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155 results for “interaction scale”

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dryad32/100

Data from: Urbanization affects oak–pathogen interactions across spatial scales

The world is rapidly urbanizing, thereby transforming natural landscapes and changing the abundance and distribution of organisms. However, insights into the effects of urbanization on species interactions, and plant-pathogen interactions in particular, are lacking. We investigated the effects of urbanization on powdery mildew infection on Quercus robur at continental and within-city scales. At the continental scale, we compared infection levels between urban and rural areas of different-sized cities in Europe, and investigated whether plant traits, climatic variables and CO2 emissions mediated the effect of urbanization on infection levels. Within one large city (Stockholm, Sweden), we further explored whether local habitat features and spatial connectivity influenced infection levels during multiple years. At the continental scale, infection severity was consistently higher on trees in urban than rural areas, with some indication that temperature mediated this effect. Within Stockholm city, temperature had no effect, while local accumulation of leaf litter negatively affected powdery mildew incidence in one out of three years, and more connected trees had lower infection levels. This study is the first to describe the effects of urbanization on plant-pathogen interactions both within and among cities, and to uncover the potential mechanisms behind the observed patterns at each scale.

opencc-zeroOct 2021View details →

dryad32/100

A method for identifying environmental stimuli and genes responsible for genotype-by-environment interactions from a large-scale multi-environment data set

It has not been fully understood in real fields what environment stimuli cause the genotype-by-environment (G × E) interactions, when they occur, and what genes react to them. Large-scale multi-environment data sets are attractive data sources for these purposes because they potentially experienced various environmental conditions. In this study, we developed a data-driven approach termed Environmental Covariate Search Affecting Genetic Correlations (ECGC) to identify environmental stimuli and genes responsible for the G × E interactions from large-scale multi-environment data sets. ECGC was applied to a soybean (Glycine max) data set that consisted of 25,158 records collected at 52 environments. ECGC illustrated what meteorological factors shaped the G × E interactions in six traits including yield, flowering time, and protein content and when they were involved. For example, it illustrated the relevance of precipitation around sowing dates and hours of sunshine just before maturity to the interactions observed for yield. Moreover, genome-wide association mapping on the sensitivities to the identified stimuli discovered candidate and known genes responsible for the G × E interactions. Our results demonstrate the capability of data-driven approaches to bring novel insights on the G × E interactions observed in fields. This dataset provides the data used in this study and supplementary tables cited in the manuscript.

opencc-zeroDec 2021View details →

dryad32/100

Interaction of diet and habitat predicts Toxoplasma gondii infection rates in wild birds at a global scale

Aim: Free-ranging wildlife are valuable sentinels for zoonotic, multi-host pathogens, and novel insight on parasite transmission patterns is possible through a macroecological approach. Toxoplasma gondii is a protozoan capable of infecting all warm-blooded animals, including humans, primarily through a free-living oocyst and/or tissue cyst life-stage. Anthropogenic disturbance is facilitating the spread of T. gondii, making it critical to understand the general ecological and life history drivers of T. gondii infections in wild birds, which are important intermediate hosts. Our goal was to determine how habitat (terrestrial vs. aquatic), dietary trophic level and scavenging behaviour influence T. gondii infection prevalence in wild birds on a global scale. Location: Global Time period: 1952-2017 Major taxa studied: Birds Methods: Our analysis used the serological, bioassay and molecular prevalence data of T. gondii in avian species compiled from 81 studies conducted worldwide and encompassing 24,344 individuals from 393 avian species from 84 families. Results: We show that at a global scale, trophic level and habitat significantly interact to influence T. gondii prevalence in avian intermediate hosts. In the terrestrial environment, T. gondii prevalence increases with trophic level, consistent with predominant tissue cyst transmission. The highest prevalence was in terrestrial omnivores, which may reflect their synanthropic foraging behaviour. In aquatic species, prevalence was more consistent across trophic levels, but high prevalence in aquatic herbivores and insectivores reflects significant waterborne exposure to oocysts. Contrary to our predictions, generalized scavenging per se was not associated with increased prevalence. Main conclusions: This study highlights the value of comparing pathogen prevalence among multiple ecological guilds and ecosystem types for a comprehensive understanding of the epidemiology of generalist pathogens, such as T. gondii. Increased effort is needed to reduce T. gondii spillover from the domestic cat cycle into wildlife populations.

opencc-zeroMar 2022View details →

dryad32/100

The role of aerosol-radiation interaction in the meteorology prediction at the weather scale

