and rapid elimination of organellar DNA could be imbalanced for B chromosomes. This hypothesis is supported by higher divergence of B-derived NUMT reads compared to A-derived NUMT reads in S. cereale  . Future analyses of other B-bearing species are needed to address the question whether organelle-to-nucleus DNA transfer is an important mechanism that drives the evolution of B chromosomes. Another possibility for the accumulation is the dependence on double strand breaks (DSBs). If B chromosomes are more prone to DSB, this could aid in the insertion of random available DNA  . Organelle DNA on Bs might be underreported in genomic studies, since organelle DNA is generally filtered out during sequence analysis, due to contamination with DNA extracted from organelles. The presence of large insertions of organelle DNA on B chromosomes might be a plant specific phenomenon, as there have not been any reports yet of animal B chromosomes with mitochondrial insertions.
In accordance with the original definition of Grime et al. (1995) it was logical to attempt or to predict specific definition within the patterns of plant species as genetic characteristics are distributed in this way (Hunt and Colasanti, 2007). This was made use of by Massant et al. (2009), where spatial patterns are considered on a meso scale (larger than 50 m x 50 m). Clustering of the strategies was found which was then explained using available environmental factors. In an aggregated pattern, the strategies showed non-random and unequal distribution. Using multi-variate statistical methods, ‘clouds’ of data were shown, which indicated the formation of definite ‘biotopes’ (areas in which certain strategies predominate). Biotopes were seen to form both in accordance with habitat and disturbance (e.g. high competitive values indicated competitive (C) biotopes found under pine; stress tolerant plants (S biotopes) were found under mixed oak-beech and pure beech stands of 100 to 150 years old; and ruderal plants (R biotopes) were found nearest roads). Detrended component analysis should be employed with caution when used with environmental data (Grime et al., 1995) due to the ‘arching effect’ of data trends on the resulting analysis. Massant et al. (2009) also relied on several methods of analysis (variance values of C, R and S, with defined measurement positions of samples, logistic regression giving probability of C, R and S, calculation of weighted averages, rank order of Ellenberg values) before making their conclusions. The work provided a useful linear interpolation of plant strategy, converting into 3 dimensions: C = (10,0,0); S = (0,10,0); R = (0,0,10); in intermediates S-R, C-S-R, C/C-S-R, etc. the C-S-R values sum to 10.
Species distribution data of vascular plants were obtained from the Atlas Florae Europaeae database (AFE) maintained by the Botanical Museum, University of Helsinki, at a resolution of 50 km 50 km. Species traits were derived from BiolFlor (Klotz et al., 2002), a database of biological and ecological traits for Central European plant species and from a dataset on dispersal type (Frank and Klotz, 1990). We extracted all AFE species with available trait information. We used the following traits to address our hypotheses: dispersal type, life span, life form, pollination type, strategy type, number of vegetation units a species is afﬁliated to and hemerobic level (see Table 1 for details). Although the BiolFlor database covers Central Europe only, we associated the data with models covering the whole of Europe, as the chosen traits are generally stable and show low intraspeciﬁc variability. Hence, this spatial mismatch should not inﬂuence the results. The AFE database covers approximately 20% of the European ﬂora but does not provide distribution data on some species rich herb families such as Asteraceae, Poaceae, Cyperaceae and Fabaceae. Preliminary tests for regions with known distributions of the full ﬂora revealed that our modelled species are generally adequate to represent the trait compositions of the whole ﬂora (Hanspach et al., unpublished). Species with less than 50 presences or absences in the AFE database were excluded to allow for reliable modelling (Kadmon et al., 2003). Data on recent climate (1961–1990) were taken from Mitchell et al. (2004) and were aggregated from the original resolution of 10 min 10 min onto the 50 km 50 km resolution of the AFE data. We derived a set of 17 standard climatic variables (see Appendix Table 1).
