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opencc-zeroJan 2024View details →

Linked collectors and determiners for: Biodiversity of the scentless plant bugs (Hemiptera: Rhopalidae) in southern South America.

Natural history specimen data linked to collectors and determiners held within, "Biodiversity of the scentless plant bugs (Hemiptera: Rhopalidae) in southern South America". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d37ec798-2cd3-4f94-9a80-808ebf53beaa">https://bionomia.net/dataset/d37ec798-2cd3-4f94-9a80-808ebf53beaa</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d37ec798-2cd3-4f94-9a80-808ebf53beaa">https://gbif.org/dataset/d37ec798-2cd3-4f94-9a80-808ebf53beaa</a>. Formatted as a Frictionless Data package.

opencc-zeroJan 2024View details →

Linked collectors and determiners for: RL Minckley Insect and Plant Collection.

Natural history specimen data linked to collectors and determiners held within, "RL Minckley Insect and Plant Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/84b69033-f9de-40bc-8d5f-8ee41987d6cc">https://bionomia.net/dataset/84b69033-f9de-40bc-8d5f-8ee41987d6cc</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/84b69033-f9de-40bc-8d5f-8ee41987d6cc">https://gbif.org/dataset/84b69033-f9de-40bc-8d5f-8ee41987d6cc</a>. Formatted as a Frictionless Data package.

opencc-by-4.0Nov 2023View details →

Rhizobia-legume symbiosis mediates direct and indirect interactions between plants, herbivores and their parasitoids

Data and R scripts for statistical analyses for the article: Rhizobia-legume symbiosis mediates direct and indirect interactions between plants, herbivores and their parasitoids By: Carlos Bustos-Segura, Adrienne L. Godschalx, Lucas Malacari, Fanny Deiss, Sergio Rasmann, Daniel J. Ballhorn, Betty Benrey    Abstract Microorganisms associated with plant roots significantly impact the quality and quantity of plant defences. However, the bottom-up effects of soil microbes on the aboveground multitrophic interactions remain largely under studied. To address this gap, we investigated the chemically-mediated effects of nitrogen-fixing rhizobia on legume-herbivore-parasitoid multitrophic interactions. To address this, we initially examined the cascading effects of the rhizobia bean association on herbivore caterpillars, their parasitoids, and subsequently investigated how rhizobia influence on plant volatiles and extrafloral nectar. Our goal was to understand how these plant-mediated effects can affect parasitoids. Lima bean plants (Phaseoulus lunatus) inoculated with rhizobia exhibited better growth, and the number of root nodules positively correlated with defensive cyanogenic compounds. Despite increase of these chemical defences, Spodoptera latifascia caterpillars preferred to feed and grew faster on rhizobia-inoculated plants. Moreover, the emission of plant volatiles after leaf damage showed distinct patterns between inoculation treatments, with inoculated plants producing more sesquiterpenes and benzyl nitrile than non-inoculated plants. Despite these differences, Euplectrus platyhypenae parasitoid wasps were similarly attracted to rhizobia- or no rhizobia-treated plants. Yet, the oviposition and offspring development of E. platyhypenae was better on caterpillars fed with rhizobia-inoculated plants. We additionally show that rhizobia-inoculated common bean plants (Phaseolus vulgaris) produced more extrafloral nectar, with higher hydrocarbon concentration, than non-inoculated plants. Consequently, parasitoids performed better when fed with extrafloral nectar from rhizobia-inoculated plants. While the overall effects of bean-rhizobia symbiosis on caterpillars were positive, rhizobia also indirectly benefited parasitoids through the caterpillar host, and directly through the improved production of high quality extrafloral nectar. This study underscores the importance of exploring diverse facets and chemical mechanisms that influence the dynamics between herbivores and predators. This knowledge is crucial for gaining a comprehensive understanding of the ecological implications of rhizobia symbiosis on these interactions.

