Assortative mating and the adaptive landscape

The ability of a population to shift from one adaptive peak to another was examined for a two-locus model with different degrees of assortative mating, selection, and linkage. As expected, if the proportion of the population that mates assortatively increases, so does its ability to shift to a new peak. Assortative mating affects this process by allowing the mean fitness of a population to increase monotonically as it passes through intermediate gene frequencies on the way to a new, higher, homozygotic peak. Similarly, if the height of the new peak increases or selection against intermediates becomes less severe, the population becomes more likely to shift to a new peak. Close linkage also helps the shift to a new adaptive peak and acts similarly to assortative mating, but it is not necessary for such a shift as was previously thought. When a population shifts to a new peak, the number of generations required is significantly less than that needed to return to the original peak when that happens. The short period of time required may be an explanation for rapid changes in the geological record. Under extremely high degrees of assortative mating, the shift takes longer, presumably because of the difficulty of breaking up less favored allelic combinations.

Robust Control of Evolutionary Dynamics

The application of principles from evolutionary biology has long been used to gain new insights into the progression and clinical control of both infectious diseases and neoplasms. This iterative evolutionary process consists of expansion, diversification and selection within an adaptive landscape - species are subject to random genetic or epigenetic alterations that result in variations; genetic information is inherited through asexual reproduction and strong selective pressures such as therapeutic intervention can lead to the adaptation and expansion of resistant variants. These principles lie at the center of modern evolutionary synthesis and constitute the primary reasons for the development of resistance and therapeutic failure, but also provide a framework that allows for more effective control.

A model system for studying the evolution of resistance and control of therapeutic failure is the treatment of chronic HIV-1 infection by broadly neutralizing antibody (bNAb) therapy. A relatively recent discovery is that a minority of HIV-infected individuals can produce broadly neutralizing antibodies, that is, antibodies that inhibit infection by many strains of HIV. Passive transfer of human antibodies for the prevention and treatment of HIV-1 infection is increasingly being considered as an alternative to a conventional vaccine. However, recent evolution studies have uncovered that antibody treatment can exert selective pressure on virus that results in the rapid evolution of resistance. In certain cases, complete resistance to an antibody is conferred with a single amino acid substitution on the viral envelope of HIV.

The challenges in uncovering resistance mechanisms and designing effective combination strategies to control evolutionary processes and prevent therapeutic failure apply more broadly. We are motivated by two questions: Can we predict the evolution to resistance by characterizing genetic alterations that contribute to modified phenotypic fitness? Given an evolutionary landscape and a set of candidate therapies, can we computationally synthesize treatment strategies that control evolution to resistance?

To address the first question, we propose a mathematical framework to reason about evolutionary dynamics of HIV from computationally derived Gibbs energy fitness landscapes -- expanding the theoretical concept of an evolutionary landscape originally conceived by Sewall Wright to a computable, quantifiable, multidimensional, structurally defined fitness surface upon which to study complex HIV evolutionary outcomes.

To design combination treatment strategies that control evolution to resistance, we propose a methodology that solves for optimal combinations and concentrations of candidate therapies, and allows for the ability to quantifiably explore tradeoffs in treatment design, such as limiting the number of candidate therapies in the combination, dosage constraints and robustness to error. Our algorithm is based on the application of recent results in optimal control to an HIV evolutionary dynamics model and is constructed from experimentally derived antibody resistant phenotypes and their single antibody pharmacodynamics. This method represents a first step towards integrating principled engineering techniques with an experimentally based mathematical model in the rational design of combination treatment strategies and offers predictive understanding of the effects of combination therapies of evolutionary dynamics and resistance of HIV. Preliminary in vitro studies suggest that the combination antibody therapies predicted by our algorithm can neutralize heterogeneous viral populations despite containing resistant mutations.

Experimental evidence for multivariate stabilizing sexual selection

Stabilizing selection is a fundamental concept in evolutionary biology. In the presence of a single intermediate optimum phenotype (fitness peak) on the fitness surface, stabilizing selection should cause the population to evolve toward such a peak. This prediction has seldom been tested, particularly for suites of correlated traits. The lack of tests for an evolutionary match between population means and adaptive peaks may be due, at least in part, to problems associated with empirically detecting multivariate stabilizing selection and with testing whether population means are at the peak of multivariate fitness surfaces. Here we show how canonical analysis of the fitness surface, combined with the estimation of confidence regions for stationary points on quadratic response surfaces, may be used to define multivariate stabilizing selection on a suite of traits and to establish whether natural populations reside on the multivariate peak. We manufactured artificial advertisement calls of the male cricket Teleogryllus commodus and played them back to females in laboratory phonotaxis trials to estimate the linear and nonlinear sexual selection that female phonotactic choice imposes on male call structure. Significant nonlinear selection on the major axes of the fitness surface was convex in nature and displayed an intermediate optimum, indicating multivariate stabilizing selection. The mean phenotypes of four independent samples of males, from the same population as the females used in phonotaxis trials, were within the 95% confidence region for the fitness peak. These experiments indicate that stabilizing sexual selection may play an important role in the evolution of male call properties in natural populations of T. commodus.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.

