Distinct communities under the snow: describing characteristics of subnivium arthropod communities.

Arthropods are active during the winter in temperate regions. Many use the seasonal snowpack as a buffer against harsh ambient conditions and are active in a refugium known as the subnivium. While the use of the subnivium by arthropods is well established, far less is known about subnivium community composition, abundance, biomass, and diversity and how these characteristics compare with the community in the summer. Understanding subnivium communities is especially important given the observed and anticipated changes in snowpack depth and duration due to the changing climate. We compared subnivium arthropod communities with those active during the summer using pitfall trapping in northern New Hampshire. We found that compositions of ground-active arthropod communities in the subnivium differed from those in the summer. The subnivium arthropod community featured moderate levels of richness and other measures of diversity that tended to be lower than the summer community. More strikingly, the subnivium community was much lower in overall abundance and biomass. Interestingly, some arthropods were dominant in the subnivium but either rare or absent in summer collections. These putative "subnivium specialists" included the spider Cicurina brevis (Emerton 1890) (Araneae: Hahniidae) and 3 rove beetles (Coleoptera: Staphylinidae): Arpedium cribratum Fauvel, 1878, Lesteva pallipes LeConte, 1863, and Porrhodites inflatus (Hatch, 1957). This study provides a detailed account of the subnivium arthropod community, establishes baseline information on arthropod communities in temperate forests of northeastern North America, and explores the idea of subnivium specialist taxa that are highly active in winter and might be especially vulnerable to climate change.

Molecular detection and identification of Diatrypaceous airborne spores in Australian vineyards revealed high species diversity between regions.

The grapevine trunk disease, Eutypa dieback (ED), causes significant vine decline and yield reduction. For many years, the fungus Eutypa lata was considered the main pathogen causing ED of grapevines in Australia. Recent studies showed other Diatrypaceous fungi were also associated with vines exhibiting dieback symptoms but there is limited information on how these fungal pathogens spread in vineyards. Thus, information on the spore dispersal patterns of Diatrypaceous fungi in different wine regions will assist in identifying high-risk infection periods in vineyards. Using more than 6800 DNA samples from airborne spores collected from eight wine regions in south-eastern Australia over 8 years using a Burkard spore trap, this study investigated the diversity and abundance of Diatrypaceous species, using multi-faceted molecular tools. A multi-target quantitative PCR (qPCR) assay successfully detected and quantified Diatrypaceous spores from 30% of the total samples with spore numbers and frequency of detection varying between regions and years. The high-resolution melting analysis (HRMA) coupled with DNA sequencing identified seven species, with E. lata being present in seven regions and the most prevalent species in the Adelaide Hills, Barossa Valley and McLaren Vale. Cryptovalsa ampelina and Diatrype stigma were the predominant species in the Clare Valley and Coonawarra, respectively while Eutypella citricola and Eu. microtheca dominated in the Hunter Valley and the Riverina regions. This study represents the first report of D. stigma and Cryptosphaeria multicontinentalis in Australian vineyards. This study further showed rainfall as a primary factor that triggers spore release, however, other weather factors that may influence the spore release in different climatic regions of Australia still requires further investigation.

Differentiation between Descending Thoracic Aortic Diseases using Machine Learning and Plasma Proteomic Signatures.

