Effect of spatiotemporal variables on abundance, biting activity and parity of Nyssorhynchus darlingi (Diptera: Culicidae) in peri-Iquitos, Peru.

BACKGROUND: In malaria endemic regions of the Peruvian Amazon, rainfall together with river level and breeding site availability drive fluctuating vector mosquito abundance and human malaria cases, leading to temporal heterogeneity. The main variables influencing spatial transmission include location of communities, mosquito behaviour, land use/land cover, and human ecology/behaviour. The main objective was to evaluate seasonal and microgeographic biting behaviour of the malaria vector Nyssorhynchus (or Anopheles) darlingi in Amazonian Peru and to investigate effects of seasonality on malaria transmission. METHODS: We captured mosquitoes from 18:00 to 06:00 h using Human Landing Catch in two riverine (Lupuna, Santa Emilia) and two highway (El Triunfo, Nuevo Horizonte) communities indoors and outdoors from 8 houses per community, during the dry and rainy seasons from February 2016 to January 2017. We then estimated parity rate, daily survival and age of a portion of each collection of Ny. darlingi. All collected specimens of Ny. darlingi were tested for the presence of Plasmodium vivax or Plasmodium falciparum sporozoites using real-time PCR targeting the small subunit of the 18S rRNA. RESULTS: Abundance of Ny. darlingi varied across village, season, and biting behaviour (indoor vs outdoor), and was highly significant between rainy and dry seasons (p < 0.0001). Biting patterns differed, although not significantly, and persisted regardless of season, with peaks in highway communities at ~ 20:00 h in contrast to biting throughout the night (i.e., 18:00-06:00) in riverine communities. Of 3721 Ny. darlingi tested for Plasmodium, 23 (0.62%) were infected. We detected Plasmodium-infected Ny. darlingi in both community types and most (20/23) were captured outdoors during the rainy season; 17/23 before midnight. Seventeen Ny. darlingi were infected with P. vivax, and 6 with P. falciparum. No infected Ny. darlingi were captured during the dry season. Significantly higher rates of parity were detected in Ny. darlingi during the rainy season (average 64.69%) versus the dry season (average 36.91%) and by community, Lupuna, a riverine village, had the highest proportion of parous to nulliparous females during the rainy season. CONCLUSIONS: These data add a seasonal dimension to malaria transmission in peri-Iquitos, providing more evidence that, at least locally, the greatest risk of malaria transmission is outdoors during the rainy season mainly before midnight, irrespective of whether the community was located adjacent to the highway or along the river.

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains.

BACKGROUND: Taxonomic classification of reads obtained by metagenomic sequencing is often a first step for understanding a microbial community, but correctly assigning sequencing reads to the strain or sub-species level has remained a challenging computational problem. RESULTS: We introduce Mora, a MetagenOmic read Re-Assignment algorithm capable of assigning short and long metagenomic reads with high precision, even at the strain level. Mora is able to accurately re-assign reads by first estimating abundances through an expectation-maximization algorithm and then utilizing abundance information to re-assign query reads. The key idea behind Mora is to maximize read re-assignment qualities while simultaneously minimizing the difference from estimated abundance levels, allowing Mora to avoid over assigning reads to the same genomes. On simulated diverse reads, this allows Mora to achieve F1 scores comparable to other algorithms while having less runtime. However, Mora significantly outshines other algorithms on very similar reads. We show that the high penalty of over assigning reads to a common reference genome allows Mora to accurately infer correct strains for real data in the form of E. coli reads. CONCLUSIONS: Mora is a fast and accurate read re-assignment algorithm that is modularized, allowing it to be incorporated into general metagenomics and genomics workflows. It is freely available at https://github.com/AfZheng126/MORA .

Multiple scale assessment of habitat, landscape, and geographic-specific attributes driving decapod assemblages in Posidonia oceanica seagrass meadows.

Seagrass meadows are biodiversity hotspots for invertebrate species including decapods. Understanding the drivers of species abundance, richness and diversity of decapod assemblages is crucial for the conservation of such hotspots, but how drivers act across multiple spatial scales remains unexplored. Here we describe the decapod assemblages of Posidonia oceanica seagrass meadows and assess the influence of attributes from three increasing spatial scales (habitat, landscape, and geographical levels) on the assemblages' structure and composition, as well as the variability partitioning among each one of these levels. Overall, geographical level attributes (i.e., inlet aperture, confinement) affected the most the decapod assemblages, while we only found a modest contribution from habitat (e.g., detritus biomass, sediment organic matter) and landscape attributes (e.g., fragmentation). We suggest that decapod assemblages are driven by the interaction of multiple processes occurring at different scales and other highly stochastic phenomena such as larval dispersion and recruitment.

