From theory to experiments for testing the proximate mechanisms of mast seeding: an agenda for an experimental ecology

Highly variable and synchronised production of seeds by plant populations, known as masting, is implicated in many important ecological processes, but how it arises remains poorly understood. The lack of experimental studies prevents underlying mechanisms from being explicitly tested, and thereby precludes meaningful predictions on the consequences of changing environments for plant reproductive patterns and global vegetation dynamics. Here we review the most relevant proximate drivers of masting and outline a research agenda that takes the biology of masting from a largely observational field of ecology to one rooted in mechanistic understanding. We divide the experimental framework into three main processes: resource dynamics, pollen limitation and genetic and hormonal regulation, and illustrate how specific predictions about proximate mechanisms can be tested, highlighting the few successful experiments as examples. We envision that the experiments we outline will deliver new insights into how and why masting patterns might respond to a changing environment.     

Human‐aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human‐aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human‐aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture‐induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under‐investigated examples of how the effects of short‐term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well‐studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.     

Describing and understanding behavioral responses to multiple stressors and multiple stimuli

Understanding the effects of environmental change on natural ecosystems is a major challenge, particularly when multiple stressors interact to produce unexpected “ecological surprises” in the form of complex, nonadditive effects that can amplify or reduce their individual effects. Animals often respond behaviorally to environmental change, and multiple stressors can have both population‐level and community‐level effects. However, the individual, not combined, effects of stressors on animal behavior are commonly studied. There is a need to understand how animals respond to the more complex combinations of stressors that occur in nature, which requires a systematic and rigorous approach to quantify the various potential behavioral responses to the independent and interactive effects of stressors. We illustrate a robust, systematic approach for understanding behavioral responses to multiple stressors based on integrating schemes used to quantitatively classify interactions in multiple‐stressor research and to qualitatively view interactions between multiple stimuli in behavioral experiments. We introduce and unify the two frameworks, highlighting their conceptual and methodological similarities, and use four case studies to demonstrate how this unification could improve our interpretation of interactions in behavioral experiments and guide efforts to manage the effects of multiple stressors. Our unified approach: (1) provides behavioral ecologists with a more rigorous and systematic way to quantify how animals respond to interactions between multiple stimuli, an important theoretical advance, (2) helps us better understand how animals behave when they encounter multiple, potentially interacting stressors, and (3) contributes more generally to the understanding of “ecological surprises” in multiple stressors research.     

Defining and measuring ecological specialization

1.  Ecological specialization is one of the main concepts in ecology and conservation. However, this concept has become highly context-dependent and is now obscured by the great variability of existing definitions and methods used to characterize ecological specialization.
2.  In this study, we clarify this concept by reviewing the strengths and limitations of different approaches commonly used to define and measure ecological specialization. We first show that ecological specialization can either be considered as reflecting species' requirements or species' impacts. We then explain how specialization depends on species-specific characteristics and on local and contingent environmental constraints. We further show why and how ecological specialization should be scaled across spatial and temporal scales, and from individuals to communities.
3.  We then illustrate how this review can be used as a practical toolbox to classify widely used metrics of ecological specialization in applied ecology, depending on the question being addressed, the method used, and the data available.
4.   Synthesis and applications . Clarifying ecological specialization is useful to make explicit connections between several fields of ecology using the niche concept. Defining this concept and its practical metrics is also a crucial step to better formulate predictions of scientific interest in ecology and conservation. Finally, understanding the different facets of ecological specialization should facilitate to investigate the causes and consequences of biotic homogenization and to derive relevant indicators of biodiversity responses to land-use changes.     

Function-valued adaptive dynamics and the calculus of variations

Adaptive dynamics has been widely used to study the evolution of scalar-valued, and occasionally vector-valued, strategies in ecologically realistic models. In many ecological situations, however, evolving strategies are best described as function-valued, and thus infinite-dimensional, traits. So far, such evolution has only been studied sporadically, mostly based on quantitative genetics models with limited ecological realism. In this article we show how to apply the calculus of variations to find evolutionarily singular strategies of function-valued adaptive dynamics: such a strategy has to satisfy Euler's equation with environmental feedback. We also demonstrate how second-order derivatives can be used to investigate whether or not a function-valued singular strategy is evolutionarily stable. We illustrate our approach by presenting several worked examples.     

