Adaptive responses to living in stressful habitats: Do invasive and native plant populations use different strategies?

Plants inhabit stressful environments characterized by a variety of stressors, including mine sites, mountains, deserts, and high latitudes. Populations from stressful and reference (non-stressful) sites often have performance differences. However, while invasive and native species may respond differently to stressful environments, there is limited understanding of the patterns in reaction norms of populations from these sites. Here, we use phylogenetically controlled meta-analysis to assess the performance of populations under stress and non-stress conditions. We ask whether stress populations of natives and invasives differ in the magnitude of lowered performance under non-stress conditions and if they vary in the degree of performance advantage under stress. We also assessed whether these distinctions differ with stress intensity. Our findings revealed that natives not only have greater adaptive advantages but also more performance reductions than invasives. Populations from very stressful sites had more efficient adaptations, and performance costs increased with stress intensity in natives only. Overall, the results support the notion that adaptation is frequently costless. Reproductive output was most closely associated with adaptive costs and benefits. Our study characterized the adaptive strategies used by invasive and native plants under stressful conditions, thereby providing important insights into the limitations of adaptation to extreme sites.

Microplastics and cadmium affect invasion success by altering complementarity and selection effects in native community.

The diversity-invasibility hypothesis predicts that native plant communities with high biodiversity should be more resistant to invasion than low biodiversity communities. However, observational studies have found that there is often a positive relationship between native community diversity and invasibility. Pollutants were not tested for their potential to cause this positive relationship. Here, we established native communities with three levels of diversity (1, 2 and 4 species) and introduced an invasive plant [Symphyotrichum subulatum (Michx.) G. L. Nesom] to test the effects of different pollutant treatments (i.e., unpolluted control, microplastics (MPs) alone, cadmium (Cd) alone, and their combination) on the relationship between native community diversity and community invasibility. Our results indicate that different MPs and Cd treatments altered the invasibility of native communities, but this effect may depend on the type of pollutant. MPs single treatment reduced invasion success, and the degree of reduction increased with increasing native community diversity (Diversity 2: - 14.1 %; Diversity 4: - 63.1 %). Cd single treatment increased the aboveground biomass of invasive plants (+ 40.2 %) and invasion success. The presence of MPs inhibited the contribution of Cd to invasion success. Furthermore, we found that the complementarity and selection effects of the native community were negatively correlated with invasion success, and their relative contributions to invasion success also depended on the pollutant type. We found new evidence of how pollutants affect the relationship between native community diversity and habitat invasibility, which provides new perspectives for understanding and managing biological invasions in the context of environmental pollution. This may contribute to promoting the conservation of biodiversity, especially in ecologically sensitive and polluted areas.

Where to draw the boundaries? Using landscape genomics to disentangle the scribbly gum species complex.

PREMISE: Species delimitation is an integral part of evolution and ecology and is vital in conservation science. However, in some groups, species delimitation is difficult, especially where ancestral relationships inferred from morphological or genetic characters are discordant, possibly due to a complicated demographic history (e.g., recent divergences between lineages). Modern genetic techniques can take into account complex histories to distinguish species at a reasonable cost and are increasingly used in numerous applications. We focus on the scribbly gums, a group of up to five closely related and morphologically similar "species" within the eucalypts. METHODS: Multiple populations of each recognized scribbly gum species were sampled over a wide region across climates, and genomewide scans were used to resolve species boundaries. RESULTS: None of the taxa were completely divergent, and there were two genetically distinct entities: the inland distributed Eucalyptus rossii and a coastal conglomerate consisting of four species forming three discernible, but highly admixed groups. Divergence among taxa was likely driven by temporal vicariant processes resulting in partial separation across biogeographic barriers. High interspecific gene flow indicated separated taxa reconnected at different points in time, blurring species boundaries. CONCLUSIONS: Our results highlight the need for genetic screening when dealing with closely related taxonomic entities, particularly those with modest morphological differences. We show that high-throughput sequencing can be effective at identifying species groupings and processes driving divergence, even in the most taxonomically complex groups, and be used as a standard practice for disentangling species complexes.

Insights into the Mechanisms Involved in Lead (Pb) Tolerance in Invasive Plants-The Current Status of Understanding.

