Resonance in Physiologically Structured Population Models

Ecologists have long sought to understand how the dynamics of natural populations are affected by the environmental variation those populations experience. A transfer function is a useful tool for this purpose, as it uses linearization theory to show how the frequency spectrum of the fluctuations in a population's abundance relates to the frequency spectrum of environmental variation. Here, we show how to derive and to compute the transfer function for a continuous-time model of a population that is structured by a continuous individual-level state variable such as size. To illustrate, we derive, compute, and analyze the transfer function for a size-structured population model of stony corals with open recruitment, parameterized for a common Indo-Pacific coral species complex. This analysis identifies a sharp multi-decade resonance driven by space competition between existing coral colonies and incoming recruits. The resonant frequency is most strongly determined by the rate at which colonies grow, and the potential for resonant oscillations is greatest when colony growth is only weakly density-dependent. While these resonant oscillations are unlikely to be a predominant dynamical feature of degraded reefs, they suggest dynamical possibilities for marine invertebrates in more pristine waters. The size-structured model that we analyze is a leading example of a broader class of physiologically structured population models, and the methods we present should apply to a wide variety of models in this class.

Stony coral populations are more sensitive to changes in vital rates in disturbed environments

Reef-building corals, like many long-lived organisms, experience environmental change as a combination of separate but concurrent processes, some of which are gradual yet long-lasting, while others are more acute but short-lived. For corals, some chronic environmental stressors, such as rising temperature and ocean acidification, are thought to induce gradual changes in colonies' vital rates. Meanwhile, other environmental changes, such as the intensification of tropical cyclones, change the disturbance regime that corals experience. Here, we use a physiologically structured population model to explore how chronic environmental stressors that impact the vital rates of individual coral colonies interact with the intensity and magnitude of disturbance to affect coral population dynamics and cover. We find that, when disturbances are relatively benign, intraspecific density dependence driven by space competition partially buffers coral populations against gradual changes in vital rates. However, the impact of chronic stressors is amplified in more highly disturbed environments, because disturbance weakens the buffering effect of space competition. We also show that coral cover is more sensitive to changes in colony growth and mortality than to external recruitment, at least in open populations, and that space competition and size structure mediate the extent and pace of coral population recovery following a large-scale mortality event. Understanding the complex interplay among chronic environmental stressors, mass-mortality events, and population size structure sharpens our ability to manage and to restore coral-reef ecosystems in an increasingly disturbed future.

Drivers of elevational richness peaks, evaluated for trees in the east Himalaya

Along elevational gradients, species richness often peaks at intermediate elevations and not the base. Here we refine and test eight hypotheses to evaluate causes of a richness peak in trees of the eastern Himalaya. In the field, we enumerated trees in 50 plots of size 0.1 ha each at eight zones along an elevational gradient and compared richness patterns with interpolation of elevational ranges of species from a thorough review of literature, including floras from the plains of India. The maximum number of species peaks at similar elevations in the two data sets (at 500 m in the field sampling and between 500 m and 1,000 m in range interpolation); concordance between the methods implies that statistical artefacts are unlikely to explain the peak in the data. We reject most hypotheses (e.g., area, speciation rate, mixing of distinct floras). We find support for a model in which climate (actual evapotranspiration [AET] or its correlates) sets both the number of species and each species optimum, coupled with a geometric constraint. We consider that AET declines with elevation, but an abrupt change in the association of AET with geographical distance into the plains means that the location of highest AET, at the base of the mountain, receives range overlaps from fewer species than the location just above the base. We formalize this explanation with a mathematical model to show how this can generate the observed low-elevation richness peak.

Contest models highlight inherent inefficiencies of scientific funding competitions

Scientific research funding is allocated largely through a system of soliciting and ranking competitive grant proposals. In these competitions, the proposals themselves are not the deliverables that the funder seeks, but instead are used by the funder to screen for the most promising research ideas. Consequently, some of the funding program's impact on science is squandered because applying researchers must spend time writing proposals instead of doing science. To what extent does the community's aggregate investment in proposal preparation negate the scientific impact of the funding program? Are there alternative mechanisms for awarding funds that advance science more efficiently? We use the economic theory of contests to analyze how efficiently grant proposal competitions advance science, and compare them with recently proposed, partially randomized alternatives such as lotteries. We find that the effort researchers waste in writing proposals may be comparable to the total scientific value of the research that the funding supports, especially when only a few proposals can be funded. Moreover, when professional pressures motivate investigators to seek funding for reasons that extend beyond the value of the proposed science (e.g., promotion, prestige), the entire program can actually hamper scientific progress when the number of awards is small. We suggest that lost efficiency may be restored either by partial lotteries for funding or by funding researchers based on past scientific success instead of proposals for future work.

