Spatial variation in the ongoing and widespread decline of a keystone plant species

Extensive dieback in dominant plant species in response to climate change is increasingly common. Climatic conditions and related variables, such as evapotranspiration, vary in response to topographical complexity. This complexity plays an important role in the provision of climate refugia. In 2008/2009, an island‐wide dieback event of the keystone cushion plant Azorella macquariensis Orchard (Apiaceae) occurred on sub‐Antarctic Macquarie Island. This signalled the start of a potential regime shift, suggested to be driven by increasing vapour pressure deficit. Eight years later, we quantified cover and dieback across the range of putative microclimates to which the species is exposed, with the aim of explaining dieback patterns. We test for the influence of evapotranspiration using a suite of topographic proxies and other variables as proposed drivers of change. We found higher cover and lower dieback towards the south of the island. The high spatial variation in A. macquariensis populations was best explained by latitude, likely a proxy for macroscale climate gradients and geology. Dieback was best explained by A. macquariensis cover and latitude, increasing with cover and towards the north of the island. The effect sizes of terrain variables that influence evapotranspiration rates were small. Island‐wide dieback remains conspicuous. Comparison between a subset of sites and historical data revealed a reduction of cover in the north and central regions of the island, and a shift south in the most active areas of dieback. Dieback remained comparatively low in the south. The presence of seedlings was independent of dieback. This study provides an empirical baseline for spatial variation in the cover and condition of A. macquariensis, both key variables for monitoring condition and ‘cover‐debt’ in this critically endangered endemic plant species. These findings have broader implications for understanding the responses of fellfield ecosystems and other Azorella species across the sub‐Antarctic under future climates.     

Red panda fine‐scale habitat selection along a Central Himalayan longitudinal gradient

Red panda Ailurus fulgens, an endangered habitat specialist, inhabits a narrow distribution range in bamboo abundance forests along mountain slopes in the Himalaya and Hengduan Mountains. However, their habitat use may be different in places with different longitudinal environmental gradients, climatic regimes, and microclimate. This study aimed to determine the habitat variables affecting red panda distribution across different longitudinal gradients through a multivariate analysis. We studied habitat selection patterns along the longitudinal gradient in Nepal's Himalaya which is grouped into the eastern, central, and western complexes. We collected data on red panda presence and habitat variables (e.g., tree richness, canopy cover, bamboo abundance, water availability, tree diameter, tree height) by surveys along transects throughout the species’ potential range. We used a multimodal inference approach with a generalized linear model to test the relative importance of environmental variables. Although the study showed that bamboo abundance had a major influence, habitat selection was different across longitudinal zones. Both canopy cover and species richness were unimportant in eastern Nepal, but their influence increased progressively toward the west. Conversely, tree height showed a decreasing influence on habitat selection from Eastern to Western Nepal. Red panda's habitat selection revealed in this study corresponds to the uneven distribution of vegetation assemblages and the dry climatic gradient along the eastern‐western Himalayas which could be related to a need to conserve energy and thermoregulate. This study has further highlighted the need of importance of bamboo conservation and site‐specific conservation planning to ensure long‐term red panda conservation.     

Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

We analyze how measures of adiposity – body mass index (BMI) and waist hip ratio (WHR) – causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable model in a Mendelian randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observed an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.     

Forecasting the potential distribution of Spodoptera exigua and S. littoralis (Lepidoptera,Noctuidae) in Iran

The beet armyworm, Spodoptera exigua (Hübner, 1808) and the Egyptian cotton leafworm, S. littoralis (Boisduval, 1833), are amongst the most notorious agricultural pest species in Iran. Spodoptera exigua is considered a serious pest of different crops, whereas S. littoralis is known as an important pest of cotton.In this paper, the potential distribution areas of these species in Iran and the important climatic factors affecting their distribution were predicted using the MaxEnt model and the ArcGIS. The results indicate that the main environmental variables contributing to S. exigua’s distribution were precipitation of the coldest quarter (bio19), average wind speed in April (wind4), and annual precipitation (bio12). Also, minimum temperature of the coldest month (bio6), mean temperature of coldest quarter (bio11), altitude and average wind speed in May (wind5) were dominant climatic factors that affected the potential distribution of S. littoralis. These species overlapped in most parts of coastal areas in the southern and northern parts of Iran, with an average overlapping range of 33.2%. Considering their preferred host plants in Iran, it is necessary to strengthen biosurveillance programes and management of these two species in their suitable areas to prevent further invasion, which endangers agricultural security.     