A generic approach to infer community-level fitness of microbial genes.

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

Low-abundance proteins-based label-free SERS approach for high precision detection of liver cancer with different stages.

BACKGROUND: Surface-enhanced Raman scattering (SERS) technology have unique advantages of rapid, simple, and highly sensitive in the detection of serum, it can be used for the detection of liver cancer. However, some protein biomarkers in body fluids are often present at ultra-low concentrations and severely interfered with by the high-abundance proteins (HAPs), which will affect the detection of specificity and accuracy in cancer screening based on the SERS immunoassay. Clearly, there is a need for an unlabeled SERS method based on low abundance proteins, which is rapid, noninvasive, and capable of high precision detection and screening of liver cancer. RESULTS: Serum samples were collected from 60 patients with liver cancer (27 patients with stage T1 and T2 liver cancer, 33 patients with stage T3 and T4 liver cancer) and 40 healthy volunteers. Herein, immunoglobulin and albumin were separated by immune sorption and Cohn ethanol fractionation. Then, the low abundance protein (LAPs) was enriched, and high-quality SERS spectral signals were detected and obtained. Finally, combined with the principal component analysis-linear discriminant analysis (PCA-LDA) algorithm, the SERS spectrum of early liver cancer (T1-T2) and advanced liver cancer (T3-T4) could be well distinguished from normal people, and the accuracy rate was 98.5% and 100%, respectively. Moreover, SERS technology based on serum LAPs extraction combined with the partial least square-support vector machine (PLS-SVM) successfully realized the classification and prediction of normal volunteers and liver cancer patients with different tumor (T) stages, and the diagnostic accuracy of PLS-SVM reached 87.5% in the unknown testing set. SIGNIFICANCE: The experimental results show that the serum LAPs SERS detection combined with multivariate statistical algorithms can be used for effectively distinguishing liver cancer patients from healthy volunteers, and even achieved the screening of early liver cancer with high accuracy (T1 and T2 stage). These results showed that serum LAPs SERS detection combined with a multivariate statistical diagnostic algorithm has certain application potential in early cancer screening.

Seeing beyond the blot: A critical look at assumptions and raw data interpretation in Western blotting.

Rapid advancements in technology refine our understanding of intricate biological processes, but a crucial emphasis remains on understanding the assumptions and sources of uncertainty underlying biological measurements. This is particularly critical in cell signaling research, where a quantitative understanding of the fundamental mechanisms governing these transient events is essential for drug development, given their importance in both homeostatic and pathogenic processes. Western blotting, a technique developed decades ago, remains an indispensable tool for investigating cell signaling, protein expression, and protein-protein interactions. While improvements in statistical analysis and methodology reporting have undoubtedly enhanced data quality, understanding the underlying assumptions and limitations of visual inspection in Western blotting can provide valuable additional information for evaluating experimental conclusions. Using the example of agonist-induced receptor post-translational modification, we highlight the theoretical and experimental assumptions associated with Western blotting and demonstrate how raw blot data can offer clues to experimental variability that may not be fully captured by statistical analyses and reported methodologies. This article is not intended as a comprehensive technical review of Western blotting. Instead, we leverage an illustrative example to demonstrate how assumptions about experimental design and data normalization can be revealed within raw data and subsequently influence data interpretation.

Abundance and diversity of fungal endophytes isolated from monk fruit (Siraitia grosvenorii) grown in a Canadian research greenhouse.

Monk fruit (Siraitia grosvenorii) is an herbaceous perennial vine of the Cucurbitaceae family cultivated commercially mainly in southern China. There is very little information available about the fungal endophytes in monk fruit. In this study, monk fruit plants were grown from seeds in a research greenhouse at Kwantlen Polytechnic University in British Columbia, Canada to explore the abundance and diversity of their fungal endophytes. Fungal endophytes were isolated from seeds, seedlings, mature monk fruit plants, and fruits, and cultured on potato dextrose agar and water agar media. Isolates were identified by microscopic examination and BLAST comparison of ITS sequences to published sequences in GenBank. At least 150 species of fungal endophytes representing 60 genera and 20 orders were recovered from monk fruit tissues. Non-metric multidimensional scaling (NMDS) was carried out to explore the similarity of fungal communities among roots, stems, leaves, flowers, fruits, and seeds based on fungal orders. Our study showed that monk fruit plants are a rich source of fungal endophytes with the greatest abundance and diversity in leaves. This work has deepened our understanding of the intricate interactions between plants and fungi that sustain ecosystems and underpin plant health and resilience.