Scientists waste substantial time writing grant proposals, potentially squandering much of the scientific value of funding programs. This Meta-Research Article shows that, unfortunately, grant-proposal competitions are inevitably inefficient when the number of awards is small, but efficiency can be restored by awarding funds through a modified lottery, or by weighting past research success more heavily in funding decisions.

The grant proposal system compels researchers to devote substantial time to writing proposals that could have instead been used to do science. Here, we use the economic theory of contests to show that as fewer grants are funded, the value of the science that researchers forgo while preparing proposals can approach or exceed the value of the science that the funding program supports. As a result, much of the scientific impact of the funding program is squandered. Unfortunately, increased waste and reduced efficiency is inevitable in a grant proposal competition when the number of awards is small. How can scarce funds be allocated efficiently, then? As one alternative, we show that a partial lottery that selects proposals for funding randomly from among those that pass a qualifying standard can restore lost efficiency by reducing investigators' incentives to invest heavily in preparing proposals. Lotteries could also improve efficiency by compelling administrators to de-emphasize grant success as a primary measure of professional achievement. If lotteries are politically untenable, another remedy would be to fund researchers based on their previous research successes, although in such a way that avoids establishing barriers to entry for junior scientists or scientists from historically underrepresented demographic groups.

Evolution of host preference in anthropophilic mosquitoes

Background

Insecticide-treated bed nets (ITNs) have played a large role in reducing the burden of malaria. There is concern however regarding the potential of the mass distributions and use of ITNs to select for insecticide and behavioural resistance in mosquito populations. A key feature of the vectorial capacity of the major sub-Saharan African malaria vector Anopheles gambiae sensu stricto (s.s.) is its tendency to feed almost exclusively on humans. Here, an evolutionary model is used to investigate the potential for ITNs to select for increased zoophily in this highly anthropophilic species and how this is influenced by ecological and operational conditions.

Results

The evolution of a single trait, namely the tendency to accept cattle as hosts, is modelled in mosquito populations which initially only bite humans. Thus, the conditions under which a resource specialist would broaden its diet and become a generalist are investigated. The results indicate that in the absence of insecticide-treated nets, host specialization in mosquitoes is either driven toward human specialization (when humans are more abundant than alternative hosts), or displays evolutionary bistability. The latter implies that the evolutionary endpoint relies on the initial trait value of the population. Bed nets select for increased zoophily while in use. When ITNs are removed, whether or not the population reverts to anthropophagic or zoophagic behaviour depends on whether the intervention had been maintained sufficiently long to drive the population past the evolutionarily unstable point.

Conclusions

The use of ITNs is likely to select for an increase in the biting preference for cattle. Bed nets may thus alter the population composition of major vector species in a manner that has positive epidemiological ramifications. Whether populations are set on a trajectory toward increased zoophily following the cessation of intense bed net usage in an area depends on the composition of host communities as well as operational conditions. This has potential implications for bed net campaigns, particularly with an eye toward scaling down interventions following interruption of transmission. Further research on malaria mosquito feeding behaviour is warranted to explore the conditions under which such adaptive shifts may actually occur in the field.

Publication bias and the canonization of false facts

Science is facing a “replication crisis” in which many experimental findings cannot be replicated and are likely to be false. Does this imply that many scientific facts are false as well? To find out, we explore the process by which a claim becomes fact. We model the community’s confidence in a claim as a Markov process with successive published results shifting the degree of belief. Publication bias in favor of positive findings influences the distribution of published results. We find that unless a sufficient fraction of negative results are published, false claims frequently can become canonized as fact. Data-dredging, p-hacking, and similar behaviors exacerbate the problem. Should negative results become easier to publish as a claim approaches acceptance as a fact, however, true and false claims would be more readily distinguished. To the degree that the model reflects the real world, there may be serious concerns about the validity of purported facts in some disciplines.

