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75 results for “biological interactions”
The local extinction of Cedrus atlantica in the Iberian Peninsula could have been completed due to biological interaction
<p>This data set is used to explore the possibility that <em>Cedrus atlantica</em> (Endl.) Carrière and <em>Pinus nigra</em> Arnold could have interacted in the past, mutually excluding each other in the areas with suitable conditions for both species and, where, ultimately, the one that was most competitive would remain. The species show very well differenciated niches and a distribution of their habitats segregated by continents (<em>P. nigra</em> in Europe and <em>C. atlantica</em> in Africa), which responds to differences in climatic affinities. However, the contact of their distributions in bordering areas suggests that <em>C. atlantica</em> maintained its presence in the Iberian Peninsula until recent times, and that <em>P. nigra</em> could have displaced it due to its higher prevalence on the continent.</p>
warmXtrophic: plant community responses to the individual and interactive effects of climate warming and herbivory across multiple years at Kellogg Biological Station Long-Term Ecological Research Sites (KBS LTER), Michigan, USA, and University of Michigan Biological Station (UMBS), Michigan, USA.
Climate change has both direct and indirect effects on ecological communities. Whereas most climate change ecology experiments manipulate abiotic drivers to measure direct effects of climate on species or communities, fewer quantify the indirect effects through biotic interactions, especially over multiple sites and years. In this factorial experiment we manipulate temperature through open-top chambers, and the level of insect herbivory through insecticide. At two early successional field sites separated by 3 degrees of latitude and 3°C of mean annual temperature (University of Michigan Biological Station, Pellston, MI and Kellogg Biological Station, Hickory Corners, MI), 6 replicate 1-m2 plots per treatment were installed in May 2015. 12 plots per site are at ambient temperature, 12 are warmed with year-round non-UV filtering polycarbonate and wood frame construction OTCs for tall-stature plants (Welshofer et al. 2018 MEE). Insecticide reduces insect herbivory in half the plots (Welshofer et al. 2018 Oecologia). Over the course of the experiment, OTCs warmed the plant communities by 1.9°C-3.0°C on average over the growing season. Each year, through 2021, plant traits and community responses were measured at the species level: plant phenology (green-up, flowering, flowering duration, seed set); plant percent cover (aerial % cover of the 1m2 plot); plant traits (specific leaf area, C and N content), herbivory damage to leaves, and plant species biomass (only in 2021). Further methodological details are found within each response variable metadata. This experiment is ongoing and further data package updates are planned. L0 data is available upon request. R scripts can be found here: https://github.com/SpaCE-Lab-MSU/warmXtrophic. The biotic and abiotic community context and relative strengths of direct vs. indirect effects may yield ecological surprises under climate change unless addressed together. Large-scale experiments like this one can improve our ability to unde
warmXtrophic plant-soil interaction greenhouse experiment, Kellogg Biological Station, Hickory Corners, MI, 2021
Climate warming influences plant communities through both direct effects, such as changes in temperature, and indirect pathways mediated by changes in soil microbial communities. These microbe-mediated indirect effects may alter plant traits and ecosystem dynamics in ways that are often overlooked in studies focused solely on the direct impacts of warming. To test these microbe-mediated indirect effects, we used field-conditioned soil from a 7-year (2015-2021) warming experiment (warmXtrophic) in an early successional plant community in Hickory Corners, Michigan, USA at Michigan State University's Kellogg Biological Station Long-Term Ecological Research site. In a greenhouse during 2021, we assessed how warmed versus ambient soil inocula influenced plant growth and traits of two species: Trifolium pratense (red clover) and Phleum pratense (Timothy grass). We measured above, below, and total biomass, height, number of leaves, timing of germination, leaf % carbon and nitrogen, C:N ratio, specific leaf area (SLA), and greenness (a proxy for chlorophyll content). We also measured the timing of emergence of the cotyledon and first leaf for Trifolium pratense.
