Evolutionary dynamics of biological auctions

Many scenarios in the living world, where individual organisms compete for winning positions (or resources), have properties of auctions. Here we study the evolution of bids in biological auctions. For each auction, n individuals are drawn at random from a population of size N. Each individual makes a bid which entails a cost. The winner obtains a benefit of a certain value. Costs and benefits are translated into reproductive success (fitness). Therefore, successful bidding strategies spread in the population. We compare two types of auctions. In “biological all-pay auctions”, the costs are the bid for every participating individual. In “biological second price all-pay auctions”, the cost for everyone other than the winner is the bid, but the cost for the winner is the second highest bid. Second price all-pay auctions are generalizations of the “war of attrition” introduced by Maynard Smith. We study evolutionary dynamics in both types of auctions. We calculate pairwise invasion plots and evolutionarily stable distributions over the continuous strategy space. We find that the average bid in second price all-pay auctions is higher than in all-pay auctions, but the average cost for the winner is similar in both auctions. In both cases, the average bid is a declining function of the number of participants, n. The more individuals participate in an auction the smaller is the chance of winning, and thus expensive bids must be avoided.     

Rationality, irrationality and escalating behavior in lowest unique bid auctions

Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions--lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce food, we find that agents adopt Lévy flight search strategies in their exploration of "bid space". The Lévy regime, which is characterized by a power-law decaying probability distribution of step lengths, holds over nearly three orders of magnitude. We develop a quantitative model for lowest unique bid online auctions that reveals that agents use nearly optimal bidding strategies. However, agents participating in these auctions do not optimize their financial gain. Indeed, as long as there are many auction participants, a rational profit optimizing agent would choose not to participate in these auction markets.     

The Inability of the Consumer Price Index to Measure “Cost of Quality” of Medical Care,Report of the Bureau of Research and Planning

The Consumer Price Index (CPI) of the Bureau of Labor Statistics is an index which measures the price changes of 300 goods and services. Among these 300 items are several which reflect price changes for selected health care and medical care services. These comprise the medical care index and physician fee index, depending on what services are being measured.The Physician Fee Index is based upon charges for five procedures rendered by physicians: Appendectomy, tonsillectomy, obstetrical delivery, home visits and office visits.Although the CPI takes into account quality changes in the prices for various goods, it is unable to do so for services, particularly physicians'' services.The difficulty in measuring the “cost” of quality of medical care overstates price increases in the physician fee and medical care indexes.     

Smarter than Others? Conjectures in Lowest Unique Bid Auctions

Research concerning various types of auctions, such as English auctions, Dutch auctions, highest-price sealed-bid auctions, and second-price sealed-bid auctions, is always a topic of considerable interest in interdisciplinary fields. The type of auction, known as a lowest unique bid auction (LUBA), has also attracted significant attention. Various models have been proposed, but they often fail to explain satisfactorily the real bid-distribution characteristics. This paper discusses LUBA bid-distribution characteristics, including the inverted-J shape and the exponential decrease in the upper region. The authors note that this type of distribution, which initially increases and later decreases, cannot be derived from the symmetric Nash equilibrium framework based on perfect information that has previously been used. A novel optimization model based on non-perfect information is presented. The kernel of this model is the premise that agents make decisions to achieve maximum profit based on imaginary information or assumptions regarding the behavior of others.     

Predictive Habitat Modelling as a Tool to Assess the Change in Distribution and Extent of an OSPAR Priority Habitat under an Increased Ocean Temperature Scenario: Consequences for Marine Protected Area Networks and Management

The aims of this study were to determine the extent and distribution of an OSPAR priority habitat under current baseline ocean temperatures; to illustrate the prospect for habitat loss under a changing ocean temperature scenario; and to demonstrate the potential application of predictive habitat mapping in “future-proofing” conservation and biodiversity management.Maxent modelling and GIS environmental envelope analysis of the biogenic bed forming species, Modiolus modiolus was carried out. The Maxent model was tested and validated using 75%/25% training/test occurrence records and validated against two sampling biases (the whole study area and a 20km buffer). The model was compared to the envelope analysis and the area under the receiver operating characteristic curve (Area Under the curve; AUC) was evaluated.The performance of the Maxent model was rated as ‘good’ to ‘excellent’ on all replicated runs and low variation in the runs was recorded from the AUC values. The extent of “most suitable”, “less suitable” and “unsuitable” habitat was calculated for the baseline year (2009) and the projected increased ocean temperature scenarios (2030, 2050, 2080 and 2100). A loss of 100% of “most suitable” habitat was reported by 2080.Maintaining a suitable level of protection of marine habitats/species of conservation importance may require management of the decline and migration rather than maintenance of present extent. Methods applied in this study provide the initial application of a plausible “conservation management tool”.     

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.     

The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.     