DOI:http://dx.doi.org/10.7554/eLife.21451.001

Electrical conductivity of oxidized-graphenic nanoplatelets obtained from bamboo: effect of the oxygen content

The large-scale production of graphene and reduced-graphene oxide (rGO) requires low-cost and eco-friendly synthesis methods. We employed a new, simple, cost-effective pyrolytic method to synthetize oxidized-graphenic nanoplatelets (OGNP) using bamboo pyroligneous acid (BPA) as a source. Thorough analyses via high-resolution transmission electron microscopy and electron energy-loss spectroscopy provides a complete structural and chemical description at the local scale of these samples. In particular, we found that at the highest carbonization temperature the OGNP-BPA are mainly in a sp(2) bonding configuration (sp(2) fraction of 87%). To determine the electrical properties of single nanoplatelets, these were contacted by Pt nanowires deposited through focused-ion-beam-induced deposition techniques. Increased conductivity by two orders of magnitude is observed as oxygen content decreases from 17% to 5%, reaching a value of 2.3 × 10(3) S m(-1) at the lowest oxygen content. Temperature-dependent conductivity reveals a semiconductor transport behavior, described by the Mott three-dimensional variable range hopping mechanism. From the localization length, we estimate a band-gap value of 0.22(2) eV for an oxygen content of 5%. This investigation demonstrates the great potential of the OGNP-BPA for technological applications, given that their structural and electrical behavior is similar to the highly reduced rGO sheets obtained by more sophisticated conventional synthesis methods.

Predicting Pre-planting Risk of Stagonospora nodorum blotch in Winter Wheat Using Machine Learning Models

Pre-planting factors have been associated with the late-season severity of Stagonospora nodorum blotch (SNB), caused by the fungal pathogen Parastagonospora nodorum, in winter wheat (Triticum aestivum). The relative importance of these factors in the risk of SNB has not been determined and this knowledge can facilitate disease management decisions prior to planting of the wheat crop. In this study, we examined the performance of multiple regression (MR) and three machine learning algorithms namely artificial neural networks, categorical and regression trees, and random forests (RF), in predicting the pre-planting risk of SNB in wheat. Pre-planting factors tested as potential predictor variables were cultivar resistance, latitude, longitude, previous crop, seeding rate, seed treatment, tillage type, and wheat residue. Disease severity assessed at the end of the growing season was used as the response variable. The models were developed using 431 disease cases (unique combinations of predictors) collected from 2012 to 2014 and these cases were randomly divided into training, validation, and test datasets. Models were evaluated based on the regression of observed against predicted severity values of SNB, sensitivity-specificity ROC analysis, and the Kappa statistic. A strong relationship was observed between late-season severity of SNB and specific pre-planting factors in which latitude, longitude, wheat residue, and cultivar resistance were the most important predictors. The MR model explained 33% of variability in the data, while machine learning models explained 47 to 79% of the total variability. Similarly, the MR model correctly classified 74% of the disease cases, while machine learning models correctly classified 81 to 83% of these cases. Results show that the RF algorithm, which explained 79% of the variability within the data, was the most accurate in predicting the risk of SNB, with an accuracy rate of 93%. The RF algorithm could allow early assessment of the risk of SNB, facilitating sound disease management decisions prior to planting of wheat.

Environmental influences on mosquito foraging and integrated vector management can delay the evolution of behavioral resistance

Along with the scaled‐up distribution of long‐lasting insecticidal nets for malaria control has become concern about insecticide resistance. A related concern regards the evolution of host‐seeking periodicity from the nocturnal to the crepuscular periods of the day. Why we observe such shifts in some areas but not others and which methods could prove useful in managing such behavioral resistance remain open questions. We developed a foraging model to explore whether environmental conditions affect the evolution of behavioral resistance. We looked at the role of the abundance of blood hosts and nectar sources and investigated the potential of attractive toxic sugar baits for integrated control. Higher encounter rates with hosts and nectar sources allowed behaviorally resistant populations to persist at higher levels of bed net coverage. Whereas higher encounter rates with nectar increased the threshold where resistance emerged, higher encounter rates of hosts lowered this threshold. Adding sugar baits lowered the coverage level of bed nets required to eliminate the vector population. In certain environments, using lower bed net coverage levels together with toxic sugar baits may delay or prevent the evolution of behavioral resistance. Designing sustainable control strategies will depend on an understanding of vector behavior expressed in local environmental conditions.

