Complex adaptive landscapes (CAL): A conceptual framework of multi-functional,non-linear ecohydrological feedback systems

Landscape ecology and complex adaptive systems (CAS) research provide numerous examples of systems with complex non-linear feedbacks, but our understanding of these systems is severely limited by a lack of conceptual frameworks built on these foundations. Here, we develop a conceptual framework by combining CAS organisation with landscape structure, functioning and change. The resulting framework, ‘complex adaptive landscapes’ (CAL), explicitly captures the reciprocal feedbacks and non-linear nature of interactions between components within and between system levels, and the consequent possibility of multiple functional states (alternate systems functioning). The CAL framework highlights six core tenets that describe landscape complexity and dynamics. CAL provides examples of how the complex ecohydrological interactions at finer-scale hillslope levels manifest changes to broader landscape levels, as well as multi-temporal feedbacks and change (days to decades). Understanding the specific feedback and non-linear responses of different components of the landscape, such as plant functional types, are of paramount importance for adequately designing monitoring and analytical frameworks for adaptive natural resource management. The CAL framework allows us to better understand the scale of ecohydrological functions within the landscape, and how substituted component types and their spatial and temporal configuration may cause dysfunctional states to arise as a result of human land use.     

Relationships between life-history strategies of European freshwater fish species and their habitat preferences

1. Focusing on the current environmental characteristics, the ‘habitat template’ theory proposes that life‐history strategies summarise how evolution has shaped species to cope with the temporal and spatial variability of their present environment. The hierarchical ‘landscape filters’ concept predicts that the distribution of species reflects their specific traits that allow them to pass through multiple habitat filters. Together, these theories showed the importance of identifying the functional relationships of species to selective habitat forces in order to predict the organisation and response of communities to the environment. 2. We test the relationships between life‐history traits of European freshwater fish species’ and their habitat preferences, to detect the strategies adopted by fish to cope with their current habitat. For this purpose, we use published data on species traits and habitat preferences (microhabitat hydraulics, temperature and oxygen level). We use multivariate analyses to classify fish species’ strategies and test the relationships between strategies and habitat preferences. 3. We identified a continuum of life‐history patterns between two extremes, with opportunistic and periodic species. Our study supports the idea that microhabitat hydraulics plays a more important role as a template for these species ecological strategies than temperature and oxygen level. Indeed, riffle habitats may select opportunistic species whereas weak relationships are found between species strategies and both their temperature and oxygen level preferences. In addition, the ratio between mortality and growth rate (dimensionless trait), reflecting a trade‐off between growth and survival, varied among species according to the use of their hydraulic habitat, with species using deep habitats exhibiting the highest values. 4. These general relationships between hydraulics and traits may be of importance in community ecology to develop predictive models to understand how fish communities change with the hydraulic environment.     

The principle of coherence in multi-level brain information processing

Synchronisation has become one of the major scientific tools to explain biological order at many levels of organisation. In systems neuroscience, synchronised subthreshold and suprathreshold oscillatory neuronal activity within and between distributed neuronal assemblies is acknowledged as a fundamental mode of neuronal information processing. Coherent neuronal oscillations correlate with all basic cognitive functions, mediate local and long-range neuronal communication and affect synaptic plasticity. However, it remains unclear how the very fast and complex changes of functional neuronal connectivity necessary for cognition, as mediated by dynamic patterns of neuronal synchrony, could be explained exclusively based on the well-established synaptic mechanisms. A growing body of research indicates that the intraneuronal matrix, composed of cytoskeletal elements and their binding proteins, structurally and functionally connects the synapses within a neuron, modulates neurotransmission and memory consolidation, and is hypothesised to be involved in signal integration via electric signalling due to its charged surface. Theoretical modelling, as well as emerging experimental evidence indicate that neuronal cytoskeleton supports highly cooperative energy transport and information processing based on molecular coherence. We suggest that long-range coherent dynamics within the intra- and extracellular filamentous matrices could establish dynamic ordered states, capable of rapid modulations of functional neuronal connectivity via their interactions with neuronal membranes and synapses. Coherence may thus represent a common denominator of neurophysiological and biophysical approaches to brain information processing, operating at multiple levels of neuronal organisation, from which cognition may emerge as its cardinal manifestation.     

