Dataset Information

Lessons from Red Data Books: Plant Vulnerability Increases with Floral Complexity.

ABSTRACT: The architectural complexity of flower structures (hereafter referred to as floral complexity) may be linked to pollination by specialized pollinators that can increase the probability of successful seed set. As plant-pollinator systems become fragile, a loss of such specialized pollinators could presumably result in an increased likelihood of pollination failure. This is an issue likely to be particularly evident in plants that are currently rare. Using a novel index describing floral complexity we explored whether this aspect of the structure of flowers could be used to predict vulnerability of plant species to extinction. To do this we defined plant vulnerability using the Red Data Book of Rare and Threatened Plants of Greece, a Mediterranean biodiversity hotspot. We also tested whether other intrinsic (e.g. life form, asexual reproduction) or extrinsic (e.g. habitat, altitude, range-restrictedness) factors could affect plant vulnerability. We found that plants with high floral complexity scores were significantly more likely to be vulnerable to extinction. Among all the floral complexity components only floral symmetry was found to have a significant effect, with radial-flower plants appearing to be less vulnerable. Life form was also a predictor of vulnerability, with woody perennial plants having significantly lower risk of extinction. Among the extrinsic factors, both habitat and maximum range were significantly associated with plant vulnerability (coastal plants and narrow-ranged plants are more likely to face higher risk). Although extrinsic and in particular anthropogenic factors determine plant extinction risk, intrinsic traits can indicate a plant's proneness to vulnerability. This raises the potential threat of declining global pollinator diversity interacting with floral complexity to increase the vulnerability of individual plant species. There is potential scope for using plant-pollinator specializations to identify plant species particularly at risk and so target conservation efforts towards them.

SUBMITTER: Stefanaki A

PROVIDER: S-EPMC4577097 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lessons from Red Data Books: Plant Vulnerability Increases with Floral Complexity.

Stefanaki Anastasia A Kantsa Aphrodite A Tscheulin Thomas T Charitonidou Martha M Petanidou Theodora T

PloS one 20150921 9

The architectural complexity of flower structures (hereafter referred to as floral complexity) may be linked to pollination by specialized pollinators that can increase the probability of successful seed set. As plant-pollinator systems become fragile, a loss of such specialized pollinators could presumably result in an increased likelihood of pollination failure. This is an issue likely to be particularly evident in plants that are currently rare. Using a novel index describing floral complexit ...[more]

PMID: 26390402

Similar Datasets

Project description:Shorter photoperiod and lower daily light integral (DLI) limit the winter greenhouse production. Extending the photoperiod by supplemental light increases biomass production but inhibits flowering in short-day plants such as Chrysanthemum morifolium. Previously, we reported that flowering in growth-chamber grown chrysanthemum with red (R) and blue (B) LED-light could also be induced in long photoperiods by applying only blue light during the last 4h of 15h long-days. This study investigates the possibility to induce flowering by extending short-days in greenhouses with 4h of blue light. Furthermore, flower induction after 4h of red light extension was tested after short-days RB-LED light in a growth-chamber and after natural solar light in a greenhouse. Plants were grown at 11h of sole source RB light (60:40) in a growth-chamber or solar light in the greenhouse (short-days). Additionally, plants were grown under long-days, which either consisted of short-days as described above extended with 4h of B or R light to long-days or of 15h continuous RB light or natural solar light. Flower initiation and normal capitulum development occurred in the blue-extended long-days in the growth-chamber after 11h of sole source RB, similarly as in short-days. However, when the blue extension was applied after 11h of full-spectrum solar light in a greenhouse, no flower initiation occurred. With red-extended long-days after 11h RB (growth-chamber) flower initiation occurred, but capitulum development was hindered. No flower initiation occurred in red-extended long-days in the greenhouse. These results indicate that multiple components of the daylight spectrum influence different phases in photoperiodic flowering in chrysanthemum in a time-dependent manner. This research shows that smart use of LED-light can open avenues for a more efficient year-round cultivation of chrysanthemum by circumventing the short-day requirement for flowering when applied in emerging vertical farm or plant factories that operate without natural solar light. In current year-round greenhouses' production, however, extension of the natural solar light during the first 11 h of the photoperiod with either red or blue sole LED light, did inhibit flowering.

Project description:Understanding how urbanization alters functional interactions among pollinators and plants is critically important given increasing anthropogenic land use and declines in pollinator populations. Pollinators often exhibit short-term specialization and visit plants of the same species during one foraging trip. This facilitates plant receipt of conspecific pollen-pollen on a pollinator that is the same species as the plant on which the pollinator was foraging. Conspecific pollen receipt facilitates plant reproductive success and is thus important to plant and pollinator persistence. We investigated how urbanization affects short-term specialization of insect pollinators by examining pollen loads on insects' bodies and identifying the number and species of pollen grains on insects caught in urban habitat fragments and natural areas. We assessed possible drivers of differences between urban and natural areas, including frequency dependence in foraging, species richness and diversity of the plant and pollinator communities, floral abundance, and the presence of invasive plant species. Pollinators were more specialized in urban fragments than in natural areas, despite no differences in the species richness of plant communities across site types. These differences were likely driven by higher specialization of common pollinators, which were more abundant in urban sites. In addition, pollinators preferred to forage on invasive plants at urban sites and native plants at natural sites. Our findings reveal indirect effects of urbanization on pollinator fidelity to individual plant species and have implications for the maintenance of plant species diversity in small habitat fragments. Higher preference of pollinators for invasive plants at urban sites suggests that native species may receive fewer visits by pollinators. Therefore, native plant species diversity may decline in urban sites without continued augmentation of urban flora or removal of invasive species.

