Population Genetic Consequences of the Allee Effect and the Role of Offspring-Number Variation

A strong demographic Allee effect in which the expected population growth rate is negative below a certain critical population size can cause high extinction probabilities in small introduced populations. But many species are repeatedly introduced to the same location and eventually one population may overcome the Allee effect by chance. With the help of stochastic models, we investigate how much genetic diversity such successful populations harbor on average and how this depends on offspring-number variation, an important source of stochastic variability in population size. We find that with increasing variability, the Allee effect increasingly promotes genetic diversity in successful populations. Successful Allee-effect populations with highly variable population dynamics escape rapidly from the region of small population sizes and do not linger around the critical population size. Therefore, they are exposed to relatively little genetic drift. It is also conceivable, however, that an Allee effect itself leads to an increase in offspring-number variation. In this case, successful populations with an Allee effect can exhibit less genetic diversity despite growing faster at small population sizes. Unlike in many classical population genetics models, the role of offspring-number variation for the population genetic consequences of the Allee effect cannot be accounted for by an effective-population-size correction. Thus, our results highlight the importance of detailed biological knowledge, in this case on the probability distribution of family sizes, when predicting the evolutionary potential of newly founded populations or when using genetic data to reconstruct their demographic history.     

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change

A new computation framework (BIOMOD: BIOdiversity MODelling) is presented, which aims to maximize the predictive accuracy of current species distributions and the reliability of future potential distributions using different types of statistical modelling methods. BIOMOD capitalizes on the different techniques used in static modelling to provide spatial predictions. It computes, for each species and in the same package, the four most widely used modelling techniques in species predictions, namely Generalized Linear Models (GLM), Generalized Additive Models (GAM), Classification and Regression Tree analysis (CART) and Artificial Neural Networks (ANN). BIOMOD was applied to 61 species of trees in Europe using climatic quantities as explanatory variables of current distributions. On average, all the different modelling methods yielded very good agreement between observed and predicted distributions. However, the relative performance of different techniques was idiosyncratic across species, suggesting that the most accurate model varies between species. The results of this evaluation also highlight that slight differences between current predictions from different modelling techniques are exacerbated in future projections. Therefore, it is difficult to assess the reliability of alternative projections without validation techniques or expert opinion. It is concluded that rather than using a single modelling technique to predict the distribution of several species, it would be more reliable to use a framework assessing different models for each species and selecting the most accurate one using both evaluation methods and expert knowledge.     

First known gall midge (Diptera: Cecidomyiidae) from Arecaceae: Normanbyomyia fructivora gen. & sp. n. damaging fruit of the black palm, Normanbya normanbyi, in tropical Australia

Abstract  A new species of gall midge, Normanbyomyia fructivora gen. & sp. n., was found infesting flowers and fruit of the black palm, Normanbya normanbyi (Arecaceae), in the tropical forest of north-eastern Australia. Larvae of the gall midge live between the perianth and the young fruit causing abnormal fruit growth. Infested fruit are substantially smaller than healthy ones, fall off prematurely and decay on the ground without producing seedlings. Normanbyomyia , a new genus erected for the new species is placed within the supertribe Lasiopteridi and is characterised by a conspicuous female abdominal segment 8 that is inflated and strongly sclerotised, and wide male parameres that loosely sheath the aedeagus and bear no papillae. A key to Australian Lasiopteridi is provided. The new species becomes the first described gall midge that feeds on a plant from the palm family, Arecaceae.     

Ethidium monoazide and propidium monoazide for elimination of unspecific DNA background in quantitative universal real-time PCR

Unspecific background DNA in quantitative universal real-time PCR utilizing a hydrolysis probe was completely suppressed by the addition of EMA or PMA to the PCR mix via cross-linking of the dyes to DNA during 650 W visible light exposure. The proposed procedure had no effect on the sensitivity of the real-time PCR reaction.     

Maize <Emphasis Type="Italic">Lc</Emphasis> transcription factor enhances biosynthesis of anthocyanins,distinct proanthocyanidins and phenylpropanoids in apple (<Emphasis Type="Italic">Malus domestica</Emphasis> Borkh.)