FIG. 6 in High-quality herbarium-label transcription by citizen scientists improves taxonomic and spatial representation of the tropical plant family Annonaceae

FIG. 6. — Temporal distribution of Annonaceae specimens collected in the Herbonautes dataset. The Histogram and left hand axis represent specimens collected per 5-year intervals. The right-hand axis and continuous line represent the cumulative specimens collected in total over the entire time period. The earliest Annonaceae collected and transcribed within the dataset is from 1740, a specimen of Annona squamosa L. collected in China by Pierre Nicolas le Chéron d'Incarville. The newest transcribed specimens are from 2015.

opencc-by-4.0Feb 2021View details →

Fig. 4 in Phylogenomics of the tropical plant family Ochnaceae using targeted enrichment of nuclear genes and 250+ taxa

Fig. 4. Distribution of specimen ages and the number of loci recovered in the phylogenomic study of Ochnaceae. A, Histogram of the collection years of all Ochnaceae specimens; B & C, Relationship between the year of collection of the specimens and the number of loci recovered for tissue obtained from herbarium material (excluding specimens with silica-dried leaf material), analysed for Ochneae and all the remaining Ochnaceae separately, either using the consensus-alignment (B) or the sample-specific (C) reference-based assembly approach. Pearson correlation coefficients and confidence intervals are given for each group.

opencc-by-4.0Feb 2021View details →

Fig. 2 in Phylogenomics of the tropical plant family Ochnaceae using targeted enrichment of nuclear genes and 250+ taxa

Fig. 2. RAxML trees based on the concatenated nuclear loci of Ochnaceae. A, Early-diverging branches of Ochnaceae and relationships within Quiinoideae based on the FAM dataset; B, Phylogenetic relationships of Sauvagesieae, Luxemburgieae and Testuleeae based on the SLT dataset. Numbers on the branches are bootstrap values>50%. Numbers in parentheses after species names correspond to the specimen IDs (only for species with multiple accessions). The indicated classification of subfamilies and tribes follows Schneider & al. (2014).

opencc-by-4.0Feb 2021View details →

Fig. 1 in Phylogenomics of the tropical plant family Ochnaceae using targeted enrichment of nuclear genes and 250+ taxa

Fig. 1. Overview of the phylogenetic relationships of the major clades of Ochnaceae based on the FAM dataset together with images of representative species. The classification follows Schneider & al. (2014). Ochninae is by far the most species-rich clade comprising about two-thirds of the family's species and six genera (Brack. = Brackenridgea; Cmp. = Campylospermum, clades A and B; I. = Idertia; Ochna; Ouratea; Rh. = Rhabdophyllum). Letters around the tree refer to the photos (mostly flowers except where indicated) and the relative position of the displayed taxa on the tree. A, Medusagyne oppositifolia (Medusagynoideae); B, Froesia venezuelensis (Quiinoideae); C, Luxemburgia schwackeana (Luxemburgieae); D, Rhytidanthera sulcata; E, Cespedesia spathulata; F, Poecilandra retusa; G, Godoya antioquiensis; H, Wallacea insignis; I, Sauvagesia semicylindrifolia; J, Sauvagesia erecta (Sauvagesieae); K, Infructescence of Lophira lanceolata with accrescent sepals (Lophirinae); L, Flower of Elvasia kollmannii (Elvasiinae); M, Perissocarpa umbellifera; N, Fruiting Rhabdophyllum arnoldianum; O, Brackenridgea nitida; P, Campylospermum glaberrimum; Q, Ochna serrulata; R, Fruit of Ochna integerrima with drupelets sitting on enlarged receptacle; S, Fruit of Ouratea sp. with enlarged red receptable; T, Ouratea sp. — Photos: A, K & N from www.africanplants.senckenberg.de (Dressler & al., 2014–); B by Julio Schneider; C by William Milliken/ Royal Botanic Gardens, Kew; D by Sandra Reinales; E by Reinaldo Aguilar; F, H & M by Francisco Farroñay; G by John Clark; I, J, S & T by Domingos Cardoso; L by Claudio Nicoletti de Fraga; O by John Elliott; P by Warran McCleland; Q by Marja Broersma; R by Pierre Grard.

Web sourced dataset for plant disease detection

The web-sourced dataset consists of plant leaf images collected from online platforms, primarily through sources like Google Images, to capture a wide range of real-world scenarios and environmental conditions. Unlike controlled laboratory datasets, these images feature diverse backgrounds, lighting variations, and different stages of plant diseases, representing how diseases appear in natural agricultural settings. The dataset includes multiple plant species and disease types, augmenting existing datasets by adding greater variability. This diversity aims to improve model robustness and generalization, enabling more accurate disease detection across varying agricultural environments.