<a name="OLE_LINK53"></a>The current capabilities of the numerical weather prediction (NWP) model to simulate aerosol-radiation interaction (ARI) impacts on weather prediction are still rarely considered compared with climate models. Here, the NWP model GRAPES_CUACE is used to evaluate the role of the ARI in meteorology prediction at the weather scale in China. The results show that the online calculation of ARI in the model can <a name="OLE_LINK99"></a>extensively improve the meteorology prediction accuracy involving temperature, wind, and pressure at most vertical <a name="OLE_LINK12"></a>levels in relatively clean, light, and heavy pollution stages. This improvement significantly occurs in the meteorology factors below 950 hPa prediction such as temperature at 2 m, 1000, and 950 hPa, and mean sea level pressure, particularly in heavy pollution areas and stages. <a name="OLE_LINK13"></a>Unlike temperature, the improvement of ARI in the predicted wind <a name="OLE_LINK52"></a>at the height of the boundary layer is more significant than near-surface. However, this improvement declines when the low-cloud exists.

opencc-zeroApr 2022View details →

zenodo32/100

Diet analysis of bats killed at wind turbines suggest large-scale losses of trophic interactions

Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly feedback on local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g. wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.

opencc-by-4.0May 2022View details →

zenodo32/100

Synthetic catalog of seismicity and stressing rate history for "Scaling and variability of interacting repeating earthquake sequences controlled by asperity density"

Sheets 1 to 14: Synthetic catalogs of seismicity listing (for each earthquake): <ul> <li>non dimensional time (1st column)</li> <li>non dimensional seismic moment (2nd column)</li> <li>non dimensional equivalent source radius (3rd column)</li> <li>non dimensional position along strike x (4th column)</li> <li>non dimensional position along dip y (5th column)2</li> </ul> Sheets 15 to 28: time series of the spatial average of: <ul> <li>non dimensional slip (2nd column)</li> <li>non dimensional slip rate (3rd column) </li> <li>non dimensional shear stress (4th column)</li> </ul> Time series corresponding to catalog in sheet i is provided in sheet i+14. See the reference paper for details about the non dimensionalization.

opencc-by-4.0Oct 2019View details →

dryad32/100

Individual flowering phenology shapes plant-pollinator interactions across ecological scales affecting plant reproduction

1. The balance of pollination competition and facilitation amongst co-flowering plants and abiotic resource availability can modify plant species and individual reproduction. Floral resource succession and spatial heterogeneity modulate plant-pollinator interactions across ecological scales (individual plant, local assemblage, interaction network of agroecological infrastructure across the farm). Intraspecific variation in flowering phenology can modulate the precise level of spatio-temporal heterogeneity in floral resources, pollen donor density and pollinator interactions that a plant individual is exposed to, thereby affecting reproduction. 2. We tested how abiotic resources and multi-scale plant-pollinator interactions affected individual plant seed set, modulated by intraspecific variation in flowering phenology and spatio-temporal floral heterogeneity arising from agroecological infrastructure. We transplanted two focal insect-pollinated plant species (Cyanus segetum and Centaurea jacea, n = 288) into agroecological infrastructure (10 sown wildflower, 6 legume-grass strips) across a farm-scale experiment (125 ha). 3. We applied an individual-based phenologically explicit approach to match precisely the flowering period of plant individuals to the concomitant level of spatio-temporal heterogeneity in plant-pollinator interactions, potential pollen donors, floral resources and abiotic conditions (temperature, water, nitrogen). 4. Individual plant attractiveness, assemblage floral density and conspecific pollen donor density (C. jacea) improved seed set. Network linkage density increased focal species' seed set and modified the effect of local assemblage richness and abundance on C. segetum. Mutual dependence on pollinators in networks increased C. segetum seed set, while C. jacea seed set was greatest where both specialization on pollinators and mutual dependence was high. Abiotic conditions were of little or no importance to seed set. 5. Intra- and interspecific plant-pollinator interactions respond to spatio-temporal heterogeneity arising from agroecological management affecting wild plant species reproduction. The interplay of pollinator interactions within and between ecological scales affecting seed set implies a co-occurrence of pollinator-mediated facilitative and competitive interactions among plant species and individuals.

opencc-zeroDec 2022View details →

zenodo32/100

Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics

Results and code to replicate analysis in "Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics" by Toneyan and Koo.

opencc-by-4.0Jul 2023View details →

dryad32/100