Using prior information to build probabilistic invasive species risk assessments

Understanding why some introduced species become naturalized and invasive whereas others do not is a major focus of invasion ecology. Invasive species risk assessments address this same question, but are not typically based on the results from recent ecological studies. Applying results from the ecological literature to risk assessment is difficult, in part because there are no general explanations of invasion likelihood across taxa. Most ecological studies are also specific to a particular region and it is unclear whether outcomes in one region will necessarily apply to another. Here we show how a hierarchical Bayesian statistical framework can make better use of ecological studies for applied risk assessments. We focus on three key opportunities afforded by these models: (1) the ability to leverage information from one region to form prior expectations for other regions about which little is known, (2) the ability to quantify uncertainty of predictions, and (3) flexibility to incorporate within-group heterogeneities in probabilities of naturalization. We illustrate these principles using a case study where we predict the probability of plant taxa naturalizing in New Zealand and Australia, showing how prior information can be particularly valuable when data are limited. As more studies document invasion patterns around the world, a framework that can formally incorporate prior information will help link the accumulating data on species introductions to risk assessments.     

Nutritional ecology beyond the individual: a conceptual framework for integrating nutrition and social interactions

Over recent years, modelling approaches from nutritional ecology (known as Nutritional Geometry) have been increasingly used to describe how animals and some other organisms select foods and eat them in appropriate amounts in order to maintain a balanced nutritional state maximising fitness. These nutritional strategies profoundly affect the physiology, behaviour and performance of individuals, which in turn impact their social interactions within groups and societies. Here, we present a conceptual framework to study the role of nutrition as a major ecological factor influencing the development and maintenance of social life. We first illustrate some of the mechanisms by which nutritional differences among individuals mediate social interactions in a broad range of species and ecological contexts. We then explain how studying individual‐ and collective‐level nutrition in a common conceptual framework derived from Nutritional Geometry can bring new fundamental insights into the mechanisms and evolution of social interactions, using a combination of simulation models and manipulative experiments.     

Applications of stable isotope analyses to avian ecology

In the past 20 years the use of stable isotope analysis has become increasingly common in ecological studies. In fact, in some instances these techniques have yielded remarkable insights into the foraging preferences and migrations of birds. Despite these advances and the potential of the approach, it is possibly still not as widely used as might be expected. In this paper we aim to illustrate the potential of the approach in the hope of encouraging more avian ecologists to think again about how these techniques might provide insights in the systems on which they work. We discuss some of the principles behind the approach, and review some of the more recent ornithological studies that have used stable isotope techniques to trace trophic pathways or infer migratory origins. We follow this by discussing some of the latest ideas on how stable isotopes may be used to generate community metrics and close by detailing the important assumptions and caveats that should be considered before undertaking any studies using this technique.     

Framework to improve the application of theory in ecology and conservation

Ecological theory often fails applied ecologists in three ways: (1) Theory has little predictive value but is nevertheless applied in conservation with a risk of perverse outcomes, (2) individual theories have limited heuristic value for planning and framing research because they are narrowly focused, and (3) theory can lead to poor communication among scientists and hinder scientific progress through inconsistent use of terms and widespread redundancy. New approaches are therefore needed that improve the distillation, communication, and application of ecological theory. We advocate three approaches to resolve these problems: (1) improve prediction by reviewing theory across case studies to develop contingent theory where possible, (2) plan new research using a checklist of phenomena to avoid the narrow heuristic value of individual theories, and (3) improve communication among scientists by rationalizing theory associated with particular phenomena to purge redundancy and by developing definitions for key terms. We explored the extent to which these problems and solutions have been featured in two case studies of long-term ecological research programs in forests and plantations of southeastern Australia. We found that our main contentions were supported regarding the prediction, planning, and communication limitations of ecological theory. We illustrate how inappropriate application of theory can be overcome or avoided by investment in boundary-spanning actions. The case studies also demonstrate how some of our proposed solutions could work, particularly the use of theory in secondary case studies after developing primary case studies without theory. When properly coordinated and implemented through a widely agreed upon and broadly respected international collaboration, the framework that we present will help to speed the progress of ecological research and lead to better conservation decisions.     