HYPERSPECTRAL ANALYSIS FOR STANDOFF DETECTION OF DIMETHYL METHYLPHOSPHONATE ON BUILDING MATERIALS

Detecting organophosphates in indoor settings can greatly benefit from more efficient and faster methods of surveying large surface areas than conventional approaches, which sample small surface areas followed by extraction and analysis. This study examined a standoff detection technique utilizing hyperspectral imaging for analysis of building materials in near-real time. In this proof-of-concept study, dimethyl methylphosphonate (DMMP) was applied to stainless steel and laminate coupons and spectra were collected during active illumination. Absorbance bands at approximately 1275 cm^-1 and 1050 cm^-1 were associated with phosphorus-oxygen double bond (P=O) and phosphorus-oxygen-carbon (P-O-C) bond stretches of DMMP, respectively. The magnitude of these bands increased linearly (r² = 0.93) with DMMP across the full absorbance spectrum, between ν₁ = 877 cm^-1 to ν₂ = 1262 cm^-1. Comparisons between bare and contaminated surfaces on stainless steel using the spectral contrast angle technique indicated that the bare samples showed no sign of contamination, with large uniformly distributed contrast angles of 45°-55°, while the contaminated samples had smaller spectral contact angles of < 20° in the contaminated region and > 40° in the uncontaminated region. The laminate contaminated region exhibited contact angles of < 25°. To the best of our knowledge, this is the first report to demonstrate that hyperspectral imaging can be used to detect DMMP on building materials, with detection levels similar to concentrations expected for some organophosphate deposition scenarios.

The differential effects of increasing frequency and magnitude of extreme events on coral populations

Extreme events, which have profound ecological consequences, are changing in both frequency and magnitude with climate change. Because extreme temperatures induce coral bleaching, we can explore the relative impacts of changes in frequency and magnitude of high temperature events on coral reefs. Here, we combined climate projections and a dynamic population model to determine how changing bleaching regimes influence coral persistence. We additionally explored how coral traits and competition with macroalgae mediate changes in bleaching regimes. Our results predict that severe bleaching events reduce coral persistence more than frequent bleaching. Corals with low adult mortality and high growth rates are successful when bleaching is mild, but bleaching resistance is necessary to persist when bleaching is severe, regardless of frequency. The existence of macroalgae-dominated stable states reduces coral persistence and changes the relative importance of coral traits. Building on previous studies, our results predict that management efforts may need to prioritize protection of "weaker" corals with high adult mortality when bleaching is mild, and protection of "stronger" corals with high bleaching resistance when bleaching is severe. In summary, future reef projections and conservation targets depend on both local bleaching regimes and biodiversity.

The community ecology of pathogens: coinfection, coexistence and community composition

Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host-pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two-pathogen susceptible-infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species-diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology.

Floral isolation is the major reproductive barrier between a pair of rewarding orchid sister species

The crucial role of reproductive isolation in speciation has long been recognized; however, a limited number of studies quantify different isolation barriers and embed reproductive isolation in a phylogenetic context. In this study, we investigate reproductive isolation between the often sympatrically occurring orchid species, Gymnadenia conopsea and G. odoratissima. We examine the phylogenetic relationship between the two species and analyse floral isolation, fruit set and seed viability from interspecies crosses, as well as the ploidy level. Additionally, we quantify interspecies differences in floral signals and morphology. The results suggest that the two species have a sister-species relationship. In terms of reproductive isolation, we found complete floral isolation between the two species, but little to no post-pollination isolation; the species also mostly had the same ploidy level in the studied populations. We also show clear distinctions in floral signals, as well as in floral size and spur length. We propose that respective adaptation to short- vs. long-tongued pollinators was the driver of speciation in the here studied Gymnadenia species. Our study supports the key role of floral isolation in orchid speciation and shows that floral isolation is not restricted to highly specialized pollination systems, but can also occur between species with less specialized pollination.

