Apps can help bridge restoration science and restoration practice

Scientists need to find innovative ways to communicate their findings with restoration practitioners in an era of global change. Apps are a promising bridge between restoration science and practice because they apply broad scientific concepts to specific situations. For example, habitat connectivity promotes ecological function, but practitioners lack ways to incorporate connectivity into decision‐making. We created an app where users calculate how habitat restoration or loss affects connectivity. By providing our app as an example and discussing the benefits and challenges in creating apps for practitioners, we encourage other restoration ecologists to similarly create apps that bridge science with practice.     

A Smartphone Ecological Momentary Assessment/Intervention “App” for Collecting Real-Time Data and Promoting Self-Awareness

We have designed a flexible ecological momentary assessment/intervention smartphone (EMA/EMI) “app”. We examine the utility of this app for collecting real-time data, and assessing intra-subject variability, by using it to assess how freshman undergraduates spend their time. We also explore whether its use can promote greater self-awareness. Participants were randomly divided into an experimental group, who used the app, and a control group, who did not. We used the app to collect both randomized in-the-moment data as well as end-of-day data to assess time use. Using a posttest survey we asked participants questions about how they spent time throughout the school semester. We also asked the experimental group about their experience with the app. Among other findings, 80.49% participants indicated that they became more aware of how they spent their time using the app. Corroborating this report, among the experimental group, end-of-semester self-assessment of time spent wasted, and time spent using electronics recreationally, predicted semester GPA at a strength comparable to high school GPA and ACT score (two of the best single predictors for first semester college GPA), but had no correlation among controls. We discuss the advantages and limitations of using apps, such as ours, for EMA and/or EMI.     

How smartphones are changing the face of mobile and participatory healthcare: an overview,with example from eCAALYX

The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of health and healthcare smartphone apps (applications) on the market today, including emerging trends and market uptake. Platforms available today include Android, Apple iOS, RIM BlackBerry, Symbian, and Windows (Windows Mobile 6.x and the emerging Windows Phone 7 platform). The paper covers apps targeting both laypersons/patients and healthcare professionals in various scenarios, e.g., health, fitness and lifestyle education and management apps; ambient assisted living apps; continuing professional education tools; and apps for public health surveillance. Among the surveyed apps are those assisting in chronic disease management, whether as standalone apps or part of a BAN (Body Area Network) and remote server configuration. We describe in detail the development of a smartphone app within eCAALYX (Enhanced Complete Ambient Assisted Living Experiment, 2009-2012), an EU-funded project for older people with multiple chronic conditions. The eCAALYX Android smartphone app receives input from a BAN (a patient-wearable smart garment with wireless health sensors) and the GPS (Global Positioning System) location sensor in the smartphone, and communicates over the Internet with a remote server accessible by healthcare professionals who are in charge of the remote monitoring and management of the older patient with multiple chronic conditions. Finally, we briefly discuss barriers to adoption of health and healthcare smartphone apps (e.g., cost, network bandwidth and battery power efficiency, usability, privacy issues, etc.), as well as some workarounds to mitigate those barriers.     

mHealth in Urology: A Review of Experts’ Involvement in App Development

IntroductionSmartphones are increasingly playing a role in healthcare and previous studies assessing medical applications (apps) have raised concerns about lack of expert involvement and low content accuracy. However, there are no such studies in Urology. We reviewed Urology apps with the aim of assessing the level of participation of healthcare professionals (HCP) and scientific Urology associations in their development.ResultsThe search yielded 372 apps, of which 150 were specific for Urology. A fifth of all apps had no HCP involvement (20.7%) and only a third had been developed with a scientific Urology association (34.7%). The lowest percentage of HCP (13.4%) and urological association (1.9%) involvement was in apps designed for the general population. Furthermore, there was no contribution from an Urology society in "Electronic Medical Record" nor in "Patient Information" apps. A limitation of the study is that only Android and iOS apps were reviewed.ConclusionsDespite the increasing Mobile Health (mHealth) market, this is the first study that demonstrates the lack of expert participation in the design of Urology apps, particularly in apps designed for the general public. Until clear regulation is enforced, the urological community should help regulate app development. Maintaining a register of certified apps or issuing an official scientific seal of approval could improve overall app quality. We propose that urologists become stakeholders in mHealth, shaping future app design and promoting peer-review app validation.     