Predicting the fundamental thermal niche of ectotherms.

Climate warming is predicted to increase mean temperatures and thermal extremes on a global scale. Because their body temperature depends on the environmental temperature, ectotherms bear the full brunt of climate warming. Predicting the impact of climate warming on ectotherm diversity and distributions requires a framework that can translate temperature effects on ectotherm life-history traits into population- and community-level outcomes. Here we present a mechanistic theoretical framework that can predict the fundamental thermal niche and climate envelope of ectotherm species based on how temperature affects the underlying life-history traits. The advantage of this framework is twofold. First, it can translate temperature effects on the phenotypic traits of individual organisms to population-level patterns observed in nature. Second, it can predict thermal niches and climate envelopes based solely on trait response data and, hence, completely independently of any population-level information. We find that the temperature at which the intrinsic growth rate is maximized exceeds the temperature at which abundance is maximized under density-dependent growth. As a result, the temperature at which a species will increase the fastest when rare is lower than the temperature at which it will recover from a perturbation the fastest when abundant. We test model predictions using data from a naturalized-invasive interaction to identify the temperatures at which the invasive can most easily invade the naturalized's habitat and the naturalized is most likely to resist the invasive. The framework is sufficiently mechanistic to yield reliable predictions for individual species and sufficiently broad to apply across a range of ectothermic taxa. This ability to predict the thermal niche before a species encounters a new thermal environment is essential to mitigating some of the major effects of climate change on ectotherm populations around the globe.

N-mixture models for population estimation: Application in spotted lanternfly egg mass survey.

Population density and structure are critical to nature conservation and pest management. Traditional sampling methods such as capture-mark-recapture and catch-effort can't be used in situations where catching, marking, or removing individuals are not feasible. N-mixture models use repeated count data to estimate population abundance based on detection probability. They are widely adopted in wildlife surveys in recent years to account for imperfect detection. However, its application in entomology is relatively new. In this paper, we describe the general procedures of N-mixture models in population studies from data collection to model fitting and evaluation. Using Lycorma delicatula egg mass survey data at 28 plots in seven sites from the field, we found that detection probability (p) was negatively correlated with tree diameter at breast height (DBH), ranged from 0.516 [95 % CI: 0.470-0.561] to 0.614 [95 % CI: 0.566-0.660] between the 1st and the 3rd sample period. Furthermore, egg mass abundance (λ) was positively associated with basal area (BA) for the sample unit (single tree), with more egg masses on tree of heaven (TOH) trees. More egg masses were also expected on trees of other species in TOH plots. Predicted egg mass density (masses/100 m2) ranged from 5.0 (95 % CI: 3.0-16.0) (Gordon) to 276.9 (95 % CI: 255.0-303.0) (Susquehannock) for TOH plots, and 11.0 (95 % CI: 9.00-15.33) (Gordon) to 228.3 (95 % CI: 209.7-248.3) (Burlington) for nonTOH plots. Site-specific abundance estimates from N-mixture models were generally higher compared to observed maximum counts. N-mixture models could have great potential in insect population surveys in agriculture and forestry in the future.

Recalling experiences of scarcity reduces children's generosity relative to recalling abundance.

Does a sense of having less or more than what one needs affect one's generosity? The question of how resource access influences prosocial behavior has received much attention in studies with adults but has produced conflicting findings. To better understand this relationship, we tested whether resource access affects generosity in the developing mind. In our preregistered investigation, we used a narrative recall method to explore how temporary, experimentally evoked states of resource abundance or scarcity affect children's sharing. In this study, 6- to 8-year-old American children (N = 148) recalled an experience of scarcity or abundance and then chose how many prizes to share with another child. We found that children in the scarce condition rated themselves as sadder, viewed their resource access as more limited, and shared fewer tokens than children in the abundant condition. Our results indicate that recalling past experiences of resource access creates distinct behavioral consequences for children and suggest that a sense of "having less" may encourage a strategy of resource conservation relative to a sense of "having more," even at a young age.

Significant shifts in latitudinal optima of North American birds.