Background: Descending thoracic aortic aneurysms and dissections can go undetected until severe and catastrophic, and few clinical indices exist to screen for aneurysms or predict risk of dissection. Methods: This study generated a plasma proteomic dataset from 75 patients with descending type B dissection (Type B) and 62 patients with descending thoracic aortic aneurysm (DTAA). Standard statistical approaches were compared to supervised machine learning (ML) algorithms to distinguish Type B from DTAA cases. Quantitatively similar proteins were clustered based on linkage distance from hierarchical clustering and ML models were trained with uncorrelated protein lists across various linkage distances with hyperparameter optimization using 5-fold cross validation. Permutation importance (PI) was used for ranking the most important predictor proteins of ML classification between disease states and the proteins among the top 10 PI protein groups were submitted for pathway analysis. Results: Of the 1,549 peptides and 198 proteins used in this study, no peptides and only one protein, hemopexin (HPX), were significantly different at an adjusted p-value <0.01 between Type B and DTAA cases. The highest performing model on the training set (Support Vector Classifier) and its corresponding linkage distance (0.5) were used for evaluation of the test set, yielding a precision-recall area under the curve of 0.7 to classify between Type B from DTAA cases. The five proteins with the highest PI scores were immunoglobulin heavy variable 6-1 (IGHV6-1), lecithin-cholesterol acyltransferase (LCAT), coagulation factor 12 (F12), HPX, and immunoglobulin heavy variable 4-4 (IGHV4-4). All proteins from the top 10 most important correlated groups generated the following significantly enriched pathways in the plasma of Type B versus DTAA patients: complement activation, humoral immune response, and blood coagulation. Conclusions: We conclude that ML may be useful in differentiating the plasma proteome of highly similar disease states that would otherwise not be distinguishable using statistics, and, in such cases, ML may enable prioritizing important proteins for model prediction.

Protein biomarkers of disease progression in patients with systemic sclerosis associated interstitial lung disease.

Systemic sclerosis is a rare connective tissue disease; and interstitial lung disease (SSc-ILD) is associated with significant morbidity and mortality. There are no clinical, radiologic features, nor biomarkers that identify the specific time when patients are at risk for progression at which the benefits from treatment outweigh the risks. Our study aimed to identify blood protein biomarkers associated with progression of interstitial lung disease in patients with SSc-ILD using an unbiased, high-throughput approach. We classified SSc-ILD as progressive or stable based on change in forced vital capacity over 12 months or less. We profiled serum proteins by quantitative mass spectrometry and analyzed the association between protein levels and progression of SSc-ILD via logistic regression. The proteins associated with at a p value of < 0.1 were queried in the ingenuity pathway analysis (IPA) software to identify interaction networks, signaling, and metabolic pathways. Through principal component analysis, the relationship between the top 10 principal components and progression was evaluated. Unsupervised hierarchical clustering with heatmapping was done to define unique groups. The cohort consisted of 72 patients, 32 with progressive SSc-ILD and 40 with stable disease with similar baseline characteristics. Of a total of 794 proteins, 29 were associated with disease progression. After adjusting for multiple testing, these associations did not remain significant. IPA identified five upstream regulators that targeted proteins associated with progression, as well as a canonical pathway with a higher signal in the progression group. Principal component analysis showed that the ten components with the highest Eigenvalues represented 41% of the variability of the sample. Unsupervised clustering analysis revealed no significant heterogeneity between the subjects. We identified 29 proteins associated with progressive SSc-ILD. While these associations did not remain significant after accounting for multiple testing, some of these proteins are part of pathways relevant to autoimmunity and fibrogenesis. Limitations included a small sample size and a proportion of immunosuppressant use in the cohort, which could have altered the expression of inflammatory and immunologic proteins. Future directions include a targeted evaluation of these proteins in another SSc-ILD cohort or application of this study design to a treatment naïve population.

High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing.

Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.

Phylogenetic risk assessment is robust for forecasting the impact of European insects on North American conifers.

Some introduced species cause severe damage, although the majority have little impact. Robust predictions of which species are most likely to cause substantial impacts could focus efforts to mitigate those impacts or prevent certain invasions entirely. Introduced herbivorous insects can reduce crop yield, fundamentally alter natural and managed forest ecosystems, and are unique among invasive species in that they require certain host plants to succeed. Recent studies have demonstrated that understanding the evolutionary history of introduced herbivores and their host plants can provide robust predictions of impact. Specifically, divergence times between hosts in the native and introduced ranges of a nonnative insect can be used to predict the potential impact of the insect should it establish in a novel ecosystem. However, divergence time estimates vary among published phylogenetic datasets, making it crucial to understand if and how the choice of phylogeny affects prediction of impact. Here, we tested the robustness of impact prediction to variation in host phylogeny by using insects that feed on conifers and predicting the likelihood of high impact using four different published phylogenies. Our analyses ranked 62 insects that are not established in North America and 47 North American conifer species according to overall risk and vulnerability, respectively. We found that results were robust to the choice of phylogeny. Although published vascular plant phylogenies continue to be refined, our analysis indicates that those differences are not substantial enough to alter the predictions of invader impact. Our results can assist in focusing biosecurity programs for conifer pests and can be more generally applied to nonnative insects and their potential hosts by prioritizing surveillance for those insects most likely to be damaging invaders.

