Predictive systems ecology

Abstract

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Trophodynamics as a Tool for Understanding Coral Reef Ecosystems

“…While some scientists have urged that more process-based ecological models be developed to identify the underlying mechanistic behavior of an ecosystem (Evans et al, 2013;Turney and Buddle, 2016), recent articles still often ignore dynamics of spatial and temporal variability as well as historical baselines (Lamy et al, 2016). Some authors have moved past dynamic models such as Ecopath and explored individual-based predator-prey population models to account for spatiotemporal heterogeneity (Thierry et al, 2015).…”

“…For Ecopath to be effective, thermodynamics and ecological knowledge behind fitting a model are required to prevent misuse (Evans et al, 2013;Young et al, 2015). Thirty-nine percent of reviewed Ecopath studies ( Table 2) for coral reefs used Fishbase (Froese and Pauly, 2000) as a source of data for the model.…”

“…Due to the complexities of marine food webs, trophic relationships are often used to categorize interactions between trophic levels and among individuals within models (Bozec et al, 2005). While linear models often show patterns in specific relationships from quantitative study, they are not robust enough to handle complex food webs such as those on coral reefs (Evans et al, 2013). Dynamic models are required to describe ecosystem organization through networks of species that interact (Liu et al, 2009).…”

The importance and adaptive value of life history evolution for metapopulation dynamics

“…These approaches rely either on experimental manipulations of evolvability [28][29][30] or statistical partitioning based on price and breeder equations or the use of Integral Projection Matrices [31-34] in time series. An alternative, largely unexplored to date, is the use of a systems approach to forecast patterns at higher metapopulation order from lower-order individual variation in life history traits [35,36]. Because metapopulation dynamics are by definition determined by processes at lower individual hierarchy, individual-based models seem highly appropriate to perform in silico experiments in systems where sound in vivo experiments are impossible to conduct at the required detail and replication.…”

Editorial

“…reviews that have appeared during 2013 include those by Evans et al [3] discussing the potential of predictive systems ecology to assess how ecosystems will respond to rapid environmental change and by Viney & Reece [4] discussing whether noise in gene expression, traditionally seen as maladaptive, may in fact be evolutionarily helpful. This year's excellent contribution from the Canadian Society for Ecology and Evolution was by Spencer C. H. Barrett regarding the evolution of plant reproductive systems [5].…”