Data for "Detection of metabolite-protein interactions in complex biological samples by high-resolution relaxometry: towards interactomics by NMR"
<p>Raw NMR data for relaxometry experiments, divided by donor sample. For every donor sample 2 or 3 different samples were used in order to record data at 19 different magnetic fields.</p> <p>Data from fast field-cycling relaxometry. All the data is in one xlsx file, divided by donor sample.</p> <p>Relaxometry results for alanine, lactate, creatinine and glutamine, obtained from the fitting of their relaxation decays recorded at 19 different fields, divided by donor sample.</p>
Global Biotic Interactions: Elton Dataset Cache Museum of Southwestern Biology and dependencies
<p>Global Biotic Interactions: Elton Dataset Cache Museum for Southwestern Biology and dependencies</p> <p>The intended use of this archive/cache is to allow for offline-enabled access versions of existing species interaction datasets. The program "Elton" (https://doi.org/10.5281/zenodo.998263) was used to populate the content of elton-datasets.tar.gz . The same program can be used to extract information from the cache archive also. Global Biotic Interactions (https://globalbioticinteractions.org, https://doi.org/10.1016/j.ecoinf.2014.08.005) also uses these archives to create derived species interaction data archives, search indexes and APIs.</p> <p>Please note that due to size considerations, offline-enabled access to an elton dataset cache of iNaturalist interaction data has been excluded from this publications and moved into a separate Zenodo publication at https://doi.org/10.5281/zenodo.3950546 .</p> <p>Contents<br> --------</p> <p>README:<br> this file</p> <p>elton-datasets.tar.gz:<br> versioned archive with species interaction datasets</p> <p>elton-datasets.tar.sha256:<br> content signature of elton-datasets.tar</p> <p>elton-datasets.tsv:<br> list of included datasets</p> <p>elton.jar:<br> commandline program to help access the species interaction datasets</p> <p>Usage<br> -----</p> <p>To install, extract elton-datasets.tar.gz into a directory of choice using:</p> <p>tar xfz elton-dataset.tar.gz</p> <p>To use, download elton.jar included this publication and execute the following to get a list of available datasets:</p> <p>java -Xmx4G -jar elton.jar datasets</p> <p>on a system that has java v8+ installed.</p> <p>If all goes well, you should be able to regenerate the included file elton-dataset.tsv .</p> <p>For more information on how to use elton.jar, execute:</p> <p>java -jar elton.jar usage</p> <p>or visit https://github.com/globalbioticinteractions/elton for more available commands.</p> <p>Alternatively, without using Elton, you can access the data by inspecting the access.tsv files in the various directories of the datasets directory.</p> <p>When using these datasets in a publication or product, please cite the *original* data providers and publications. You can find the citations in the data.</p> <p>Included datasets:</p> <p>globalbioticinteractions/msb-para Museum for Southern Biology (MSB) Parasite Collection https://github.com/globalbioticinteractions/msb-para/archive/54643c878313d7ccbf30325c713925d6c937fc9c.zip 2021-11-13T01:22:28.662Z 43a7e837b6e27532cc90eb50995fb4db169d0c8109aa27742cfabdedb3d390dc 0.12.2</p> <p>Associated content ids:</p> <p>hash://sha256/567720ed6bc8ed0e73020eb1cefb601ce274715926f42ad3b22197e26f07dbd6<br> hash://sha256/3e401123bcfe9d67ffa149b3a5208c4d91e3291c56a089796287ab9f90a3aed9<br> hash://sha256/8b0e05281afa51031f25fdd9238a9a8df2beba81dbb71aee8f05fd1265e8216a<br> hash://sha256/072be68d48c9e841458a1f60da6e66173406a97af569a04953e8a06272c3f3f4<br> hash://sha256/69493156747f43e6dedd09bdfca0ae89a8e0c97183ce71f7c8a51965361d8529<br> hash://sha256/5dbc9eb2b059a72e13c9726ffb4b6af203361254d85cfa4b4ab59cfdb7bf8395<br> hash://sha256/3af388dbae61d93e6a4509b50c141ee8705f65f4fe4e05c37b30ce7f3f7fb4f4<br> 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hash://sha256/bf0a250e665bb620a0777b369c65af1d3950a773435464552fd1cd85159d2510<br> hash://sha256/0f0885a27ff7d752f6707eb6f563f704ae5d346c256b83d0855d2f981eed7f89</p> <p> </p>
Interactions among multiple stressors vary with exposure duration and biological response
