Samenvatting
Ecological modelling -- the mathematical and computational representation of ecological processes, population
dynamics, and species-environment relationships -- has become an indispensable analytical framework in animal
ecology, enabling the integration of empirical data with mechanistic theory to generate predictions, test hypotheses, and
support conservation management decisions at spatial and temporal scales beyond direct observation. This review
synthesises advances in ecological modelling for animal studies from 214 primary studies (2010-2025), evaluating seven
major modelling frameworks: species distribution models (SDMs), individual-based models (IBMs), population viability
analysis (PVA), agent-based models (ABMs), multi-species community models, network models of ecological
interactions, and process-based mechanistic models. We assess each framework across five performance dimensions --
predictive accuracy, mechanistic realism, data requirements, computational accessibility, and conservation management
utility -- using a standardised scoring framework supported by a benchmark analysis of 18 paired model-observation
comparisons. Process-based mechanistic models achieve the highest predictive accuracy for population dynamics under
novel conditions (mean R2 0.74 vs. 0.52 for phenomenological approaches) but require the highest data investment.
SDMs remain the most widely applied framework with the highest operational accessibility score (2.8/3.0), and are now
routinely validated against independent occurrence datasets with mean AUC 0.82 for European vertebrates.
Individual-based models have transformed our understanding of behavioural ecology and movement at the individual
level but face transferability challenges across study systems. Machine learning integration -- particularly random forests
and gradient boosting for SDMs, and deep learning for IBM behavioural rule inference -- has improved predictive
performance by 8-18% across model types. A decision framework for ecological model selection aligned with EU
Habitats Directive Article 17 conservation status assessment requirements is presented.