Invasive plant species possess remarkable abilities to establish themselves in new environments and to displace native species. Their success can be attributed to various physiological and biochemical mechanisms, allowing them to tolerate adverse environmental conditions, including high lead (Pb) toxicity. Comprehension of the mechanisms responsible for Pb tolerance in invasive plants is still limited, but it is rapidly evolving. Researchers have identified several strategies in invasive plants to tolerate high levels of Pb. This review provides an overview of the current understanding of the ability of invasive species to tolerate or even accumulate Pb in plant tissues, including vacuoles and cell walls, as well as how rhizosphere biota (bacteria and mycorrhizal fungi) help them to enhance Pb tolerance in polluted soils. Furthermore, the article highlights the physiological and molecular mechanisms regulating plant responses to Pb stress. The potential applications of these mechanisms in developing strategies for remediating Pb-contaminated soils are also discussed. Specifically, this review article provides a comprehensive understanding of the current status of research on the mechanisms involved in Pb tolerance in invasive plants. The information presented in this article may be useful in developing effective strategies for managing Pb-contaminated soils, as well as for developing more resilient crops in the face of environmental stressors.

Effects of Warming, Phosphorous Deposition, and Both Treatments on the Growth and Physiology of Invasive Solidago canadensis and Native Artemisia argyi.

Anthropogenic climate change and species invasion are two major threats to biodiversity, affecting the survival and distribution of many species around the world. Studying the responses of invasive species under climate change can help better understand the ecological and genetic mechanisms of their invasion. However, the effects of warming and phosphorus deposition on the phenotype of native and invasive plants are unknown. To address the problem, we applied warming (+2.03 °C), phosphorus deposition (4 g m-2 yr-1 NaH2PO4), and warming × phosphorus deposition to Solidago canadensis and Artemisia argyi to measure the direct effects of environmental changes on growth and physiology at the seedling stage. Our results reveal that the physiology parameters of A. argyi and S. canadensis did not change significantly with the external environment. Under phosphorus deposition, S. canadensis had higher plant height, root length, and total biomass compared to A. argyi. Interestingly, warming has an inhibitory effect on the growth of both A. argyi and S. canadensis, but overall, the reduction in total biomass for S. canadensis (78%) is significantly higher than A. argyi (52%). When the two plants are treated with warming combined with phosphorus deposition, the advantage gained by S. canadensis from phosphorus deposition is offset by the negative effects of warming. Therefore, under elevated phosphorus, warming has a negative effect on the invasive S. canadensis and reduces its growth advantage.

Influence of multiple global change drivers on plant invasion: Additive effects are uncommon.

Invasive plants threaten biodiversity and cause huge economic losses. It is thought that global change factors (GCFs) associated with climate change (including shifts in temperature, precipitation, nitrogen, and atmospheric CO2) will amplify their impacts. However, only few studies assessed mixed factors on plant invasion. We collated the literature on plant responses to GCFs to explore independent, combined, and interactive effects on performance and competitiveness of native and invasive plants. From 176 plant species, our results showed that: (1) when native and invasive plants are affected by both independent and multiple GCFs, there is an overall positive effect on plant performance, but a negative effect on plant competitiveness; (2) under increased precipitation or in combination with temperature, most invasive plants gain advantages over natives; and (3) interactions between GCFs on plant performance and competitiveness were mostly synergistic or antagonistic. Our results indicate that native and invasive plants may be affected by independent or combined GCFs, and invasive plants likely gain advantages over native plants. The interactive effects of factors on plants were non-additive, but the advantages of invasive plants may not increase indefinitely. Our findings show that inferring the impacts of climate change on plant invasion from factors individually could be misleading. More mixed factor studies are needed to predict plant invasions under global change.

Floristic composition of Jandaf Mountain as biodiversity hotspot area in southwestern Saudi Arabia.

Arid environments around the world are characterized by lower plant diversity. However, some specific locations have relatively high species richness and have significant importance in terms of vegetation structure and plant diversity. Jabal Al-Jandaf is located in an arid area within the eastern side of mountainous region in the southwest of Saudi Arabia. It consists of valleys, lower plain and upper plain habitats with unique and diverse vegetation. These habitats range from 1000 m above sea level near the Tarj valley to 1910 m at the summit. In this study, we conducted a first survey of the floristic diversity at Jandaf Mountain. Furthermore, we applied the criteria of the Important Plant Area (IPA) and the High Conservation Value (HCV) approaches to assess whether the plant community at Jandaf Mountain qualifies as a significant conservation area. We found that the study area has great plant diversity with plant composition varying among the different habitats (e.g., valleys, upper and lower elevations) within the study area. We recorded 118 species from 97 genera belonging to 42 families, including endemic (e.g. Aloe pseudorubroviolacea), near-endemic (e.g. Monolluma quadrangular), and endangered species (e.g. Dracaena serrulata, Combretum molle, and Moringa peregrine). The plant diversity at Jandaf Mountain achieves the criteria outlined in the IPA and HCV approaches. Therefore, we conclude that Jandaf Mountain has a unique vegetation structure, and the area qualifies for conservation as a high value area for biodiversity and conservation of global significance.

