Myrmica rubra microhabitat selection and putative ecological impact

1. Myrmica rubra (European fire ant) has invaded northern latitude coastal areas in North America. This macroscale distribution suggests that M. rubra is moisture‐ and temperature‐limited, but the distribution of the invaded range may reflect the legacy of original introduction locations preserved by limited dispersal. 2. This study examined a two‐decade population change in M. rubra (1994–2015) and the microscale abiotic (moisture and temperature), biotic (plants), anthropogenic (pesticide) and physiological (thermal tolerance) limits on the invasion at the Tifft Nature Preserve in Buffalo, NY (U.S.A.). Changes in the abundance of native ants and other invertebrates were also examined. 3. Despite localised declines with pesticide treatments, overall M. rubra forager abundance increased 27% between 1994 and 2015. Abundance increased the most in the warmest areas (native ants were unaffected by temperature), but M. rubra colony locations were strongly linked to higher soil moisture and lower soil temperature. Myrmica rubra ants also exhibited relatively low thermal tolerances consistent with high‐latitude and high‐elevation ants. 4. Where local M. rubra populations increased the most, native ant species decreased, and where local M. rubra populations declined, native ant species increased. Some arthropod species had lower abundance with M. rubra presence, but the impacts were less striking. 5. Myrmica rubra population growth was promoted at the microhabitat scale where relatively higher temperatures prompted foraging, and relatively lower temperatures and high moisture supported nesting. These results suggest that macroscale M. rubra invaded‐range distributions in northern climates near coastal areas are replicated at the microscale where the ant prefers cooler, moister microsites.     

Regression with empirical variable selection: description of a new method and application to ecological datasets

Despite recent papers on problems associated with full-model and stepwise regression, their use is still common throughout ecological and environmental disciplines. Alternative approaches, including generating multiple models and comparing them post-hoc using techniques such as Akaike''s Information Criterion (AIC), are becoming more popular. However, these are problematic when there are numerous independent variables and interpretation is often difficult when competing models contain many different variables and combinations of variables. Here, we detail a new approach, REVS (Regression with Empirical Variable Selection), which uses all-subsets regression to quantify empirical support for every independent variable. A series of models is created; the first containing the variable with most empirical support, the second containing the first variable and the next most-supported, and so on. The comparatively small number of resultant models (n = the number of predictor variables) means that post-hoc comparison is comparatively quick and easy. When tested on a real dataset – habitat and offspring quality in the great tit (Parus major) – the optimal REVS model explained more variance (higher R²), was more parsimonious (lower AIC), and had greater significance (lower P values), than full, stepwise or all-subsets models; it also had higher predictive accuracy based on split-sample validation. Testing REVS on ten further datasets suggested that this is typical, with R² values being higher than full or stepwise models (mean improvement = 31% and 7%, respectively). Results are ecologically intuitive as even when there are several competing models, they share a set of “core” variables and differ only in presence/absence of one or two additional variables. We conclude that REVS is useful for analysing complex datasets, including those in ecology and environmental disciplines.     

洞穴型蝙蝠的栖息环境选择、生态作用及保护

多数蝙蝠为洞穴型。在野外调查的基础上,结合前人调查的结果,对洞穴型蝙蝠的栖息环境选择及其在洞穴生态系统中的特殊生态作用进行了探讨。针对目前随着人类活动的增加,洞穴型蝙蝠的生存环境遭到日益严重的干扰、破坏和污染而导致蝙蝠的物种多样性降低,加之国内对洞穴型蝙蝠研究不足的现状,提出了加强对洞穴型蝙蝠的栖息和捕食环境进行保护、对蝙蝠的多样性进行调查的建议。     

The evolution of female ornaments and weaponry: social selection, sexual selection and ecological competition

Ornaments, weapons and aggressive behaviours may evolve in female animals by mate choice and intrasexual competition for mating opportunities-the standard forms of sexual selection in males. However, a growing body of evidence suggests that selection tends to operate in different ways in males and females, with female traits more often mediating competition for ecological resources, rather than mate acquisition. Two main solutions have been proposed to accommodate this disparity. One is to expand the concept of sexual selection to include all mechanisms related to fecundity; another is to adopt an alternative conceptual framework-the theory of social selection-in which sexual selection is one component of a more general form of selection resulting from all social interactions. In this study, we summarize the history of the debate about female ornaments and weapons, and discuss potential resolutions. We review the components of fitness driving ornamentation in a wide range of systems, and show that selection often falls outside the limits of traditional sexual selection theory, particularly in females. We conclude that the evolution of these traits in both sexes is best understood within the unifying framework of social selection.     