FIG. 5 in High-quality herbarium-label transcription by citizen scientists improves taxonomic and spatial representation of the tropical plant family Annonaceae

FIG. 5. — Spatial distribution of species richness in datasets for Madagascar at 0.5 × 0.5° grid resolution: A, curated expert dataset; B, herbonautes transcribed data; C, GBIF data. Equirectangular (EPSG 4326) projection.

FIG. 4 in High-quality herbarium-label transcription by citizen scientists improves taxonomic and spatial representation of the tropical plant family Annonaceae

FIG. 4. — Global spatial coverage of datasets, showing regions covered by both Herbonautes (P) and GBIF data, just by GBIF and just by Herbonautes. Grid resolution 1 × 1° (c. 110 × 110 km at the equator), equirectangular (EPSG 4326) projection.

opencc-by-4.0Oct 2024View details →

An Analysis of Plant Disease and Their Detection

One of the biggest revolutions of modern history is the invention of agriculture for a healthier lifestyle. It significantly changed the human culture and played an important role in the development of the population and biological improvements in food production and domestication. The frequency of pests on food crops increased because environmental circumstances were changing, and diseases on crops increased rapidly. These diseases inflict catastrophic social, economic, and ecological casualties, and this extraordinary challenge is a concern for the correct and prompt detection of diseases. In this contest, technology has left its mark on the potential of farmers and is still to be exploited. As input for making the right decision, farmers need timely and credible sources of knowledge. Study into Agriculture have to be planned by improving the disease diagnostics method with the use of newer technology to enhance efficiency and quantity for agricultural production and its allied operation. In various applications of the agricultural industry, computer methodologies have been used for automation. Timely farming decisions and disease management are taken using image analysis and machinery of learning techniques in planning and creating a method for the diagnosis of diseases.

dryad40/100

Data from: A tale of two studies: detection and attribution of the impacts of invasive plants in observational surveys

1.Short-term experiments cannot characterize how long-lived, invasive shrubs influence ecological properties that can be slow to change, including native diversity and soil fertility. Observational studies are thus necessary, but often suffer from methodological issues. 2.To highlight ways of improving the design and interpretation of observational studies that assess the impacts of invasive plants, we compare two studies of nutrient cycling and earthworms along two separate gradients of invasive shrub abundance. By considering the divergent sampling strategies and statistical analyses of these two studies, and interpreting their contradictory results in the context of other studies, we also aim to better describe the impacts of the focal invader, Rhamnus cathartica. 3.In a new study of a single site in Minnesota, we observed positive correlations between buckthorn abundance and soil pH, soil nutrient pools, nutrient fluxes through leaf litterfall, earthworm abundance, and root biomass. Multiple regression models showed these relationships persisted after accounting for variability in soil texture and tree species composition. For a separate, more expansive study in Illinois, other authors reported little to no correlation between buckthorn abundance and 10 soil properties, including earthworm abundance, pH, and nutrient concentrations. However, like many other studies, their regression models only assessed predictors related to invader abundance. R2 values for models of ecosystem properties ranged from 0-0.79 (adjusted-R2) for our study in Minnesota and from <0.05-0.16 (unadjusted) for the prior study in Illinois. 4.Differences in sampling error and use of predictor variables between the two studies likely explain the contrasting results. 5.Synthesis and applications. To reduce the uncertainty of conclusions from observational studies of invasive plants, future studies must ensure that heterogeneity of soils and vegetation is adequately accounted for in the sampling strategy and statistical analyses (e.g., analysis of covariance, multiple regression). Particular attention should be given to ecosystem properties with variability that likely predates the invader (e.g., geophysical features and tree community composition). In our study, effects of buckthorn on ecosystem properties were not only robust to the inclusion of potentially confounding predictors, but also consistent with expectations based on ecological stoichiometry and mass balance of element flow.

opencc-zeroDec 2016View details →

dryad40/100

Data supporting: Methodological overview and data-merging approaches in the study of plant-frugivore interactions

