Integration of urban science and urban climate adaptation research: opportunities to advance climate action.

There is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.

A global horizon scan for urban evolutionary ecology.

Research on the evolutionary ecology of urban areas reveals how human-induced evolutionary changes affect biodiversity and essential ecosystem services. In a rapidly urbanizing world imposing many selective pressures, a time-sensitive goal is to identify the emergent issues and research priorities that affect the ecology and evolution of species within cities. Here, we report the results of a horizon scan of research questions in urban evolutionary ecology submitted by 100 interdisciplinary scholars. We identified 30 top questions organized into six themes that highlight priorities for future research. These research questions will require methodological advances and interdisciplinary collaborations, with continued revision as the field of urban evolutionary ecology expands with the rapid growth of cities.

Global urban environmental change drives adaptation in white clover.

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale.

Detecting patterns of vertebrate biodiversity across the multidimensional urban landscape.

Explicit characterisation of the complexity of urban landscapes is critical for understanding patterns of biodiversity and for detecting the underlying social and ecological processes that shape them. Urban environments exhibit variable heterogeneity and connectivity, influenced by different historical contingencies, that affect community assembly across scales. The multidimensional nature of urban disturbance and co-occurrence of multiple stressors can cause synergistic effects leading to nonlinear responses in populations and communities. Yet, current research design of urban ecology and evolutionary studies typically relies on simple representation of the parameter space that can be observed. Sampling approaches apply simple urban gradients such as linear transects in space or comparisons of urban sites across the urban mosaic accounting for a few variables. This rarely considers multiple dimensions and scales of biodiversity, and proves to be inadequate to explain observed patterns. We apply a multidimensional approach that integrates distinctive social, ecological and built characteristics of urban landscapes, representing variations along dimensions of heterogeneity, connectivity and historical contingency. Measuring species richness and beta diversity across 100 US metropolitan areas at the city and 1-km scales, we show that distinctive signatures of urban biodiversity can result from interactions between socioecological heterogeneity and connectivity, mediated by historical contingency.

Back to the Future: Reintegrating Biology to Understand How Past Eco-evolutionary Change Can Predict Future Outcomes.

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: (1) utilizing knowledge of biological systems to better inform eco-evolutionary models, (2) generating models with more accurate predictions, and (3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.

Integrating solutions to adapt cities for climate change.

Record climate extremes are reducing urban liveability, compounding inequality, and threatening infrastructure. Adaptation measures that integrate technological, nature-based, and social solutions can provide multiple co-benefits to address complex socioecological issues in cities while increasing resilience to potential impacts. However, there remain many challenges to developing and implementing integrated solutions. In this Viewpoint, we consider the value of integrating across the three solution sets, the challenges and potential enablers for integrating solution sets, and present examples of challenges and adopted solutions in three cities with different urban contexts and climates (Freiburg, Germany; Durban, South Africa; and Singapore). We conclude with a discussion of research directions and provide a road map to identify the actions that enable successful implementation of integrated climate solutions. We highlight the need for more systematic research that targets enabling environments for integration; achieving integrated solutions in different contexts to avoid maladaptation; simultaneously improving liveability, sustainability, and equality; and replicating via transfer and scale-up of local solutions. Cities in systematically disadvantaged countries (sometimes referred to as the Global South) are central to future urban development and must be prioritised. Helping decision makers and communities understand the potential opportunities associated with integrated solutions for climate change will encourage urgent and deliberate strides towards adapting cities to the dynamic climate reality.

Socio-eco-evolutionary dynamics in cities.

Cities are uniquely complex systems regulated by interactions and feedbacks between nature and human society. Characteristics of human society-including culture, economics, technology and politics-underlie social patterns and activity, creating a heterogeneous environment that can influence and be influenced by both ecological and evolutionary processes. Increasing research on urban ecology and evolutionary biology has coincided with growing interest in eco-evolutionary dynamics, which encompasses the interactions and reciprocal feedbacks between evolution and ecology. Research on both urban evolutionary biology and eco-evolutionary dynamics frequently focuses on contemporary evolution of species that have potentially substantial ecological-and even social-significance. Still, little work fully integrates urban evolutionary biology and eco-evolutionary dynamics, and rarely do researchers in either of these fields fully consider the role of human social patterns and processes. Because cities are fundamentally regulated by human activities, are inherently interconnected and are frequently undergoing social and economic transformation, they represent an opportunity for ecologists and evolutionary biologists to study urban "socio-eco-evolutionary dynamics." Through this new framework, we encourage researchers of urban ecology and evolution to fully integrate human social drivers and feedbacks to increase understanding and conservation of ecosystems, their functions and their contributions to people within and outside cities.

A roadmap for urban evolutionary ecology.

Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Global urban signatures of phenotypic change in animal and plant populations.

