Table 3. Evaluation of different algorithms considered for predictive ecosystem modelling. Features are drawn from recent reviews (Nieto-Lugilde et al 2018, Norberg et al 2017), methodological guides (Mokany et al 2022), personal communication (Ovaskainen 2021), and from assessments of individual algorithms (e.g., Poggiato et al 2021). Algorithms described in Table 2. A – Multivariate regression tree, B – Multiresponse multivariate adaptive regression splines, C – Constrained linear ordination, D – Constrained quadratic ordination, E – Constrained additive ordination, F – Multiresponse artificial neural networks, G – Multivariate stochastic neural network, H - Hierarchical Bayesian model / Latent variable model, I – Generalized dissimilarity modelling, J – Gradient forest, K – Region of common profile, L – Generalized joint attribute modelling