Floristic description and ecological characteristics of the plants of Pashat Valley,Pak-Afghan border,district Bajaur,Pakistan

This study was conducted during 2018–19 to evaluate the floristic composition and ecological characteristics of vegetation of Pashat valley, Bajaur. Floristic list of the valley contains 385 species distributed in 291 genera and 102 families. The dicotyledons having 83 families with 311 species and monocotyledons with 12 families contains 61 species. Pteridophytes having 05 families with 11 species and gymnosperm with a single family of two species. The leading family was Asteraceae with 42 species (10.90%) followed by Poaceae with 39 species (10.10%), Papilionaceae (Fabaceae) with 24 species (6.23%), Lamiaceae with 20 species (5. 19%) and Rosaceae with 15 species (3.90%). Therophytes 180 species (46.80%), hemicryptophytes 53 species (13.80%), nanophanerophytes 51 species (13.20%) and geophytes 35 species (9.09%) were the dominant life form groups. Leaf size class was dominated by microphylls (138 species, 35.84%) followed by nanophylls (124 species, 32.21%) and mesophylls (89 species, 23.12%). Habit wise the vegetation was mostly herbs (289 species) followed by shrubs (54 species), trees (38 species) and lianas (4 species). According to flowering phenology, most plants (62.30%) bloomed in spring followed by in summer (34%), in autumn (1.82%), in the whole year (1.30%) and in winter (0.52%). Based on chorological affinities, most of the species were bioregional in distribution (170 species, 44.15%) followed by mono-regional (157 species, 40.78%), pluri-regional (43 species, 11.17%) and cosmopolitan (15 species, 3.89%). The ecological characteristics like life form and leaf size spectra of the vegetation have a strong correlation with the prevailing environmental conditions such as altitude, slope, precipitation and temperature.     

海洋生态修复:概念、类型与实施路径选择

生态修复是我国生态文明建设的重要内容。在对生态修复相关概念梳理的基础上,从公共物品治理视角对海洋生态修复主体、修复标准、修复路径及修复措施保障等关键环节进行论述,研究表明：污染和破坏者作为赔偿型海洋生态修复的主体,可通过自行修复和委托修复等方式,将受损海洋生态修复到破坏前的基线水平;国家作为补偿型海洋生态修复的主体,依据边际成本收益分析法确定最优修复规模,通过政府市场采购和创建市场等经济激励型路径实施生态修复以增加公众福利。未来我国海洋生态修复应重点关注修复的资金保障、监督制度以及生态修复的技术研发和修复完成后的成本收益评估等。     

鄱阳湖生态经济区生态经济指数评价

大力推进生态文明建设已成为全社会关注的焦点,衡量和评价区域生态经济发展状态是当前研究重点和难点。在借鉴经济增长生态指数及生态效率概念的基础上,运用层次分析法和专家咨询法,构建了包括社会发展、经济增长、生态建设、资源利用和环境保护等5个模块在内的生态经济指数评价指标体系和模型,并将其应用到鄱阳湖生态经济区。结果表明:(1)鄱阳湖生态经济区各县(市、区)生态经济指数差异明显,其中万年县的生态经济指数最高,达到55.74,在研究区中生态经济发展状态最优;瑞昌市的生态经济指数最低,只有28.65,即生态经济发展状态最差;(2)生态经济指数得分较高的经济较发达的县(市、区)在发展生态经济过程中应提高资源利用效率,加大环保力度,加强生态建设;其他地区应将经济增长的速度和质量相结合;(3)生态经济指数得分较低的县(市、区)在发展生态经济的过程中,应在保护环境的前提下,大力发展经济,提高经济发展水平和质量,并努力提高资源利用效率;(4)鄱阳湖生态经济区生态经济指数的总体得分也较低,只有38.37,处于较差水平,需从提高环境保护和资源利用水平入手。最后就生态经济指数评价体系构建方法和存在的问题进行了有益的探讨。     

Optical recording of the compression dynamics of DT-gas-filled pellets in indirect-drive targets

The spatiotemporal dynamics of the compression region of DT-gas filled micropellets was recorded using an optical streak camera in experiments on micropellet implosion in the Iskra-5 high-power laser facility. The experimental data agree with calculations and results of X-ray measurements.     

