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379 results for “naturalized plants”
PhytoNodes for Environmental Monitoring: Stimulus Classification based on Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System
<p>Cities worldwide are growing, putting bigger populations at risk due to urban pollution. Environmental monitoring is essential and requires a major paradigm shift. We need green and inexpensive means of measuring at high sensor densities and with high user acceptance. We propose using phytosensing: using natural living plants as sensors. In plant experiments we gather electrophysiological data with sensor nodes. We expose the plant <em>Zamioculcas zamiifolia</em> to five different stimuli: wind, temperature, blue light, red light, or no stimulus. Using that data we train ten different types of artificial neural networks to classify measured time series according to the respective stimulus. We achieve good accuracy and succeed in running trained classifying artificial neural networks online on the microcontroller of our small energy-efficient sensor node. To indicate later possible use cases, we showcase the system by sending a notification to a smartphone application once our continuous signal analysis detects a given stimulus.</p> <p> </p> <p>Data repository for our paper "PhytoNodes for Environmental Monitoring: Stimulus Classification based on<br> Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System", submitted to the GoodIT conference. Please refer to the paper for more information.</p> <p> </p> <p><strong>Contents of this repository</strong></p> <ul> <li><em>mu_interface:</em> Code for our data collection plant experiments, based on Raspberry Pis and the <a href="http://cybertronica.co/?q=products/phytosensor">Cybertronica phytosensing and phytoactuating system</a>.</li> <li><em>raw_data: </em>The datasets from our plant experiments for the stimuli wind, temperature, red light, blue light, and no stimulus.</li> <li><em>dl-4-tsc:</em> Deep learning framework developed by <a href="https://doi.org/10.1007/s10618-019-00619-1">Fawaz et. al (Deep learning for time series classification: a review)</a> and adapted to our use case. Find the training and testing datasets in the archives folder as well as the trained classifiers in the results folder.</li> <li><em>classification_results.ods: </em>Overview of the results from the deep learning framework (accuracy, precision, recall, training time).</li> <li><em>TFLite_Models: </em>The trained classifiers in TensorFlow Lite Format.</li> <li><em>00_AI_BLE_MeasuringOnlyWind: </em>Source code for classification on STM-based PhytoNodes (using MCDCNN two-class classifier) and Bluetooth communication. The code is written for the STM32WB55 Nucleo board and can be transferred to the dongle.</li> <li><em>zavrsniProjekt_iOS: </em>Source code of the iOS app used to receive data from the STM-based PhytoNodes.</li> <li><em>Watchplant_application_documentation.pdf: </em>Instructions to build and use the iOS app.</li> </ul>
Data from: Ruderals naturalize, competitors invade: varying roles of plant adaptive strategies along the invasion continuum
<p>1. It is increasingly recognized that the factors facilitating plant invasions depend on the stage along the introduction-naturalization-invasion continuum. Adaptative strategies, i.e., combinations of functional traits that represent overall fitness in the face of one or more selection pressures, have shown promise in explaining plant invasions. However, whether adaptive strategy patterns change with the stages of plant invasion is not yet known. </p> <p>2. Using the Pladias Database of the Czech Flora and Vegetation, we explored how Grime's adaptive strategies (competitors, stress-tolerators, ruderals; CSR) and introduction pathways (deliberate vs. accidental) relate to plant invasion along the introduction-naturalization-invasion continuum.</p> <p>3. Phylogenetically corrected ANOVAs showed that naturalized species (referring to non-invasive naturalized species in this study) were mostly R-selected, whereas invasive species tended to be C-selected. The results of phylogenetic regression analysis further confirmed that across the deliberately and accidentally introduced species, R- and C-selection were positively related to naturalization and invasion success, respectively. We also found that deliberate introduction was negatively related to naturalization success and grid-cell occupancy of naturalized species, likely due to the different CSR strategies possessed by deliberately and accidentally introduced aliens.</p> <p>4. Our study provides empirical evidence that different adaptive strategies are associated with species that have reached different invasion stages and confirms the usefulness of the CSR strategy framework for understanding plant invasion. It has implications for predicting and preventing potential high-impact invaders. For example, our results show that naturalized C-selected species have a higher probability of becoming invasive than naturalized R-selected species. Therefore, management actions are essential to prevent further introductions and spread of competitors.</p> <p> </p>
Text-fig. 4. Lepidocarpon cone in the process of disaggregating as part of the dispersal strategy of the plants. When preserved isolated, the sporophylls are assigned to the fossil-genus Lepidostrobophyllum. Refigured from Thomas (1981). Grovesend Formation (upper Asrturian – lower Moscovian), Kilmersdon Tip, Radstock Coalfield, UK; Natural History Museum (London) specimen V.60431. in Naming Of Parts: The Use Of Fossil-Taxa In Palaeobotany
Text-fig. 4. Lepidocarpon cone in the process of disaggregating as part of the dispersal strategy of the plants. When preserved isolated, the sporophylls are assigned to the fossil-genus Lepidostrobophyllum. Refigured from Thomas (1981). Grovesend Formation (upper Asrturian – lower Moscovian), Kilmersdon Tip, Radstock Coalfield, UK; Natural History Museum (London) specimen V.60431.
