The limits to prediction in ecological systems

Abstract

Abstract. Predicting the future trajectories of ecological systems is increasingly important as the magnitude of anthropogenic perturbation of the earth systems grows. We distinguish between two types of predictability: the intrinsic or theoretical predictability of a system and the realized predictability that is achieved using available models and parameterizations. We contend that there are strong limits on the intrinsic predictability of ecological systems that arise from inherent characteristics of biological systems. While the realized predictability of ecological systems can be limited by process and parameter misspecification or uncertainty, we argue that the intrinsic predictability of ecological systems is widely and strongly limited by computational irreducibility. When realized predictability is low relative to intrinsic predictability, prediction can be improved through improved model structure or specification of parameters. Computational irreducibility, however, asserts that future states of the system cannot be derived except through computation of all of the intervening states, imposing a strong limit on the intrinsic or theoretical predictability. We argue that ecological systems are likely to be computationally irreducible because of the difficulty of pre-stating the relevant features of ecological niches, the complexity of ecological systems and because the biosphere can enable its own novel system states or adjacent possible. We argue that computational irreducibility is likely to be pervasive and to impose strong limits on the potential for prediction in ecology.

Space can substitute for time in predicting climate-change effects on biodiversity

“…This adds to recent results showing that predictive ability through time decreased for spatial models of turnover as the magnitude of climate change increased (39). There are other good reasons to exercise caution when applying empirically calibrated models to project biodiversity responses to 21st century climate change, including the prospect of shifting realized niches and emergent species interactions, the challenge of extrapolating models to no-analog climates, and the overarching question of whether ecological systems are computationally irreducible (15,24,26,40). Nevertheless, this study complements studies that have focused on modeling changes in species richness (16,18) and adds support to the prospect of projecting impacts to biodiversity as a result of climate change.…”

Generality and Causal Interdependence in Ecology

“…The most commonly cited culprit for difficulties in ecological research, especially with respect to generality and predictability, is complexity (see Beckage et al 2011;Odenbaugh 2003;Mikkelson 2001). Ecological systems are made up of many interacting parts but we cannot capture all of the parts, properties and interactions between them in our experiments, nor represent all of them in our models.…”

“…Second, scientists in other fields that study complex systems, such as physics and chemistry, do not seem to face such extensive tradeoffs (Matthewson 2011). In fact, if we look more closely at the language in ecologists' complaints concerning the pursuit of generality, we will notice that ecological systems and the factors that operate within them are characterised as 'idiosyncratic' (Lawton 1999;Beckage et al 2011). That is, the factors that affect ecological systems are not just intertwined with many others, but they or their effects are sometimes peculiar and uncommon.…”

Scientific and Normative Foundations for the Valuation of Alien-Species Impacts: Thirteen Core Principles

“…and Ecosystem Services assessment on invasive alien species and their control), in the recent literature on biological invasions (e.g., Beckage et al 2011, Blackburn et al 2014, and in other global change phenomena (e.g., Gardiner 2011, Stern 2015b.…”