How to approach the study of syndromes in macroevolution and ecology

Syndromes, wherein multiple traits evolve convergently in response to a shared selective driver, form a central concept in ecology and evolution. Recent work has questioned the existence of some classic syndromes, such as pollination and seed dispersal syndromes. Here, we discuss some of the major issues that have afflicted research into syndromes in macroevolution and ecology. First, correlated evolution of traits and hypothesized selective drivers is often relied on as the only evidence for adaptation of those traits to those hypothesized drivers, without supporting evidence. Second, the selective driver is often inferred from a combination of traits without explicit testing. Third, researchers often measure traits that are easy for humans to observe rather than measuring traits that are suited to testing the hypothesis of adaptation. Finally, species are often chosen for study because of their striking phenotypes, which leads to the illusion of syndromes and divergence. We argue that these issues can be avoided by combining studies of trait variation across entire clades or communities with explicit tests of adaptive hypotheses and that taking this approach will lead to a better understanding of syndrome‐like evolution and its drivers.     

The enemy release hypothesis as a hierarchy of hypotheses

In ecology, a hypothesis is usually not discarded if a few studies reject it, as long as there are other studies supporting it. How to assess the usefulness of ecological hypotheses is therefore not straightforward. Using the enemy release hypothesis as an example, we show how creating a hierarchy of hypotheses (HoH) can help reviewing and evaluating evidence for and against an ecological hypothesis. In a HoH, a broad, overarching hypothesis branches into more specific and better testable sub‐hypotheses. The enemy release hypothesis is a major hypothesis in invasion ecology and posits that the absence of enemies in the exotic range of an alien species is a cause of its invasion success. Based on a systematic review of empirical tests of this hypothesis, we divided it into sub‐hypotheses, differentiating among 1) indicators for enemy release, 2) types of comparisons, and 3) types of enemies. We identified 176 empirical tests and weighted each test according to the number of alien species studied and the research method (experimental vs observational, field vs enclosure vs laboratory). For the broadly formulated enemy release hypothesis, we found nearly as much supporting (36%) as questioning evidence (43%). At the sub‐hypotheses level, however, we found that some sub‐hypotheses are strongly supported by empirical evidence, whereas others receive hardly any support. These differences are further emphasized for some types of habitat and focal taxonomic groups. Our findings suggest that several specific formulations (i.e. sub‐hypotheses) of the broad enemy release hypothesis are useful, whereas other formulations should be viewed more critically. In general, the approach outlined here can help evaluate major ecological hypotheses and their specific sub‐hypotheses. Our study also highlights the need for a scientific debate on how much supporting evidence is sufficient to consider an ecological hypothesis to be useful.     

Masting,mixtures and modes: are two models better than one?

A key hypothesis in population ecology is that synchronous and intermittent seed production, known as mast seeding, is driven by the alternating allocation of carbohydrates and mineral nutrients between growth and reproduction in different years, i.e. ‘resource switching’. Such behaviour may ultimately generate bimodal distributions of long‐term flower and seed production, and evidence of these patterns has been taken to support the resource switching hypothesis. Here, we show how a widely‐used statistical test of bimodality applied by many studies in different ecological contexts may fail to reject the null hypothesis that focal probability distributions are unimodal. Using data from five tussock grass species in South Island, New Zealand, we find clear evidence of bimodality only when flowering patterns are analyzed with probabilistic mixture models. Mixture models provide a theory oriented framework for testing hypotheses of mast seeding patterns, enabling the different responses underlying medium‐ and high‐ versus non‐ and low‐flowering years to be modelled more realistically by associating these with distinct probability distributions. Coupling theoretical expectations with more rigorous statistical approaches will empower ecologists to reject null hypotheses more often.     

Can plants use entomopathogens as bodyguards?

For 20 years, ecologists have been gathering evidence in support of the hypothesis that plants can use insect natural enemies such as predators and parasitoids as bodyguards to protect themselves from herbivory, but entomopathogens have escaped this consideration. We extend the bodyguard hypothesis to ask whether plants can use entomopathogens as bodyguards. We first discuss the evolutionary context of such tritrophic interactions and then categorize possible mechanisms as: (1) maintaining a population of bodyguards on the plant surface, (2) increasing contact rates between insect host and pathogen and (3) increasing the susceptibility of the host. We explore these mechanisms further, examining published studies for evidence for the hypothesis. We then discuss potential costs to the plant of promoting pathogens as bodyguards which may include a reduction in the efficiency of other "bodyguard" species, the incidental promotion of plant pathogens and the risk of entomopathogens developing phytopathogenicity. Aside from our intention to stimulate the testing of the bodyguard hypothesis with entompathogens and to provide a conceptual framework for this, we hope to bring evolutionary ecology and insect pathology closer together.     