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Mimicking Natural Deterrent Strategies in Plants using Adhesive Spheres
<p>With a continuous increase in world population and food production, chemical pesticide use is growing accordingly, yet unsustainably. As chemical pesticides are harmful to the environment and pests develop resistance, sustainable and effective pesticide alternatives are needed. Inspired by nature, we mimic one defense strategy of plants, glandular trichomes, to shift away from using chemical pesticides by moving towards a physical immobilization strategy via adhesive particles. Through a controlled oxidation of a biobased starting material, triglyceride oils, an adhesive material is created while monitoring the reactive intermediates. After being milled into particles, nanoindentation shows these particles to be adhesive even at low contact forces. A suspension of particles is then sprayed onto chrysanthemum leaves and found to be highly effective at immobilizing a target pest, thrips, \textit{Frankliniella occidentalis}. Typical of small arthropod pests, thrips cause crop damage predominantly through virus transfer, which is prevented by their immobilization. We show that through this scalable fabrication process, biosourced materials can be used to create an effective, sustainable physical pesticide.</p>
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
<p>Climate change is rapidly altering the distribution of suitable habitats for many species as well as their pathogenic microbes. For many pathogens, including vector-borne diseases of humans and agricultural pathogens, climate change is expected to increase transmission and lead to pathogen range expansions. However, if pathogens have a lower heat tolerance than their host, increased warming could generate 'thermal refugia' for hosts. Predicting the outcomes of warming on disease transmission requires detailed knowledge of the thermal tolerances of both the host and the pathogen. Such thermal tolerance studies are generally lacking for fungal pathogens of wild plant populations, despite the fact that plants form the base of all terrestrial communities. Here, we quantified three aspects of the thermal tolerance (growth, infection, and propagule production) of the naturally occurring fungal pathogen <em>Microbotryum lychnidis-dioicae</em>, which causes a sterilizing anther-smut disease on the herbaceous plant <em>Silene latifolia</em>. We also quantified two aspects of host thermal tolerance: seedling survival and flowering rate. We found that temperatures >30 degreeC reduced the ability of anther-smut spores to germinate, grow, and conjugate in vitro. In addition, we found that high temperatures (30 degreeC) during, or shortly after the time of inoculation strongly reduced the likelihood of infection in seedlings. Finally, we found that high summer temperatures in the field temporarily cured infected plants, likely reducing transmission. Notably, high temperatures did not reduce survival or flowering of the host plants. Taken together, our results show that the fungus is considerably more sensitive to high temperatures than its host plant. A warming climate could therefore result in reduced disease spread or even local pathogen extirpation, leading to thermal refugia for the host.</p>
Fig. 2 in The Flora Of Vascular Plants In The Nature Reserve "Pašuliene Forest"
Fig. 2. Territory of the nature reserve "Pašuliene Forest" and vicinity in two-verst map published in 1833, issued in Russia (left), and in tophographical map of 1925, issued in Latvia (right).
Fig. 1 in Host plants and natural enemies of rugose spiraling whitefly (Hemiptera: Aleyrodidae) in Florida
Fig. 1. County distribution of rugose spiraling whitefly and its key natural enemies (Encarsia spp. and Nephaspis oculata) in Florida.
Fig. 2. Linear regression models showing the relationship between Aphis citricola and Harmonia axyridis abundance. A in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 2. Linear regression models showing the relationship between Aphis citricola and Harmonia axyridis abundance. A: Catnip (Nepeta cataria) + French marigold (Tagetes patula), B: ageratum (Ageratum houstonianum) + French marigold, C: catnip + ageratum, and D: native vegetation.
Fig. 6 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 6. Typical chromatograms obtained from headspace collections of volatiles from French marigold (Tagetes patula) (B) and catnip (Nepeta cataria) (C). A, air control.
Fig. 9 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 9. An Aphis citricola infestation model showing the effects of aromatic plant volatiles. Solid arrows refer to positive effects. Dotted lines refer to negative effect. The thickness of the arrows indicates the magnitude of the effects. The model includes data from this study and the studies by Song et al. (2013) and Chen et al (2014).