Flavonoids are a large family of polyphenolic compounds with manifold functions in plants. Present in a wide range of vegetables and fruits, flavonoids form an integral part of the human diet and confer multiple health benefits. Here, we report on metabolic engineering of the flavonoid biosynthetic pathways in apple (Malus domestica Borkh.) by overexpression of the maize (Zea mays L.) leaf colour (Lc) regulatory gene. The Lc gene was transferred into the M. domestica cultivar Holsteiner Cox via Agrobacterium tumefaciens-mediated transformation which resulted in enhanced anthocyanin accumulation in regenerated shoots. Five independent Lc lines were investigated for integration of Lc into the plant genome by Southern blot and PCR analyses. The Lc-transgenic lines contained one or two Lc gene copies and showed increased mRNA levels for phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), flavanone 3 beta-hydroxylase (FHT), dihydroflavonol 4-reductase (DFR), leucoanthocyanidin reductases (LAR), anthocyanidin synthase (ANS) and anthocyanidin reductase (ANR). HPLC-DAD and LC-MS analyses revealed higher levels of the anthocyanin idaein (12-fold), the flavan 3-ol epicatechin (14-fold), and especially the isomeric catechin (41-fold), and some distinct dimeric proanthocyanidins (7 to 134-fold) in leaf tissues of Lc-transgenic lines. The levels of phenylpropanoids and their derivatives were only slightly increased. Thus, Lc overexpression in Malus domestica resulted in enhanced biosynthesis of specific flavonoid classes, which play important roles in both phytopathology and human health.     

Investigation of the mechanism of nicotine demethylation in Nicotiana through 2H and 15N heavy isotope effects: implication of cytochrome P450 oxidase and hydroxyl ion transfer

Heavy-atom isotope effects for the N-demethylation of nicotine have been determined in vivo in static-phase biosynthetically incompetent plant cell cultures of Nicotiana species. A (2)H kinetic isotope effect of 0.587 and a (15)N kinetic isotope effect of 1.0028 were obtained. An identical (15)N kinetic isotope effect of 1.0032 was obtained for the nicotine analogue, N-methyl-2-phenylpyrrolidine. The magnitude of the (15)N heavy-atom isotope effect indicates that the fission of the CN bond is not rate limiting for demethylation. The theoretical calculation of heavy-atom isotope effects for a model of the reaction pathway based on cytochrome P450 best fits the measured kinetic isotope effect to the addition of hydroxyl ion to iminium to form N-hydroxymethyl, for which the computed (2)H- and (15)N kinetic isotope effects are 0.689 and 1.0081, respectively. This large inverse (2)H kinetic isotope effect is not compatible with the initial abstraction of the H from the methyl group playing a significant kinetic role in the overall kinetic limitation of the reaction pathway, since computed values for this step (4.54 and 0.9995, respectively) are inconsistent with the experimental data.     

A plastid-localized glycogen synthase kinase 3 modulates stress tolerance and carbohydrate metabolism

Glycogen synthase kinase 3 (GSK-3) was originally identified as a regulator of glycogen synthesis in mammals. Like starch in plants, glycogen is a polymer of glucose, and serves as an energy and carbon store. Starch is the main carbohydrate store in plants. Regulation of starch metabolism, in particular in response to environmental cues, is of primary importance for carbon and energy flow in plants but is still obscure. Here, we provide evidence that MsK4, a novel Medicago sativa GSK-3-like kinase, connects stress signalling with carbon metabolism. MsK4 was found to be a plastid-localized protein kinase that is associated with starch granules. High-salt stress rapidly induced the in vivo kinase activity of MsK4. Metabolic profiling of MsK4 over-expressor lines revealed changes in sugar metabolism, including increased amounts of maltose, the main degradation product of starch in leaves. Plants over-expressing MsK4 showed improved tolerance to salt stress. Moreover, under high-salinity conditions, MsK4-over-expressing plants accumulated significantly more starch and showed modified carbohydrate content compared with wild-type plants. Overall, these data indicate that MsK4 is an important regulator that adjusts carbohydrate metabolism to environmental stress.