Network spandrels reflect ecological assembly

Ecological networks that exhibit stable dynamics should theoretically persist longer than those that fluctuate wildly. Thus, network structures which are over‐represented in natural systems are often hypothesised to be either a cause or consequence of ecological stability. Rarely considered, however, is that these network structures can also be by‐products of the processes that determine how new species attempt to join the community. Using a simulation approach in tandem with key results from random matrix theory, we illustrate how historical assembly mechanisms alter the structure of ecological networks. We demonstrate that different community assembly scenarios can lead to the emergence of structures that are often interpreted as evidence of ‘selection for stability’. However, by controlling for the underlying selection pressures, we show that these assembly artefacts—or spandrels—are completely unrelated to stability or selection, and are instead by‐products of how new species are introduced into the system. We propose that these network‐assembly spandrels are critically overlooked aspects of network theory and stability analysis, and we illustrate how a failure to adequately account for historical assembly can lead to incorrect inference about the causes and consequences of ecological stability.     

Design of a binary biomarker study from the results of a pilot study

Biomarkers are increasingly used in clinical and epidemiologic studies. Prior to these studies, small pilot studies are often conducted to assess the reproducibility of the biomarker. This article discusses how the results of a pilot study can be used to design subsequent studies when the biomarker is a binary assessment. We consider situations in which the pilot study has two factors (e.g., laboratory and individual) that are either crossed or nested. We discuss how binary random-effects models can be used for estimating the sources of variation and how parameter estimates from these models can be used to appropriately design future studies. We also show that fitting a linear variance components model that ignores the binary nature of the data is a simple alternative method that results in nearly unbiased and moderately efficient estimators of important design parameters. We illustrate the methodology with data from a study assessing the reproducibility of p53 immunohistochemistry in bladder tumors.     

The method of synthesis in ecology

Synthesis of results from different investigations is an important activity for ecologists but when compared with analysis the method of synthesis has received little attention. Ecologists usually proceed intuitively and this can lead to a problem in defining differences between the syntheses made by different scientists. It also leads to criticism from scientists favoring analytical approaches that the construction of general theory is an activity that does not follow the scientific method. We outline a methodology for scientific inference about integrative concepts and the syntheses made in constructing them and illustrate how this can be applied in the development of general theory from investigations into particular ecological systems. The objective is to construct a causal scientific explanation. This has four characteristics. (1) It defines causal and/or organizational processes that describe how systems function. (2) These processes are consistent – under the same conditions they will produce the same effect. (3) A causal scientific explanation provides general information about events of a similar kind. (4) When experiments are possible then a designed manipulation will produce a predictable response. The essential characteristic of making synthesis to construct a causal scientific explanation is that it is progressive and we judge progress made by assessing the coherence of the explanation using six criteria: acceptability of individual propositions including that they have been tested with data, consistency of concept definitions, consistency in the type of concepts used in making the explanation, that ad hoc propositions are not used, that there is economy in the number of propositions used, that the explanation applies to broad questions. We illustrate development of a causal scientific explanation for the concept of long-lived pioneer tree species, show how the coherence of this explanation can be assessed, and how it could be improved.     

When mechanism matters: Bayesian forecasting using models of ecological diffusion

Ecological diffusion is a theory that can be used to understand and forecast spatio‐temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white‐tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression‐based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.     