Experimental and observational evidence of negative conspecific density dependence in temperate ectomycorrhizal trees.

Conspecific negative density dependence (CNDD) promotes tree species diversity by reducing recruitment near conspecific adults due to biotic feedbacks from herbivores, pathogens, or competitors. While this process is well-described in tropical forests, tests of temperate tree species range from strong positive to strong negative density dependence. To explain this, several studies have suggested that tree species traits may help predict the strength and direction of density dependence: for example, ectomycorrhizal-associated tree species typically exhibit either positive or weaker negative conspecific density dependence. More generally, the strength of density dependence may be predictably related to other species-specific ecological attributes such as shade tolerance, or the relative local abundance of a species. To test the strength of density dependence and whether it affects seedling community diversity in a temperate forest, we tracked the survival of seedlings of three ectomycorrhizal-associated species experimentally planted beneath conspecific and heterospecific adults on the Prospect Hill tract of the Harvard Forest, in Massachusetts, USA. Experimental seedling survival was always lower under conspecific adults, which increased seedling community diversity in one of six treatments. We compared these results to evidence of CNDD from observed sapling survival patterns of 28 species over approximately 8 years in an adjacent 35-ha forest plot. We tested whether species-specific estimates of CNDD were associated with mycorrhizal association, shade tolerance, and local abundance. We found evidence of significant, negative conspecific density dependence (CNDD) in 23 of 28 species, and positive conspecific density dependence in two species. Contrary to our expectations, ectomycorrhizal-associated species generally exhibited stronger (e.g., more negative) CNDD than arbuscular mycorrhizal-associated species. CNDD was also stronger in more shade-tolerant species but was not associated with local abundance. Conspecific adult trees often have a negative influence on seedling survival in temperate forests, particularly for tree species with certain traits. Here we found strong experimental and observational evidence that ectomycorrhizal-associating species consistently exhibit CNDD. Moreover, similarities in the relative strength of density dependence from experiments and observations of sapling mortality suggest a mechanistic link between negative effects of conspecific adults on seedling and sapling survival and local tree species distributions.

Obtaining and Maintaining Cultures of Pinewood Nematodes Bursaphelenchus xylophilus from Wild Dauers.

The establishment of laboratory isolates of the pinewood nematode Bursaphelenchus xylophilus, the causal agent of the pine wilt disease, has been crucial to research on this important forest pathogen. Here we describe a simple, low-cost, and easy way to obtain samples of wild populations of B. xylophilus by culturing dauers extracted directly from the insect vector.

Insect infestations and the persistence and functioning of oak-pine mixedwood forests in the mid-Atlantic region, USA.

Damage from infestations of Lymantria dispar L. in oak-dominated stands and southern pine beetle (Dendroctonus frontalis Zimmermann) in pine-dominated stands have far exceeded impacts of other disturbances in forests of the mid-Atlantic Coastal Plain over the last two decades. We used forest census data collected in undisturbed and insect-impacted stands combined with eddy covariance measurements made pre- and post-disturbance in oak-, mixed and pine-dominated stands to quantify how these infestations altered forest composition, structure and carbon dynamics in the Pinelands National Reserve of southern New Jersey. In oak-dominated stands, multi-year defoliation during L. dispar infestations resulted in > 40% mortality of oak trees and the release of pine saplings and understory vegetation, while tree mortality was minimal in mixed and pine-dominated stands. In pine-dominated stands, southern pine beetle infestations resulted in > 85% mortality of pine trees but had minimal effect on oaks in upland stands or other hardwoods in lowland stands, and only rarely infested pines in hardwood-dominated stands. Because insect-driven disturbances are both delaying and accelerating succession in stands dominated by a single genus but having less effect in mixed-composition stands, long-term disturbance dynamics are favoring the formation and persistence of uneven age oak-pine mixedwood stands. Changes in forest composition may have little impact on forest productivity and evapotranspiration; although seasonal patterns differ, with highest daily rates of net ecosystem production (NEP) during the growing season occurring in an oak-dominated stand and lowest in a pine-dominated stand, integrated annual rates of NEP are similar among oak-, mixed and pine-dominated stands. Our research documents the formation of mixedwood stands as a consequence of insect infestations in the mid-Atlantic region and suggests that managing for mixedwood stands could reduce damage to forest products and provide greater continuity in ecosystem functioning.