Crowdsourcing Language Change with Smartphone Applications

Crowdsourcing linguistic phenomena with smartphone applications is relatively new. In linguistics, apps have predominantly been developed to create pronunciation dictionaries, to train acoustic models, and to archive endangered languages. This paper presents the first account of how apps can be used to collect data suitable for documenting language change: we created an app, Dialäkt Äpp (DÄ), which predicts users’ dialects. For 16 linguistic variables, users select a dialectal variant from a drop-down menu. DÄ then geographically locates the user’s dialect by suggesting a list of communes where dialect variants most similar to their choices are used. Underlying this prediction are 16 maps from the historical Linguistic Atlas of German-speaking Switzerland, which documents the linguistic situation around 1950. Where users disagree with the prediction, they can indicate what they consider to be their dialect’s location. With this information, the 16 variables can be assessed for language change. Thanks to the playfulness of its functionality, DÄ has reached many users; our linguistic analyses are based on data from nearly 60,000 speakers. Results reveal a relative stability for phonetic variables, while lexical and morphological variables seem more prone to change. Crowdsourcing large amounts of dialect data with smartphone apps has the potential to complement existing data collection techniques and to provide evidence that traditional methods cannot, with normal resources, hope to gather. Nonetheless, it is important to emphasize a range of methodological caveats, including sparse knowledge of users’ linguistic backgrounds (users only indicate age, sex) and users’ self-declaration of their dialect. These are discussed and evaluated in detail here. Findings remain intriguing nevertheless: as a means of quality control, we report that traditional dialectological methods have revealed trends similar to those found by the app. This underlines the validity of the crowdsourcing method. We are presently extending DÄ architecture to other languages.     

From infanticide to parental care: why spatial structure can help adults be good parents

We investigate the evolution of parental care and cannibalism in a spatially structured population where adults can either help or kill juveniles in their neighborhood. We show that spatial structure can reverse the selective pressures on adult behavior, leading to the evolution of parental care, whereas the nonspatial model predicts that cannibalism is the sole evolutionary outcome. Our analysis emphasizes that evolution of such spatially structured populations is best understood at the level of the cluster of invading mutants, and we define invasion fitness as the growth rate of that cluster. We derive an analytical expression for the selective pressures on the trait and show that relatedness and Hamilton's rule are recovered as emergent properties of the spatial ecological dynamics. When adults can also help other adults, the benefits to each class of recipients are weighted by the class reproductive value, a result consistent with that of other models of kin selection. Finally, we advocate a different approach to moment equations and argue that even though the development of moment closure approximations is a necessary line of research, much-needed ecological and evolutionary insight can be gained by studying the unclosed moment equations.     

Information use in colonial living

Despite the fact that many animals live in groups, there is still no clear consensus about the ecological or evolutionary mechanisms underlying colonial living. Recently, research has suggested that colonies may be important as sources of social information. The ready availability of information from conspecifics allows animals to make better decisions about avoiding predators, reducing brood parasitism, migratory phenology, mate choice, habitat choice and foraging. These choices can play a large part in the development and maintenance of colonies. Here we review the types of information provided by colonial animals and examine the different ways in which decision‐making in colonies can be enhanced by social information. We discuss what roles information might take in the evolution, formation and maintenance of colonies. In the process, we illustrate that information use permeates all aspects of colonial living.     

Challenges for identifying functionally important genetic variation: the promise of combining complementary research strategies

Strategies for the identification of functional genetic variation underlying phenotypic traits of ecological and evolutionary importance have received considerable attention in the literature recently. This paper aims to bring together and compare the relative strengths and limitations of various potentially useful research strategies for dissecting functionally important genetic variation in a wide range of organisms. We briefly explore the relative strengths and limitations of traditional and emerging approaches and evaluate their potential use in free-living populations. While it is likely that much of the progress in functional genetic analyses will rely on progress in traditional model species, it is clear that with prudent choices of methods and appropriate sampling designs, much headway can be also made in a diverse range of species. We suggest that combining research approaches targeting different functional and biological levels can potentially increase understanding the genetic basis of ecological and evolutionary processes both in model and non-model organisms.     