Information forgotten or overlooked: fundamental flaws in the conventional view of the living cell.

Old ideas often persist long after sound evidence dictates otherwise. I attempt to report one such case in the life sciences, by pointing out what are perceived to be fundamental flaws or questions in conventional wisdom. It is my experience that much evidence not in support of the well accepted membrane pump view of the living cell has been overlooked, forgotten or even ignored. In presenting this idea, the evolution of our knowledge from the establishment of cellular and protoplasmic theory to the emergence of solution theory is presented. The universal hypothesis based on physical chemical principles is presented, followed by the advent of the membrane-situated energy-requiring pump. The experimental demonstration of an inadequate energy supply for the first pump is discussed, followed by a review of new evidence that calls to question the use of dilute solution theory in describing adequately cellular function. Finally, roles for cellular water are suggested to explain the cellular exclusion of sodium and to serve as a barometer for the healthy state. Within the context of a metaphor, I attempt to qualitatively embrace the physical findings. It is concluded that the mobility of water molecules may be considered to change with the progression of normal tissue to a state of disease. These changes in the mobility of water molecules are "fingerprinted" by changes in the molecular motion of the solids.     

From interesting details to dynamical relevance: toward more effective use of empirical insights in theory construction

A perennial challenge in ecology is to develop dynamical systems models that appropriately abstract and characterize the dynamics of natural systems. Deriving an appropriate model of system dynamics can be a long and iterative process whose outcome depends critically on the quality of empirical data describing the long‐term behavior of a natural system. Most ecological time series are insufficient to offer insight into the way organizational hierarchies and spatial scales are causally linked to natural system dynamics. Moreover, the classic tradition of hypothesis testing in ecology is not likely to lead to those key insights. This because empirical research is geared almost exclusively toward testing model predictions based on underlying causal relationships assumed by theorists. So, empirical research relies heavily on theory for guidance on what is or is not dynamically relevant. I argue here that it is entirely possible to reduce much of this guesswork involved with deciding on causal structure by giving empirical research a new role in theory development. In this role, natural history and field observations are used to develop stochastic, individual‐based and spatially explicit computational models or IBMs that can explore the range of contingency and complexity inherent in real‐world systems.
IBMs can be used to run simulations allowing deductions to be made about the causal linkages between organizational hierarchies, spatial scales, and dynamics. These deductions can be tested under field conditions using experiments that manipulate the putative causal structure and evaluate the dynamical consequences. The emerging insights from this stage can then be used to inspire an analytical construct that embodies the dynamically relevant scales and mechanisms. In essence, computational modeling serves as an intermediate step in theory development in that a wide range of possibly important biological details are considered and then reduced to a subset that is dynamically relevant.     

The causes of species richness patterns across space, time, and clades and the role of "ecological limits"

A major goal of research in ecology and evolution is to explain why species richness varies across habitats, regions, and clades. Recent reviews have argued that species richness patterns among regions and clades may be explained by "ecological limits" on diversity over time, which are said to offer an alternative explanation to those invoking speciation and extinction (diversification) and time. Further, it has been proposed that this hypothesis is best supported by failure to find a positive relationship between time (e.g., clade age) and species richness. Here, I critically review the evidence for these claims, and propose how we might better study the ecological and evolutionary origins of species richness patterns. In fact, ecological limits can only influence species richness in clades by influencing speciation and extinction, and so this new "alternative paradigm" is simply one facet of the traditional idea that ecology influences diversification. The only direct evidence for strict ecological limits on richness (i.e., constant diversity over time) is from the fossil record, but many studies cited as supporting this pattern do not, and there is evidence for increasing richness over time. Negative evidence for a relationship between clade age and richness among extant clades is not positive evidence for constant diversity over time, and many recent analyses finding no age-diversity relationship were biased to reach this conclusion. More comprehensive analyses strongly support a positive age-richness relationship. There is abundant evidence that both time and ecological influences on diversification rates are important drivers of both large-scale and small-scale species richness patterns. The major challenge for future studies is to understand the ecological and evolutionary mechanisms underpinning the relationships between time, dispersal, diversification, and species richness patterns.     

