An important goal of the angiosperm systematics community has been to develop a shared approach to molecular data collection, such that phylogenomic data sets from different focal clades can be combined for meta-studies across the entire group. Although significant progress has been made through efforts such as DNA barcoding, transcriptome sequencing, and whole-plastid sequencing, the community current lacks a cost efficient methodology for collecting nuclear phylogenomic data across all angiosperms. Here, we leverage genomic resources from 43 angiosperm species to develop enrichment probes useful for collecting ~500 loci from non-model taxa across the diversity of angiosperms. By taking an anchored phylogenomics approach, in which probes are designed to represent sequence diversity across the group, we are able to efficiently target loci with sufficient phylogenetic signal to resolve deep, intermediate, and shallow angiosperm relationships. After demonstrating the utility of this resource, we present a method that generates a heat map for each node on a phylogeny that reveals the sensitivity of support for the node across analysis conditions, as well as different locus, site, and taxon schemes. Focusing on the effect of locus and site sampling, we use this approach to statistically evaluate relative support for the alternative relationships among eudicots, monocots, and magnoliids. Although the results from supermatrix and coalescent analyses are largely consistent across the tree, we find support for this deep relationship to be more sensitive to the particular choice of sites and loci when a supermatrix approach as employed. Averaged across analysis approaches and data subsampling schemes, our data support a eudicot-monocot sister relationship, which is supported by a number of recent angiosperm studies.
BackgroundThere is widespread interest in biofuel crops as a solution to the world's energy needs, particularly in light of concerns over greenhouse-gas emissions. Despite reservations about their adverse environmental impacts, no attempt has been made to quantify actual, relative or potential invasiveness of terrestrial biofuel crops at an appropriate regional or international scale, and their planting continues to be largely unregulated.Methodology/Principal FindingsUsing a widely accepted weed risk assessment system, we analyzed a comprehensive list of regionally suitable biofuel crops to show that seventy percent have a high risk of becoming invasive versus one-quarter of non-biofuel plant species and are two to four times more likely to establish wild populations locally or be invasive in Hawaii or in other locations with a similar climate.Conclusions/SignificanceBecause of climatic and ecological similarities, predictions of biofuel crop invasiveness in Hawaii are applicable to other vulnerable island and subtropical ecosystems worldwide. We demonstrate the utility of an accessible and scientifically proven risk assessment protocol that allows users to predict if introduced species will become invasive in their region of interest. Other evidence supports the contention that propagule pressure created by extensive plantings will exacerbate invasions, a scenario expected with large-scale biofuel crop cultivation. Proactive measures, such as risk assessments, should be employed to predict invasion risks, which could then be mitigated via implementation of appropriate planting policies and adoption of the “polluter-pays” principle.
BackgroundPlant invasions are causing habitat degradation in Galapagos. Problems are concentrated on the four inhabited islands. Plants introduced to rural areas in the humid highlands and urban areas on the arid coast act as foci for invasion of the surrounding Galapagos National Park.Methodology/Principal FindingsHere we present results of the most comprehensive inventory to date of alien vascular plants in the inhabited areas of Galapagos. The survey was conducted between 2002 and 2007, in 6031 properties (97% of the total) on Floreana, Isabela, San Cristobal and Santa Cruz Islands. In total 754 alien vascular plant taxa were recorded, representing 468 genera in 123 families. Dicotyledons represented 554 taxa, monocotyledons 183, there were 7 gymnosperms and 10 pteridophytes. Almost half (363) of the taxa were herbaceous. The most represented families were Fabaceae (sensu lato), Asteraceae and Poaceae. The three most recorded species in the humid rural areas were Psidium guajava, Passiflora edulis and Bryophyllum pinnatum, and in the dry urban areas, Aloe vera, Portulaca oleracea and Carica papaya. In total, 264 (35%) taxa were recorded as naturalized. The most common use for taxa was ornamental (52%).Conclusions/SignificanceThis extensive survey has increased the known alien vascular flora of Galapagos by 257 species, giving a ratio of alien to native taxa of 1.57∶1. It provides a crucial baseline for plant invasion management in the archipelago and contributes data for meta analyses of invasion processes worldwide. A repeat of the survey in the future would act as an effective early detection tool to help avoid further invasion of the Galapagos National Park.