Persistence and change in community composition of reef corals through present, past, and future climates

The reduction in coral cover on many contemporary tropical reefs suggests a different set of coral community assemblages will dominate future reefs. To evaluate the capacity of reef corals to persist over various time scales, we examined coral community dynamics in contemporary, fossil, and simulated future coral reef ecosystems. Based on studies between 1987 and 2012 at two locations in the Caribbean, and between 1981 and 2013 at five locations in the Indo-Pacific, we show that many coral genera declined in abundance, some showed no change in abundance, and a few coral genera increased in abundance. Whether the abundance of a genus declined, increased, or was conserved, was independent of coral family. An analysis of fossil-reef communities in the Caribbean revealed changes in numerical dominance and relative abundances of coral genera, and demonstrated that neither dominance nor taxon was associated with persistence. As coral family was a poor predictor of performance on contemporary reefs, a trait-based, dynamic, multi-patch model was developed to explore the phenotypic basis of ecological performance in a warmer future. Sensitivity analyses revealed that upon exposure to thermal stress, thermal tolerance, growth rate, and longevity were the most important predictors of coral persistence. Together, our results underscore the high variation in the rates and direction of change in coral abundances on contemporary and fossil reefs. Given this variation, it remains possible that coral reefs will be populated by a subset of the present coral fauna in a future that is warmer than the recent past.

Response diversity can increase ecological resilience to disturbance in coral reefs

Community-level resilience depends on the interaction between multiple populations that vary in individual responses to disturbance. For example, in tropical reefs, some corals can survive higher stress (resistance) while others exhibit faster recovery (engineering resilience) following disturbances such as thermal stress. While each type will negatively affect the other through competition, each might also benefit the other by reducing the potential for an additional competitor such as macroalgae to invade after a disturbance. To determine how community composition affects ecological resilience, we modeled coral-macroalgae interactions given either a resistant coral, a resilient coral, or both together. Having both coral types (i.e., response diversity) can lead to observable enhanced ecological resilience if (1) the resilient coral is not a superior competitor and (2) disturbance levels are high enough such that the resilient coral would collapse when considered alone. This enhanced resilience occurs through competitor-enabled rescue where each coral increases the potential for the other to recover from disturbance through external recruitment, such that both corals benefit from the presence of each other in terms of total cover and resilience. Therefore, conservation management aimed at protecting resilience under global change requires consideration of both diversity and connectivity between sites experiencing differential disturbance.

Biodiversity simultaneously enhances the production and stability of community biomass, but the effects are independent

To predict the ecological consequences of biodiversity loss, researchers have spent much time and effort quantifying how biological variation affects the magnitude and stability of ecological processes that underlie the functioning of ecosystems. Here we add to this work by looking at how biodiversity jointly impacts two aspects of ecosystem functioning at once: (1) the production of biomass at any single point in time (biomass/area or biomass/ volume), and (2) the stability of biomass production through time (the CV of changes in total community biomass through time). While it is often assumed that biodiversity simultaneously enhances both of these aspects of ecosystem functioning, the joint distribution of data describing how species richness regulates productivity and stability has yet to be quantified. Furthermore, analyses have yet to examine how diversity effects on production covary with diversity effects on stability. To overcome these two gaps, we reanalyzed the data from 34 experiments that have manipulated the richness of terrestrial plants or aquatic algae and measured how this aspect of biodiversity affects community biomass at multiple time points. Our reanalysis confirms that biodiversity does indeed simultaneously enhance both the production and stability of biomass in experimental systems, and this is broadly true for terrestrial and aquatic primary producers. However, the strength of diversity effects on biomass production is independent of diversity effects on temporal stability. The independence of effect sizes leads to two important conclusions. First, while it may be generally true that biodiversity enhances both productivity and stability, it is also true that the highest levels of productivity in a diverse community are not associated with the highest levels of stability. Thus, on average, diversity does not maximize the various aspects of ecosystem functioning we might wish to achieve in conservation and management. Second, knowing how biodiversity affects productivity gives no information about how diversity affects stability (or vice versa). Therefore, to predict the ecological changes that occur in ecosystems after extinction, we will need to develop separate mechanistic models for each independent aspect of ecosystem functioning.

Quantifying secondary pest outbreaks in cotton and their monetary cost with causal-inference statistics

Secondary pest outbreaks occur when the use of a pesticide to reduce densities of an unwanted target pest species triggers subsequent outbreaks of other pest species. Although secondary pest outbreaks are thought to be familiar in agriculture, their rigorous documentation is made difficult by the challenges of performing randomized experiments at suitable scales. Here, we quantify the frequency and monetary cost of secondary pest outbreaks elicited by early-season applications of broad-spectrum insecticides to control the plant bug Lygus spp. (primarily L. hesperus) in cotton grown in the San Joaquin Valley, California, USA. We do so by analyzing pest-control management practices for 969 cotton fields spanning nine years and 11 private ranches. Our analysis uses statistical methods to draw formal causal inferences from nonexperimental data that have become popular in public health and economics, but that are not yet widely known in ecology or agriculture. We find that, in fields that received an early-season broad-spectrum insecticide treatment for Lygus, 20.2% +/- 4.4% (mean +/- SE) of late-season pesticide costs were attributable to secondary pest outbreaks elicited by the early-season insecticide application for Lygus. In 2010 U.S. dollars, this equates to an additional $6.00 +/- $1.30 (mean +/- SE) per acre in management costs. To the extent that secondary pest outbreaks may be driven by eliminating pests' natural enemies, these figures place a lower bound on the monetary value of ecosystem services provided by native communities of arthropod predators and parasitoids in this agricultural system.