Zooplankton research: the contribution of limnology to general ecological paradigms

Biotic interactions and density dependent processes are particularly important in the pelagic zone of a lake. Plankton has numerous properties (e.g., short life cycles, size structure) that makes them suitable objects for testing hypotheses and developing concepts relevant for general ecology. Zooplankton being in the center of aquatic food webs and influenced strongly by both bottom-up and top-down processes have often been used as models for ecological paradigms. The trophic-dynamic concept, the theory of population dynamics, and the analysis of predator-prey relationships are examples of successful contributions of zooplankton research. In recent years, zooplankton research has developed new ideas in community, population and evolutionary ecology. This is illustrated by studies on mechanisms of seasonal succession, competition and phenotypic plasticity. The new concept of physiological ecology is explained with copepod diapause behaviour. The blending of ideas from ecology and evolutionary genetics, which is undergoing a rapid development of new tools, will create new paradigms in the future, and zooplankton research will play an important part in this process.     

Validation of null model tests using Neyman–Pearson hypothesis testing theory

A long-standing question in ecology is whether interspecific competition affects co-occurrence patterns of species. Null model tests of presence–absence data (NMTPAs) constitute an important approach to address the question, but different tests often give conflicting results when applied to the same data. Neyman–Pearson hypothesis testing theory provides a rigorous and well accepted framework for assessing the validity and optimality of statistical tests. Here, I treat NMTPAs within this framework, and measure the robustness and bias of 72 representative tests. My results indicate that, when restrictive assumptions are met, existing NMTPAs are adequate, but for general testing situations, the use of all existing NMTPAs is unjustified — the tests are nonrobust or biased. For many current applications of NMTPAs, restrictive assumptions appear unmet, so these results illustrate an area in which existing NMTPAs can be improved. In addition to highlighting useful improvements to existing NMTPAs, the results here provide a rigorous framework for developing improved methods.     

Landscape ecology development supported by geospatial technologies: A review

Numerous technologies have contributed to the recent development of landscape ecology, especially the geospatial technological advances constitute a revolution in landscape ecology. Extensive applications of geospatial technologies, such as fractal theory, geographic information systems (GIS) and remote sensing (RS) in landscape ecology research, suggest the necessity of such a review of research progress in this field. In this study, a brief introduction to fractal theory, GIS and RS and how they were applied in landscape ecology were provided first. Then, the current state-of-the-art was summarized and analyzed as reference for further promoting the development of landscape ecology science and its applications. Finally, opportunities and challenges of landscape ecology applications using these new technologies were discussed and concluded for future research. It was contended that a combination and integration of these technologies can substantially advance the study of landscape ecology for data acquisition, process modeling, scale transformation, result analysis and visualization. However, as no theoretical framework and application cases of applying an integration of fractal theory, GIS and RS techniques to landscape ecology research have been established, further studies are still much needed.     

Postglacial colonization of Ireland by mustelids, with particular reference to the badger (Meles meles L.)

There exists some confusion as to the means by which Ireland developed its current mammalian fauna. In this paper, I use a multivariate analysis of cranial measurements to test the hypothesis that Irish mustelids should resemble their Scottish counterparts more so than those from England, thus providing morphological evidence for postglacial colonization via an Ireland/Scotland landbridge. An examination of badger ( Meles meles L.), stoat ( Mustela erminea L.) and otter ( Lutra lutra L.) failed to provide support for this hypothesis. Based on these results and consideration of our knowledge of the ecology of these species, it is concluded that postglacial colonization via a landbridge was unlikely. Evidence for human-aided colonization is reviewed. It is concluded that, while further morphologic and genetic studies are very much required, the problem of postglacial colonization can only be solved through archaeozoological research.     