Analytical approaches for evaluating passive acoustic monitoring data: A case study of avian vocalizations.

The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand-annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated.We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling.To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer-based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days.Although our analyses used hand-annotated data, the methods will extend readily to large-scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer-based studies of avian ecology.

Impact of Stand and Landscape Management on Forest Pest Damage.

One promising approach to mitigate the negative impacts of insect pests in forests is to adapt forestry practices to create ecosystems that are more resistant and resilient to biotic disturbances. At the stand scale, local stand management practices often cause idiosyncratic effects on forest pests depending on the environmental context and the focal pest species. However, increasing tree diversity appears to be a general strategy for reducing pest damage across several forest types. At the landscape scale, increasing forest heterogeneity (e.g., intermixing different forest types and/or age classes) represents a promising frontier for improving forest resistance and resilience and for avoiding large-scale outbreaks. In addition to their greater resilience, heterogeneous forest landscapes frequently support a wide range of ecosystem functions and services. A challenge will be to develop cooperation and coordination among multiple actors at spatial scales that transcend historical practices in forest management.

Limited evidence that larger acorns buffer Quercus rubra seedlings from density-dependent biotic stressors.

PREMISE: Plant performance and functional traits vary considerably within species, particularly in response to environmental variation. Plant responses may reflect life-history trade-offs, such as between resource acquisition and resource conservation. Larger seeds may buffer young plants from the negative effects of environmental variation, such as limitations in nutrients or water. However, whether seed size plays a similar role in how plants respond to variation in their biotic environment, including competition and soil microbial communities, remains poorly understood. METHODS: We used a greenhouse experiment to test the interactive effects of intraspecific competition, the origin of the soil microbial community, and seed size on performance and functional traits in Quercus rubra L. seedlings. RESULTS: Intraspecific variation in seedling traits weakly aligned with a resource acquisition-conservation trade-off. Across the wide range of initial acorn mass, competition decreased seedling biomass by about 35%. Competition directly decreased the root mass ratio and indirectly increased specific leaf area and specific root length, via the negative effects on total biomass. In contrast, soil microbial communities had minor effects on seedlings, and we found no differences between plants receiving soil originating from a conspecific adult and plants receiving soil originating from a heterospecific adult. CONCLUSIONS: Competition is a more important driver of intraspecific variation in young Quercus rubra seedling performance and traits, both directly and by delaying ontogenetic development, than soil microbial communities. Seed size is an important predictor of seedling biomass, but a larger seed does not necessarily buffer seedlings from the effects of competition.

Discovery Proteomics for COVID-19: Where We Are Now.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the pandemic coronavirus disease 2019 (COVID-19), which has had a devastating impact on society. Here, we summarize proteomic research that has helped elucidate hallmark proteins associated with the disease with respect to both short- and long-term diagnosis and prognosis. Additionally, we review the highly variable humoral response associated with COVID-19 and the increased risk of autoimmunity.

Quantifying the nature and strength of intraspecific density dependence in Arctic mosquitoes.

