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8 results for “Mutualism disruption”
Disruption of an ant-plant mutualism shapes interactions between lions and their primary prey
<p><strong>Data and file overview:</strong></p> <ol> <li>Kamaru_Path_Analysis_Data.csv</li> <li>Kamaru_Path_Analysis.R</li> <li>Kamaru_Zebra_RSF_Data.csv</li> <li>Kamaru_Zebra_RSF.R</li> </ol> <p><strong>Layers used to build Zebra RSF:</strong></p> <ol> <li>Kamaru_DWater: distance to water</li> <li>Kamaru_DGlade: distance to glade</li> <li>Kamaru_DSettlement: distance to human settlement</li> <li>Kamaru_OPC_Veg: vegetation layer (classes: <em>V. drepanolobium</em>, <em>E. divinorum, </em>others)</li> </ol> <p><strong>SPECIFIC INFORMATION FOR: Kamaru_Path_Analysis_Data.csv</strong></p> <ol> <li>Number of variables: 11</li> <li>Description: This data file includes 105 zebra kill sites and paired random locations from June 2019 to August 2020. It also includes: (A) monthly utilization distributions of lion prides associated with each kill site and paired point; and (B) zebra densities estimated from resource selection functions, associated with each kill site, and paired random location. Please see our supplementary materials for more details on data and methods.</li> <li>Variable list:</li> </ol> <p>(A) rsf.block: Resource Selection Function blocks (block 1: Jan-Apr 2019, block 2: May-Sep 2019, block 3: Oct 2019 – Jan 2020, block 4: Feb-May 2020, block 5: Jun-Sep 2020)</p> <p>(B) Kill_ID: kill identifier.</p> <p>(C) Lion_ID: individual lion pride identifier.</p> <p>(D) Date (Day, Month, Year) when a specific kill occurred.</p> <p>(E) Zebra_kill (1 = kill site, 0 = paired random location).</p> <p>(F). Species: Zebra.</p> <p>(G) Visibility: openness measurement using a rangefinder in (m).</p> <p>(H) Lion_activity: Utilization distributions (UD) of lions.</p> <p>(I) Invasion (1 = invaded by big-headed ants, 0 = uninvaded by big-headed ants).</p> <p>(J) zeb.rsf: resource selection function value.</p> <p>(K) zeb.density: zebra density estimated from resource selection functions.</p> <p><strong>SPECIFIC INFORMATION FOR: Kamaru_Zebra_RSF_Data.csv</strong></p> <ol> <li>Number of variables: 10</li> <li>Description: This data file includes 182 zebra sightings, paired with 10 random points created for each sighting/used point. Also, the data includes actual GPS locations of each sighting and the total number of zebras in each sighting. Please see our supplementary materials for more details on data and methods.</li> <li>Variable list:</li> </ol> <p>(A) Species: Zebra.</p> <p>(B) Date (Day, Month, Year) for that sighting.</p> <p>(C) Survey: count identifier (Survey 2 to 21).</p> <p>(D) GPS location (X and Y), longitude and latitude of that sighting location.</p> <p>(E) Transect: Transect number.</p> <p>(F) Used: (1= zebra sighting, 0 = paired point).</p> <p>(G) zebra.ct: total number of zebras in each sighting.</p> <p> </p> <p><strong>R CODE</strong></p> <p><strong>SPECIFIC INFORMATION FOR: Kamaru_Path_Analysis.R</strong></p> <ol> <li>Description: Apply this code to Kamaru_Path_Analysis_Data.csv to build nested path models.</li> </ol> <p><strong>SPECIFIC INFORMATION FOR: Kamaru_Zebra_RSF.R</strong></p> <ol> <li>Description: Apply this code to Kamaru_Zebra_RSF_Data.csv to build resource selection functions for zebra. Use the following layers: Kamaru_DWater, Kamaru_DGlade, Kamaru_DSettlement and Kamaru_OPC_Veg to build the Zebra RSF.</li> </ol>
Ant-scale mutualism increases scale infestation, decreases folivory, and disrupts biological control in restored tropical forests
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Parasites disrupt a keystone mutualism that underpins the structure, functioning, and resilience of a coastal ecosystem
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Data from: Ant–scale mutualism increases scale infestation, decreases folivory, and disrupts biological control in restored tropical forests
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Bromus tectorum alters mycorrhizal fungal communities and disrupts mutualism
<p class="MsoNormal">Exotic plant invasions alter native plant productivity and ecosystem function. Mechanisms of plant invasions can include altered disturbance regimes or altered plant-soil feedbacks. Some important hypotheses regarding the invasion of cheatgrass in North America include pathogen spillover and mutualism disruption. Since an important mutualistic interaction in ecosystems is that of mycorrhizal fungi, here we test the mutualism disruption hypothesis by closely examining mycorrhizal allocation and community composition. We conducted a greenhouse study where we grew a native perennial grass in association with invaded and uninvaded soils. We found altered mycorrhizal communities and mycorrhizal allocation patterns associated with cheatgrass-invaded soils supporting the mutualism disruption hypothesis.</p>
Bromus tectorum alters mycorrhizal fungal communities and disrupts mutualism
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Data from: Genetic conflict with a parasitic nematode disrupts the legume-rhizobia mutualism
Genetic variation for partner quality in mutualisms is an evolutionary paradox. One possible resolution to this puzzle is that there is a tradeoff between partner quality and other fitness-related traits. Here, we tested whether a susceptibility to parasitism is one such tradeoff in the mutualism between legumes and nitrogen-fixing bacteria (rhizobia). We performed two greenhouse experiments with the legume Medicago truncatula. In the first, we inoculated each plant with the rhizobia Ensifer meliloti and with one of 40 genotypes of the parasitic root-knot nematode Meloidogyne hapla. In the second experiment, we inoculated all plants with rhizobia and half of the plants with a genetically variable population of nematodes. Using the number of nematode galls as a proxy for infection severity, we found that plant genotypes differed in susceptibility to nematode infection, and nematode genotypes differed in infectivity. Second, we showed that there was a genetic correlation between the number of mutualistic structures formed by rhizobia (nodules) and the number of parasitic structures formed by nematodes (galls). Finally, we found that nematodes disrupt the rhizobia mutualism: nematode-infected plants formed fewer nodules and had less nodule biomass than uninfected plants. Our results demonstrate that there is genetic conflict between attracting rhizobia and repelling nematodes in Medicago. If genetic conflict with parasitism is a general feature of mutualism, it could account for the maintenance of genetic variation in partner quality and influence the evolutionary dynamics of positive species interactions.
Data from: Genetic conflict with a parasitic nematode disrupts the legume-rhizobia mutualism
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