Speciation, diversity, and Mode 1 technologies: the impact of variability selection

Over geological timescales, organisms encounter periodic shifts in selective conditions driven by environmental change. The variability selection hypothesis suggests that increases in environmental fluctuation have led to the evolution of complex, flexible behaviours able to respond to novel and unpredictable adaptive settings. This hypothesis is tested via the framework of a single locus genetic model in which an invading ‘versatilist’ allele competes with two opposed specialists in a selection regime driven by a fluctuating environment, modelled initially as a sine wave and subsequently as an empirical climate curve covering the past 5 million years. Results demonstrate that generalist alleles achieve fixation in the sine wave environment, whilst versatilist alleles do so in the empirical environment, even at a range of very low fitness advantages over the basic generalist template. Variability selection is found to be a particularly strong force between approximately 2.5 and 1.2 Ma (millions of years ago). These results are discussed in relation to the spread of Oldowan lithics and the patterns of speciation and extinction documented in the hominin fossil record. It is suggested that the flexibility required for survival in a variable climatic regime may have been a stimulus to the development of the first stone tool technologies, whilst the ecological opportunities provided by heightened variability may have been a factor in prompting the hominin adaptive radiation evidenced during this period.     

Medical journals,impact and social media: an ecological study of the Twittersphere

Background:

Twitter is an increasingly popular means of research dissemination. I sought to examine the relation between scientific merit and mainstream popularity of general medical journals.

Methods:

I extracted impact factors and citations for 2014 for all general medical journals listed in the Thomson Reuters InCites Journal Citation Reports. I collected Twitter statistics (number of followers, number following, number of tweets) between July 25 and 27, 2015 from the Twitter profiles of journals that had Twitter accounts. I calculated the ratio of observed to expected Twitter followers according to citations via the Kardashian Index. I created the (Fifty Shades of) Grey Scale to calculate the analogous ratio according to impact factor.

Results:

Only 28% (43/153) of journals had Twitter profiles. The scientific and social media impact of journals were correlated: in adjusted models, Twitter followers increased by 0.78% (95% confidence interval [CI] 0.38%–1.18%) for every 1% increase in impact factor and by 0.62% (95% CI 0.34%–0.90%) for every 1% increase in citations. Kardashian Index scores above the 99% CI were obsverved in 16% (7/43) of journals, including 6 of the 7 highest ranked journals by impact factor, whereas 58% (25/43) had scores below this interval. For the Grey Scale, 12% (5/43) of journals had scores above and 35% (15/43) had scores below the 99% CI.

Interpretation:

The size of a general medical journal’s Twitter following is strongly linked to its impact factor and citations, suggesting that higher quality research received more mainstream attention. Many journals have not capitalized on this dissemination method, although others have used it to their advantage.Social media has reached near ubiquity; medical research, researchers and journals are no exception to its pervasiveness.^1–7 One of the most popular social media platforms is Twitter, with an estimated 302 million monthly active users sending 500 million tweets per day.⁸ Twitter differs from other social media platforms in that posts are limited to 140 or fewer characters. With an emphasis on brevity, Twitter provides a unique opportunity for medical knowledge to be disseminated to the general public.^9,10 However, people with questionable medical research pedigrees are the stars of Twitter.With more than 65 million followers, Canadian @justinbieber is one of the most popular Twitter celebrities, narrowly edging out the most popular physician (@bengoldacre) by a margin of 64.5 million followers. Despite widespread distaste among non-Beliebers, it can be argued that The Biebs does display a modicum of musical talent (assuming multiplatinum albums and chart-topping singles¹¹ are a proxy for talent). Conversely, the woefully popular @KimKardashian, who trumps top scientists by more than 33 million followers, falls into the “famous for being famous” trope, alongside fellow Glitterati Paris Hilton and Nicole Richie. The notion that people with dubious levels of talent and questionable means of attaining celebrity can become immensely popular is worrisome. This notion has sparked debate within the scientific community. Do these self-perpetuated self-promoters exist in academia? Are any scientists “renowned for being renowned”?¹²There has been increasing use of alternative means of quantifying journals’ impact, notably using the Altmetric statistic, which conglomerates an article’s social media presence through blogs, news outlets, Facebook and Twitter. In response to the meteoric unmeritocratic rise of social media celebrities via Twitter, @neilhall_uk developed the playfully dubbed Kardashian Index (K-index) to address these issues in an academic context.¹² The K-index quantifies the discrepancy between mainstream popularity and scientific merit by examining one’s social media profile in relation to one’s citations in peer reviewed works.Continuing in this vein, I propose the (Fifty Shades of) Grey Scale for use with medical journals (in reference to the book, which has sold more than 125 million copies to date, despite being critically lambasted).¹³ Using a similar equation to the K-index, the Grey Scale calculates the ratio of the number of actual to expected followers using journal impact factor (rather than citations, as in the K-index) as the predictor variable. Journal impact factor and total citations are closely related. Impact factor is the ratio of total citations to the number of articles published by the journal, which adjusts for journals that have many more, or fewer, citable publications (e.g., weekly or bimonthly journals).¹⁴Unpacking the mechanisms of Twitter celebrity is difficult. Personal Twitter profiles often include humour, wit and other attributes not normally attributed to the reporting of a new paper, as per general medical journal Tweets. By eliminating the individuality of the Tweet, looking only at medical journals’ Twitter profiles rather than individual researchers’, a more direct examination of the relation between Twitter celebrity and scientific merit is possible. Although Tweets linking to papers have been associated with greater citations than non-Tweeted papers,¹⁵ whether or not this translates into greater Twitter followings for the authors and the journal in which the paper was published has yet to explored. The relation between the number of Twitter followers and impact factor scores has recently been investigated in urology journals, where nonsignificant correlations between the number of Twitter followers and the impact factor of the journal were found.¹⁶The current study seeks to examine whether scientific merit (captured by journal impact factor and citations) translates into Twitter celebrity (i.e., number of followers) in general medical journals.     

How spatial resource distribution and memory impact foraging success: A hybrid model and mechanistic index

Understanding how animals forage has always been a fundamental issue in Ethology and has become critical more recently in Environmental Conservation. Since the formalization of optimal foraging theory, theoretical models intended to depict the behavior of a generic forager have served as the main tools to analyze and ultimately comprehend the mechanisms of foraging. Due to complexity and technical constraints, these models have traditionally focused on single aspects of foraging, leaving out other concurrent processes that may also interplay. The recent inclusion of several facets inside united models has given rise to interesting results on the importance of interacting factors such as memory and resource heterogeneity.In this paper, we present a hybrid model integrating metabolism, foraging decisions, memory, as well as spatially explicit movement and resource distribution. We use it to examine the effects of spatial resource distribution – an aspect often neglected in favor of probabilistic resource heterogeneity – on the viability of a generic random-walking forager, and rely on the model to devise an ecological metric that can explain and render the relative profitability of given spatial distributions. Furthermore, we assess the significance of memory properties relatively to the profitability of resource distributions. Most notably, we reveal contrasted effects of memory depending on the aspect of resource varied in space (i.e. prey abundance, or prey body mass).On the whole, a general comparison of our findings with results obtained with spatially implicit models leads us to stress the complex interaction between memory and spatial resource distribution as well as the criticality of spatial representation in the modeling of foraging. Accordingly, we conclude with a discussion on the ecological implications of these results, as well as the advantages of hybrid modeling for the accurate simulation of foraging.     

The impact of epistatic selection on the genomic traces of selection

The rapid accumulation of genomic data has led to an explosion of studies searching for signals of past selection left within DNA sequences. Yet the majority of theoretical studies investigating the traces of selection have assumed a simple form of selection, without interactions among selectively fixed sites. Fitness interactions—‘epistasis’—are commonplace, however, and take on a myriad of forms ( Whitlock et al. 1995 ; Segrèet al. 2005 ; Phillips 2008 ). It is thus important to determine how such epistasis would influence selective sweeps. On p. 5018 of this issue, Takahasi (2009) explores the effect of epistasis on genetic variation neighbouring two sites that interact in determining fitness, finding that such epistasis has a dramatic impact on the genetic variability in regions surrounding the interacting sites.     