Scaling up: how do exogenous fluctuations in individual-based resource competition models re-emerge in aggregated stochastic population models?

In applied population dynamics the choice of stochastic per capita growth function has implications for population viability analyses, management recommendations, and pest control. This model choice is often based on statistical criteria, mathematical tractability or personal preferences, and general ecological guidelines are either too vague or entirely missing. To identify such guidelines, it is important to understand how exogenous and endogenous factors interact at the individual level and re-emerge at the aggregated population level. We therefore study different types of resource competition (contest vs. scramble competition) and different types of exogenous fluctuations (food and weather fluctuations) at the individual level in a simple individual-based simulation model. We statistically fit the resulting time series to find out (1) which functional form of the growth function (‘hyperbolic’ or ‘exponential’) better describes contest and scramble competition and (2) whether the pattern of population fluctuations resulting from the simulations can be assigned to vertical, lateral or nonlinear perturbations in the stochastic growth function (a classification scheme suggested by Royama 1992, Analytical Population Dynamics, Chapman and Hall, London). We found that the same type of competition can result in ‘hyperbolic’ or ‘exponential’ functional forms, depending on the type of exogenous fluctuations. So it is the interplay between exogenous variability and endogenous resource competition that affects model performance. In contrast to the widespread assumption of vertical (additive) perturbations, our findings highlight the importance of (non-additive) lateral and nonlinear perturbations and their combinations with vertical perturbations. The choice of the stochastic growth function should therefore consider not only statistical criteria but also ecological guidelines. We derive such ecological guidelines from our analysis.     

Predicting substrate specificity of adenylation domains of nonribosomal peptide synthetases and other protein properties by latent semantic indexing

Successful genome mining is dependent on accurate prediction of protein function from sequence. This often involves dividing protein families into functional subtypes (e.g., with different substrates). In many cases, there are only a small number of known functional subtypes, but in the case of the adenylation domains of nonribosomal peptide synthetases (NRPS), there are >500 known substrates. Latent semantic indexing (LSI) was originally developed for text processing but has also been used to assign proteins to families. Proteins are treated as ‘‘documents’’ and it is necessary to encode properties of the amino acid sequence as ‘‘terms’’ in order to construct a term-document matrix, which counts the terms in each document. This matrix is then processed to produce a document-concept matrix, where each protein is represented as a row vector. A standard measure of the closeness of vectors to each other (cosines of the angle between them) provides a measure of protein similarity. Previous work encoded proteins as oligopeptide terms, i.e. counted oligopeptides, but used no information regarding location of oligopeptides in the proteins. A novel tokenization method was developed to analyze information from multiple alignments. LSI successfully distinguished between two functional subtypes in five well-characterized families. Visualization of different ‘‘concept’’ dimensions allows exploration of the structure of protein families. LSI was also used to predict the amino acid substrate of adenylation domains of NRPS. Better results were obtained when selected residues from multiple alignments were used rather than the total sequence of the adenylation domains. Using ten residues from the substrate binding pocket performed better than using 34 residues within 8 Å of the active site. Prediction efficiency was somewhat better than that of the best published method using a support vector machine.     

Mapping landscape corridors

Corridors are important geographic features for biological conservation and biodiversity assessment. The identification and mapping of corridors is usually based on visual interpretations of movement patterns (functional corridors) or habitat maps (structural corridors). We present a method for automated corridor mapping with morphological image processing, and demonstrate the approach with a forest map derived from satellite imagery of northern Slovakia. We show how the approach can be used to differentiate between relatively narrow (‘line’) and wide (‘strip’) structural corridors by mapping corridors at multiple scales of observation, and indicate how to map functional corridors with maps of observed or simulated organism movement. An application to environmental reporting is demonstrated by assessing structural forest corridors in relation to forest types in northern Slovakia.     

Functional complexity: The source of value in biodiversity

Biodiversity may be seen as a scientific measure of the complexity of a biological system, implying an information basis. Complexity cannot be directly valued, so economists have tried to define the services it provides, though often just valuing the services of ‘key’ species. Here we provide a new definition of biodiversity as a measure of functional information, arguing that complexity embodies meaningful information as Gregory Bateson defined it. We argue that functional information content (FIC) is the potentially valuable component of total (algorithmic) information content (AIC), as it alone determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. Establishing substitutability is an essential foundation for valuation. From it, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and the production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science.     