C-S-R triangle theory: community-level predictions, tests, evaluation of criticisms, and relation to other theories

Grime's C - S - R triangle theory has been discussed in plant ecology for two decades, but it has rarely been tested, and not often dispassionately evaluated. We consider the theory from a community viewpoint, and attempt to develop and test predictions for plant communities. C - S - R assumes that in high-disturbance (ruderal, R ) patches or habitats, competition will be absent, or low in intensity. Testing this is problematic because of the difficulty of defining the intensity of competition, and we could find no rigorous evidence to support or refute the prediction. The theory also implies that in high-disturbance habitats there will be no difference in species composition between 'competition' and 'stress' sites, but from available evidence this does not seem to be true. C - S - R assumes that in stressful ( S ) habitats, competition will be low. This assumption is difficult to define or test, because of the overall difference in plant growth rate between habitats. A prediction from the theory is that in stressful habitats autosuccession should occur, i.e. that the climax species should regenerate directly, with no specialist secondary pioneer ( R ) species. There is some evidence that autosuccession occurs under the most extreme stresses of various types. Previous criticisms of C - S - R are evaluated. Only a few are considered valid, mainly those that emphasise that C - S - R theory is a considerable simplification of reality. Previous tests of C - S - R theory appear to be inconclusive. C - S - R theory is basically a combination of r / K theory and Leaf Amortisation theory. We conclude that there is limited support for the C - S - R theory. Whether the gain in generality that the theory offers justifies the loss via simplification that it involves is still an open question. As formulated, it has limited utility as a predictive model in community ecology. Yet, it is currently the most comprehensive and coherent theory for community ecology.     

Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications

The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P‐values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p‐values and for model stability investigations. Procedures which make use of bootstrapped information criteria are often applied in model stability investigations and model averaging approaches as well as when estimating the error of model selection procedures which involve tuning parameters. From the literature, however, there is evidence that p‐values and model selection criteria evaluated on bootstrap data sets do not represent what would be obtained on the original data or new data drawn from the overall population. We explain the reasons for this and, through the use of a real data set and simulations, we assess the practical impact on procedures relevant to biometrical applications in cases where it has not yet been studied. Moreover, we investigate the behavior of subsampling (i.e., drawing from a data set without replacement) as a potential alternative solution to the bootstrap for these procedures.     

Riverine landscapes: taking landscape ecology into the water

1. Landscape ecology deals with the influence of spatial pattern on ecological processes. It considers the ecological consequences of where things are located in space, where they are relative to other things, and how these relationships and their consequences are contingent on the characteristics of the surrounding landscape mosaic at multiple scales in time and space. Traditionally, landscape ecologists have focused their attention on terrestrial ecosystems, and rivers and streams have been considered either as elements of landscape mosaics or as units that are linked to the terrestrial landscape by flows across boundaries or ecotones. Less often, the heterogeneity that exists within a river or stream has been viewed as a `riverscape' in its own right.
2. Landscape ecology can be unified about six central themes: (1) patches differ in quality (2) patch boundaries affect flows, (3) patch context matters, (4) connectivity is critical, (5) organisms are important, and (6) the importance of scale. Although riverine systems differ from terrestrial systems by virtue of the strong physical force of hydrology and the inherent connectivity provided by water flow, all of these themes apply equally to aquatic and terrestrial ecosystems, and to the linkages between the two.
3. Landscape ecology therefore has important insights to offer to the study of riverine ecosystems, but these systems may also provide excellent opportunities for developing and testing landscape ecological theory. The principles and approaches of landscape ecology should be extended to include freshwater systems; it is time to take the `land' out of landscape ecology.     

EQUIP: Implementing chronic care principles and applying formative evaluation methods to improve care for schizophrenia: QUERI Series

Background

The PARiHS framework (Promoting Action on Research Implementation in Health Services) has proved to be a useful practical and conceptual heuristic for many researchers and practitioners in framing their research or knowledge translation endeavours. However, as a conceptual framework it still remains untested and therefore its contribution to the overall development and testing of theory in the field of implementation science is largely unquantified.

Discussion

This being the case, the paper provides an integrated summary of our conceptual and theoretical thinking so far and introduces a typology (derived from social policy analysis) used to distinguish between the terms conceptual framework, theory and model – important definitional and conceptual issues in trying to refine theoretical and methodological approaches to knowledge translation. Secondly, the paper describes the next phase of our work, in particular concentrating on the conceptual thinking and mapping that has led to the generation of the hypothesis that the PARiHS framework is best utilised as a two-stage process: as a preliminary (diagnostic and evaluative) measure of the elements and sub-elements of evidence (E) and context (C), and then using the aggregated data from these measures to determine the most appropriate facilitation method. The exact nature of the intervention is thus determined by the specific actors in the specific context at a specific time and place. In the process of refining this next phase of our work, we have had to consider the wider issues around the use of theories to inform and shape our research activity; the ongoing challenges of developing robust and sensitive measures; facilitation as an intervention for getting research into practice; and finally to note how the current debates around evidence into practice are adopting wider notions that fit innovations more generally.