Towards the co‐ordination of terrestrial ecosystem protocols across European research infrastructures

The study of ecosystem processes over multiple scales of space and time is often best achieved using comparable data from multiple sites. Yet, long‐term ecological observatories have often developed their own data collection protocols. Here, we address this problem by proposing a set of ecological protocols suitable for widespread adoption by the ecological community. Scientists from the European ecological research community prioritized terrestrial ecosystem parameters that could benefit from a more consistent approach to data collection within the resources available at most long‐term ecological observatories. Parameters for which standard methods are in widespread use, or for which methods are evolving rapidly, were not selected. Protocols were developed by domain experts, building on existing methods where possible, and refined through a process of field testing and training. They address above‐ground plant biomass; decomposition; land use and management; leaf area index; soil mesofaunal diversity; soil C and N stocks, and greenhouse gas emissions from soils. These complement existing methods to provide a complete assessment of ecological integrity. These protocols offer integrated approaches to ecological data collection that are low cost and are starting to be used across the European Long Term Ecological Research community.     

Digitally supported public health interventions through the lens of structural injustice: The case of mobile apps responding to violence against women and girls

Mobile applications (apps) have gained significant popularity as a new intervention strategy responding to violence against women and girls. Despite their growing relevance, an assessment from the perspective of public health ethics is still lacking. Here, we base our discussion on the understanding of violence against women and girls as a multidimensional, global public health issue on structural, societal and individual levels and situate it within the theoretical framework of structural injustice, including epistemic injustice. Based on a systematic app review we previously conducted, we evaluate the content and functions of apps through the lens of structural injustice. We argue that technological solutions such as apps may be a useful tool in the fight against violence against women and girls but have to be situated within the broader frame of public health that considers the structural dimensions of such violence. Ultimately, the concerns raised by structural injustice are—alongside key concerns of safety, data privacy, importance of human supportive contact, and so forth—crucial dimensions in the ethical assessment of such apps. However, research on the role and relevance of apps as strategies to address the structural and epistemic dimensions of violence remains scarce. This article aims to provide a foundation for further discussion in this area and could be applicable to other areas in public health policy and practice.     

Eco‐evolutionary partitioning metrics: assessing the importance of ecological and evolutionary contributions to population and community change

Interest in eco‐evolutionary dynamics is rapidly increasing thanks to ground‐breaking research indicating that evolution can occur rapidly and can alter the outcome of ecological processes. A key challenge in this sub‐discipline is establishing how important the contribution of evolutionary and ecological processes and their interactions are to observed shifts in population and community characteristics. Although a variety of metrics to separate and quantify the effects of evolutionary and ecological contributions to observed trait changes have been used, they often allocate fractions of observed changes to ecology and evolution in different ways. We used a mathematical and numerical comparison of two commonly used frameworks – the Price equation and reaction norms – to reveal that the Price equation cannot partition genetic from non‐genetic trait change within lineages, whereas the reaction norm approach cannot partition among‐ from within‐lineage trait change. We developed a new metric that combines the strengths of both Price‐based and reaction norm metrics, extended all metrics to analyse community change and also incorporated extinction and colonisation of species in these metrics. Depending on whether our new metric is applied to populations or communities, it can correctly separate intraspecific, interspecific, evolutionary, non‐evolutionary and interacting eco‐evolutionary contributions to trait change.     

C3-PRO: Connecting ResearchKit to the Health System Using i2b2 and FHIR

A renewed interest by consumer information technology giants in the healthcare domain is focused on transforming smartphones into personal health data storage devices. With the introduction of the open source ResearchKit, Apple provides a framework for researchers to inform and consent research subjects, and to readily collect personal health data and patient reported outcomes (PRO) from distributed populations. However, being research backend agnostic, ResearchKit does not provide data transmission facilities, leaving research apps disconnected from the health system. Personal health data and PROs are of the most value when presented in context along with health system data. Our aim was to build a toolchain that allows easy and secure integration of personal health and PRO data into an open source platform widely adopted across 140 academic medical centers. We present C3-PRO: the Consent, Contact, and Community framework for Patient Reported Outcomes. This open source toolchain connects, in a standards-compliant fashion, any ResearchKit app to the widely-used clinical research infrastructure Informatics for Integrating Biology and the Bedside (i2b2). C3-PRO leverages the emerging health data standard Fast Healthcare Interoperability Resources (FHIR).     