Humans challenge the phenotypic, genetic, and cultural makeup of species by affecting the fitness landscapes on which they evolve. Recent studies show that cities might play a major role in contemporary evolution by accelerating phenotypic changes in wildlife, including animals, plants, fungi, and other organisms. Many studies of ecoevolutionary change have focused on anthropogenic drivers, but none of these studies has specifically examined the role that urbanization plays in ecoevolution or explicitly examined its mechanisms. This paper presents evidence on the mechanisms linking urban development patterns to rapid evolutionary changes for species that play important functional roles in communities and ecosystems. Through a metaanalysis of experimental and observational studies reporting more than 1,600 phenotypic changes in species across multiple regions, we ask whether we can discriminate an urban signature of phenotypic change beyond the established natural baselines and other anthropogenic signals. We then assess the relative impact of five types of urban disturbances including habitat modifications, biotic interactions, habitat heterogeneity, novel disturbances, and social interactions. Our study shows a clear urban signal; rates of phenotypic change are greater in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to traits that affect ecosystem function, we can map potential ecoevolutionary implications of emerging patterns of urban agglomerations and uncover insights for maintaining key ecosystem functions upon which the sustainability of human well-being depends.

Urban driven phenotypic changes: empirical observations and theoretical implications for eco-evolutionary feedback.

Emerging evidence that cities drive micro-evolution raises the question of whether rapid urbanization of Earth might impact ecosystems by causing systemic changes in functional traits that regulate urban ecosystems' productivity and stability. Intraspecific trait variation-variation in organisms' morphological, physiological or behavioural characteristics stemming from genetic variability and phenotypic plasticity-has significant implications for ecological functions such as nutrient cycling and primary productivity. While it is well established that changes in ecological conditions can drive evolutionary change in species' traits that, in turn, can alter ecosystem function, an understanding of the reciprocal and simultaneous processes associated with such interactions is only beginning to emerge. In urban settings, the potential for rapid trait change may be exacerbated by multiple selection pressures operating simultaneously. This paper reviews evidence on mechanisms linking urban development patterns to rapid phenotypic changes, and differentiates phenotypic changes for which there is evidence of micro-evolution versus phenotypic changes which may represent plasticity. Studying how humans mediate phenotypic trait changes through urbanization could shed light on fundamental concepts in ecological and evolutionary theory. It can also contribute to our understanding of eco-evolutionary feedback and provide insights for maintaining ecosystem function over the long term.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'.

Eco-evolutionary dynamics in an urbanizing planet.

A great challenge for ecology in the coming decades is to understand the role humans play in eco-evolutionary dynamics. If, as emerging evidence shows, rapid evolutionary change affects ecosystem functioning and stability, current rapid environmental change and its evolutionary effects might have significant implications for ecological and human wellbeing on a relatively short time scale. Humans are major selective agents with potential for unprecedented evolutionary consequences for Earth's ecosystems, especially as cities expand rapidly. In this review, I identify emerging hypotheses on how urbanization drives eco-evolutionary dynamics. Studying how human-driven micro-evolutionary changes interact with ecological processes offers us the chance to advance our understanding of eco-evolutionary feedbacks and will provide new insights for maintaining biodiversity and ecosystem function over the long term.

Standardized evaluation methodology and reference database for evaluating IVUS image segmentation.

This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.

Automatic non-rigid temporal alignment of intravascular ultrasound sequences: method and quantitative validation.

Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages.

Relation between plaque type, plaque thickness, blood shear stress, and plaque stress in coronary arteries assessed by X-ray angiography and intravascular ultrasound.

PURPOSE: Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries. METHODS: First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations. RESULTS: The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall. CONCLUSIONS: Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed.

HoliMAb: a holistic approach for Media-Adventitia border detection in intravascular ultrasound.

We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed.

Automatic bifurcation detection in coronary IVUS sequences.

In this paper, we present a fully automatic method which identifies every bifurcation in an intravascular ultrasound (IVUS) sequence, the corresponding frames, the angular orientation with respect to the IVUS acquisition, and the extension. This goal is reached using a two-level classification scheme: first, a classifier is applied to a set of textural features extracted from each image of a sequence. A comparison among three state-of-the-art discriminative classifiers (AdaBoost, random forest, and support vector machine) is performed to identify the most suitable method for the branching detection task. Second, the results are improved by exploiting contextual information using a multiscale stacked sequential learning scheme. The results are then successively refined using a-priori information about branching dimensions and geometry. The proposed approach provides a robust tool for the quick review of pullback sequences, facilitating the evaluation of the lesion at bifurcation sites. The proposed method reaches an F-Measure score of 86.35%, while the F-Measure scores for inter- and intraobserver variability are 71.63% and 76.18%, respectively. The obtained results are positive. Especially, considering the branching detection task is very challenging, due to high variability in bifurcation dimensions and appearance.