Fig. 8 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 8. Response of Harmonia axyridis adults to 12.5 μL/L, 25 μL/L, and 50 μL/L 1:1 mixed D-limonene and terpinolene afer 60 min. A: No aphids; B: aphids present. The numbers of asterisks represent the level of significance: ** highly significant (P <0.01); * significant (P <0.05); n.s. no significant difference.
Fig. 5 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 5. Differences in the number of Harmonia axyridis adults responding to French marigold (Tagetes patula) (A) and catbip (Nepeta cataria) (B) afer 60 min. T: Apple trees + aromatic plants; CK: apple trees. Aphids removed: aphids introduced for 2 h and then removed. The numbers of asterisks represent the level of significance: * significant (P <0.05); n.s. no significant difference.
Fig. 7 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 7. Differences in the number Harmonia axyridis adults in response to 12.5 μL/L, 25 μL/L, and 50 μL/L D-limonene (A, B) and terpinolene (C, D) afer 60 min. A, C: No aphids;B, D: aphids present.The numbers of asterisks represent the level of significance:** highly significant (P <0.01);* significant (P <0.05);n.s. no significant difference.
Fig. 3 in Behavioral responses of Aphis citricola (Hemiptera: Aphididae) and its natural enemy Harmonia axyridis (Coleoptera: Coccinellidae) to non-host plant volatiles
Fig. 3. Linear regression models showing the relationship in the ratio of Harmonia axyridis abundance to Aphis citricola abundance with sampling years. A: Catnip (Nepeta cataria) + French marigold (Tagetes patula), B: ageratum (Ageratum houstonianum) + French marigold, C: catnip + ageratum, and D: native vegetation.
Agriculture - General: Natural Resources and Environment, Plant Production and Protection
<p>Original data comes from a project which takes or took place as part of the DFG priority program “Exploratories for large-scale and long-term functional biodiversity research”. The data is stored together with descriptive metadata, in combination called a dataset, in the project repository (<a href="https://www.bexis.uni-jena.de">https://www.bexis.uni-jena.de</a>). Species information was extracted from that original dataset. The second paragraph is part of the metadata of the original <a href="<a href="http://dataset.in/">http://dataset.in/</a>">dataset.In this project we investigate seed bank and bryophyte propagule content in top soil in grasslands. Müller J (2016). Seed bank grassland. Biodiversity Exploratories. Occurrence dataset <a href="https://doi.org/10.15468/jax26w">https://doi.org/10.15468/jax26w</a> accessed via GBIF.org</p>
Fig. 1 in Successional patterns of carabid fauna (Coleoptera: Carabidae) in planted and natural regenerated pine forests growing on old arable land
Fig. 1: Principal components analysis (PCA) carried out with the dataset. Years of study are given in brackets behind the study areas/sites.
Fig. 7 in A study of Cactoblastis cactorum (Lepidoptera: Pyralidae) in its native range: further insights into life cycle, larval identification, developmental parameters, natural enemies, and damage to the host plant Opuntia ficus-indica (Caryophyllales: Cactaceae)
Fig. 7. Comparison of 3 characteristic forms of damage: (a) hole and feces coming from inside the pad, useful to distinguish pads with Cactoblastis cactorum; (b) typical damage observed in plants that were attacked by C. cactorum; (c) circular black spot fungal damage; (d) map black spot fungal damage.
Fig. 6 in A study of Cactoblastis cactorum (Lepidoptera: Pyralidae) in its native range: further insights into life cycle, larval identification, developmental parameters, natural enemies, and damage to the host plant Opuntia ficus-indica (Caryophyllales: Cactaceae)
Fig. 6. Proportion of Cactoblastis cactorum infected cladodes parasitized by Apanteles opuntiarum and proportion per cladode of C. cactorum larvae parasitized by A. opuntiarum throughout the yr for sites from Santiago del Estero, Córdoba, and Tucumán provinces. The average and standard deviation of the number of pupae of A. opuntiarum per C. cactorum larvae also is shown.
Fig. 2 in A study of Cactoblastis cactorum (Lepidoptera: Pyralidae) in its native range: further insights into life cycle, larval identification, developmental parameters, natural enemies, and damage to the host plant Opuntia ficus-indica (Caryophyllales: Cactaceae)
Fig. 2. Description of spots and setae from larval I to VI, shown in the pro- and meso-thoracic segment, and the seventh and anal abdominal segments: D1–2: dorsal setae; SD1–2: subdorsal setae; XD1–2: prothoracic setae; L1–3: lateral setae; SV1–2: subventral setae; PP1: posterior setae; spot "k" in prothorax, "h" in mesothorax, "a" and "c" in the seventh abdominal segment, and anal shield in the tenth and last abdominal segment.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.