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68 results for “fitness differences”
Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models
<p><strong>Baum_et_al_2019_Supplementary_Figures.pdf: </strong>Supplementary Figures S1-S4. Legends are included under each figure.</p> <p><strong>sbm-for-correlation-based-networks-master.zip: </strong>Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks.</p>
F I G U R E 2 Fitted logistic curves with 95 in Circadian and seasonal flight activity differences between the sexes of the biocontrol agent Eadya daenerys (Hymenoptera: Braconidae) and the impact of host size on adult emergence
F I G U R E 2 Fitted logistic curves with 95% confidence intervals for the effect of Paropsisterna agricola beetle prepupal weight (mg) for three post-beetle prepupal outcomes (dead beetle prepupa, beetle or E. daenerys wasp).
Different measures of niche and fitness differences tell different tales
<p>In Modern Coexistence Theory, species coexistence can either arise via strong niche differences or weak fitness differences. Having a common currency for interpreting these mechanisms is essential for synthesizing knowledge across different studies and systems. However, several methods for quantifying niche and fitness differences exist, with little guidance on how and why these methods differ. Here, we first organize the available methods into three groups and review their differences from a conceptual point of view.Next, we apply four methods to quantify niche and fitness differences to one simulated and one empirical data set. We show that these methods do not only differ quantitatively, but affect how we interpret coexistence. Specifically, the different methods disagree on how resource supply rates (simulated data) or plant traits (empirical data) affect niche and fitness differences. We argue for a better theoretical understanding of what connects and sets apart different methods and more precise empirical measurements to foster appropriate method selection in coexistence theory.</p>
Different measures of niche and fitness differences tell different tales
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Data from: The repeatable opportunity for selection differs between pre- and post-copulatory fitness components
<p>In species with multiple mating, intense sexual selection may occur both before and after copulation. However, comparing the strength of pre- and postcopulatory selection is challenging, because i) postcopulatory processes are generally difficult to observe and ii) the often-used opportunity for selection (<i>I</i>) metric contains both deterministic and stochastic components. Here, we quantified pre- and postcopulatory male fitness components of the simultaneously hermaphroditic flatworm, <i>Macrostomum lignano</i>. We did this by tracking fluorescent sperm—using transgenics—through the transparent body of sperm recipients, enabling to observe postcopulatory processes <i>in vivo</i>. Moreover, we sequentially exposed focal worms to three independent mating groups, and in each assessed their mating success, sperm-transfer efficiency, sperm fertilising efficiency, and partner fecundity. Based on these multiple measures, we could, for each fitness component, combine the variance (<i>I</i>) with the repeatability (<i>R</i>) in individual success to assess the amount of repeatable variance in individual success—a measure we call the repeatable opportunity for selection (<i>I<sub>R</sub></i>). We found higher repeatable opportunity for selection in sperm-transfer efficiency and sperm fertilising efficiency compared to mating success, which clearly suggests that postcopulatory selection is stronger than precopulatory selection. Our study demonstrates that the opportunity for selection contains a repeatable deterministic component, which can be assessed and disentangled from the often large stochastic component, to provide a better estimate of the strength of selection.</p>
The repeatable opportunity for selection differs between pre- and postcopulatory fitness components
<p>Mating movies and sperm movies of the flatworm <em>Macrostomum lignano</em> supporting the article "The repeatable opportunity for selection differs between pre- and postcopulatory fitness components" published in Evolution Letters.</p>
Data from: Higher-order species interactions cause time-dependent niche and fitness differences: experimental evidence in plant-feeding arthropods
<p><strong>trajectories.csv </strong>(the raw data)</p> <p><strong>id</strong>: replicate identifier<br><strong>variant</strong>: co-existence status ("competition" or "monoculture")<br><strong>day</strong>: day of experiment<br><strong>species</strong>: mite species ("CRM" or "WCM")<br><strong>n</strong>: population density</p> <p> </p> <p><strong>model.R</strong></p> <p>The R script with the GAMM fitted to the trajectory data (the GAMM model is saved as <strong>model.RData</strong>); also produces simulations from this model (saved as <strong>sim.csv</strong>).</p> <p> </p> <p><strong>model.RData</strong></p> <p>The GAMM for growth rates.</p> <p> </p> <p><strong>sim.csv</strong> (simulations from the GAMM)</p> <p><strong>day</strong>: day of experiment<br><strong>spec_var</strong>: combination of co-existence status ("competition" or "monoculture") and species ("CRM" or "WCM")<br><strong>X1:X1000</strong>: population densities simulated from the fitted GAMM (on the log scale)</p> <p> </p> <p><strong>NFD_over_time_monte_carlo_gam.py</strong></p> <p>Python script to compute niche and fitness differences. Takes <strong>sim.csv</strong> (densities over time for different instantiations) and <strong>model.RData</strong> (stores the GAMM from R for the growth rates) as input and generates the file <strong>Data_NFD_monte_carlo_multi_c.csv</strong> which stores the niche and fitness differences computed for these communities.</p> <p> </p> <p><strong>figures.R</strong></p> <p>The R script that produces Figures 2-4.</p> <p> </p> <p><strong>plot_biotic_model.py</strong></p> <p>Python code to generate the figures S3 and S4 showing the simulations of a biotic resource competition model. </p> <p> </p> <p><strong>plot_abiotic_model.py</strong></p> <p>Python code to generate the figures S1 and S2 showing simulations of an abiotic resource competition model. </p>
Data for the article entitled "ENVIRONMENTAL AND SOCIAL CORRELATES, AND ENERGETIC CONSEQUENCES OF FITNESS MAXIMISATION ON DIFFERENT MIGRATORY BEHAVIOURS IN A LONG-LIVED SCAVENGER"
<p>Data used in the statistical analyses of the article entitled "ENVIRONMENTAL AND SOCIAL CORRELATES, AND ENERGETIC CONSEQUENCES OF FITNESS MAXIMISATION ON DIFFERENT MIGRATORY BEHAVIOURS IN A LONG-LIVED SCAVENGER"</p>