海河流域农田生态系统环境损益分析

根据生态系统服务的内涵,建立了海河流域农田生态系统服务功能评价指标体系,并利用市场价值法、影子工程法和机会成本法等,定量评价了海河流域农田生态系统服务的经济价值和农田环境成本.结果表明：2005年,海河流域农田生态系统环境效益总价值为1802.64亿元;其中,调节功能的价值（794.16亿元）占44.06%,支持功能的价值（1008.48亿元）占55.94%,提供产品和文化功能未进行核算.从不同的功能类型来看,其价值量大小依次为释氧>涵养水源>营养元素循环>土壤保持>废弃物净化>环境净化>固碳>秸秆还田.2005年,海河流域化肥流失和温室气体排放的环境成本较大,为422.93亿元.其中,化肥流失量为427.42×10⁴ t,成本为151.91亿元;产生的温室气体折算为CO₂的量为3599.65×10⁴ t,成本为271.02亿元.     

Portrayal of the Human Resource Crisis and Accountability in Healthcare: A Qualitative Analysis of Ugandan Newspapers

Background

Uganda is one of the 57 countries with a critical shortage of health workers. The aim of this study was to determine how the human resources and health service crisis was covered in Ugandan newspapers and, in particular, how the newspapers attributed accountability for problems in the health services.

Methods

We collected all articles related to health workers and health services for the calendar year 2012 in the two largest national newspapers in Uganda (collection on daily basis) and in one local newspaper (collection on weekly basis). These articles were analysed qualitatively regarding the main themes covered and attribution of accountability.

Results

The two more urban national newspapers published 229 articles on human resources and health services in Uganda (on average over two articles per week), whereas the local more rural newspaper published only a single article on this issue in the 12 month period. The majority of articles described problems in the health service without discussing accountability. The question of accountability is raised in only 46% of articles (106 articles). The responsibility of the government was discussed in 50 articles (21%), and negligence, corruption and misbehaviour by individual health workers was reported in 56 articles (25%). In the articles about corruption (n=35), 60% (21 articles) mention corruption by health workers and 40% (14 articles) mention corruption by government officials. Six articles defended the situation of health workers in Uganda.

Conclusions

The coverage of accountability in the Ugandan newspapers surveyed is insufficient to generate informed debate on what political actions need to be taken to improve the crisis in health care and services. There exists not only an “inverse care law” but also an “inverse information law”: those sections of society with the greatest health needs and problems in accessing quality health care receive the least information about health services.     

Permissible Home Range Estimation (PHRE) in Restricted Habitats: A New Algorithm and an Evaluation for Sea Otters

Parametric and nonparametric kernel methods dominate studies of animal home ranges and space use. Most existing methods are unable to incorporate information about the underlying physical environment, leading to poor performance in excluding areas that are not used. Using radio-telemetry data from sea otters, we developed and evaluated a new algorithm for estimating home ranges (hereafter Permissible Home Range Estimation, or “PHRE”) that reflects habitat suitability. We began by transforming sighting locations into relevant landscape features (for sea otters, coastal position and distance from shore). Then, we generated a bivariate kernel probability density function in landscape space and back-transformed this to geographic space in order to define a permissible home range. Compared to two commonly used home range estimation methods, kernel densities and local convex hulls, PHRE better excluded unused areas and required a smaller sample size. Our PHRE method is applicable to species whose ranges are restricted by complex physical boundaries or environmental gradients and will improve understanding of habitat-use requirements and, ultimately, aid in conservation efforts.     

Civil Emergency Planning in Canada

The national objectives of civilian emergency planning are: (1) protection and preservation of life and property; (2) maintenance of governmental structure; and (3) conservation of resources. The Canada Emergency Measures Organization (E.M.O.) has been developed to accomplish these objectives. E.M.O. co-ordinates other departments and agencies of federal government and its organization is reflected within provincial and municipal governments.Present E.M.O. accomplishments include: an attack warning system; an emergency broadcasting system; emergency government facilities; 400 emergency measure organizations across Canada; plans to implement general readiness; a medical stockpile; and “shadow agencies” for control of housing, food and manpower.Present undertakings include: a national survey of fallout shelters; the equipping of the radiation defence (RADEF); the pre-positioning of the items of the medical stockpile; and the training at the Canadian Emergency Measures College at Arnprior.     