Recording species interactions is one of the main challenges in ecological studies. Frugivory has received much attention for decades as a model for mutualisms among free-living species, and a variety of methods have been designed and developed for sampling and monitoring plant–frugivore interactions. The diversity of techniques poses an important challenge when comparing, combining or replicating results from different sources with different methodologies. With the emergence of modern techniques, such as molecular analysis or multimedia remote recorders, issues when combining data from different sources have become especially relevant. We provide an overview of all the techniques used for monitoring endozoochorous primary seed dispersal, focusing on a critical appraisal of the advantages and limitations, as well as the context-dependency nature, of the different methods. We propose five data merging approaches potentially useful to combine frugivory interactions data from different methodologies. Additionally, we provide two case studies where we combine empirical data from plant–animal interactions in Mediterranean shrublands using different methodologies. Data merging resulted in a net increase in the number of distinct pairwise interactions recorded and compensated biases inherent to different methods, resulting in a more robust estimation of network topological descriptors. These case studies clarify the context-dependent character of the merging approaches, highlighting the value of collecting detailed information on the sampling effort in terms of reliable results and reproducibility. Finally, we discuss the trends with different methodological approaches used in the last decades and future perspectives in this field.

opencc-zeroJun 2021View details →

opencc-by-4.0May 2021View details →

Figure 1. Plant tissue-culture growth chamber Percival. A in Survivorship of soybean aphid biotypes (Hemiptera: Aphididae) on winter hosts, common and glossy buckthorn

Figure 1. Plant tissue-culture growth chamber Percival. A) Soybean plants maintained in a plant growth chamber for 21 days before placed Rhamnus cathartica. B) Leaf of R. cathartica infested with soybean aphid biotype 1. C) Leaf of Frangula alnus with soybean aphid biotype 4.

Data from: Microbial effects on plant phenology and fitness

The enclosed files store the literature search results described in O'Brien et al. (2021) Microbial effects on plant phenology and fitness. American Journal of Botany (in press as of 5 July 2021) The preprint version of this article may be found at: https://ecoevorxiv.org/exadg/ <ul> <li>search_results.tsv = Tab-delimited database of articles returned by Web of Science in response to the query described in the article.</li> <li>split_records.tsv = Tab-delimited database of microbial effects on plant phenology, manually curated by O'Brien et al. from the articles listed in search_results.tsv and from closely related articles. Many of the reviewed articles included multiple plant species, multiple treatments, or other experimental factors, and some measured multiple phenological traits. This file lists each experimental observation separately, broken down by plant life-history strategy, microbe type, treatment method, plant organ, and other relevant details.</li> </ul>

opencc-zeroJun 2021View details →

Data and scripts used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE et al.

Images, script and data used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX

Fig. 4 in Relicthemisia, a new subgenus of the oil-collecting bee genus Centris Fabricius, 1804 with notes on distribution and host plants of C. xanthomelaena Moure & Castro, 2001 (Hymenoptera: Apidae)

Fig. 4. Female of Centris (Relicthemisia) xanthomelaena Moure & Castro, 2001 visiting Krameria sp. (Krameriaceae) in Estação Ecológica do Seridó, Rio Grande do Norte State, Brazil.

Fig. 3 in Relicthemisia, a new subgenus of the oil-collecting bee genus Centris Fabricius, 1804 with notes on distribution and host plants of C. xanthomelaena Moure & Castro, 2001 (Hymenoptera: Apidae)

Fig. 3. Distribution records of Centris (Relicthemisia) xanthomelaena Moure & Castro, 2001. The limits of biogeographical provinces are depicted in the map. Most records of this species are found in the Caatinga province in northeastern Brazil and marginally in the Cerrado Province, both in the South American diagonal of dry open areas.

Fig. 2 in Relicthemisia, a new subgenus of the oil-collecting bee genus Centris Fabricius, 1804 with notes on distribution and host plants of C. xanthomelaena Moure & Castro, 2001 (Hymenoptera: Apidae)

Fig. 2. Morphological characteristics of Centris (Relicthemisia) xanthomelaena Moure & Castro, 2001. A. Female basitibial plate. B. Male S7. C. Male S8. D. Female pygidial plate. E. Genital capsule (dorsal view). F. Genital capsule (ventral view). Scale bars = 0.5 mm.

Fig. 1 in Relicthemisia, a new subgenus of the oil-collecting bee genus Centris Fabricius, 1804 with notes on distribution and host plants of C. xanthomelaena Moure & Castro, 2001 (Hymenoptera: Apidae)

Fig. 1. Centris (Relicthemisia) xanthomelaena Moure & Castro, 2001. A–B. ♀. A. Frontal view. B. Habitus, lateral view. C–D. ♂. C. Frontal view. D. Habitus, lateral view. Scale bars: A, C = 2 mm; B, D = 5 mm.