Different proxies, different stories? Imperfect correlations and different determinants of fitness in bighorn sheep
<p>Measuring individual fitness empirically is required to assess selective pressures and predict evolutionary changes in nature. There is, however, little consensus on how fitness should be empirically estimated. As fitness proxies vary in their underlying assumptions, their relative sensitivity to individual, environmental, and demographic factors may also vary. Here, using a long-term study, we aimed at identifying the determinants of individual fitness in bighorn sheep (<em>Ovis</em> <em>canadensis</em>) using seven fitness proxies. Specifically, we compared four-lifetime fitness proxies: lifetime breeding success, lifetime reproductive success, individual growth rate, and individual contribution to population growth, and three multi-generational proxies: number of granddaughters, individual descendance in the next generation, and relative genetic contribution to the next generation. We found that all proxies were positively correlated, but the magnitude of the correlations varied substantially. Longevity was the main determinant of most fitness proxies. Individual fitness calculated over more than one generation was also affected by population density and growth rate. Because they are affected by contrasting factors, our study suggests that different fitness proxies should not be used interchangeably as they may convey different information about selective pressures and lead to divergent evolutionary predictions. Uncovering the mechanisms underlying variation in individual fitness and improving our ability to predict evolutionary change might require the use of several, rather than one, proxy of individual fitness.</p>
Database for "Phenotype-fitness relationships and pollen transfer efficiency of five orchid species with different pollination strategies" American Journal of Botany 2023
<p>Public data from the paper: Phenotype-fitness relationships and pollen transfer efficiency of five orchid species with different pollination strategies by M. Capò, J. Borràs, S. Perellò-Suau, J. Rita and J. Cursach, published in American Journal of Botany 2023. <a href="https://doi.org/10.5281/zenodo.7826601">DOI: 10.5281/zenodo.7826601</a></p>
Fitness and niche differences are both important in explaining responses of plant diversity to nutrient addition
<p><span>Plant species loss due to eutrophication is a common phenomenon in temperate perennial grasslands. It occurs in a non-random fashion and is usually explained by increased competitive size asymmetry between co-occurring winner (tall species with optima in productive habitats) and loser species (small-statured plants typical for unproductive habitats). It remains unclear why nutrient addition decreases diversity in communities consisting of losers only, whereas it has little effect on winner-only communities. Here, I used the framework of modern coexistence theory to explore fertilization-driven changes in fitness and niche differences between different combinations of field-identified winner (W) and loser (L) species. I experimentally estimated competition parameters for plant species pairs constructed from a pool of eight species, including pairs of species from the same (WW, LL) and different species categories (LW) grown for approximately two years in control and fertilized conditions. Concurrently, I also followed plant species diversity in mesocosm communities constructed from the same species pool (four-species communities including winners, losers, or both) exposed to control and nutrient addition. </span><span>I found that nutrient addition can reduce but, unexpectedly, also promote species coexistence depending on the type of species pairs. Whereas nutrient addition eroded coexistence of losers with winners, but also with other losers, treatment had the opposite effect on the persistence of winner species. Fertilization induced large fitness differences between species in loser-winner and loser-loser combinations, but had little effect on the fitness differences of species within the winner-winner combination. In addition, the persistence of winner pairs was promoted by larger niche differences compared to loser species, irrespective of soil nutrients. The differences in how nutrient addition modified coexistence at the pairwise level were reflected by differences in evenness of multispecies communities assembled from the corresponding species categories.</span> <span>These results suggest that the effect of eutrophication on plant species richness cannot simply be explained by an increased competitive asymmetry. To fully understand the effect of fertilization on the diversity of temperate grasslands, interspecific and intraspecific interactions should be explored while considering differences in species' ecological optima.</span></p>
[Dataset] Difference spectrum fitting of the ion-neutral collision frequency from dual-frequency EISCAT measurements
<p>Dataset used for "Difference spectrum fitting of the ion-neutral collision frequency from dual-frequency EISCAT measurements"</p>
Different proxies, different stories? Imperfect correlations and different determinants of fitness in bighorn sheep
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Experimental test of the fitness effects of divergent marine-freshwater chromosomal inversions in stickleback under different salinity conditions
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Data from: The repeatable opportunity for selection differs between pre- and post-copulatory fitness components
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Data from: One size does not fit all: caste and sex differences in the response of bumblebees (Bombus impatiens) to chronic oral neonicotinoid exposure
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Fitness differences override variation-dependent coexistence mechanisms in California grasslands
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Fitness and niche differences are both important in explaining responses of plant diversity to nutrient addition
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Data from: A comparative study on the physical fitness of college students from different grades and majors in Jiangxi province
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Data from: Arbuscular mycorrhizal fungi equalize differences in plant fitness and facilitate plant species coexistence through niche differentiation
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Allen Brain Atlas
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