Direct and indirect ecosystem effects of evolutionary adaptation in the Trinidadian guppy (Poecilia reticulata)

Ecological and evolutionary processes may interact on the same timescale, but we are just beginning to understand how. Several studies have examined the net effects of adaptive evolution on ecosystem properties. However, we do not know whether these effects are confined to direct interactions or whether they propagate further through indirect ecological pathways. Even less well understood is how the combination of direct and indirect ecological effects of the phenotype promotes or inhibits evolutionary change. We coupled mesocosm experiments and ecosystem modeling to evaluate the ecological effects of local adaptation in Trinidadian guppies (Poecilia reticulata). The experiments show that guppies adapted to life with and without predators alter the ecosystem directly through differences in diet. The ecosystem model reveals that the small total indirect effect of the phenotype observed in the experiments is likely a combination of several large indirect effects that act in opposing directions. The model further suggests that these indirect effects can reverse the direction of selection that direct effects alone exert back on phenotypic variation. We conclude that phenotypic divergence can have major effects deep in the web of indirect ecological interactions and that even small total indirect effects can radically change the dynamics of adaptation.     

Genetic Analysis of Macromolecular Transport across the Nuclear Envelope

Numerous factors that promote movement of macromolecules in and out of the nucleus have now been identified. These include both soluble cytoplasmic and nucleoplasmic proteins and proteins of the nuclear pore complex (NPC). Genetic analyses of the nuclear transport process in the model organism, the budding yeastSaccharomyces cerevisiae,have revealed remarkable conservation of all of these factors. In addition, important clues as to how these factors promote the unique bidirectional movement across the NPC have emerged from studies of yeast. We summarize the characterization and genetic interactions of the soluble transport factors and present data to illustrate how genetic experiments can be used to further define the import and export pathways.     

The ecological forecast horizon,and examples of its uses and determinants

Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.     

Means and extremes: building variability into community‐level climate change experiments

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of ‘generations’ based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new ‘generation’ of climate change experiments using down‐scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments.     

Toward an integration of evolutionary biology and ecosystem science

At present, the disciplines of evolutionary biology and ecosystem science are weakly integrated. As a result, we have a poor understanding of how the ecological and evolutionary processes that create, maintain, and change biological diversity affect the flux of energy and materials in global biogeochemical cycles. The goal of this article was to review several research fields at the interfaces between ecosystem science, community ecology and evolutionary biology, and suggest new ways to integrate evolutionary biology and ecosystem science. In particular, we focus on how phenotypic evolution by natural selection can influence ecosystem functions by affecting processes at the environmental, population and community scale of ecosystem organization. We develop an eco-evolutionary model to illustrate linkages between evolutionary change (e.g. phenotypic evolution of producer), ecological interactions (e.g. consumer grazing) and ecosystem processes (e.g. nutrient cycling). We conclude by proposing experiments to test the ecosystem consequences of evolutionary changes.     

Direct experimental evidence for alternative stable states: a review

A large number of studies have presented empirical arguments for the existence of alternative stable states (ASS) in a wide range of ecological systems. However, most of these studies have used non-manipulative, indirect methods, which findings remain open for alternative explanations. Here, we review the direct evidence for ASS resulting from manipulation experiments. We distinguish four conclusive experimental approaches which test for predictions made by the hysteresis effect: (1) discontinuity in the response to an environmental driving parameter, (2) lack of recovery potential after a perturbation, (3) divergence due to different initial conditions and (4) random divergence. Based on an extensive literature search we found 35 corresponding experiments. We assessed the ecological stability of the reported contrasting states using the minimum turnover of individuals in terms of life span and classified the studies according to 4 categories: (1) experimental system, (2) habitat type, (3) involved organisms and (4) theoretical framework. 13 experiments have directly demonstrated the existence of alternative stable states while 8 showed the absence of ASS in other cases. 14 experiments did not fulfil the requirements of a conclusive test, mostly because they applied a too short time scale. We found a bias towards laboratory experiments compared to field experiments in demonstrating bistability. There was no clear pattern of the distribution of ASS over categories. The absence of ASS in 38% of the tested systems indicates that ASS are just one possibility of how ecological systems can behave. The relevance of the concept of ASS for natural systems is discussed, in particular under consideration of the observed laboratory bias, perturbation frequency and variable environments. It is argued, that even for a permanently transient system, alternative attractors may still be of relevance.