Effects of stochasticity on the length and behaviour of ecological transients

There is a growing recognition that ecological systems can spend extended periods of time far away from an asymptotic state, and that ecological understanding will therefore require a deeper appreciation for how long ecological transients arise. Recent work has defined classes of deterministic mechanisms that can lead to long transients. Given the ubiquity of stochasticity in ecological systems, a similar systematic treatment of transients that includes the influence of stochasticity is important. Stochasticity can of course promote the appearance of transient dynamics by preventing systems from settling permanently near their asymptotic state, but stochasticity also interacts with deterministic features to create qualitatively new dynamics. As such, stochasticity may shorten, extend or fundamentally change a system\u27s transient dynamics. Here, we describe a general framework that is developing for understanding the range of possible outcomes when random processes impact the dynamics of ecological systems over realistic time scales. We emphasize that we can understand the ways in which stochasticity can either extend or reduce the lifetime of transients by studying the interactions between the stochastic and deterministic processes present, and we summarize both the current state of knowledge and avenues for future advances

Transient phenomena in ecology

The importance of transient dynamics in ecological systems and in the models that describe them has become increasingly recognized. However, previous work has typically treated each instance of these dynamics separately. We review both empirical examples and model systems, and outline a classification of transient dynamics based on ideas and concepts from dynamical systems theory. This classification provides ways to understand the likelihood of transients for particular systems, and to guide investigations to determine the timing of sudden switches in dynamics and other characteristics of transients. Implications for both management and underlying ecological theories emerge

Using ecological niche theory to avoid uninformative biodiversity surrogates

Surrogates and indicators of biodiversity are used to infer the state and dynamics of species populations and ecosystems, as well as to inform conservation and management actions. Despite their widespread use, few studies have examined how ecological theory can guide the selection or surrogates and indicators, and thus reduce the likelihood of failure or cost of validation. We argue that ecological niche theory and knowledge of the extent to which particular limiting factors (e.g. physiological tolerances, limits to growth rates, or competitive exclusion) affect species distributions, abundance and coexistence could inform the choice of potential surrogates. Focusing on the environmental characteristics that define species niches makes it possible to identify situations where surrogates are likely to be ineffective, such as when there is no mechanistic basis for a candidate surrogate to be related to a biodiversity target. We describe two case studies where different candidate surrogate variables are shown to have contrasting potential as indicators of sustainable farming. Variables not mechanistically linked to the driver of change or responsive over appropriate timeframes or spatial scales are suggested a priori to be uninformative. The niche concept provides a framework for exploring ecological relationships that can inform the selection or exclusion of potential biodiversity surrogates. We think that this new approach to integrating ecological theory and application could lead to improved effectiveness of biodiversity monitoring and conservation.DBL was funded by an ARC Laureate Fellowship (LF120100108). MRW was supported in part by a grant from the US National Science Foundation (DEB-1546686)

The long-run behaviour of the terms of trade between primary commodities and manufactures : a panel data approach

This paper examines the Prebisch and Singer hypothesis using a panel of twenty-four commodity prices from 1900 to 2010. The modelling approach stems from the need to meet two key concerns: (i) the presence of cross-sectional dependence among commodity prices; and (ii) the identification of potential structural breaks. To address these concerns, the Hadri and Rao (Oxf Bull Econ Stat 70:245–269, 2008) test is employed. The findings suggest that all commodity prices exhibit a structural break whose location differs across series, and that support for the Prebisch and Singer hypothesis is mixed. Once the breaks are removed from the underlying series, the persistence of commodity price shocks is shorter than that obtained in other studies using alternative methodologies.info:eu-repo/semantics/publishedVersio

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

SGH

Colony forming units of e.coli and total in various treatments. Rows 1-6 used for analysis, remaining rows are additional informatio