Small-scale genotypic richness stabilizes plot biomass and increases phenotypic variance in the invasive grass Phalaris arundinacea

Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China. All rights reserved. Aims We aim to understand how small-scale genotypic richness and genotypic interactions influence the biomass and potential invasiveness of the invasive grass, Phalaris arundinacea under two different disturbance treatments: intact plots and disturbed plots, where all the native vegetation has been removed. Specifically, we address the following questions (i) Does genotypic richness increase biomass production? (ii) Do genotypic interactions promote or reduce biomass production? (iii) Does the effect of genotypic richness and genotypic interactions differ in different disturbance treatments? Finally (iv) Is phenotypic variation greater as genotypic richness increases? Methods We conducted a 2-year common garden experiment in which we manipulated genotype richness using eight genotypes planted under both intact and disturbed conditions in a wetland in Burlington, Vermont (44°27′23″N, 73°11′29″W). The experiment consisted of a randomized complete block design of three blocks, each containing 20 plots (0.5 m 2) per disturbed treatment. We calculated total plot biomass and partitioned the net biodiversity effect into three components: dominance effect, trait-dependent complementarity and trait-independent complementarity. We calculated the phenotypic variance for each different genotype richness treatment under the two disturbance treatments. Important Findings Our results indicate that local genotypic richness does not increase total biomass production of the invasive grass P. arundinacea in either intact or disturbed treatments. However, genotypic interactions underlying the responses showed very different patterns in response to increasing genotypic richness. In the intact treatment, genotypic interactions resulted in the observed biomass being greater than the predicted biomass from monoculture plots (e.g., overyielding) and this was driven by facilitation. However, facilitation was reduced as genotypic richness increased. In the disturbed treatment, genotypic interactions resulted in underyielding with observed biomass being slightly less than expected from the performance of genotypes in monocultures; however, underyielding was reduced as genotypic richness increased. Thus, in both treatments, higher genotypic richness resulted in plot biomass nearing the additive biomass from individual monocultures. In general, higher genotypic richness buffered populations against interactions that would have reduced biomass and potentially spread. Phenotypic variance also had contrasting patterns in intact and disturbed treatments. In the intact treatment, phenotypic variance was low across all genotypic richness levels, while in the disturbed treatment, phenotypic variance estimates increased as genotypic richness increased. Thus, under the disturbed treatment, plots with higher genotypic richness had a greater potential response to selection. Therefore, limiting the introduction of new genotypes, even if existing genotypes of the invasive species are already present, should be considered a desirable management strategy to limit the invasive behavior of alien species

Simulating phase transitions and control measures for network epidemics caused by infections with presymptomatic, asymptomatic, and symptomatic stages

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. We investigate phase transitions associated with three control methods for epidemics on small world networks. Motivated by the behavior of SARS-CoV-2, we construct a theoretical SIR model of a virus that exhibits presymptomatic, asymptomatic, and symptomatic stages in two possible pathways. Using agent-based simulations on small world networks, we observe phase transitions for epidemic spread related to: 1) Global social distancing with a fixed probability of adherence. 2) Individually initiated social isolation when a threshold number of contacts are infected. 3) Viral shedding rate. The primary driver of total number of infections is the viral shedding rate, with probability of social distancing being the next critical factor. Individually initiated social isolation was effective when initiated in response to a single infected contact. For each of these control measures, the total number of infections exhibits a sharp phase transition as the strength of the measure is varied

Similarity of introduced plant species to native ones facilitates naturalization, but differences enhance invasion success

The search for traits associated with plant invasiveness has yielded contradictory results, in part because most previous studies have failed to recognize that different traits are important at different stages along the introduction–naturalization–invasion continuum. Here we show that across six different habitat types in temperate Central Europe, naturalized non-invasive species are functionally similar to native species occurring in the same habitat type, but invasive species are different as they occupy the edge of the plant functional trait space represented in each habitat. This pattern was driven mainly by the greater average height of invasive species. These results suggest that the primary determinant of successful establishment of alien species in resident plant communities is environmental filtering, which is expressed in similar trait distributions. However, to become invasive, established alien species need to be different enough to occupy novel niche space, i.e. the edge of trait space

