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Data from: Grouper (Epinephelidae) spawning aggregations affect activity space of grey reef sharks, Carcharhinus amblyrhynchos, in Pohnpei, Micronesia
- 负责人：
- DOI：
- doi:10.5061/dryad.6ck4218
- 摘要：
- , while average monthly activity space was concentrated around FSA. Best-fit models for the GLMM indicated that activity spaces were most influenced by month
Data from: Within guild co-infections influence parasite community membership: a longitudinal study in African Buffalo
- 负责人：
- Henrichs, Brian
- DOI：
- doi:10.5061/dryad.vq61n
- 摘要：
- in determining haemoparasite infection patterns in free living mammalian hosts. Our findings suggest a role for interactions among parasites infecting a singl
Data from: Assessing gene-environment interactions for common and rare variants with binary traits using gene-trait similarity regression
- 负责人：
- DOI：
- doi:10.5061/dryad.742gv
- 摘要：
- Accounting for gene-environment (GxE) interactions in complex trait association studies can facilitate our understanding of genetic heterogeneity under different environmental exposures, improve the ability to discover susceptible genes that exhibit little marginal effect, provide insight into the biological mechanisms of complex diseases, help to identify high-risk subgroups in the population, and uncover hidden heritability. However, significant GxE interactions can be difficult to find. The sample sizes required for sufficient power to detect association are much larger than those needed for genetic main effects, and interactions are sensitive to misspecification of the main effects model. These issues are exacerbated when working with binary phenotypes and rare variants, which bear less information on association. In this work, we present a similarity-based regression method for evaluating GxE interactions for rare variants with binary traits. The proposed model aggregates the genetic and GxE information across markers using genetic similarity thus increasing the ability to detect GxE signals. The model has a random effects interpretation, which leads to robustness against main effect misspecifications when evaluating GxE interactions. We construct score tests to examine GxE interactions and a computationally efficient EM algorithm to estimate the nuisance variance components. Using simulations and data applications, we show that the proposed method is a flexible and powerful tool to study the GxE effect in common or rare variant studies with binary traits.
Data from: Seedling recruitment in subalpine grassland forbs: predicting field regeneration behaviour from lab germination responses
- 负责人：
- DOI：
- doi:10.5061/dryad.04f8c
- 摘要：
- Environmental cueing that restricts seed germination onto times and places where mortality risk is relatively low may have considerable selective advantage. The predictive power of lab germination responses for field regeneration behaviour is rarely tested. We screened 11 alpine grassland forbs for germination behaviours predictive of microsite and seasonal selectivity, and seed carry-over across years. The predictions were tested in a field experiment. Germination in the lab ranged from 0.05% to 67.9%, and was affected by light (5 species), temperature (6), fluctuating temperatures (4), moist chilling prior to germination (cold-stratification) (6), and dormancy-breaking by means of gibberellic acid (8). Seedling emergence in the field varied from 0.1% to 14.1%, and increased in low-competition microsites (bare-ground gaps and cut vegetation; 7 species), and showed seasonal timing (1 in autumn and 1 in spring), and seed carry-over across years (7). Lab germination responses successfully predicted microsite selectivity in the field and to some extent seed carry-over across years but not seasonal timing of germination. Gap-detecting species were generally small-seeded, low-growing, and found in unproductive habitats. Larger-seeded species germinated in all microsites but experienced increased mortality in high-competition microsites. Seed carry-over across years was lower in alpine specialists than in more widely-distributed species.
Data from: Habitat urbanization and stress response are primary predictors of personality variation in Northern cardinals (Cardinalis cardinalis)
- 负责人：
- 关键词：
- behavioral syndrome;state-dependent theory;structural equation modeling;urbanization;corticosterone
- DOI：
- doi:10.5061/dryad.47d7wm38j
- 摘要：
- followed by general linear mixed model (GLMM), we found that habitat type, baseline CORT and CORT short-term response affected some personality traits
Data from: Effect of light-level geolocators on apparent survival of two highly aerial swift species
- 负责人：
- DOI：
- doi:10.5061/dryad.b1t42
- 摘要：
- ’). We performed both traditional GLMM using return rate as a proxy for survival and mark-recapture models to estimate survival while accounting for recapture
Data from: Genomics of the divergence continuum in an African plant biodiversity hotspot, I: drivers of population divergence in Restio capensis (Restionaceae)
- 负责人：
- DOI：
- doi:10.5061/dryad.060d2
- 摘要：
- , and phytogeographic data, using a Bayesian generalized linear mixed modeling (GLMM) approach. The results indicate that population divergence ac
Data from: The interplay of nested biotic interactions and the abiotic environment regulates populations of a hypersymbiont
- 负责人：
- DOI：
- doi:10.5061/dryad.bs8313h
- 摘要：
- for GLMM to assess the relative importance of: 1) traits of symbiotic hosts (ostracod sex and abundance), 2) traits of basal hosts (crayfish body weight
Data from: Biogeography and anthropogenic impact shape the success of invasive wasps on New Zealand’s offshore islands
- 负责人：
- DOI：
- doi:10.5061/dryad.zkh189368
- 摘要：
- mixed effect model (GLMM) was fitted to identify drivers of Vespula and Polistes abundance on offshore islands.
Res
Data from: The effect of demographic correlations on the stochastic population dynamics of perennial plants
- 负责人：
- DOI：
- doi:10.5061/dryad.mp935
- 摘要：
- Understanding the influence of environmental variability on population dynamics is a fundamental goal of ecology. Theory suggests that, for populations in variable environments, temporal correlations between demographic vital rates (e.g., growth, survival, reproduction) can increase (if positive) or decrease (if negative) the variability of year-to-year population growth. Because this variability generally decreases long-term population viability, vital rate correlations may importantly affect population dynamics in stochastic environments. Despite long-standing theoretical interest, it is unclear whether vital rate correlations are common in nature, whether their directions are predominantly negative or positive, and whether they are of sufficient magnitude to warrant broad consideration in studies of stochastic population dynamics. We used long-term demographic data for three perennial plant species, hierarchical Bayesian parameterization of population projection models, and stochastic simulations to address the following questions: (1) What are the sign, magnitude, and uncertainty of temporal correlations between vital rates? (2) How do specific pairwise correlations affect the year-to-year variability of population growth? (3) Does the net effect of all vital rate correlations increase or decrease year-to-year variability? (4) What is the net effect of vital rate correlations on the long-term stochastic population growth rate (?S)? We found only four moderate to strong correlations, both positive and negative in sign, across all species and vital rate pairs; otherwise, correlations were generally weak in magnitude and variable in sign. The net effect of vital rate correlations ranged from a slight decrease to an increase in the year-to-year variability of population growth, with average changes in variance ranging from -1% to +22%. However, vital rate correlations caused virtually no change in the estimates of ?S (mean effects ranging from -0.01% to +0.17%). Therefore, the proportional changes in the variance of population growth caused by demographic correlations were too small on an absolute scale to importantly affect population growth and viability. We conclude that in our three focal populations and perhaps more generally, vital rate correlations have little effect on stochastic population dynamics. This may be good news for population ecologists, because estimating vital rate correlations and incorporating them into population models can be data-intensive and technically challenging.