The EcoData Retriever: Improving Access to Existing Ecological Data

Ecological research relies increasingly on the use of previously collected data. Use of existing datasets allows questions to be addressed more quickly, more generally, and at larger scales than would otherwise be possible. As a result of large-scale data collection efforts, and an increasing emphasis on data publication by journals and funding agencies, a large and ever-increasing amount of ecological data is now publicly available via the internet. Most ecological datasets do not adhere to any agreed-upon standards in format, data structure or method of access. Some may be broken up across multiple files, stored in compressed archives, and violate basic principles of data structure. As a result acquiring and utilizing available datasets can be a time consuming and error prone process. The EcoData Retriever is an extensible software framework which automates the tasks of discovering, downloading, and reformatting ecological data files for storage in a local data file or relational database. The automation of these tasks saves significant time for researchers and substantially reduces the likelihood of errors resulting from manual data manipulation and unfamiliarity with the complexities of individual datasets.     

The Trajectory of Dispersal Research in Conservation Biology. Systematic Review

Dispersal knowledge is essential for conservation management, and demand is growing. But are we accumulating dispersal knowledge at a pace that can meet the demand? To answer this question we tested for changes in dispersal data collection and use over time. Our systematic review of 655 conservation-related publications compared five topics: climate change, habitat restoration, population viability analysis, land planning (systematic conservation planning) and invasive species. We analysed temporal changes in the: (i) questions asked by dispersal-related research; (ii) methods used to study dispersal; (iii) the quality of dispersal data; (iv) extent that dispersal knowledge is lacking, and; (v) likely consequences of limited dispersal knowledge. Research questions have changed little over time; the same problems examined in the 1990s are still being addressed. The most common methods used to study dispersal were occupancy data, expert opinion and modelling, which often provided indirect, low quality information about dispersal. Although use of genetics for estimating dispersal has increased, new ecological and genetic methods for measuring dispersal are not yet widely adopted. Almost half of the papers identified knowledge gaps related to dispersal. Limited dispersal knowledge often made it impossible to discover ecological processes or compromised conservation outcomes. The quality of dispersal data used in climate change research has increased since the 1990s. In comparison, restoration ecology inadequately addresses large-scale process, whilst the gap between knowledge accumulation and growth in applications may be increasing in land planning. To overcome apparent stagnation in collection and use of dispersal knowledge, researchers need to: (i) improve the quality of available data using new approaches; (ii) understand the complementarities of different methods and; (iii) define the value of different kinds of dispersal information for supporting management decisions. Ambitious, multi-disciplinary research programs studying many species are critical for advancing dispersal research.     

Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change—A review

Marine life is controlled by multiple physical and chemical drivers and by diverse ecological processes. Many of these oceanic properties are being altered by climate change and other anthropogenic pressures. Hence, identifying the influences of multifaceted ocean change, from local to global scales, is a complex task. To guide policy‐making and make projections of the future of the marine biosphere, it is essential to understand biological responses at physiological, evolutionary and ecological levels. Here, we contrast and compare different approaches to multiple driver experiments that aim to elucidate biological responses to a complex matrix of ocean global change. We present the benefits and the challenges of each approach with a focus on marine research, and guidelines to navigate through these different categories to help identify strategies that might best address research questions in fundamental physiology, experimental evolutionary biology and community ecology. Our review reveals that the field of multiple driver research is being pulled in complementary directions: the need for reductionist approaches to obtain process‐oriented, mechanistic understanding and a requirement to quantify responses to projected future scenarios of ocean change. We conclude the review with recommendations on how best to align different experimental approaches to contribute fundamental information needed for science‐based policy formulation.     

Assessing variation in life‐history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists

Mixed models are now well‐established methods in ecology and evolution because they allow accounting for and quantifying within‐ and between‐individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi‐modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life‐history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life‐history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long‐term studies of large mammals to illustrate the potential of using mixture models for assessing within‐population variation in life‐history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life‐history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users.     