Stress-free microbes lack vitality

Stress is an inextricable aspect of life, and stress biology has been a field of intensive study over the last 200–300 years. In human psychology, we consider a stress-free condition to be one of relaxation or happiness, yet with respect to microbial cells we do not have a concept that describes being non-stressed. Stresses within, and stress tolerance of, microbial systems lie at the crux of critical global challenges, such as optimising soil- and plant-health and crop yields; reducing food spoilage; bioremediation of polluted environments; effective biological control and biofuel production; gaining insight into aging processes in humans; and understanding astrobiology. There is no consensus on how to measure cellular stress, or even how we define it. ‘Stress’ implies that physical forces act on the microbial system in such a way that impairs its ability to function. Ironically, however, a cell that exhibits optimal growth also has reduced energy generation, is less resilient to change, and can have poor competitive ability. Furthermore, rapid growth is associated with a high level of oxidative damage and compromised vitality of the system. Stresses induced by temperature, pH, water activity, chaotropicity, reactive oxygen species, dehydration-rehydration cycles, ionizing radiation, and changes in turgor or other mechanical forces are well-known. Our knowledge of cellular stress responses, such as signal-transduction pathways, compatible-solute metabolism, protein-stabilization proteins, and plasma-membrane adaptations, is also considerable. However, we have limited understanding of the complex and dynamic stresses that typically occur in microbial habitats or industrial systems, and how these impact the biophysics, cellular biology and evolutionary trajectories of microbes. There is also a paucity of information on why the cellular system ultimately fails under extremes of stress, and it is even debatable whether any microbe can ever be completely stress-free. However, cells that exhibit optimal rates of biotic activity are likely to exhibit low ecological fitness compared with those that are moderately stressed; in other words, stress can enhance microbial vitality, vigour and resilience. ‘Stress’ is sometimes applied mistakenly to describe the effects of toxic substances that have target site-specific modes-of-action (e.g. antibiotics) rather than and do not inhibit the cell via any type of stress-mediated mechanism. Whereas terms such as ‘rapid-growth stress’, ‘nutrient stress’ and ‘biotic stress’ span a range of logical categories, their modes-of-action do usually involve a biophysical component. Stress can impact all levels of biology (from biomacromolecules to ecosystems), is a potent driver for evolutionary processes and - it could be argued - is an inherent property of life itself. The published articles that follow include a number of unprecedented findings and were compiled for this special issue Biology of Fungal Systems under Stress. Collectively, they are testament to the breadth and importance of the stress-biology field.     

Cyclone Winston and Community-Based Marine Conservation in Fiji

ABSTRACT

The establishment and use of community-based natural resource management (CBNRM) groups is now the established route towards conservation in large parts of the Pacific, especially in Fiji. One of the main strengths of CBNRM that is often mentioned is its adaptability to different contexts and to changing objectives among stakeholders, an aspect thoroughly tested by events such as ‘natural’ disasters. This paper is based on 10 months of fieldwork in Kubulau district in Fiji before, during and after Cyclone Winston. It provides an ethnographic account of how this ‘natural’ disaster affected a community and the local CBNRM group. It looks at how this event was experienced and managed by the group, and how the group’s involvement in disaster assistance shifted its role both within and outside of the community, as well as changing its future agenda during the months that followed. We can see in the aftermath of disaster a shift within the group away from the original primary focus on conservation and towards development. The paper provides an account of how the disaster seemingly strengthened the group and the ‘community’ in terms of organisation, knowledge and motivation, but also how it challenged previous norms and exposed weaknesses that are arguably inherent within CBNRM itself.     

Eco-evolutionary maintenance of diversity in fluctuating environments

Growing evidence suggests that temporally fluctuating environments are important in maintaining variation both within and between species. To date, however, studies of genetic variation within a population have been largely conducted by evolutionary biologists (particularly population geneticists), while population and community ecologists have concentrated more on diversity at the species level. Despite considerable conceptual overlap, the commonalities and differences of these two alternative paradigms have yet to come under close scrutiny. Here, we review theoretical and empirical studies in population genetics and community ecology focusing on the ‘temporal storage effect’ and synthesise theories of diversity maintenance across different levels of biological organisation. Drawing on Chesson's coexistence theory, we explain how temporally fluctuating environments promote the maintenance of genetic variation and species diversity. We propose a further synthesis of the two disciplines by comparing models employing traditional frequency-dependent dynamics and those adopting density-dependent dynamics. We then address how temporal fluctuations promote genetic and species diversity simultaneously via rapid evolution and eco-evolutionary dynamics. Comparing and synthesising ecological and evolutionary approaches will accelerate our understanding of diversity maintenance in nature.     