Pathogen resistance in Sphagneticola trilobata (Singapore daisy): molecular associations and differentially expressed genes in response to disease from a widespread fungus.

Understanding the molecular associations underlying pathogen resistance in invasive plant species is likely to provide useful insights into the effective control of alien plants, thereby facilitating the conservation of native biodiversity. In the current study, we investigated pathogen resistance in an invasive clonal plant, Sphagneticola trilobata, at the molecular level. Sphagneticola trilobata (i.e., Singapore daisy) is a noxious weed that affects both terrestrial and aquatic ecosystems, and is less affected by pathogens in the wild than co-occurring native species. We used Illumina sequencing to investigate the transcriptome of S. trilobata following infection by a globally distributed generalist pathogen (Rhizoctonia solani). RNA was extracted from leaves of inoculated and un-inoculated control plants, and a draft transcriptome of S. trilobata was generated to examine the molecular response of this species following infection. We obtained a total of 49,961,014 (94.3%) clean reads for control (un-inoculated plants) and 54,182,844 (94.5%) for the infected treatment (inoculated with R. solani). Our analyses facilitated the discovery of 117,768 de novo assembled contigs and 78,916 unigenes. Of these, we identified 3506 differentially expressed genes and 60 hormones associated with pathogen resistance. Numerous genes, including candidate genes, were associated with plant-pathogen interactions and stress response in S. trilobata. Many recognitions, signaling, and defense genes were differentially regulated between treatments, which were confirmed by qRT-PCR. Overall, our findings improve our understanding of the genes and molecular associations involved in plant defense of a rapidly spreading invasive clonal weed, and serve as a valuable resource for further work on mechanism of disease resistance and managing invasive plants.

Looks can be deceiving: speciation dynamics of co-distributed Angophora (Myrtaceae) species in a varying landscape.

Understanding the mechanisms underlying species divergence remains a central goal in evolutionary biology. Landscape genetics can be a powerful tool for examining evolutionary processes. We used genome-wide scans to genotype samples from populations of eight Angophora species. Angophora is a small genus within the eucalypts comprising common and rare species in a heterogeneous landscape, making it an appropriate group to study speciation. We found A. hispida was highly differentiated from the other species. Two subspecies of A. costata (subsp. costata and subsp. euryphylla) formed a group, while the third (subsp. leiocarpa, which is only distinguished by its smooth fruits and provenance) was supported as a distinct pseudocryptic species. Other species that are morphologically distinct could not be genetically differentiated (e.g., A. floribunda and A. subvelutina). Distribution and genetic differentiation within Angophora were strongly influenced by temperature and humidity, as well as biogeographic barriers, particularly rivers and higher elevation regions. While extensive introgression was found between many populations of some species (e.g., A. bakeri and A. floribunda), others only hybridized at certain locations. Overall, our findings suggest multiple mechanisms drove evolutionary diversification in Angophora and highlight how genome-wide analyses of related species in a diverse landscape can provide insights into speciation.

Cadmium hyperaccumulation as an inexpensive metal armor against disease in Crofton weed.

Invasive plants readily invade metal-contaminated areas. The hyperaccumulation of toxic heavy metals is not an uncommon feature among plant species. Although several hypotheses were proposed to explain this phenomenon, it is currently unclear how hyperaccumulation may benefit plants. The invasive Crofton weed (Ageratina adenophora) is a known hyperaccumulator of chromium and lead. We previously found that the species can also hyperaccumulate cadmium. The role of phytoaccumulation in defense to pathogen attack is unclear. We inoculated A. adenophora plants with a common generalist pathogen (Rhizoctonia solani) to test its resistance under cadmium treatment. We found evidence that cadmium hyperaccumulation reduced pathogen infection in A. adenophora. Our findings indicate elemental defense is highly cost efficient for hyperaccumulators inhabiting metal-contaminated sites, where plants were only modestly affected by cadmium. The reduction in pathogen damage conferred by cadmium was relatively high, particularly under lower cadmium levels. However, the benefits at higher levels may be capped. Elemental defense may be a key mechanism for plant invasion into polluted sites, especially in regions with widespread industrial activity. Our study highlights the importance of testing different metal concentrations when testing plant resistance and the importance of considering enemy attack when selecting plants for phytoremediation.