<p>Coastal ecosystems are exposed to multiple anthropogenic stressors. Effective management actions would be better informed from generalized predictions of the individual, combined and interactive effects of multiple stressors; however, few generalities are shared across different meta-analyses. Using an experimental study, we present an approach for analysing regression-based designs with generalized additive models that allowed us to capture nonlinear effects of exposure duration and stressor intensity and access interactions among stressors. We tested the approach on a globally distributed marine diatom, using 72 h photosynthesis and growth assays to quantify the individual and combined effects of three common water quality stressors; photosystem II-inhibiting herbicide exposure, dissolved inorganic nitrogen (DIN) enrichment and reduced light (due to excess suspended sediment). Exposure to DIN and reduced light generally resulted in additivity, while exposure to diuron and reduced light resulted in additive, antagonistic or synergistic interactions, depending on the stressor intensity, exposure period and biological response. We thus find the context of experimental studies to be a primary driver of interactions. The experimental and modelling approaches used here bridge the gap between two-way designs and regression-based studies, which provides a way forward to identify generalities in multiple stressor interactions.</p>
Fig. 10 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 10. Comparisons of inflammatory cells recruited to inflammatory foci in cane toads, Rhinella marina (a) and native frogs, Cyclorana australis (b). Each anuran species was exposed to infective larvae of Rhabdias hylae (white bars) and Rhabdias pseudosphaerocephala (grey bars). Graphs show average values ± 1 S.E.M.
Fig. 7 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 7. Histological investigation of lungworm infection in anurans. Graphs show the proportion of (a) metamorph native frogs (Cyclorana australis) and (b) metamorph cane toads (Rhinella marina) infected with lungworms, not infected with lungworms, or with inflammatory 'foci' (probable cases of a lungworm larva penetrating the anuran's body but failing to survive).
Fig. 2 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 2. The distribution of lungworm larvae in cane toad metamorphs. (a) Toad metamorphs infected with Rhabdias hylae (native frog lungworm) and (b) toad metamorphs infected with Rhabdias pseudosphaerocephala (cane toad lungworm). Data in panel (b) are from Pizzatto et al. (2010), with permission. LUNG refers to adult lungworms found within the lung, SKIN/MUSCLE refers to larvae found in the skeletal muscle or subcutaneous tissue, HEAD refers to larvae detected in the head or neck region (excluding those found in eye tissue), EYE indicates larvae found in the eye or periocular tissue, and COELOM denotes larvae within the coelom or coelomic membranes.
Fig. 1. Histological image depicting a in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 1. Histological image depicting a transverse section of (a) R. hylae larva in the connective tissue of the head of a cane toad and (b) the inflammatory response composed primarily of macrophages and multinucleated giant cells surrounding the parasite. Haematoxylin and eosin stain, 400× magnification, scale bar equals 30 μm.
Fig. 4 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 4. Effect of time since exposure to Rhabdias hylae larvae on cane toad metamorphs: (a) shows the number of larvae found in toads and (b) shows the number of foci (areas of inflammation with no visible larvae) in toads, as determined by histological methods.
Fig. 9 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 9. Change in the average number of inflammatory foci (probable cases of larval parasites breaking down) observed in all anurans over time. Graph shows average values ± 1 S.E.M.
Fig. 6 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 6. Effects of Rhabdias hylae infection on cane toad metamorphs: (a) the average percentage of neutrophils and (b) lymphocytes around inflammation sites over time in cane toads infected with Rhabdias hylae. Graphs show average values ±1 S.E.M.
Fig. 3 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 3. The state of Rhabdias hylae larvae in cane toads as a function of days-post treatment. The graph shows larval numbers as the percentage of total larvae that were seen at each time period.