Trait positions for elevated invasiveness in adaptive ecological networks

Our ability to predict the outcome of invasion declines rapidly as non-native species progress through intertwined ecological barriers to establish and spread in recipient ecosystems. This is largely due to the lack of systemic knowledge on key processes at play as species establish self-sustaining populations within the invaded range. To address this knowledge gap, we present a mathematical model that captures the eco-evolutionary dynamics of native and non-native species interacting within an ecological network. The model is derived from continuous-trait evolutionary game theory (i.e., Adaptive Dynamics) and its associated concept of invasion fitness which depicts dynamic demographic performance that is both trait mediated and density dependent. Our approach allows us to explore how multiple resident and non-native species coevolve to reshape invasion performance, or more precisely invasiveness, over trait space. The model clarifies the role of specific traits in enabling non-native species to occupy realised opportunistic niches. It also elucidates the direction and speed of both ecological and evolutionary dynamics of residing species (natives or non-natives) in the recipient network under different levels of propagule pressure. The versatility of the model is demonstrated using four examples that correspond to the invasion of (i) a horizontal competitive community; (ii) a bipartite mutualistic network; (iii) a bipartite antagonistic network; and (iv) a multi-trophic food web. We identified a cohesive trait strategy that enables the success and establishment of non-native species to possess high invasiveness. Specifically, we find that a non-native species can achieve high levels of invasiveness by possessing traits that overlap with those of its facilitators (and mutualists), which enhances the benefits accrued from positive interactions, and by possessing traits outside the range of those of antagonists, which mitigates the costs accrued from negative interactions. This ‘central-to-reap, edge-to-elude’ trait strategy therefore describes the strategic trait positions of non-native species to invade an ecological network. This model provides a theoretical platform for exploring invasion strategies in complex adaptive ecological networks

Targeting breast cancer stem cells

The cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self‐renewing CSC population that is also capable of differentiating into non‐self‐renewing cell populations that constitute the bulk of the tumor. Although, the CSC hypothesis does not directly address the cell of origin of cancer, it is postulated that tissue‐resident stem or progenitor cells are the most common targets of transformation. Clinically, CSCs are predicted to mediate tumor recurrence after chemo‐ and radiation‐therapy due to the relative inability of these modalities to effectively target CSCs. If this is the case, then CSC must be efficiently targeted to achieve a true cure. Similarities between normal and malignant stem cells, at the levels of cell‐surface proteins, molecular pathways, cell cycle quiescence, and microRNA signaling present challenges in developing CSC‐specific therapeutics. Approaches to targeting CSCs include the development of agents targeting known stem cell regulatory pathways as well as unbiased high‐throughput siRNA or small molecule screening. Based on studies of pathways present in normal stem cells, recent work has identified potential “Achilles heals” of CSC, whereas unbiased screening provides opportunities to identify new pathways utilized by CSC as well as develop potential therapeutic agents. Here, we review both approaches and their potential to effectively target breast CSC.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135704/1/mol2201045404.pd

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Closely related invasive species may be controlled by the same demographic life stages

Invasive species that are closely related to each other may have similar population dynamics and, therefore, be controlled by targeting similar life stages. We studied two invasive knapweed species, spotted knapweed (Centaurea stoebe subsp. micranthos) and the hybrid meadow knapweed complex (Centaurea × moncktonii) in New York, USA, to determine their individual population growth rates (λ) across several sites over three years. Both knapweed species had growth rates that were greater than 1 (spotted knapweed λ ranged from 1.005–1.440; meadow knapweed λ ranged from 1.541–2.408), but there was high variability between years and sites. One study population of meadow knapweed was composed primarily of individuals of black knapweed ancestry (C. nigra), a species that, while introduced, is not invasive. For this population, the projected dynamics were stable (λ approximately 1). Elasticity analysis showed that the flowering-to-flowering stage contributed the most to population growth rate for six of seven sites and three additional transitions were also influential for four of seven sites of spotted and meadow knapweed: the seedling-to-vegetative stage, vegetative-to-flowering stage and flowering-to-seedling stage. We simulated how increasing vital rates would affect population growth and found that both spotted and meadow knapweed followed the same pattern. The vital rate of established seedlings maturing to flowering plants had the greatest effect on population growth, followed by the survival of new and established seedlings. In all cases, the responses were non-linear, with small initial changes having a large effect. Increases in the vital rates of later stages also tended to have a positive effect on growth rate, but the effects were more modest. Although the sensitivity analysis indicated that early vital rates had the largest effect on population growth, targeting these stages is not practical for management. Rather, reducing older life stage survival or delaying maturation of vegetative individuals would be more effective. The similarity between the population dynamics and how each life stage contributes to population growth provides support that protocols developed for one species should be effective for the other species with the caveat that any biological control agent should be directly tested on the target species before being utilised