Metal Artifacts Reduction in CT Scans using Convolutional Neural Network with Ground Truth Elimination.

Metal artifacts are very common in CT scans since metal insertion or replacement is performed for enhancing certain functionality or mechanism of patient's body. These streak artifacts could degrade CT image quality severely, and consequently, they could influence clinician's diagnosis. Many existing supervised learning methods approaching this problem assume the availability of clean images data, images free of metal artifacts, at the part with metal implant. However, in clinical practices, those clean images do not usually exist. Therefore, there is no support for the existing supervised learning based methods to work clinically. We focus on reducing the streak artifacts on the hip scans and propose a convolutional neural network based method to eliminate the need of the clean images at the implant part during model training. The idea is to use the scans of the parts near the hip for model training. Our method is able to suppress the artifacts in corrupted images, highly improve the image quality, and preserve the details of surrounding tissues, without using any clean hip scans. We apply our method on clinical CT hip scans from multiple patients and obtain artifact-free images with high image quality.

Allelopathy confers an invasive Wedelia higher resistance to generalist herbivore and pathogen enemies over its native congener.

The Novel Defense Hypothesis predicts that introduced plants may possess novel allelochemicals which act as a defense against native generalist enemies. Here, we aim to test if the chemicals involved in allelopathy in the invasive plant Wedelia trilobata can contribute to higher resistance against generalist herbivore and pathogen enemies by comparing with its native congener W. chinensis in controlled laboratory conditions. The allelopathic effects of the leaf extract from W. trilobata on the generalist enemies were also assessed. We showed that the larvae of two moth species preferred W. chinensis over W. trilobata. The growth rate of larvae feeding on W. trilobata leaves was significantly lower than those feeding on W. chinensis leaves. When detached leaves were inoculated with phytopathogens, the infected leaf area of W. trilobata was significantly smaller than that of W. chinensis. In addition, the leaf extract of W. trilobata also effectively inhibited the growth of the larvae and the mycelial growth of the phytopathogens. Our results indicate that the defenses of invasive W. trilobata against generalist herbivore and pathogen enemies are stronger than that of its native congener, which may be attributed to the allelopathic effects. This study provides novel insights that can comprehensively link the Novel Defense, Behavioral Constraint and Enemy Release hypotheses. These combined hypotheses would explain how invasive plants escape from their natural specialist enemies, where their allelopathic chemicals may deter herbivorous insects and inhibit pathogen infection.

Gene Expression Profiling Reveals Enhanced Defense Responses in an Invasive Weed Compared to Its Native Congener During Pathogenesis.

Invasive plants are a huge burden on the environment, and modify local ecosystems by affecting the indigenous biodiversity. Invasive plants are generally less affected by pathogens, although the underlying molecular mechanisms responsible for their enhanced resistance are unknown. We investigated expression profiles of three defense hormones (salicylic acid, jasmonic acid, and ethylene) and their associated genes in the invasive weed, Alternanthera philoxeroides, and its native congener, A. sessilis, after inoculation with Rhizoctonia solani. Pathogenicity tests showed significantly slower disease progression in A. philoxeroides compared to A. sessilis. Expression analyses revealed jasmonic acid (JA) and ethylene (ET) expressions were differentially regulated between A. philoxeroides and A. sessilis, with the former having prominent antagonistic cross-talk between salicylic acid (SA) and JA, and the latter showing weak or no cross-talk during disease development. We also found that JA levels decreased and SA levels increased during disease development in A. philoxeroides. Variations in hormonal gene expression between the invasive and native species (including interspecific differences in the strength of antagonistic cross-talk) were identified during R. solani pathogenesis. Thus, plant hormones and their cross-talk signaling may improve the resistance of invasive A. philoxeroides to pathogens, which has implications for other invasive species during the invasion process.

Automated segmentation of cellular images using an effective region force.