Ecoinformatics for integrated pest management: expanding the applied insect ecologist's tool-kit

Experimentation has been the cornerstone of much of integrated pest management (IPM) research. Here, we aim to open a discussion on the possible merits of expanding the use of observational studies, and in particular the use of data from farmers or private pest management consultants in "ecoinformatics" studies, as tools that might complement traditional, experimental research. The manifold advantages of experimentation are widely appreciated: experiments provide definitive inferences regarding causal relationships between key variables, can produce uniform and high-quality data sets, and are highly flexible in the treatments that can be evaluated. Perhaps less widely considered, however, are the possible disadvantages of experimental research. Using the yield-impact study to focus the discussion, we address some reasons why observational or ecoinformatics approaches might be attractive as complements to experimentation. A survey of the literature suggests that many contemporary yield-impact studies lack sufficient statistical power to resolve the small, but economically important, effects on crop yield that shape pest management decision-making by farmers. Ecoinformatics-based data sets can be substantially larger than experimental data sets and therefore hold out the promise of enhanced power. Ecoinformatics approaches also address problems at the spatial and temporal scales at which farming is conducted, can achieve higher levels of "external validity," and can allow researchers to efficiently screen many variables during the initial, exploratory phases of research projects. Experimental, observational, and ecoinformatics-based approaches may, if used together, provide more efficient solutions to problems in pest management than can any single approach, used in isolation.

Noninvasive genomic detection of melanoma

BACKGROUND

Early detection and treatment of melanoma is important for optimal clinical outcome, leading to biopsy of pigmented lesions deemed suspicious for the disease. The vast majority of such lesions are benign. Thus, a more objective and accurate means for detection of melanoma is needed to identify lesions for excision.

OBJECTIVES

To provide proof-of-principle that epidermal genetic information retrieval (EGIR™; DermTech International, La Jolla, CA, U.S.A.), a method that noninvasively samples cells from stratum corneum by means of adhesive tape stripping, can be used to discern melanomas from naevi.

METHODS

Skin overlying pigmented lesions clinically suspicious for melanoma was harvested using EGIR. RNA isolated from the tapes was amplified and gene expression profiled. All lesions were removed for histopathological evaluation.

RESULTS

Supervised analysis of the microarray data identified 312 genes differentially expressed between melanomas, naevi and normal skin specimens (P<0·001, false discovery rate q<0·05). Surprisingly, many of these genes are known to have a role in melanocyte development and physiology, melanoma, cancer, and cell growth control. Subsequent class prediction modelling of a training dataset, consisting of 37 melanomas and 37 naevi, discovered a 17-gene classifier that discriminates these skin lesions. Upon testing with an independent dataset, this classifier discerned in situ and invasive melanomas from naevi with 100% sensitivity and 88% specificity, with an area under the curve for the receiver operating characteristic of 0·955.

CONCLUSIONS

These results demonstrate that EGIR-harvested specimens can be used to detect melanoma accurately by means of a 17-gene genomic biomarker.

Canopy and litter ant assemblages share similar climate-species density relationships

Tropical forest canopies house most of the globe's diversity, yet little is known about global patterns and drivers of canopy diversity. Here, we present models of ant species density, using climate, abundance and habitat (i.e. canopy versus litter) as predictors. Ant species density is positively associated with temperature and precipitation, and negatively (or non-significantly) associated with two metrics of seasonality, precipitation seasonality and temperature range. Ant species density was significantly higher in canopy samples, but this difference disappeared once abundance was considered. Thus, apparent differences in species density between canopy and litter samples are probably owing to differences in abundance-diversity relationships, and not differences in climate-diversity relationships. Thus, it appears that canopy and litter ant assemblages share a common abundance-diversity relationship influenced by similar but not identical climatic drivers.