A Biodiversity Indicators Dashboard: Addressing Challenges to Monitoring Progress towards the Aichi Biodiversity Targets Using Disaggregated Global Data

Recognizing the imperiled status of biodiversity and its benefit to human well-being, the world''s governments committed in 2010 to take effective and urgent action to halt biodiversity loss through the Convention on Biological Diversity''s “Aichi Targets”. These targets, and many conservation programs, require monitoring to assess progress toward specific goals. However, comprehensive and easily understood information on biodiversity trends at appropriate spatial scales is often not available to the policy makers, managers, and scientists who require it. We surveyed conservation stakeholders in three geographically diverse regions of critical biodiversity concern (the Tropical Andes, the African Great Lakes, and the Greater Mekong) and found high demand for biodiversity indicator information but uneven availability. To begin to address this need, we present a biodiversity “dashboard” – a visualization of biodiversity indicators designed to enable tracking of biodiversity and conservation performance data in a clear, user-friendly format. This builds on previous, more conceptual, indicator work to create an operationalized online interface communicating multiple indicators at multiple spatial scales. We structured this dashboard around the Pressure-State-Response-Benefit framework, selecting four indicators to measure pressure on biodiversity (deforestation rate), state of species (Red List Index), conservation response (protection of key biodiversity areas), and benefits to human populations (freshwater provision). Disaggregating global data, we present dashboard maps and graphics for the three regions surveyed and their component countries. These visualizations provide charts showing regional and national trends and lay the foundation for a web-enabled, interactive biodiversity indicators dashboard. This new tool can help track progress toward the Aichi Targets, support national monitoring and reporting, and inform outcome-based policy-making for the protection of natural resources.     

High Quality Topic Extraction from Business News Explains Abnormal Financial Market Volatility

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their “thematic” features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be “abnormally large,” can be partially explained by the flow of news. In this sense, our results prove that there is no “excess trading,” when restricting to times when news is genuinely novel and provides relevant financial information.     

Applying conservation reserve design strategies to define ecosystem monitoring priorities

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long‐time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well‐known approaches for conservation design, the “minimum set” and the “maximal coverage” problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot‐by‐plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long‐term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range‐rarity‐richness was balanced in terms of complementarity and representativeness, whereas its richness‐corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision‐making.     

Habitat Fragmentation Intensifies Trade-Offs between Biodiversity and Ecosystem Services in a Heathland Ecosystem in Southern England

While habitat fragmentation represents a major threat to global biodiversity, its impacts on provision of ecosystem services are largely unknown. We analysed biodiversity value and provision of multiple ecosystem services in 110 fragments of lowland heathland ecosystems in southern England, in which vegetation dynamics have been monitored for over 30 years. Decreasing fragment size was found to be associated with a decrease in biodiversity and recreational values, but an increase in relative carbon storage, aesthetic value and timber value. The trade-off between either biodiversity or recreational values with the other ecosystem services therefore became more pronounced as heathland size decreased. This was attributed to a higher rate of woody succession in smaller heathland fragments over the past three decades, and contrasting values of different successional vegetation types for biodiversity and provision of ecosystem services. These results suggest that habitat fragmentation can reduce the potential for developing “win win” solutions that contribute to biodiversity conservation while also supporting socio-economic development. Approaches to multi-purpose management of fragmented landscapes should therefore consider the potential trade-offs in ecosystem services and biodiversity associated with fragmentation, in order to make an effective contribution to sustainable development.     

Human Collective Intelligence under Dual Exploration-Exploitation Dilemmas

The exploration-exploitation dilemma is a recurrent adaptive problem for humans as well as non-human animals. Given a fixed time/energy budget, every individual faces a fundamental trade-off between exploring for better resources and exploiting known resources to optimize overall performance under uncertainty. Colonies of eusocial insects are known to solve this dilemma successfully via evolved coordination mechanisms that function at the collective level. For humans and other non-eusocial species, however, this dilemma operates within individuals as well as between individuals, because group members may be motivated to take excessive advantage of others'' exploratory findings through social learning. Thus, even though social learning can reduce collective exploration costs, the emergence of disproportionate “information scroungers” may severely undermine its potential benefits. We investigated experimentally whether social learning opportunities might improve the performance of human participants working on a “multi-armed bandit” problem in groups, where they could learn about each other''s past choice behaviors. Results showed that, even though information scroungers emerged frequently in groups, social learning opportunities reduced total group exploration time while increasing harvesting from better options, and consequentially improved collective performance. Surprisingly, enriching social information by allowing participants to observe others'' evaluations of chosen options (e.g., Amazon''s 5-star rating system) in addition to choice-frequency information had a detrimental impact on performance compared to the simpler situation with only the choice-frequency information. These results indicate that humans groups can handle the fundamental “dual exploration-exploitation dilemmas” successfully, and that social learning about simple choice-frequencies can help produce collective intelligence.     