Looking for a needle in a haystack: inference about individual fitness components in a heterogeneous population

Studies of wild vertebrates have provided evidence of substantial differences in lifetime reproduction among individuals and the sequences of life history ‘states’ during life (breeding, nonbreeding, etc.). Such differences may reflect ‘fixed’ differences in fitness components among individuals determined before, or at the onset of reproductive life. Many retrospective life history studies have translated this idea by assuming a ‘latent’ unobserved heterogeneity resulting in a fixed hierarchy among individuals in fitness components. Alternatively, fixed differences among individuals are not necessarily needed to account for observed levels of individual heterogeneity in life histories. Individuals with identical fitness traits may stochastically experience different outcomes for breeding and survival through life that lead to a diversity of ‘state’ sequences with some individuals living longer and being more productive than others, by chance alone. The question is whether individuals differ in their underlying fitness components in ways that cannot be explained by observable ‘states’ such as age, previous breeding success, etc. Here, we compare statistical models that represent these opposing hypotheses, and mixtures of them, using data from kittiwakes. We constructed models that accounted for observed covariates, individual random effects (unobserved heterogeneity), first‐order Markovian transitions between observed states, or combinations of these features. We show that individual sequences of states are better accounted for by models incorporating unobserved heterogeneity than by models including first‐order Markov processes alone, or a combination of both. If we had not considered individual heterogeneity, models including Markovian transitions would have been the best performing ones. We also show that inference about age‐related changes in fitness components is sensitive to incorporation of underlying individual heterogeneity in models. Our approach provides insight into the sources of individual heterogeneity in life histories, and can be applied to other data sets to examine the ubiquity of our results across the tree of life.     

An ecological framework of neophobia: from cells to organisms to populations

Neophobia is the fear of novel stimuli or situations. This phenotype has recently received much ecological attention, primarily in the context of decision making. Here, we explore neophobia across biological levels of organisation, first describing types of neophobia among animals and the underlying causes of neophobia, highlighting high levels of risk and uncertainty as key drivers. We place neophobia in the framework of Error Management Theory and Signal Detection Theory, showing how increases in overall risk and uncertainty can lead to costly non‐responses towards novel threats unless individuals lower their response threshold and become neophobic. We then discuss how neophobic behaviour translates into population and evolutionary consequences before introducing neophobia‐like processes at the cellular level, where some phenomena such as allergy and autoimmunity can parallel neophobic behaviour. Finally, we discuss neophobia attenuation, considering how a sudden change in the environment from dangerous to safe can lead to problematic over‐responses (i.e. the ‘maladaptive defensive carry‐over’ hypothesis), and discuss treatment methods for such over‐responses. We anticipate that bridging the concept of neophobia with a process‐centered perspective can facilitate a transfer of insight across organisational levels.     

Neutralizing Antibodies Against Allosteric Proteins: Insights From a Bacterial Adhesin

Allosteric proteins transition between ‘inactive’ and ‘active’ states. In general, such proteins assume distinct conformational states at the level of secondary, tertiary and/or quaternary structure. Different conformers of an allosteric protein can be antigenically dissimilar and induce antibodies with a highly distinctive specificities and neutralizing functional effects. Here we summarize studies on various functional types of monoclonal antibodies obtained against different allosteric conformers of the mannose-specific bacterial adhesin FimH – the most common cell attachment protein of Escherichia coli and other enterobacterial pathogens. Included are types of antibodies that activate the FimH function via interaction with ligand-induced binding sites or by wedging between domains as well as antibodies that inhibit FimH through orthosteric, parasteric, or novel dynasteric mechanisms. Understanding the molecular mechanism of antibody action against allosteric proteins provides insights on how to design antibodies with a desired functional effect, including those with neutralizing activity against bacterial and viral cell attachment proteins.     

