Statistical modelling of communities and ecosystems using the LAMDA software tool

Understanding species interactions is critical to discovering community dynamics. Recently, statistical methods for estimating species interaction strengths from time series data have been developed based on multivariate auto-regressive first-order, or MAR(1), models. However, the complex coding required presents a substantial barrier for most ecologists. We have developed LAMBDA, a software program that allows users to easily fit MAR(1) models to multi-species time series data. The LAMBDA package covers: data input and transformation, selection of the interactions to include via a search algorithm and model selection, estimation of interaction parameters via conditional least squares (CLS) regression or two different maximum-likelihood (ML) algorithms, estimation of confidence intervals via bootstrapping, and computation of community stability properties using the estimated model. We describe performance tests on the variability of estimates, computation speed, and CLS versus ML estimation using simulated data.