Diversification in evolutionary arenas—Assessment and synthesis

Understanding how and why rates of evolutionary diversification vary is a key issue in evolutionary biology, ecology, and biogeography. Evolutionary rates are the net result of interacting processes summarized under concepts such as adaptive radiation and evolutionary stasis. Here, we review the central concepts in the evolutionary diversification literature and synthesize these into a simple, general framework for studying rates of diversification and quantifying their underlying dynamics, which can be applied across clades and regions, and across spatial and temporal scales. Our framework describes the diversification rate (d) as a function of the abiotic environment (a), the biotic environment (b), and clade‐specific phenotypes or traits (c); thus, d ~ a,b,c. We refer to the four components (a–d) and their interactions collectively as the “Evolutionary Arena.” We outline analytical approaches to this framework and present a case study on conifers, for which we parameterize the general model. We also discuss three conceptual examples: the Lupinus radiation in the Andes in the context of emerging ecological opportunity and fluctuating connectivity due to climatic oscillations; oceanic island radiations in the context of island formation and erosion; and biotically driven radiations of the Mediterranean orchid genus Ophrys. The results of the conifer case study are consistent with the long‐standing scenario that low competition and high rates of niche evolution promote diversification. The conceptual examples illustrate how using the synthetic Evolutionary Arena framework helps to identify and structure future directions for research on evolutionary radiations. In this way, the Evolutionary Arena framework promotes a more general understanding of variation in evolutionary rates by making quantitative results comparable between case studies, thereby allowing new syntheses of evolutionary and ecological processes to emerge.     

Testing the ecological consequences of evolutionary change using elements

Understanding the ecological consequences of evolutionary change is a central challenge in contemporary biology. We propose a framework based on the ~25 elements represented in biology, which can serve as a conduit for a general exploration of poorly understood evolution‐to‐ecology links. In this framework, known as ecological stoichiometry, the quantity of elements in the inorganic realm is a fundamental environment, while the flow of elements from the abiotic to the biotic realm is due to the action of genomes, with the unused elements excreted back into the inorganic realm affecting ecological processes at higher levels of organization. Ecological stoichiometry purposefully assumes distinct elemental composition of species, enabling powerful predictions about the ecological functions of species. However, this assumption results in a simplified view of the evolutionary mechanisms underlying diversification in the elemental composition of species. Recent research indicates substantial intraspecific variation in elemental composition and associated ecological functions such as nutrient excretion. We posit that attention to intraspecific variation in elemental composition will facilitate a synthesis of stoichiometric information in light of population genetics theory for a rigorous exploration of the ecological consequences of evolutionary change.     

Influence of killing method on Lepidoptera DNA barcode recovery

The global DNA barcoding initiative has revolutionized the field of biodiversity research. Such large‐scale sequencing projects require the collection of large numbers of specimens, which need to be killed and preserved in a way that is both DNA‐friendly and which will keep voucher specimens in good condition for later study. Factors such as time since collection, correct storage (exposure to free water and heat) and DNA extraction protocol are known to play a role in the success of downstream molecular applications. Limited data are available on the most efficient, DNA‐friendly protocol for killing. In this study, we evaluate the quality of DNA barcode (cytochrome oxidase I) sequences amplified from DNA extracted from specimens collected using three different killing methods (ethyl acetate, cyanide and freezing). Previous studies have suggested that chemicals, such as ethyl acetate and formaldehyde, degraded DNA and as such may not be appropriate for the collection of insects for DNA‐based research. All Lepidoptera collected produced DNA barcodes of good quality, and our study found no clear difference in nucleotide signal strength, probability of incorrect base calling and phylogenetic utility among the three different treatment groups. Our findings suggest that ethyl acetate, cyanide and freezing can all be used to collect specimens for DNA analysis.     

Molecular‐clock methods for estimating evolutionary rates and timescales

The molecular clock presents a means of estimating evolutionary rates and timescales using genetic data. These estimates can lead to important insights into evolutionary processes and mechanisms, as well as providing a framework for further biological analyses. To deal with rate variation among genes and among lineages, a diverse range of molecular‐clock methods have been developed. These methods have been implemented in various software packages and differ in their statistical properties, ability to handle different models of rate variation, capacity to incorporate various forms of calibrating information and tractability for analysing large data sets. Choosing a suitable molecular‐clock model can be a challenging exercise, but a number of model‐selection techniques are available. In this review, we describe the different forms of evolutionary rate heterogeneity and explain how they can be accommodated in molecular‐clock analyses. We provide an outline of the various clock methods and models that are available, including the strict clock, local clocks, discrete clocks and relaxed clocks. Techniques for calibration and clock‐model selection are also described, along with methods for handling multilocus data sets. We conclude our review with some comments about the future of molecular clocks.