Summary

The paper concludes by suggesting that the future direction of the work on the PARiHS framework is to develop a two-stage diagnostic and evaluative approach, where the intervention is shaped and moulded by the information gathered about the specific situation and from participating stakeholders. In order to expedite the generation of new evidence and testing of emerging theories, we suggest the formation of an international research implementation science collaborative that can systematically collect and analyse experiences of using and testing the PARiHS framework and similar conceptual and theoretical approaches. We also recommend further refinement of the definitions around conceptual framework, theory, and model, suggesting a wider discussion that embraces multiple epistemological and ontological perspectives.     

Ecological paradoxes*

Two controversial areas of ecology are examined critically to ascertain the limits of some current theories. In the field of population ecology it is argued that no general theory can explain the regulation of animal numbers. Existing theories are considered inadequate because either (1) evidence points to multiple causes rather than a single cause, (2) propositions lose scientific appeal by accumulating qualifiers, or (3) conflicting theories are irrefutable in scientific inquiry. Different research strategies are required to discover generalities in population regulation. In the field of community organization it is pointed out that too much emphasis on the competitive exclusion principle has blinded ecologists from the clustering of resources and of species populations. Conditions of co-existence as well as segregation are considered important in the organization of communities, which allow elements of chance in small scale distribution. The ecological world is likened to the physical world in which small scale disorder leads to order on a large scale. For the development of a global ecology the acceleration of studies in the tropics and the southern hemisphere is urged.     

Model selection in ecology and evolution

Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.     

Community-wide character displacement in the presence of clines: a test of Holarctic weasel guilds

1. Competition is thought to be a major influence on community assembly, ecology and evolution; presence of competitors may cause divergence in traits related to resource use (character displacement). 2. Such traits, however, often vary clinally, and this phenomenon may be independent of the presence or absence of competing species. 3. The presence of such clines can either obscure the effects of competition, or create an impression that competition is operating when, in fact, it is not. 4. We corrected for clinal variation while testing for character displacement in two well-studied weasel (Mustela) guilds, in the Nearctic and the west Palaearctic. 5. Without accounting for clines, our results agreed with previous studies suggesting character displacement in these guilds. 6. However, when we corrected for clines, predictions of competition theory were not met - and often we obtained evidence for character convergence in sympatry. 7. This may suggest that the nature of the resource base may be more important than interspecific competition in shaping morphology and size in these carnivores. 8. Our results highlight the need to account for geographic variation when studying character displacement and cast some doubt on prevailing ideas regarding the effect of competition on morphological evolution.     

The statistical basis of public policy: a paradigm shift is overdue.

The recent controversy over the increased risk of venous thrombosis with third generation oral contraceptives illustrates the public policy dilemma that can be created by relying on conventional statistical tests and estimates: case-control studies showed a significant increase in risk and forced a decision either to warn or not to warn. Conventional statistical tests are an improper basis for such decisions because they dichotomise results according to whether they are or are not significant and do not allow decision makers to take explicit account of additional evidence--for example, of biological plausibility or of biases in the studies. A Bayesian approach overcomes both these problems. A Bayesian analysis starts with a "prior" probability distribution for the value of interest (for example, a true relative risk)--based on previous knowledge--and adds the new evidence (via a model) to produce a "posterior" probability distribution. Because different experts will have different prior beliefs sensitivity analyses are important to assess the effects on the posterior distributions of these differences. Sensitivity analyses should also examine the effects of different assumptions about biases and about the model which links the data with the value of interest. One advantage of this method is that it allows such assumptions to be handled openly and explicitly. Data presented as a series of posterior probability distributions would be a much better guide to policy, reflecting the reality that degrees of belief are often continuous, not dichotomous, and often vary from one person to another in the face of inconclusive evidence.     

What hypothesis tests are not: a response to Colegrave and Ruxton

It is always flattering to see one's work cited by others. Notonly does it boost the ego, but it provides a satisfying feelingthat one's efforts are both appreciated and contributing tothe advance of science. So I was pleased when a colleague pointedout that Colegrave and Ruxton (2003) had cited a recent paperof mine, "The insignificance of statistical significance testing"(Johnson, 1999). In that article I argued, as did Colegraveand Ruxton, that confidence intervals often are much more informativethan are p values associated with hypothesis tests. My pleasure, alas, was short-lived.