Fig. 5 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 5. Average inflammation severity surrounding Rhabdias hylae larvae and foci (probable larvae being broken down by the host's immune system) within infected cane toads at different numbers of days post-infection. Graph shows average values ±1 S.E.M.
Fig. 8 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 8. Changes through time (days post-infection) on the relative numbers of anurans that were infected with lungworms, and that contained adult versus juvenile stages of the parasites involved. Data are shown for two lungworm species (Rhabdias hylae from native frogs, and Rhabdias pseudosphaerocephala from invasive cane toads) and for two types of host: the native frog, Cyclorana australis, and the cane toad, Rhinella marina. The panels show data for (a) C. australis infected with R. pseudosphaerocephala, (b) C. australis infected with R. hylae, (c) cane toads infected with R. pseudosphaerocephala and (d) cane toads infected with R. hylae.
Figure 1 in Interaction between biological aspects of Tetranychus urticae Koch (Acari: Tetranychidae) and some chemical composition in two colored Acalypha wilkesiana Müll. Arg. (Malpighiales: Euphorbiaceae) leaves
Figure 1. Graph of Pearson's correlation analysis among the different studied leaf parameters including the chemical analysis of Acalypha leaves and the T. urticae female characteristics. The colors represent variations in the obtained data. * indicates the significant at P-value <0.05.
Figures 4-7 in Cocoon morphology of Bicyrtes variegatus (Oliver, 1789) (Hymenoptera: Crabronidae), with notes on habitat and biological interactions
Figures 4-7. Details of cocoon structures of Bicyrtes variegatus (Oliver). 4. Apical portion, internal view. 5. Basal portion, internal view, showing the fecal mass. 6. External surface, white arrows point the pores. 7. Internal domes of the pores, covered with light brownish silken threads. / Detalles de las estructuras del capullo de Bicyrtes variegatus (Oliver). 4. Porción apical, vista interna. 5. Porción basal, vista interna, que muestra la masa fecal. 6. Superficie externa, flechas señalan los poros. 7. Cúpulas internas de los poros cubiertas con hilos sedosos de color marrón claro.
Fig. 2 in Effect of tenthredinid leaf miner invasions on growth of Alaska white birch in Anchorage, Alaska, USA, and the interaction with biological control of amber-marked birch leaf miner
Fig. 2. Time series analysis of mean radial growth increments (mm) of Alaska white birch (Betula neoalaskana) in Anchorage, Alaska (n = 99) from 1984 to 2018: (1) pre-amber-marked birch leaf miner (Profenusa thomsoni) outbreak control period (1984–1995) (black dots); (2) amber-marked birch leaf miner outbreak period (1996–2007) (red dots); and (3) the amber-marked birch leaf miner suppression period due to biological control (2008–2018) (green dots). Time Series Mean = 1.7938, Std = 0.3843, N = 35, Zero Mean ADF (Augmented Dickey Fuller test) = −0.9887, Single ADF = −2.8315, Trend ADF = −4.8800.
Fig. 1 in Effect of tenthredinid leaf miner invasions on growth of Alaska white birch in Anchorage, Alaska, USA, and the interaction with biological control of amber-marked birch leaf miner
Fig. 1. Percentage of Alaska white birch (Betula neoalaskana) leaves in Anchorage mined by the amber-marked birch leaf miner (AMBLM on graph) (Profenusa thomsoni) or the late birch leaf edge miner (LEM on graph) (Heterarthrus nemoratus) from 1990 to 2019, from the initial invasion of amber-marked birch leaf miner (around 1991) through its suppression by classical biocontrol (2004– 2015) and the invasion of a second species of leaf miner (H. nemoratus) (around 2008). Data on percentage of birch leaves mined by each species were taken from multiple sources: (1) P. thomsoni: 2006–2011 (Soper et al. 2015); 2015 and 2018 (Wenninger unpublished 2018); and 2019 (Andersen et al. 2021); and (2) H. nemoratus: 2008–2010 (Lundquist et al. 2012); 2011 (Mulvey &Lamb 2012, p. 15); 2015 and 2018 (Wenninger unpublished 2018); and 2019 (Andersen et al. 2021).
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