The extensive fossil history of Nothofagus indicates that diversification of the genus was a significant vege- tational event in the Late Cretaceous of Gondwana. Four of the eight pollen types described in the fossil literature define the four modern clades independently supported by molecular data. Therefore, the presence of additional pollen types in the fossil record of the genus most likely represents the evolution and subsequent extinction of a considerable portion of this diversification. The explosive radiation of Nothofagus as marked by pollen diversity occurred within a narrow time frame, estimated to be between 83 and 70 Mya (Dettman et al., 1990). Molec- ular data have captured the remaining hierarchical order of cladogenesis from that period, whereas macrofossil data provide additional temporal context by indicating that key evolutionary novelties within the genus had de- veloped by the Oligocene, ; 40 Mya (Hill, 1991). Rec- onciling the well-established fossil record of Nothofagus with a robust hypothesis of phylogeny suggests that ex- tinction and vicariance events remain the most viable his- torical explanation for the modern distribution of the ge- nus. For the subgenera Brassospora and Nothofagus, ex- tinction appears to have limited the biogeographical in- formativeness of living taxa for understanding the biogeography of the Southern Hemisphere.
monophyly for the tribes of Schulz (1936), and to test scenarios of trichome evolution, we used the Shimodaira-Hasegawa test (S–H test) (Shimodaira and Hasegawa, 1999) to compare 30 different phylogenetic hypotheses (Table 1). To test the monophyly of Schulz’s (1936) tribes, we used MacClade 4.05 to construct constraint trees with all the sampled tribes as monophyletic simultaneously (Schulz, 1936, Table 1), and individually (one constraint tree for each sampled tribe, e.g., Matthioleae, Table 1). Thirteen taxa included in this study were described after Schulz’s 1936 publication, and these taxa were designated as “new taxa”, placed in one of Schulz’s tribes based on morphology, and used in the construction of additional constraint trees (e.g., tribes new taxa, Matthioleae new taxa). Similarly, to test scenarios of trichome evolution, we constructed constraint trees in which each trichome morphology evolved only once (e.g., simple, dendritic, malpighiaceous, stellate), trichome branching evolved only once (branching), trichomes evolved only once (trichome), and in which each trichome type defined a distinct monophyletic clade (trichome clades). Following the construction of constraint trees, we used PAUP* with the original data set to infer likelihood phylogenies for each designated constraint under the TVM+I+Γ model using the same parameters as for the unconstrained search. Finally, the most likely topologies inferred under the constraints, as well as the parsimony, unconstrained likelihood, and Bayesian tree topologies were input into PAUP* where an S–H test was used to determine whether the constraint trees were statistically worse than the most likely tree (1000 bootstrap replicates to generate a distribution by resampling estimated log likelihoods [RELL method]).
Cladistic analyses of plastid DNA sequences rbcL and trnL-F are presented separately and combined for 48 genera of Amaryllidaceae and 29 genera of related asparagalean families. The combined analysis is the most highly resolved of the three and provides good support for the monophyly of Amaryllidaceae and indicates Agapanthaceae as its sister family. Alliaceae are in turn sister to the Amaryllidaceae/Agapanthaceae clade. The origins of the family appear to be western Gondwanaland (Africa), and infrafamilial relationships are resolved along biogeographic lines. Tribe Amaryllideae, primarily South African, is sister to the rest of Amaryllidaceae; this tribe is supported by numerous morphological synapomorphies as well. The remaining two African tribes of the family, Haemantheae and Cyrtantheae, are well supported, but their position relative to the Australasian Calostemmateae and a large clade comprising the Eurasian and American genera, is not yet clear. The Eurasian and American elements of the family are each monophyletic sister clades. Internal resolution of the Eurasian clade only partially supports currently accepted tribal concepts, and few conclusions can be drawn on the rela- tionships of the genera based on these data. A monophyletic Lycorideae (Central and East Asian) is weakly supported. Galanthus and Leucojum (Galantheae pro parte) are supported as sister genera by the bootstrap. The American clade shows a higher degree of internal resolution. Hippeastreae (minus Griffinia and Worsleya) are well supported, and Zephyranthinae are resolved as a distinct subtribe. An Andean clade marked by a chromosome number of 2n 5 46 (and derivatives thereof) is resolved with weak support. The plastid DNA phylogenies are discussed in the context of biogeography and character evolution in the family.
