A pattern-oriented simulation for forecasting species spread through time and space: A case study on an ecosystem engineer on the move

Modelling the spread of introduced ecosystem engineers is a conservation priority due to their potential to cause irreversible ecosystem-level changes. While existing models predict potential distributions and spread capacities, new approaches that simulate the trajectory of a species’ spread over time are needed. We developed novel simulations that predict spatial and temporal spread, capturing both continuous diffusion-dispersal and occasional long-distance leaps. We focused on the introduced population of Superb Lyrebird (Menura novaehollandiae) in Tasmania, Australia. Initially introduced as an insurance population, lyrebirds have become novel bioturbators, spreading across key natural areas and becoming "unwanted but challenging to eradicate". Using multi-scale ecological data, our research (1) identified broad and fine-scale correlates of lyrebird occupation and (2) developed a spread simulation guided by a pattern-oriented framework. This occurrence-based modelling framework is useful when demographic data are scarce. We found that the cool, wet forests of western Tasmania with open understories offer well-connected habitats for lyrebird foraging and nesting. By 2023, lyrebirds had reached quasi-equilibrium within a core range in southern Tasmania, and were expanding northwest, with the frontier reaching the western coast. Our model forecasts that by 2085, lyrebirds will have spread widely across suitable regions of western Tasmania. By pinpointing current and future areas of lyrebird occupation, we provide land managers with targeted locations for monitoring the effects of their expansion. Further, our Area of Applicability (AOA) analysis identified regions where environmental variables deviate from the training data, guiding future data collection to improve model certainty. Our findings offer an evidence-based approach for future monitoring and provide a framework for understanding the dynamics of other range-expanding species with invasive potential.

Methods
This dataset integrates fine- and broad-scale ecological data collected between 1970 and 2023. Fine-scale data was obtained from 210 camera trap sites in Tasmania, recording vegetation structure and lyrebird detections. Broad-scale data was compiled from citizen science records via the Atlas of Living Australia, combined with environmental predictors such as climatic variables, elevation, and land-use data.

Fine-scale habitat data was derived from camera trap detections, with vegetation classified into dense or sparse categories using a 3×3 grid overlay method. Broad-scale occurrence records were filtered for spatial and temporal accuracy, and pseudo-absence data was generated based on effort-controlled absence criteria.

Predictor variables for Species Distribution Models (SDMs) were z-transformed, and categorical variables (e.g., vegetation, land-use types) were aggregated into broader classes. Spread simulations used a stochastic grid-cell model with parameters calibrated via a pattern-oriented framework using Approximate Bayesian Computation.

For full details on data collection and processing, please refer to the associated publication: https://doi.org/10.1111/ecog.07597.