Genetic architecture,biochemical underpinnings and ecological impact of floral UV patterning

Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral UV patterning (i.e. UV ‘bulls‐eye nectar guides) among crop and wild accessions of Brassica rapa. We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation in UV patterning between wild (commonly lacking UV patterns) and crop (commonly exhibiting UV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RILs) derived from an oilseed crop × WI fast‐plant^® cross exhibit UV patterns, the size of which varies extensively among genotypes. In RILs, we further observe strong statistical‐genetic and QTL correlations within petal morphological traits and within measurements of petal UV patterning; however, correlations between morphology and UV patterning are weak or nonsignificant, suggesting that UV patterning is regulated and may evolve independently of overall petal size. HPLC analyses reveal a high concentration of sinapoyl glucose in UV‐absorbing petal regions, which, in concert with physical locations of UV‐trait QTLs, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers with UV bulls‐eye patterns over those that lack patterns, validating the importance of UV patterning in pollen‐limited populations of B. rapa.     

On the selection of phylogenetic eigenvectors for ecological analyses

Among the statistical methods available to control for phylogenetic autocorrelation in ecological data, those based on eigenfunction analysis of the phylogenetic distance matrix among the species are becoming increasingly important tools. Here, we evaluate a range of criteria to select eigenvectors extracted from a phylogenetic distance matrix (using phylogenetic eigenvector regression, PVR) that can be used to measure the level of phylogenetic signal in ecological data and to study correlated evolution. We used a principal coordinate analysis to represent the phylogenetic relationships among 209 species of Carnivora by a series of eigenvectors, which were then used to model log‐transformed body size. We first conducted a series of PVRs in which we increased the number of eigenvectors from 1 to 70, following the sequence of their associated eigenvalues. Second, we also investigated three non‐sequential approaches based on the selection of 1) eigenvectors significantly correlated with body size, 2) eigenvectors selected by a standard stepwise algorithm, and 3) the combination of eigenvectors that minimizes the residual phylogenetic autocorrelation. We mapped the mean specific component of body size to evaluate how these selection criteria affect the interpretation of non‐phylogenetic signal in Bergmann's rule. For comparison, the same patterns were analyzed using autoregressive model (ARM) and phylogenetic generalized least‐squares (PGLS). Despite the robustness of PVR to the specific approaches used to select eigenvectors, using a relatively small number of eigenvectors may be insufficient to control phylogenetic autocorrelation, leading to flawed conclusions about patterns and processes. The method that minimizes residual autocorrelation seems to be the best choice according to different criteria. Thus, our analyses show that, when the best criterion is used to control phylogenetic structure, PVR can be a valuable tool for testing hypotheses related to heritability at the species level, phylogenetic niche conservatism and correlated evolution between ecological traits.     

Evaluation of selection index: application to the choice of an indirect multitrait selection index for soybean breeding

Summary Selection indices can be used to predict one trait from information available on several traits in order to improve the prediction accuracy. Plant or animal breeders are interested in selecting only the best individuals, and need to compare the efficiency of different trait combinations in order to choose the index ensuring the best prediction quality for individual values. As the usual tools for index evaluation do not remain unbiased in all cases, we propose a robust way of evaluation by means of an estimator of the mean-square error of prediction (EMSEP). This estimator remains valid even when parameters are not known, as usually assumed, but are estimated. EMSEP is applied to the choice of an indirect multitrait selection index at the F₅ generation of a classical breeding scheme for soybeans. Best predictions for precocity are obtained by means of indices using only part of the available information.     

Sexual selection and conflict as engines of ecological diversification

Ecological diversification presents an enduring puzzle: how do novel ecological strategies evolve in organisms that are already adapted to their ecological niche? Most attempts to answer this question posit a primary role for genetic drift, which could carry populations through or around fitness "valleys" representing maladaptive intermediate phenotypes between alternative niches. Sexual selection and conflict are thought to play an ancillary role by initiating reproductive isolation and thereby facilitating divergence in ecological traits through genetic drift or local adaptation. Here, I synthesize theory and evidence suggesting that sexual selection and conflict could play a more central role in the evolution and diversification of ecological strategies through the co-optation of sexual traits for viability-related functions. This hypothesis rests on three main premises, all of which are supported by theory and consistent with the available evidence. First, sexual selection and conflict often act at cross-purposes to viability selection, thereby displacing populations from the local viability optimum. Second, sexual traits can serve as preadaptations for novel viability-related functions. Third, ancestrally sex-limited sexual traits can be transferred between sexes. Consequently, by allowing populations to explore a broad phenotypic space around the current viability optimum, sexual selection and conflict could act as powerful drivers of ecological adaptation and diversification.