Project description:The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In contrast, machine learning approaches exploit similarities between the input text and already curated instances contained in a knowledge base to infer a functional profile. GO Annotations (GOA) and MEDLINE make possible to exploit a growing amount of curated abstracts (97 000 in November 2012) for populating this knowledge base. Our study compares a state-of-the-art thesaurus-based system with a machine learning system (based on a k-Nearest Neighbours algorithm) for the task of proposing a functional profile for unseen MEDLINE abstracts, and shows how resources and performances have evolved. Systems are evaluated on their ability to propose for a given abstract the GO terms (2.8 on average) used for curation in GOA. We show that since 2006, although a massive effort was put into adding synonyms in GO (+300%), our thesaurus-based system effectiveness is rather constant, reaching from 0.28 to 0.31 for Recall at 20 (R20). In contrast, thanks to its knowledge base growth, our machine learning system has steadily improved, reaching from 0.38 in 2006 to 0.56 for R20 in 2012. Integrated in semi-automatic workflows or in fully automatic pipelines, such systems are more and more efficient to provide assistance to biologists. DATABASE URL: http://eagl.unige.ch/GOCat/

Project description:BACKGROUND: Degradation is essential for RNA maturation, turnover, and quality control. RNA degradome sequencing that integrates a modified 5'-rapid amplification of cDNA ends protocol with next-generation sequencing technologies is a high-throughput approach for profiling the 5'-end of uncapped RNA fragments on a genome-wide scale. The primary application of degradome sequencing has been to identify the truncated transcripts that result from endonucleolytic cleavage guided by microRNAs or small interfering RNAs. As many pathways are involved in RNA degradation, degradome data should contain other RNA species besides the cleavage remnants of small RNA targets. Nevertheless, no systematic approaches have been established to explore the hidden complexity of plant degradome. RESULTS: Through analyzing Arabidopsis and rice RNA degradome data, we recovered 11 short motifs adjacent to predominant and abundant uncapped 5'-ends. Uncapped ends associated with several of these short motifs were more prevalent than those targeted by most miRNA families especially in the 3' untranslated region of transcripts. Through genome-wide analysis, five motifs showed preferential accumulation of uncapped 5'-ends at the same position in Arabidopsis and rice. Moreover, the association of uncapped 5'-ends with a CA-repeat motif and a motif recognized by Pumilio/Fem-3 mRNA binding factor (PUF) proteins was also found in non-plant species, suggesting that common mechanisms are present across species. Based on these motifs, potential sources of RNA ends that constitute degradome data were proposed and further examined. The 5'-end of small nucleolar RNAs could be precisely captured by degradome sequencing. Position-specific enrichment of uncapped 5'-ends was seen upstream of motifs recognized by several RNA binding proteins especially for the binding site of PUF proteins. False uncapped 5'-ends produced from capped transcripts through non-specific PCR amplification were common artifacts among degradome datasets. CONCLUSIONS: The complexity of plant RNA degradome data revealed in this study may contribute to the alternative applications of degradome in RNA research.

Project description:The study examines the potential influence of sub-regional variations in climate, and specifically heavy rain events, in determining relative vulnerabilities of locations in twelve Caribbean countries. An aggregate vulnerability index, referred to as the Caribbean Vulnerability Score (CVS), is created using historical demographic and socioeconomic data and climate data representing extreme rain events. Four scenarios are explored. Firstly, comparative vulnerabilities are determined when heavy rainfall is incorporated in CVS versus when it is excluded. The impact of climate change is also investigated using future climate data derived from statistical downscaling but holding demographic and socioeconomic sub-indices constant. The analysis is repeated with projections of future demographic structure from the Shared Socioeconomic Pathway data (SSP3), future climate projections and constant socioeconomic. Finally, the sensitivity of the results is examined with respect to applying different weights i.e. versus using equal weights for the climate and non-climatic components of CVS as is done for the first three scenarios. Results suggest that the inclusion of historical susceptibility to rainfall extremes influences relative vulnerabilities within the Caribbean when compared to the rankings of vulnerability derived using only socioeconomic and demographic inputs. In some cases significant increases in relative rankings are noted. Projected changes in the intensity of rain events across the Caribbean region in the 2030s and 2050s, do not significantly alter the top and lowest ranked vulnerable locations when demographic and socioeconomic indices are held constant. Changes may however occur in the order of the top ranked locations dependent on scenario and time slice. In general, future shifts in relative vulnerabilities were found to be dependent on (i) changes in both future climate and demographic scenarios, (ii) the time horizons being considered, and (iii) the weighting assigned to climate in the future.

Dataset Information

Lessons from Red Data Books: Plant Vulnerability Increases with Floral Complexity.

Publications

Lessons from Red Data Books: Plant Vulnerability Increases with Floral Complexity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets