Concepts

20 concepts

structural equation modeling

Statistical approach allowing estimation of directional relationships among variables and comparison of direct versus indirect effects

methodological15 papers

model type

linear mixed effects model

Statistical model accounting for both fixed and random effects to analyze hierarchical or repeated measures data

methodological5 papers

model type

avalanche dynamics modeling

Computational simulation of avalanche flow physics to predict runout distance and impact parameters

methodological3 papers

model type

individual-based model

Computational model that simulates individual organisms and their life histories to understand population-level patterns

methodological3 papers

model type

principal component analysis

Statistical method used to identify the structuring factors driving life-history variation and to detect slow-fast continuum patterns

methodological3 papers

model type

Long Short-Term Memory

Type of recurrent neural network capable of learning temporal dependencies in sequential data through gated memory cells

methodological2 papers

model type

biophysical models

Tools implemented to accurately predict an organism's physiological response to attributes of interest such as water loss and body temperature

conservation ecology (1)

pollination ecology (1)

remote sensing (1)

geophysics (1)

environmental stress (1)

methodological2 papers

model type

Bayesian clustering

Statistical method for assigning individuals to groups based on genetic similarity

methodological1 paper

model type

Complex Refractive Index Method

Method relating electromagnetic wave speed in snowpack to dry snow density using known wave speeds of constituent materials

methodological1 paper

model type

Cox proportional hazard model

Semi-parametric survival analysis that allows mortality hazard to fluctuate with time while measuring effects of covariates on survival probability

methodological1 paper

model type

Gaussian mixture model

A clustering approach that assumes feature space is a product of a finite number of Gaussian components, each representing distinct co-varied features in multivariable space

methodological1 paper

model type

Lomax distribution

Probability distribution used to model distance-decay patterns in pollen dispersal

methodological1 paper

model type

approximate Bayesian computation

A computational method for model fitting that contrasts the influence of different mechanisms by simulating data under different parameter sets

methodological1 paper

model type

broken-stick model

Statistical model used to determine the number of principal components to retain, setting threshold above which a component explains more variation than expected by chance alone

methodological1 paper

model type

convolutional neural networks

Deep learning architecture using convolutional layers for image classification and segmentation tasks

methodological1 paper

model type

empirical models

Statistical models fitted to observational data to predict patterns and test hypotheses

methodological1 paper

model type

exponential decline function

Mathematical function Y = A·e^(-β·d) where Y is root mass, A is root mass at soil surface, d is soil depth, and β defines steepness of decline

methodological1 paper

model type

exponential decline model

Mathematical model describing how pollen deposition decreases exponentially with successive flower visits

methodological1 paper

model type

null model

Statistical model that generates random patterns while preserving certain constraints, used as baseline for comparison

methodological1 paper

model type

ordinal logistic regression

A regression approach that allows for multiple ordered response categories and provides more specific interpretation of exact probability of socioeconomic characteristics on constraints

methodological1 paper