“ The Creation of an Urban Landscape” in Adaptive reuse,the modern movement toward the future, 14th international conference proceedings, Do_co.mo.mo international, Lisboa ( indexed by SCOPUS)

The headquarters and park of the Calouste Gulbenkian Foundation in Lisbon represent the first modern Portuguese environment with an outstanding relation between exterior and interior as a spatial continuum . As such, the project refused the more common conceptual attitude of interior plus exterior. This unitary view revealed a clear understanding of the proposed site for the project and what could have been Calouste Sarkis Gulbenkian (1869-1955) expectations, while concretizing Modern Movement ideals regarding landscape architecture and architecture. Through its design the park mediates the relation between the buildings’ super-structures, the urban context, and the human scale, while generating a unifying system established by the complicity between natural and synthetic materials. From the first moment of the project’s design process, this complicity resulted in a set of strategies that met programmatic

A collaborative design to adaptively manage for landscape sustainability in north Australia: lessons from a decade of cooperative research

Approaches to manage for the sustainable use of natural and cultural resources in a landscape can have many different designs. One design is adaptive collaborative landscape management (ACLM) where research providers and users work closely together on projects to develop resources while adaptively managing to sustain or maintain landscapes in the long term. We propose that collaborative projects are more useful for achieving outcomes than integrative projects where participants merely join their separate contributions. To foster collaborative research projects to adaptively manage landscapes in northern Australia, a Tropical Savannas Cooperative Research Centre (TSCRC) was established in 1995. The TSCRC is a joint venture of major organizations involved in research and land management. This paper is our perspective on the four most important 'lessons learned' after using a ACLM-type approach for over 10 y. We learnt that collaboration (working in combination) not necessarily integration (combining parts into a whole) achieved sustainable outcomes. We found that integration across culturally diverse perspectives seldom achieved sustainable solutions because it devalued the position of the less empowered participants. In addition, positive outcomes were achieved when participants developed trust and respect for each other by embracing and respecting their differences and by sharing unifying concepts such as savanna health. Another lesson learned was that a collaborative organization must act as an honest broker by resisting advocacy of one view point over another. Finally, we recognized the importance of strongly investing in communication and networking so that people could adaptively learn from one another's experiences, understand each other's challenges and respect each other's choices. Our experience confirms the usefulness of the ACLM approach and highlights its role in the process of sustaining healthy landscapes.

How does complex adaptive system theory inform innovation in complex project based organisations?

Innovation enables organisations to endure by responding to emergence and to improve efficiency. Innovation in a complex organisation can be difficult due to complexities contributing to slow decision-making. Complex projects fail due to an inability to respond to emergence which consumes finances and impacts on resources and organisational success. Therefore, for complex organisations to improve on performance and resilience, it would be advantageous to understand how to improve the management of innovation and thus, the ability to respond to emergence. The benefits to managers are an increase in the number of successful projects and improved productivity. This study will explore innovation management in a complex project based organisation. The contribution to the academic literature will be an in-depth, qualitative exploration of innovation in a complex project based organisation using a comparative case study approach.

Landscape and farm scale management to enhance biodiversity conservation in the cocoa producing region of southern Bahia, Brazil

In southern Bahia, Brazil, large land areas are used for the production of cocoa (Theobroma cacao), which is predominantly grown under the shade of native trees in an agroforestry system locally known as cabruca. As a dominant forest-like landscape element of the cocoa region, the cabrucas play an important role in the conservation of the region`s biodiversity. The purpose of this review is to provide the scientific basis for an action plan to reconcile cocoa production and biodiversity conservation in southern Bahia. The available research collectively highlights the diversity of responses of different species and biological groups to both the habitat quality of the cabrucas themselves and to the general characteristics of the landscape, such as the relative extent and spatial configuration of different vegetation types within the landscape mosaic. We identify factors that influence directly or indirectly the occurrence of native species in the cabrucas and the wider landscape of the cocoa region and develop recommendations for their conservation management. We show that the current scientific knowledge already provides a good basis for a biodiversity friendly management of the cocoa region of southern Bahia, although more work is needed to refine some management recommendations, especially on shade canopy composition and density, and verify their economic viability. The implementation of our recommendations should be accompanied by appropriate biological and socioeconomic monitoring and the findings should inform a broad program of adaptive management of the cabrucas and the wider cocoa landscape.

Genetic diversity, phenotypic variation and local adaptation in the alpine landscape: case studies with alpine plant species

Plant survival in alpine landscapes is constantly challenged by the harsh and often unpredictable environmental conditions. Steep environmental gradients and patchy distribution of habitats lead to small size and spatial isolation of populations and restrict gene flow. Agricultural land use has further increased the diversity of habitats below and above the treeline. We studied the consequences of the highly structured alpine landscape for evolutionary processes in four study plants: Epilobium fleischeri, Geum reptans, Campanula thyrsoides and Poa alpina. The main questions were: (1) How is genetic diversity distributed within and among populations and is it affected by altitude, population size or land use? (2) Do reproductive traits such as allocation to sexual or vegetative reproduction vary with altitude or land use? Furthermore, we studied if seed weight increases with altitude. Within-population genetic diversity of the four species was high and mostly not related to altitude and population size. Nevertheless, genetic differentiation among populations was pronounced and strongly increasing with distance. In Poa alpina genetic diversity was affected by land use. Results suggest considerable genetic drift among populations of alpine plants. Reproductive allocation was affected by altitude and land use in Poa alpina and by succession in Geum reptans. Seed weight was usually higher in alpine species than in related lowland species. We conclude that the evolutionary potential to respond to global change is mostly intact in alpine plants, even at high altitude. Phenotypic variability is shaped by adaptive as well as by random evolutionary processes; moreover plastic responses to growth conditions seem to be crucial for survival of plants in the alpine landscape.

Competition and fixation of cohorts of adaptive mutations under Fisher geometrical model

One of the simplest models of adaptation to a new environment is Fisher's Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations-mutation cohorts-along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation-FGM.