The genomic revolution offers renewed hope of resolving rapid radiations in the Tree of Life. The development of the multispecies coalescent (MSC) model and improved gene tree estimation methods can better accommodate gene tree heterogeneity caused by incomplete lineage sorting (ILS) and gene tree estimation error stemming from the short internal branches. However, the relative influence of these factors in species tree inference is not well understood. Using anchored hybrid enrichment, we generated a data set including 423 single-copy loci from 64 taxa representing 39 families to infer the species tree of the flowering plant order Malpighiales. This order includes nine of the top ten most unstable nodes in angiosperms, which have been hypothesized to arise from the rapid radiation during the Cretaceous. Here, we show that coalescent-based methods do not resolve the backbone of Malpighiales and concatenation methods yield inconsistent estimations, providing evidence that gene tree heterogeneity is high in this clade. Despite high levels of ILS and gene tree estimation error, our simulations demonstrate that these two factors alone are insufficient to explain the lack of resolution in this order. To explore this further, we examined triplet frequencies among empirical gene trees and discovered some of them deviated significantly from those attributed to ILS and estimation error, suggesting gene flow as an additional and previously unappreciated phenomenon promoting gene tree variation in Malpighiales. Finally, we applied a novel method to quantify the relative contribution of these three primary sources of gene tree heterogeneity and demonstrated that ILS, gene tree estimation error, and gene flow contributed to 10.0%, 34.8%, and 21.4% of the variation, respectively. Together, our results suggest that a perfect storm of factors likely influence this lack of resolution, and further indicate that recalcitrant phylogenetic relationships like the backbone of Malpighiales may be better represented as phylogenetic networks. Thus, reducing such groups solely to existing models that adhere strictly to bifurcating trees greatly oversimplifies reality, and obscures our ability to more clearly discern the process of evolution.
Plant pathology must address a number of challenges, most of which are characterized by complexity. Network analysis offers useful tools for addressing complex systems and an opportunity for synthesis within plant pathology and between it and relevant disciplines such as in the social sciences. We discuss applications of network analysis, which ultimately may be integrated together into more synthetic analyses of how to optimize plant disease management systems. The analysis of microbiome networks and tripartite phytobiome networks of host-vector-pathogen interactions offers promise for identifying biocontrol strategies and anticipating disease emergence. Linking epidemic network analysis with social network analysis will support strategies for sustainable agricultural development and for scaling up solutions for disease management. Statistical tools for evaluating networks, such as Bayesian network analysis and exponential random graph models, have been underused in plant pathology and are promising for informing strategies. We conclude with research priorities for network analysis applications in plant pathology.
Seed systems have an important role in the distribution of high quality seed and improved varieties. The structure of seed networks also helps to determine the epidemiological risk for seedborne disease. We present a new method for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (CONPAPA) in Ecuador. We surveyed farmers to estimate the structure of networks of farmer seed tuber and ware potato transactions, and farmer information sources about pest and disease management. Then we simulated pathogen spread through seed transaction networks to identify priority nodes for disease detection. The likelihood of pathogen establishment was weighted based on the quality and/or quantity of information sources about disease management. CONPAPA staff and facilities, a market, and certain farms are priorities for disease management interventions, such as training, monitoring and variety dissemination. Advice from agrochemical store staff was common but assessed as significantly less reliable. Farmer access to information (reported number and quality of sources) was similar for both genders. Women had a smaller amount of the market share for seed-tubers and ware potato, however. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements.
Seed systems have an important role in the distribution of high-quality seed and improved varieties. The structure of seed networks also helps to determine the epidemiological risk for seedborne disease. We present a new approach for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (Consorcio de Productores de Papa [CONPAPA]) in Ecuador. We surveyed farmers to estimate the structure of networks of farmer seed tuber and ware potato transactions, and farmer information sources about pest and disease management. Then, we simulated pathogen spread through seed transaction networks to identify priority nodes for disease detection. The likelihood of pathogen establishment was weighted based on the quality or quantity of information sources about disease management. CONPAPA staff and facilities, a market, and certain farms are priorities for disease management interventions such as training, monitoring, and variety dissemination. Advice from agrochemical store staff was common but assessed as significantly less reliable. Farmer access to information (reported number and quality of sources) was similar for both genders. However, women had a smaller amount of the market share for seed tubers and ware potato. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .
19 20Seed systems are critical for deployment of improved varieties, and serve as major 21
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