Processes that change with density are inherent in all populations, yet quantifying density dependence with empirical data remains a challenge. This is especially true for animals recruiting in patchy landscapes because heterogeneity in habitat quality in combination with habitat choice can obscure patterns expected from density dependence. Mosquitoes (Diptera: Culicidae) typically experience strong density dependence when larvae compete for food, however, effects vary across species and contexts. If populations experience intense intraspecific density-dependent mortality then overcompensation can occur, where the number of survivors declines at high densities producing complex endogenous dynamics. To seek generalizations about density dependence in a widespread species of Arctic mosquito, Aedes nigripes, we combined a laboratory experiment, field observations, and modeling approaches. We evaluated alternative formulations of discrete population models and compared best-performing models from our lab study to larval densities from ponds in western Greenland. Survivorship curves from the lab were the best fit by a Hassell model with compensating density dependence (equivalent to a Beverton-Holt model) where peak recruitment ranged from 8 to 80 mosquitoes per liter depending on resource supply. In contrast, our field data did not show a signal of strong density dependence, suggesting that other processes such as predation may lower realized densities in nature, and that expected patterns may be obscured because larval abundance covaries with resources (cryptic density dependence). Our study emphasizes the importance of covariation between the environment, habitat choice, and density dependence in understanding population dynamics across landscapes, and demonstrates the value of pairing lab and field studies.

The epidemiological impact of the NHS COVID-19 app.

The COVID-19 pandemic has seen the emergence of digital contact tracing to help to prevent the spread of the disease. A mobile phone app records proximity events between app users, and when a user tests positive for COVID-19, their recent contacts can be notified instantly. Theoretical evidence has supported this new public health intervention1-6, but its epidemiological impact has remained uncertain7. Here we investigate the impact of the National Health Service (NHS) COVID-19 app for England and Wales, from its launch on 24 September 2020 to the end of December 2020. It was used regularly by approximately 16.5 million users (28% of the total population), and sent approximately 1.7 million exposure notifications: 4.2 per index case consenting to contact tracing. We estimated that the fraction of individuals notified by the app who subsequently showed symptoms and tested positive (the secondary attack rate (SAR)) was 6%, similar to the SAR for manually traced close contacts. We estimated the number of cases averted by the app using two complementary approaches: modelling based on the notifications and SAR gave an estimate of 284,000 (central 95% range of sensitivity analyses 108,000-450,000), and statistical comparison of matched neighbouring local authorities gave an estimate of 594,000 (95% confidence interval 317,000-914,000). Approximately one case was averted for each case consenting to notification of their contacts. We estimated that for every percentage point increase in app uptake, the number of cases could be reduced by 0.8% (using modelling) or 2.3% (using statistical analysis). These findings support the continued development and deployment of such apps in populations that are awaiting full protection from vaccines.

Increasing shrub damage by invertebrate herbivores in the warming and drying tundra of West Greenland.

Rapid warming is predicted to increase insect herbivory across the tundra biome, yet how this will impact the community and ecosystem dynamics remains poorly understood. Increasing background invertebrate herbivory could impede Arctic greening, by serving as a top-down control on tundra vegetation. Many tundra ecosystems are also susceptible to severe insect herbivory outbreaks which can have lasting effects on vegetation communities. To explore how tundra-insect herbivore systems respond to warming, we measured shrub traits and foliar herbivory damage at 16 sites along a landscape gradient in western Greenland. Here we show that shrub foliar insect herbivory damage on two dominant deciduous shrubs, Salix glauca and Betula nana, was positively correlated with increasing temperatures throughout the first half of the 2017 growing season. We found that the majority of insect herbivory damage occurred in July, which was outside the period of rapid leaf expansion that occurred throughout most of June. Defoliators caused the most foliar damage in both shrub species. Additionally, insect herbivores removed a larger proportion of B. nana leaf biomass in warmer sites, which is due to a combination of increased foliar herbivory with a coinciding decline in foliar biomass. These results suggest that the effects of rising temperatures on both insect herbivores and host species are important to consider when predicting the trajectory of Arctic tundra shrub expansion.

Modeling the Sensitivity of Blacklegged Ticks (Ixodes scapularis) to Temperature and Land Cover in the Northeastern United States.