Meta‐analysis shows that environmental DNA outperforms traditional surveys,but warrants better reporting standards

1. Decades of environmental DNA (eDNA) method application, spanning a wide variety of taxa and habitats, has advanced our understanding of eDNA and underlined its value as a tool for conservation practitioners. The general consensus is that eDNA methods are more accurate and cost‐effective than traditional survey methods. However, they are formally approved for just a few species globally (e.g., Bighead Carp, Silver Carp, Great Crested Newt). We conducted a meta‐analysis of studies that directly compare eDNA with traditional surveys to evaluate the assertion that eDNA methods are consistently “better.”
2. Environmental DNA publications for multiple species or single macro‐organism detection were identified using the Web of Science, by searching “eDNA” and “environmental DNA” across papers published between 1970 and 2020. The methods used, focal taxa, habitats surveyed, and quantitative and categorical results were collated and analyzed to determine whether and under what circumstances eDNA outperforms traditional surveys.
3. Results show that eDNA methods are cheaper, more sensitive, and detect more species than traditional methods. This is, however, taxa‐dependent, with amphibians having the highest potential for detection by eDNA survey. Perhaps most strikingly, of the 535 papers reviewed just 49 quantified the probability of detection for both eDNA and traditional survey methods and studies were three times more likely to give qualitative statements of performance.
4. Synthesis and applications: The results of this meta‐analysis demonstrate that where there is a direct comparison, eDNA surveys of macro‐organisms are more accurate and efficient than traditional surveys. This conclusion, however, is based on just a fraction of available eDNA papers as most do not offer this granularity. We recommend that conclusions are substantiated with comparable and quantitative data. Where a direct comparison has not been made, we caution against the use of qualitative statements about relative performance. This consistency and rigor will simplify how the eDNA research community tracks methods‐based advances and will also provide greater clarity for conservation practitioners. To this end suggest reporting standards for eDNA studies.

     

Improving timeliness in the neglected tropical diseases preventive chemotherapy donation supply chain through information sharing: A retrospective empirical analysis

BackgroundBillions of doses of medicines are donated for mass drug administrations in support of the World Health Organization’s “Roadmap to Implementation,” which aims to control, eliminate, and eradicate Neglected Tropical Diseases (NTDs). The supply chain to deliver these medicines is complex, with fragmented data systems and limited visibility on performance. This study empirically evaluates the impact of an online supply chain performance measurement system, “NTDeliver,” providing understanding of the value of information sharing towards the success of global health programs.MethodsRetrospective secondary data were extracted from NTDeliver, which included 1,484 shipments for four critical medicines ordered by over 100 countries between February 28, 2006 and December 31, 2018. We applied statistical regression models to analyze the impact on key performance metrics, comparing data before and after the system was implemented.FindingsThe results suggest information sharing has a positive association with improvement for two key performance indicators: purchase order timeliness (β = 0.941, p = 0.003) and—most importantly—delivery timeliness (β = 0.828, p = 0.027). There is a positive association with improvement for three variables when the data are publicly shared: shipment timeliness (β = 2.57, p = 0.001), arrival timeliness (β = 2.88, p = 0.003), and delivery timeliness (β = 2.82, p = 0.011).ConclusionsOur findings suggest that information sharing between the NTD program partners via the NTDeliver system has a positive association with supply chain performance improvements, especially when data are shared publicly. Given the large volume of medicine and the significant number of people requiring these medicines, information sharing has the potential to provide improvements to global health programs affecting the health of tens to hundreds of millions of people.     

西北地区生物多样性特点及其研究思路

在探讨西北地区生物多样性特点的基础上,院述了西北地区生物多样保护研究的现状,分析了生物多样性面临的危机。在此基础上,提出了西北地区生物多样性研究的方向和具体思路：１．编目和监测系统研究;２．稀有濒危动植物的保护生物学研究;３．迁地保护和人工繁育,扩大人工种群的研究;４．生物多样性恢复的研究;５．生物多样性持续利用研究。     

Biological auctions with multiple rewards

The competition for resources among cells, individuals or species is a fundamental characteristic of evolution. Biological all-pay auctions have been used to model situations where multiple individuals compete for a single resource. However, in many situations multiple resources with various values exist and single reward auctions are not applicable. We generalize the model to multiple rewards and study the evolution of strategies. In biological all-pay auctions the bid of an individual corresponds to its strategy and is equivalent to its payment in the auction. The decreasingly ordered rewards are distributed according to the decreasingly ordered bids of the participating individuals. The reproductive success of an individual is proportional to its fitness given by the sum of the rewards won minus its payments. Hence, successful bidding strategies spread in the population. We find that the results for the multiple reward case are very different from the single reward case. While the mixed strategy equilibrium in the single reward case with more than two players consists of mostly low-bidding individuals, we show that the equilibrium can convert to many high-bidding individuals and a few low-bidding individuals in the multiple reward case. Some reward values lead to a specialization among the individuals where one subpopulation competes for the rewards and the other subpopulation largely avoids costly competitions. Whether the mixed strategy equilibrium is an evolutionarily stable strategy (ESS) depends on the specific values of the rewards.