Forecasting phenology: from species variability to community patterns

Shifts in species' phenology in response to climate change have wide-ranging consequences for ecological systems. However, significant variability in species' responses, together with limited data, frustrates efforts to forecast the consequences of ongoing phenological changes. Herein, we use a case study of three North American plant communities to explore the implications of variability across levels of organisation (within and among species, and among communities) for forecasting responses to climate change. We show how despite significant variation among species in sensitivities to climate, comparable patterns emerge at the community level once regional climate drivers are accounted for. However, communities differ with respect to projected patterns of divergence and overlap among their species' phenological distributions in response to climate change. These analyses and a review of hypotheses suggest how explicit consideration of spatial scale and levels of biological organisation may help to understand and forecast phenological responses to climate change.     

Unifying concepts of biological function from molecules to ecosystems

The concept of function arises at all levels of biological study and is often loosely and variously defined, especially within ecology. This has led to ambiguity, obscuring the common structure that unites levels of biological organisation, from molecules to ecosystems. Here we build on already successful ideas from molecular biology and complexity theory to create a precise definition of biological function which spans levels of biological organisation and can be quantified in the unifying currency of biomass, enabling comparisons of functional effectiveness (irrespective of the specific function) across the field of ecology. We give precise definitions of ecological and ecosystem function that bring clarity and precision to studies of biodiversity– ecosystem function relationships and questions of ecological redundancy. To illustrate the new concepts and their unifying power, we construct a simple community‐level model with nutrient cycling and animal‐plant mutualism, emphasising the importance of its network structure in determining overall functioning. This type of network structure is that of an autocatalytic set of functional relationships, which also appears at biochemical, cellular and organism levels of organisation, creating a nested hierarchy. This enables a common and unifying concept of function to apply from molecular interaction networks up to the global ecosystem.     

Lethal interactions among vertebrate top predators: a review of concepts,assumptions and terminology

Lethal interactions among large vertebrate predators have long interested researchers because of ecological and conservation issues. Research focusing on lethal interactions among vertebrate top predators has used several terms with a broad sense, and also introduced new terminology. We analysed the published literature with reference to the main underlying concepts and the use of terminology and its ecological context. The most frequently used terms in the literature were ‘predation’, ‘intraguild predation’, ‘interference competition’, and ‘interspecific killing’. Most studies presented evidence of the killing of the victim (77%), but information regarding its consumption was not given in 48% of cases. More than half of the analysed studies (56%) had no solid information on the degree of competition between interacting species. By reviewing definitions and their underlying assumptions, we demonstrate that lethal interactions among large vertebrate predators could be designated using four terms—‘predation’, ‘intraguild predation’, ‘interspecific competitive killing’, and ‘superpredation’—without the need to employ additional terminology that may increase confusion and misuse. For a correct framework of these lethal interactions it is critical to assess if the kill is consumed, if the victim is indeed a competitor of the killer, and if the prey is a high‐order predator. However, these elements of the framework are simultaneously the most common constraints to studies of lethal interactions, since they often require a great effort to obtain. The proper use of terms and concepts is fundamental to understanding the causes behind lethal interactions and, ultimately, what is actually happening in these complex interactions.     

Proteomics advances for precision therapy in ovarian cancer

ABSTRACT

Introduction: Due to the relatively low mutation rate and high frequency of copy number variation, finding actionable genetic drivers of high-grade serous carcinoma (HGSC) is a challenging task. Furthermore, emerging studies show that genetic alterations are frequently poorly represented at the protein level adding a layer of complexity. With improvements in large-scale proteomic technologies, proteomics studies have the potential to provide robust analysis of the pathways driving high HGSC behavior.

Areas covered: This review summarizes recent large-scale proteomics findings across adequately sized ovarian cancer sample sets. Key words combined with ‘ovarian cancer’ including ‘proteomics’, ‘proteogenomic’, ‘reverse-phase protein array’, ‘mass spectrometry’, and ‘adaptive response’, were used to search PubMed.

Expert opinion: Proteomics analysis of HGSC as well as their adaptive responses to therapy can uncover new therapeutic liabilities, which can reduce the emergence of drug resistance and potentially improve patient outcomes. There is a pressing need to better understand how the genomic and epigenomic heterogeneity intrinsic to ovarian cancer is reflected at the protein level and how this information could be used to improve patient outcomes.