Understanding the behavior of cells is an important problem for biologists. Significant research has been done to facilitate this by automating the segmentation of microscopic cellular images. Bright-field images of cells prove to be particularly difficult to segment, due to features such as low contrast, missing boundaries, and broken halos. We present two algorithms for automated segmentation of cellular images. These algorithms are based on a graph-partitioning approach, where each pixel is modeled as a node of a weighted graph. The method combines an effective region force with the Laplacian and total variation boundary forces, respectively, to give the two models. This region force can be interpreted as a conditional probability of a pixel belonging to a certain class (cell or background) given a small set of already labeled pixels. For practicality, we use a small set of only background pixels from the border of cell images as the labeled set. Both algorithms are tested on bright-field images to give good results. Due to faster performance, the Laplacian-based algorithm is also tested on a variety of other datasets, including fluorescent images, phase-contrast images, and 2-D and 3-D simulated images. The results show that the algorithm performs well and consistently across a range of various cell image features, such as the cell shape, size, contrast, and noise levels.

Reconstruction of missing cells by a Killing energy minimizing nonrigid image registration.

Fluorescent microscopy has been a popular and important tool for studying live cells. One challenge of analyzing cell images obtained from fluorescent microscopy is that cells in fluorescent images frequently disappear and reappear, making cell tracking difficult. In this paper, we present an image registration approach which can reconstruct both the cell appearance and location of the missing cells from the image frames where the cells become invisible. The idea is to perform an image registration on the images before and after a cell disappears. The missing image frames between these two images are given by the intermediate registration results. The formulation is based on the nonrigid particle registration model, which captures soft deformation of the cells. In addition, to obtain natural and more rigid cell movements such as translation and rotation, we propose a new registration technique which is Killing energy minimizing, motivated by the fact that a Killing vector field with zero Killing energy will generate an isometric deformation. We will present reconstruction results of C2C12 cells in fluorescent images to illustrate the effectiveness of our model by different numerical examples.

A continuous method for reducing interpolation artifacts in mutual information-based rigid image registration.

We propose an approach for computing mutual information in rigid multimodality image registration. Images to be registered are modeled as functions defined on a continuous image domain. Analytic forms of the probability density functions for the images and the joint probability density function are first defined in 1D. We describe how the entropies of the images, the joint entropy, and mutual information can be computed accurately by a numerical method. We then extend the method to 2D and 3D. The mutual information function generated is smooth and does not seem to have the typical interpolation artifacts that are commonly observed in other standard models. The relationship between the proposed method and the partial volume (PV) model is described. In addition, we give a theoretical analysis to explain the nonsmoothness of the mutual information function computed by the PV model. Numerical experiments in 2D and 3D are presented to illustrate the smoothness of the mutual information function, which leads to robust and accurate numerical convergence results for solving the image registration problem.

Reconstruction of missing cells in fluorescent microscopy.

Fluorescent microscopy is one of the several types of imaging techniques used by biologists to study cell activities. One challenge of tracking cells from fluorescence microscopy is that cells in fluorescent images frequently disappear and reappear. The situation is further complicated by cell divisions, which also occur frequently in an image sequence. In this paper, we apply a level set method to reconstruct cells that disappear in an image sequence and in particular, cells that are undergoing cell division. The image frames are stacked together to form a 3D image volume. The disappearance of a cell leads to a broken cell path. We reconstruct the incomplete cell paths by a level set segmentation of the 3D image volume. If the disappearance happens during cell division, the level set method segments the visible cell paths before and after cell division, and then joins them together by extending the cell paths into the missing gap. We also propose a simple and cost-efficient method similar to inpainting techniques to capture the cell appearance when it disappears by making use of the level set function obtained from the segmentation. The idea is that the intensities of a visible cell on a level set contour are copied to the corresponding contours of a disappeared cell. We will present results for reconstruction of cells undergoing cell division for C2C12 cells in fluorescent images to illustrate the effectiveness of our method.

A spectral k-means approach to bright-field cell image segmentation.

Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

Real-time intensity-based rigid 2d-3d medical image registration using RapidMind Multi-core Development Platform.

In this paper, we present an efficient intensity-based rigid 2D-3D image registration method. We implement the algorithm using the RapidMind Multi-core Development Platform(1) to exploit the highly parallel multi-core architecture of graphics processing units (GPUs). We use a ray casting algorithm to generate the digitally reconstructed radiographs (DRRs) on GPUs and efficiently reduce the complexity of DRR construction. The registration optimization problem is solved by the Gauss-Newton method. To fully exploit the multi-core parallelism, we implement almost the entire registration process in parallel by RapidMind. We also discuss the RapidMind implementation of the major computation steps. Numerical results are presented to demonstrate the efficiency of our method.