Changes in climate can alter environmental conditions faster than most species can adapt. A prediction under a warming climate is that species will shift their distributions poleward through time. While many studies focus on range shifts, latitudinal shifts in species' optima can occur without detectable changes in their range. We quantified shifts in latitudinal optima for 209 North American bird species over the last 55 y. The latitudinal optimum (m) for each species in each year was estimated using a bespoke flexible non-linear zero-inflated model of abundance vs. latitude, and the annual shift in m through time was quantified. One-third (70) of the bird species showed a significant shift in their optimum. Overall, mean peak abundances of North American birds have shifted northward, on average, at a rate of 1.5 km per year (±0.58 SE), corresponding to a total distance moved of 82.5 km (±31.9 SE) over the last 55 y. Stronger poleward shifts at the continental scale were linked to key species' traits, including thermal optimum, habitat specialization, and territoriality. Shifts in the western region were larger and less variable than in the eastern region, and they were linked to species' thermal optimum, habitat density preference, and habitat specialization. Individual species' latitudinal shifts were most strongly linked to their estimated thermal optimum, clearly indicating a climate-driven response. Displacement of species from their historically optimal realized niches can have dramatic ecological consequences. Effective conservation must consider within-range abundance shifts. Areas currently deemed "optimal" are unlikely to remain so.

Ecological aspects and relationships of the emblematic Vachellia spp. exposed to anthropic pressures and parasitism in natural hyper-arid ecosystems: ethnobotanical elements, morphology, and biological nitrogen fixation.

MAIN CONCLUSION: Emblematic Vachellia spp. naturally exposed to hyper-arid conditions, intensive grazing, and parasitism maintain a high nitrogen content and functional mutualistic nitrogen-fixing symbioses. AlUla region in Saudi Arabia has a rich history regarding mankind, local wildlife, and fertility islands suitable for leguminous species, such as the emblematic Vachellia spp. desert trees. In this region, we investigated the characteristics of desert legumes in two nature reserves (Sharaan and Madakhil), at one archaeological site (Hegra), and in open public domains et al. Ward and Jabal Abu Oud. Biological nitrogen fixation (BNF), isotopes, and N and C contents were investigated through multiple lenses, including parasitism, plant tissues, species identification, plant maturity, health status, and plant growth. The average BNF rates of 19 Vachellia gerrardii and 21 Vachellia tortilis trees were respectively 39 and 67%, with low signs of inner N content fluctuations (2.10-2.63% N) compared to other co-occurring plants. The BNF of 23 R. raetam was just as high, with an average of 65% and steady inner N contents of 2.25 ± 0.30%. Regarding parasitism, infected Vachellia trees were unfazed compared to uninfected trees, thereby challenging the commonly accepted detrimental role of parasites. Overall, these results suggest that Vachellia trees and R. raetam shrubs exploit BNF in hyper-arid environments to maintain a high N content when exposed to parasitism and grazing. These findings underline the pivotal role of plant-bacteria mutualistic symbioses in desert environments. All ecological traits and relationships mentioned are further arguments in favor of these legumes serving as keystone species for ecological restoration and agro-silvo-pastoralism in the AlUla region.

Global prevalence of microplastics in tap water systems: Abundance, characteristics, drivers and knowledge gaps.

Tap water is a main route for human direct exposure to microplastics (MPs). This study recompiled baseline data from 34 countries to assess the current status and drivers of MP contamination in global tap water systems (TWS). It was shown that MPs were detected in 87 % of 1148 samples, suggesting the widespread occurrence of MPs in TWS. The detected concentrations of MPs spanned seven orders of magnitude and followed the linearized log-normal distribution (MSE = 0.035, R2 = 0.965), with cumulative concentrations at 5th, 50th and 95th percentiles of 0.028, 4.491 and 728.105 items/L, respectively. The morphological characteristics were further investigated, indicating that particles smaller than 50 µm dominated in global TWS, with fragment, polyester and transparent as the most common shape, composition and color of MPs, respectively. Subsequently, the SHapley Additive exPlanations (SHAP) algorithm was implemented to quantify the importance of variables affecting the MP abundance in global TWS, showing that the lower particle size limit was the most important variables. Subgroup analysis revealed that the concentration of MPs counted at the size limit of 1 µm was >20 times higher than that above 1 µm. Ultimately, current knowledge gaps and future research needs were elucidated.

CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies.

Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as "defaunation." This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.

Camera trap surveys of Atlantic Forest mammals: A data set for analyses considering imperfect detection (2004-2020).