Plant species loss decreases arthropod diversity and shifts trophic structure

Plant diversity is predicted to be positively linked to the diversity of herbivores and predators in a foodweb. Yet, the relationship between plant and animal diversity is explained by a variety of competing hypotheses, with mixed empirical results for each hypothesis. We sampled arthropods for over a decade in an experiment that manipulated the number of grassland plant species. We found that herbivore and predator species richness were strongly, positively related to plant species richness, and that these relationships were caused by different mechanisms at herbivore and predator trophic levels. Even more dramatic was the threefold increase, from low- to high-plant species richness, in abundances of predatory and parasitoid arthropods relative to their herbivorous prey. Our results demonstrate that, over the long term, the loss of plant species propagates through food webs, greatly decreasing arthropod species richness, shifting a predator-dominated trophic structure to being herbivore dominated, and likely impacting ecosystem functioning and services.

Does productivity drive diversity or vice versa? A test of the multivariate productivity-diversity hypothesis in streams

The idea that productivity regulates species diversity is deeply ingrained in the field of ecology. Yet, over the past few decades, an increasing number of experiments have shown that species diversity controls, rather than simply responds to, biomass production. These contrasting perspectives have led to a seeming paradox: Is diversity the cause or the consequence of biological production? Here we present empirical evidence for the multivariate productivity-diversity (MPD) hypothesis, which argues that differing perspectives on productivity-diversity relationships can be resolved by recognizing that historical research has focused on how resource supply regulates both the productivity and richness of local competitors, whereas more recent studies have focused on how the richness of a colonist pool regulates the efficiency by which resources are captured and converted into new tissue. The MPD hypothesis predicts that three pathways operate concurrently to generate productivity diversity relationships in nature: (1) resource supply directly limits the standing biomass and/or rate of new production by primary producers, (2) producer biomass is directly influenced by the richness of species that locally compete for resources, and (3) resource supply rate indirectly affects producer biomass by influencing the fraction of species from a colonist pool that locally coexist. To examine whether this set of pathways explains covariation between productivity and diversity in natural streams, we used nutrient-diffusing agar "patches" to manipulate resource supply rates in 20 streams throughout the Sierra Nevada mountain range, California, USA. We then measured the fraction of periphyton species from the stream colonist pool co-occurring on each nutrient patch, as well as the standing biomass and rates of primary production. Natural patterns of covariation agreed with predictions of the MPD hypothesis. Algal biomass was an increasing function of nutrient supply, and an increasing function of local richness. The fraction of species from the colonist pool found co-occurring on a patch was a concave-down function of nutrient supply, causing nutrients to indirectly affect biomass via control over local richness. These results suggest that the MPD hypothesis is a viable explanation of patterns of diversity and productivity in natural stream ecosystems, and that it has potential to merge the historical view that productivity drives diversity with a parallel view that diversity drives productivity.

Separating the influence of resource 'availability' from resource 'imbalance' on productivity-diversity relationships

One of the oldest and richest questions in biology is that of how species diversity is related to the availability of resources that limit the productivity of ecosystems. Researchers from a variety of disciplines have pursued this question from at least three different theoretical perspectives. Species energy theory has argued that the summed quantities of all resources influence species richness by controlling population sizes and the probability of stochastic extinction. Resource ratio theory has argued that the imbalance in the supply of two or more resources, relative to the stoichiometric needs of the competitors, can dictate the strength of competition and, in turn, the diversity of coexisting species. In contrast to these, the field of Biodiversity and Ecosystem Functioning has argued that species diversity acts as an independent variable that controls how efficiently limited resources are utilized and converted into new tissue. Here we propose that all three of these fields give necessary, but not sufficient, conditions to explain productivity-diversity relationships (PDR) in nature. However, when taken collectively, these three paradigms suggest that PDR can be explained by interactions among four distinct, non-interchangeable variables: (i) the overall quantity of limiting resources, (ii) the stoichiometric ratios of different limiting resources, (iii) the summed biomass produced by a group of potential competitors and (iv) the richness of co-occurring species in a local competitive community. We detail a new multivariate hypothesis that outlines one way in which these four variables are directly and indirectly related to one another. We show how the predictions of this model can be fit to patterns of covariation relating the richness and biomass of lake phytoplankton to three biologically essential resources (N, P and light) in a large number of Norwegian lakes.