Another difference between plant and animal DPMs concerns the extent to which they are developmentally ‘flexible’ in evolu- tionarily more derived lineages. The original proposal concerning animal DPMs postulated that these modules were initially flexible in terms of phenotypic outcome but that they became integrated into more robust and less plastic developmental processes, pos- sibly via canalization (sensu Waddington) and selection. This may have also been the case for plant development and evolution but to a lesser degree for lineages in which sessile multicellular or- ganisms evolved. In these lineages, it is reasonable to conjecture that natural selection would have favored plants that retained implementation of more plastic DPMs, particularly those with an open indeterminate growth pattern in which new tissues or organs are added indefinitely over the course of a life-time. Less rigidly integrated systems of DPMs would permit development to track changes in ambient environmental conditions, which can change sometimes dramatically over the course of long-lived species such as trees. This conjecture is amenable experimentally to fal- sification by means of broad developmental comparisons among unicellular versus multicellular organisms and determinate versus indeterminate species.
From the early days of microbiology as a science, microbiologists have realized the difficulties in establishing a satisfactory classification system for bacteria. Procaryotes are morphologically very simple, so morphological characters, so useful in the systematics of eucaryotes, are of little help. Moreover, a useful fossil record is altogether lacking, as those fossils that do exist are phylogenetically uninformative. One of the first attempts toward a classification of the bacteria was made by Ferdinand Cohn in the 1870s. Cohn grouped the bacteria according to their overall morphological appearance, and he discerned six genera based on morphological criteria (e.g., cocci, short rods, spirals). He also clearly pointed out that morphological properties are insufficient, as similarly shaped bacteria may have different physiological characters, and may differ in important properties such as metabolites produced, pathogenesis, etc. He also perceived the close relationship between the "common bacteria" and the cyanobacteria (then called blue-green algae), and grouped them together as the Schizophyta.
The topology of the angiosperm phylogeny (Stevens, 2001 onwards) suggests that coloured nectar has evolved independently at the level of order at least 13 times (Fig. 3), and 15 times at the level of family (Table 1). For the majority of taxa with coloured nectar there are no species-level phylogenies available, and thus we cannot answer questions about single versus multiple origins of coloured nectar within these taxa, or speculate on when the trait arose within a lineage. One exception is Schiedea, where all four species with coloured nectar form a monophyletic group nested within a well-resolved phylogeny (Soltis et al., 1996; Weller et al., 1995; Wagner et al., 2005). In this case it is most parsimonious to assume that coloured nectar arose once within the clade, most likely in a species from Kaua’i, the older of the two islands where coloured nectar occurs. For Nesocodon mauritianus, recent molecular phylogenetic work shows it to be nested within the genus Heterochaenia with three species found on the neighbouring island of La Re´union (J. M. Olesen & B. K. Ehlers, unpublished data). The flowers of H. ensifolia and H. rivalsii have clear nectar, but nectar colour is unknown in H. borbonica. Here, we can hypothesise a relatively recent origin of the evolution of col- oured nectar, as La Re´union is approximately two million years old (McDougall, 1971). As Mauritius is about eight million years old (McDougall & Chamalaun, 1969), it is thus most likely that N. mauritianus is a recent addition to the Mauritian flora, and that coloured nectar evolved here after colonisation from La Re´union during a relatively short time. Although no well-resolved species-level phylogenies exist for the other taxa with coloured nectar, it is still possible to make inferences about evolutionary events in some of the lineages. In Hoya, coloured nectar is found in all five species in the section Amblyostemma (Kloppenburg, 1994). This suggests that coloured nectar arose only once in Hoya. However, further phylogenetic studies are needed to confirm the monophyly of this section (Wanntorp et al., 2006, Wanntorp et al., in press). Similarly, the Banksia species with coloured nectar are all found in one group, Sphaerocarpa, in the series Abietinae (George, 1999). How- ever, as our knowledge about nectar in this series is incomplete (Markey & Lamont, 1995), and as there is no species-level phylogeny, we cannot deduce anything about single or multiple origins of coloured nectar. In Jaltomata, Mione et al. (1994) constructed a phylogeny of parts of the