The prevalence of Lyme disease and other tick-borne diseases is dramatically increasing across the United States. While the rapid rise in Lyme disease is clear, the causes of it are not. Modeling Ixodes scapularis Say (Acari: Ixodidae), the primary Lyme disease vector in the eastern United States, presents an opportunity to disentangle the drivers of increasing Lyme disease, including climate, land cover, and host populations. We improved upon a recently developed compartment model of ordinary differential equations that simulates I. scapularis growth, abundance, and infection with Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) by adding land cover effects on host populations, refining the representation of growth stages, and evaluating output against observed data. We then applied this model to analyze the sensitivity of simulated I. scapularis dynamics across temperature and land cover in the northeastern United States. Specifically, we ran an ensemble of 232 simulations with temperature from Hanover, New Hampshire and Storrs, Connecticut, and land cover from Hanover and Cardigan in New Hampshire, and Windsor and Danielson in Connecticut. Consistent with observations, simulations of I. scapularis abundance are sensitive to temperature, with the warmer Storrs climate significantly increasing the number of questing I. scapularis at all growth stages. While there is some variation in modeled populations of I. scapularis infected with B. burgdorferi among land cover distributions, our analysis of I. scapularis response to land cover is limited by a lack of observations describing host populations, the proportion of hosts competent to serve as B. burgdorferi reservoirs, and I. scapularis abundance.

Fine roots and mycorrhizal fungi accelerate leaf litter decomposition in a northern hardwood forest regardless of dominant tree mycorrhizal associations.

●Fine roots and mycorrhizal fungi may either stimulate leaf litter decomposition by providing free-living decomposers with root-derived carbon, or may slow decomposition through nutrient competition between mycorrhizal and saprotrophic fungi. ●We reduced the presence of fine roots and their associated mycorrhizal fungi in a northern hardwood forest in New Hampshire, USA by soil trenching. Plots spanned a mycorrhizal gradient from 96% arbuscular mycorrhizal (AM) associations to 100% ectomycorrhizal (ECM)-associated tree basal area. We incubated four species of leaf litter within these plots in areas with reduced access to roots and mycorrhizal fungi and in adjacent areas with intact roots and mycorrhizal fungi. ●Over a period of 608 d, we found that litter decayed more rapidly in the presence of fine roots and mycorrhizal hyphae regardless of the dominant tree mycorrhizal association. Root and mycorrhizal exclusion reduced the activity of acid phosphatase on decomposing litter. ●Our results indicate that both AM- and ECM-associated fine roots stimulate litter decomposition in this system. These findings suggest that the effect of fine roots and mycorrhizal fungi on litter decay in a particular ecosystem likely depends on whether interactions between mycorrhizal roots and saprotrophic fungi are antagonistic or facilitative.

The Influence of Water Deficit Stress on the Grapevine Trunk Disease Pathogens Eutypa lata and Diplodia seriata.

The increasing prevalence of the grapevine trunk diseases Eutypa and Botryosphaeria dieback has been attributed, in part, to abiotic stresses imposed on vineyards as production intensifies worldwide. The aim of this study was to evaluate the influence of water deficit irrigation practices on the infection of pruning wounds by Eutypa lata and Diplodia seriata and the subsequent rate of colonization. Two vineyard trials were conducted over two consecutive seasons in South Australia, one in the Riverland with 'Cabernet Sauvignon' with four irrigation treatments (100, 50, 25, and 12.5% of the standard irrigation program) and another in the Barossa Valley with 'Shiraz' on six rootstocks and own roots, either irrigated or not irrigated. According to leaf water potential assessments, vines with reduced irrigation were generally in water deficit and therefore subjected to stress. On the whole, incidence of wound infection and distance of colonization were similar between irrigation treatments for both pathogens, except in the Riverland, where E. lata colonized canes to a greater extent in well-watered vines than those in water deficit. Only vines on rootstock 'Ramsey' in the Barossa Valley had greater extent of colonization by E. lata in the nonirrigated vines. There was no correlation between internal staining and colonization, with both pathogens recovered to nearly 20 cm ahead of the staining. Water deficit did not increase the susceptibility of grapevine pruning wounds to infection or colonization of the subtending tissue by E. lata and D. seriata. In fact, there was evidence of lower susceptibility to colonization by E. lata in vines subjected to severe water deficit.