The Future of Predictive Ecology

Abstract

Prediction is an important aspect of scientific practice, because it helps us to confirm theories and effectively intervene on the systems we are investigating. In ecology, prediction is a controversial topic: even though the number of papers focusing on prediction is constantly increasing, many ecologists believe that the quality of ecological predictions is unacceptably low, in the sense that they are not sufficiently accurate sufficiently often. Moreover, ecologists disagree on how predictions can be improved. On one side are the ‘theory-driven’ ecologists, those who believe that ecology lacks a sufficiently strong theoretical framework. For them, more general theories will yield more accurate predictions. On the other are the ‘applied’ ecologists, whose research is focused on effective interventions on ecological systems. For them, deeper knowledge of the system in question is more important than background theory. The aim of this paper is to provide a philosophical examination of both sides of the debate: as there are strengths and weaknesses in both approaches to prediction, a pluralistic approach is best for the future of predictive ecology.

Systematic bias in studies of consumer functional responses

“…Most functional‐response studies have been justified by a generic desire to better describe and understand the functional form of consumer feeding rates to better predict population dynamics. Old and rejuvenated literatures on the varied and overlapping meanings of description, understanding and prediction in ecology showcase the many ways in which this expressed desire is too simplistic (Levins, 1966; Odenbaugh, 2005; Doak et al ., 2008; Shmueli, 2010; Evans et al ., 2013; Maris et al ., 2018; Elliott‐Graves, 2019; Pennekamp et al ., 2019). Although a synthesis of these terms for ecology is far from complete, pertinent highlights of the literature include evidence that simple, non‐mechanistic population models can often better forecast population dynamics than even the models with which the dynamics were simulated in the first place (Perretti et al ., 2013); that parameter estimates need not all be well‐constrained to make accurate predictions in complex systems (Gutenkunst et al ., 2007); that consumers may often experience a small enough range in prey population sizes that their functional responses are effectively linear under field conditions (Novak, 2010; Preston et al ., 2018); and that functional nonlinearities important to describing variation at some spatial, temporal or biological scales need not be important – or indeed logical – at other scales (Chesson, 2009; Morozov and Petrovskii, 2013).…”

Systematic bias in studies of consumer functional responses

“…Most functional-response studies have been justified by a generic desire to better describe and understand the functional form of consumer feeding rates to better predict population dynamics. Old and rejuvenated literatures on the varied and overlapping meanings of description, understanding, and prediction in ecology show-case the many ways in which this expressed desire is too simplistic (Doak et al , 2008; Elliott-Graves, 2019; Evans et al , 2013; Levins, 1966; Maris et al , 2018; Odenbaugh, 2005; Pennekamp et al , 2019; Shmueli, 2010). Although a synthesis of these terms for ecology is far from complete, pertinent highlights of the literature include evidence that simple, non-mechanistic population models can often better forecast population dynamics than even the models with which the dynamics were simulated in the first place (Perretti et al , 2013); that parameter estimates need not all be well-constrained to make accurate predictions in complex systems (Gutenkunst et al , 2007); that consumers may often experience a small enough range in prey population sizes that their functional responses are effectively linear under field conditions (Novak, 2010; Preston et al , 2018); and that functional nonlinearities important to describing variation at some spatial, temporal, or biological scales need not be important – or indeed logical – at other scales (Chesson, 2009; Morozov & Petrovskii, 2013).…”

Reflexivity and fragility

“…In the upper-right corner, there is fragility but not reflexivity. Consider invasive species, as reported by Alkistis Elliott-Graves ( 2016 , see also 2018 , 2019 ). The relevant kinds here are things like tree species, soil nutrients, islands, and lakes.…”