The members of the genus Alphavirus cause a wide range of diseases in humans and animals. Many Old World viruses, including the Ross River, Barmah Forest, Mayaro, o’nyong- nyong, chikungunya, and Sindbis viruses, cause an arthralgia syndrome (47, 52), while encephalitis is caused by VEEV, eastern equine encephalitis virus (EEEV), and western equine encephalitis virus (WEEV) in the New World. In addition to causing febrile illness in equines, pigs, and calves, Getah virus has been reported to potentially induce abortion or stillbirth in pregnant sows (20, 44). Highlands J virus causes dramatic decreases in egg production and mortality in domestic birds (13, 70). Seroprevalence data on many of the remaining alpha- viruses indicate that they infect people and/or domestic ani- mals but have unknown clinical manifestations or cause only a mild febrile illness (1, 29–31, 41, 63, 65). Interestingly, alpha- viruses causing similar disease symptoms are maintained under diverse ecological conditions and can have a widespread dis- tribution. For example, Mayaro virus is limited geographically to Latin America (46, 64) while o’nyong-nyong virus has never been identified outside of Africa (21, 33, 48). These two viruses cause almost identical clinical signs and symptoms. This un- usual epidemiological pattern seen among the various alpha- viruses presents some intriguing questions regarding evolution- ary relationships of the members of the Alphavirus genus, including the origins of the genus and subsequent geographic expansion of the genus and species.
shelf from the Thailand-‐Peninsular Malaysia border northwards, and westwards to India and Sri Lanka; (C) West Malesia including the southern part of the Sunda shelf from the Thailand-‐Peninsular Malaysia border southwards; (D) Central Malesia (or Wallacea); (E) New Guinea and the surrounding islands (e.g. New Britain); (F) Australia; (G) New Zealand; and (H) the Pacific including New Caledonia. The Sunda shelf was separated into two biogeographical areas in this study based on the differences in the species composition between the northern and southern parts. Of 42 taxa sampled from the southern part, only five (E. angustifolius complex, E. nitidus Jack, E. petiolatus (Jack) Wall., E. robustus Roxb. and E. stipularis Blume) of them extend to the northern part. The northern Sunda shelf was grouped together with Continental Asia. Similarly, the Sahul shelf was segregated into two biogeographical areas, New Guinea and Australia, as these areas show marked differences in their species composition. Of the 30 taxa known from Australia including offshore islands (Australian Plant Census, accessed Jan 15, 2015), only four (E. angustifolius, E. arnhemicus F.Muell., E. culminicola Warb., and E. miegei Weibel [this last species was not sampled in this study]) are also found in New Guinea. Some of these biogeographical areas, i.e. Continental Asia (area B) and Central Malesia (area D), have different palaeogeographical
Since Vincia and Pythia share the same hadronisation model and both have dipole-style showers, it is not surprising that they exhibit similar behaviors as parameters are changed. The biggest surprise is the significant change observed when using an alternative shower evolution variable (“alt Q E ”), which persists at hadron level. Although this variation is theoretically disfavored (the default p ⊥ evolution variable has been shown to reproduce the logarithmic structure of the q ¯ q → qg¯q antenna function to second order in α s [ 116 ]), formal control of the ambiguity would depend on one-loop corrections. It would therefore be interesting to determine the extent to which multi-leg NLO merging techniques (such as UNLOPS [ 117 ]) would reduce it, and/or whether second-order corrections to the shower kernels are required (for which only a proof of concept currently exists [ 118 ]).