Camera traps became the main observational method of a myriad of species over large areas. Data sets from camera traps can be used to describe the patterns and monitor the occupancy, abundance, and richness of wildlife, essential information for conservation in times of rapid climate and land-cover changes. Habitat loss and poaching are responsible for historical population losses of mammals in the Atlantic Forest biodiversity hotspot, especially for medium to large-sized species. Here we present a data set from camera trap surveys of medium to large-sized native mammals (>1 kg) across the Atlantic Forest. We compiled data from 5380 ground-level camera trap deployments in 3046 locations, from 2004 to 2020, resulting in 43,068 records of 58 species. These data add to existing data sets of mammals in the Atlantic Forest by including dates of camera operation needed for analyses dealing with imperfect detection. We also included, when available, information on important predictors of detection, namely the camera brand and model, use of bait, and obstruction of camera viewshed that can be measured from example pictures at each camera location. Besides its application in studies on the patterns and mechanisms behind occupancy, relative abundance, richness, and detection, the data set presented here can be used to study species' daily activity patterns, activity levels, and spatiotemporal interactions between species. Moreover, data can be used combined with other data sources in the multiple and expanding uses of integrated population modeling. An R script is available to view summaries of the data set. We expect that this data set will be used to advance the knowledge of mammal assemblages and to inform evidence-based solutions for the conservation of the Atlantic Forest. The data are not copyright restricted; please cite this paper when using the data.

As armadilhas fotográficas tornaram­se o principal método de observação de muitas espécies em grandes áreas. Os dados obtidos com armadilhas fotográficas podem ser usados para descrever os padrões e monitorar a ocupação, abundância e riqueza da vida selvagem, informação essencial para a conservação em tempos de rápidas mudanças climáticas e de cobertura do solo. A perda de habitat e a caça furtiva são responsáveis pelas perdas populacionais históricas de mamíferos no hotspot de biodiversidade da Mata Atlântica, especialmente para espécies de médio e grande porte. Aqui apresentamos um conjunto de dados de levantamentos com armadilhas fotográficas de mamíferos de médio e grande porte (>1 kg) em toda a Mata Atlântica. Compilamos dados de 5.380 armadilhas fotográficas instaladas no nível do chão em 3.046 locais, de 2004 a 2020, resultando em 43.068 registros de 58 espécies. Esses dados acrescentam aos conjuntos de dados existentes de mamíferos na Mata Atlântica por incluir as datas de operação das câmeras, que são necessárias para análises que lidam com detecção imperfeita. Também incluímos, quando disponíveis, informações sobre importantes preditores de detecção, como marca e modelo da câmera, uso de isca e obstrução do visor da câmera que pode ser medido a partir de imagens de exemplo em cada local da câmera. Além de estudos sobre os padrões e mecanismos por trás da ocupação, abundância relativa, riqueza e detecção, o conjunto de dados aqui apresentado pode ser usado para estudar os padrões de atividade diária das espécies, nível de atividade e interações espaço­temporais entre as espécies. Além disso, os dados podem ser usados em combinação com outras fontes de dados em diversas análises com modelagem populacional integrada. Um script R está disponível para visualizar um resumo do conjunto de dados. Esperamos que este conjunto de dados seja usado para aumentar o conhecimento sobre as assembleias de mamíferos e usado para informar soluções baseadas em evidências para a conservação da Mata Atlântica. Os dados não são restritos por direitos autorais e, por favor, cite este documento ao usar os dados.

Shifting mammal communities and declining species richness along an elevational gradient on Mount Kenya.

Conservation areas encompassing elevation gradients are biodiversity hotspots because they contain a wide range of habitat types in a relatively small space. Studies of biodiversity patterns along elevation gradients, mostly on small mammal or bird species, have documented a peak in diversity at mid elevations. Here, we report on a field study of medium and large mammals to examine the impact of elevation, habitat type, and gross primary productivity on community structure. Species richness was observed using a camera trap transect with 219 sites situated across different habitat types from 2329 to 4657 m above the sea level on the western slope of Mt Kenya, the second highest mountain in Africa. We found that the lowest elevation natural habitats had the highest species richness and relative abundance and that both metrics decreased steadily as elevation increased, paralleling changes in gross primary productivity, and supporting the energy richness hypothesis. We found no evidence for the mid-domain effect on species diversity. The lowest elevation degraded Agro-Forestry lands adjacent to the National Park had high activity of domestic animals and reduced diversity and abundance of native species. The biggest difference in community structure was between protected and unprotected areas, followed by more subtle stepwise differences between habitats at different elevations. Large carnivore species remained relatively consistent but dominant herbivore species shifted along the elevation gradient. There was some habitat specialization and turnover in species, such that the elevation gradient predicts a high diversity of species, demonstrating the high conservation return for protecting mountain ecosystems for biodiversity conservation.

