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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.

Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Understanding the consequences of environmental change on ecological and evolutionary dynamics is inherently problematic because of the complex interplay between them. Using invertebrates in microcosms, we characterise phenotypic, population and evolutionary dynamics before, during and after exposure to a novel environment and harvesting over 20 generations. We demonstrate an evolved change in life-history traits (the age- and size-at-maturity, and survival to maturity) in response to selection caused by environmental change (wild to laboratory) and to harvesting (juvenile or adult). Life-history evolution, which drives changes in population growth rate and thus population dynamics, includes an increase in age-to-maturity of 76% (from 12.5 to 22 days) in the unharvested populations as they adapt to the new environment. Evolutionary responses to harvesting are outweighed by the response to environmental change (~ 1.4 vs. 4% change in age-at-maturity per generation). The adaptive response to environmental change converts a negative population growth trajectory into a positive one: an example of evolutionary rescue. [ABSTRACT FROM AUTHOR]

1. Dispersal of individuals between habitat patches depends on both the propensity to emigrate from a patch and the ability to survive inter-patch movement. Environmental factors and individual characteristics have been shown to influence dispersal rates but separating the effects of emigration and dispersal mortality on dispersal can often be difficult. In this study, we use a soil mite laboratory system to investigate factors affecting emigration and dispersal mortality. 2. We tested the movement of different age groups in two-patch systems with different inter-patch distances. Differences in immigration among age groups were primarily driven by differences in emigration but dispersal mortality was greater for some groups. Immigration declined with increasing inter-patch distance, which was due to increasing dispersal mortality and decreasing emigration. 3. In a second experiment, we compared the dispersal of recently matured males and females and tested the impact of food availability during the developmental period on their dispersal. Dispersal was found to be male biased but there was no significant sex bias in dispersal mortality. There was some evidence that food availability could affect emigration and dispersal mortality. 4. These results demonstrate that both emigration and dispersal mortality can be affected by factors such as individual age and resource availability. Understanding these effects is likely to be important for predicting the fitness costs and population consequences of dispersal. [ABSTRACT FROM AUTHOR]

Intergenerational effects arise when parents' actions influence the reproduction and survival of their offspring and possibly later descendants. Models suggest that intergenerational effects have important implications for both population dynamical patterns and the evolution of life-history traits. However, these will depend on the nature and duration of intergenerational effects. Here we show that manipulating parental food environments of soil mites produced intergenerational effects that were still detectable in the life histories of descendents three generations later. Intergenerational effects varied in different environments and from one generation to the next. In low-food environments, variation in egg size altered a trade-off between age and size at maturity and had little effect on the size of eggs produced in subsequent generations. Consequently, intergenerational effects decreased over time. In contrast, in high-food environments, variation in egg size predominantly influenced a tradeoff between fecundity and adult survival and generated increasing variation in egg size. As a result, the persistence and significance of intergenerational effects varied between high- and low-food environments. Context-dependent intergenerational effects can therefore have complex but important effects on population dynamics. [ABSTRACT FROM AUTHOR]

Knowledge of the ecological and evolutionary causes of dispersal can be crucial in understanding the behaviour of spatially structured populations, and predicting how species respond to environmental change. Despite the focus of much theoretical research, simplistic assumptions regarding the dispersal process are still made. Dispersal is usually regarded as an unconditional process although in many cases fitness gains of dispersal are dependent on environmental factors and individual state. Condition-dependent dispersal strategies will often be superior to unconditional, fixed strategies. In addition, dispersal is often collapsed into a single parameter, despite it being a process composed of three interdependent stages: emigration, inter-patch movement and immigration, each of which may display different condition dependencies. Empirical studies have investigated correlates of these stages, emigration in particular, providing evidence for the prevalence of conditional dispersal strategies. Ill-defined use of the term 'dispersal', for movement across many different spatial scales, further hinders making general conclusions and relating movement correlates to consequences at the population level. Logistical difficulties preclude a detailed study of dispersal for many species, however incorporating unrealistic dispersal assumptions in spatial population models may yield inaccurate and costly predictions. Further studies are necessary to explore the importance of incorporating specific condition-dependent dispersal strategies for evolutionary and population dynamic predictions. [ABSTRACT FROM AUTHOR]

Evidence from wildlife and human populations indicates that conditions during early development can have marked effects on the subsequent performance of individuals and cohorts. Likewise, the effects of maternal and, more generally, parental environments can be transferred among individuals between generations. These delayed life-history effects are found consistently and suggestions have been made that they can be one source of both variability and of delayed density dependence in population dynamics. Assessments of several different time series indicate that population variability and delayed density dependence are common and that understanding the mechanisms giving rise to them is crucial for the interpretation and application of such models to basic and applied research. Therefore, it is necessary to assess the different ways in which history in the life history might give rise to variability and delayed density dependence in population dynamics. Here, we build on recent appraisals of the pervasive influence of past environmental conditions on current and future fitness and link the details of these life-history studies to classic features of population dynamics. [Copyright &y& Elsevier]

The article talks about a simple risk-assessment model focused on the prediction and analysis of the effects of environmental change on farmland biodiversity. The biological mechanisms connecting the changing environment to the changing population size and the focus of conservation biology on the management of biodiversity in an agricultural setting are discussed. The article also talks about the study conducted by S. J. Butler and his colleagues which evaluated how farmland birds respond to changes in the farmed environment.

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. [ABSTRACT FROM AUTHOR]