Urban greening with shrubs can supercharge invertebrate abundance and diversity.

In urban areas, diverse and complex habitats for biodiversity are often lacking. This lack of diversity not only compromises essential ecological processes, such as pollination and nutrient cycling, but also diminishes the resilience of urban ecosystems to pests and diseases. To enhance urban biodiversity, a possible solution is to integrate shrubs alongside trees, thereby increasing the overall amount of vegetation, structural complexity and the associated resource diversity. Here, using a common garden experiment involving a variety of trees and shrubs planted alone and in combination, we evaluate how canopy-associated invertebrate assemblages are influenced by vegetation type. In particular, we test whether the presence of shrubs, alone or with trees, results in increased abundance and taxonomic richness of invertebrates, compared to trees on their own. We found that the overall abundance of invertebrates, and that of specific functional groups (e.g., herbivores, pollinators, detritivores), was higher on shrubs, compared to trees, and when trees and shrubs were planted in combination (relative to trees on their own). Our results suggest that planting shrub and tree species with wide and dense crowns can increase the associated abundance and taxonomic and functional group richness of invertebrate communities. Overall, our findings indicate that urban planning would benefit from incorporating shrubs alongside urban trees to maximise invertebrate abundance, diversity and function in urban landscapes.

Investigating Circadian Gating of Temperature Responsive Genes.

Understanding gene expression dynamics in the context of the time of day and temperature response is an important part of understanding plant thermotolerance in a changing climate. Performing "gating" experiments under constant conditions and light-dark cycles allows users to identify and dissect the contribution of the time of day and circadian clock to the dynamic nature of stress-responsive genes. Here, we describe the design of specific laboratory experiments in plants (Arabidopsis thaliana and bread wheat, Triticum aestivum) to investigate temporal responses to heat (1 h at 37 °C) or cold (3 h at 4 °C), and we include known marker genes that have circadian-gated responses to temperature changes.

Powdery mildew-induced changes in phyllosphere microbial community dynamics of cucumber.

As an important habitat for microorganisms, the phyllosphere has a great impact on plant growth and health, and changes in phyllosphere microorganisms are closely related to the occurrence of leaf diseases. However, there remains a limited understanding regarding alterations to the microbial community in the phyllosphere resulting from pathogen infections. Here, we analyzed and compared the differences in phyllosphere microorganisms of powdery mildew cucumber from three disease severity levels (0% < L1 < 30%, 30% ≤ L2 < 50%, L3 ≥ 50%, the number represents the lesion coverage rate of powdery mildew on leaves). There were significant differences in α diversity and community structure of phyllosphere communities under different disease levels. Disease severity altered the community structure of phyllosphere microorganisms, Rosenbergiella, Rickettsia, and Cladosporium accounted for the largest proportion in the L1 disease grade, while Bacillus, Pantoea, Kocuria, and Podosphaera had the highest relative abundance in the L3 disease grade. The co-occurrence network analysis of the phyllosphere microbial community indicated that the phyllosphere bacterial community was most affected by the severity of disease. Our results suggested that with the development of cucumber powdery mildew, the symbiotic relationship between species was broken, and the entire bacterial community tended to compete.

Cascade Microbial Metabolism of Ferulic Acid In Vitro Fermented by the Human Fecal Inoculum.

Ferulic acid (FA), predominantly existing in most cereals, can modulate the gut microbiome, but the influences of its metabolites on the microbial population and FA-transforming microorganisms are still unclear. In this study, FA and its potential phenolic metabolites were fermented in vitro for 24 h with the human fecal inoculum. A comparable short chain fatty acid (SCFA) production trend was observed in the presence and absence of substrates, suggesting limited contribution of FA mechanism to SCFA formation. Dihydroferulic acid, 3-(3,4-dihydroxyphenyl)propionic acid, and 3-(3-hydroxyphenyl)propionic acid were ascertained to be successive metabolites of FA, by tracking the intermediate variation. FA remarkably promoted the absolute abundances of total bacteria, while different metabolites affected bacterial growth of selective genera. Specific genera were identified as quantitatively correlating to the content of FA and its metabolites. Ultimately, FA-mediated gut microbiota modulation involves both the action of metabolizing microbes and the regulation effects of metabolites on bacterial growth.