三峡库区水体中固氮微生物多样性及其影响因素

【目的】研究分析不同时空条件下三峡库区水体固氮微生物多样性,并探讨其与地球化学参数的相关性。【方法】采集三峡库区不同时间(三月份和六月份)和空间(干流与支流)的水体样品,对其进行地球化学参数分析,并通过构建克隆文库分析样品中固氮功能基因(nifH)的多样性进而探讨其与水体地化参数的相关关系。【结果】统计分析显示三峡库区水体固氮微生物α-多样性和群落组成具有时空差异。支流水体样品的固氮微生物α-多样性高于干流水体样品;六月水体样品的固氮微生物α-多样性高于三月水体样品。三峡库区三月水体样品中的固氮微生物群落以Proteobacteria (50.3%)和Firmicutes (40.0%)为主;六月水体样品的固氮微生物群落以Proteobacteria(48.4%)、Firmicutes(25.4%)和Cyanobacteria(19.0%)为主。Mantel检验结果显示:固氮微生物群落结构的差异与温度、pH和DIC等地球化学参数具有显著(P0.05)相关性,其中温度和pH的相关性系数最大。【结论】三峡库区固氮微生物的种群结构和多样性具有时空差异,影响三峡水库水体中固氮微生物群落结构与多样性的主要环境因素为温度和pH,同时浊度、DIC、氨氮也对库区水体固氮微生物群落结构和多样性有一定的影响。     

Binary Responses and the Three-period Cross-over

Problems with carry-over effects in the simple two-period cross-over have lead to interest in more complex cross-over designs. A method for analysing the optimum two-treatment three-period design with binary response variables is given by making a simple extension to Gart's logistic model. The method gives independent tests for, and estimates of the difference in treatment and first-order carry-over effects. An example of the analysis is given, using the loglinear models facility in GLIM.     

Modeling continuous auxiliary covariate data in generalized linear mixed models using the kernel smoother

Auxiliary covariate data are often collected in biomedical studies when the primary exposure variable is only assessed on a subset of the study subjects. In this study, we investigate a semiparametric‐estimated likelihood estimation for the generalized linear mixed models (GLMM) in the presence of a continuous auxiliary variable. We use a kernel smoother to handle continuous auxiliary data. The method can be used to deal with missing or mismeasured covariate data problems in a variety of applications when an auxiliary variable is available and cluster sizes are not too small. Simulation study results show that the proposed method performs better than that which ignores the random effects in GLMM and that which only uses data in the validation data set. We illustrate the proposed method with a real data set from a recent environmental epidemiology study on the maternal serum 1,1‐dichloro‐2,2‐bis(p‐chlorophenyl) ethylene level in relationship to preterm births.     

Analyzing a randomized trial on breast self-examination with noncompliance and missing outcomes

Recently, instrumental variables methods have been used to address non-compliance in randomized experiments. Complicating such analyses is often the presence of missing data. The standard model for missing data, missing at random (MAR), has some unattractive features in this context. In this paper we compare MAR-based estimates of the complier average causal effect (CACE) with an estimator based on an alternative, nonignorable model for the missing data process, developed by Frangakis and Rubin (1999, Biometrika, 86, 365-379). We also introduce a new missing data model that, like the Frangakis-Rubin model, is specially suited for models with instrumental variables, but makes different substantive assumptions. We analyze these issues in the context of a randomized trial of breast self-examination (BSE). In the study two methods of teaching BSE, consisting of either mailed information about BSE (the standard treatment) or the attendance of a course involving theoretical and practical sessions (the new treatment), were compared with the aim of assessing whether teaching programs could increase BSE practice and improve examination skills. The study was affected by the two sources of bias mentioned above: only 55% of women assigned to receive the new treatment complied with their assignment and 35% of the women did not respond to the post-test questionnaire. Comparing the causal estimand of the new treatment using the MAR, Frangakis-Rubin, and our new approach, the results suggest that for these data the MAR assumption appears least plausible, and that the new model appears most plausible among the three choices.     

Chromosome Inversion Polymorphisms Influence Morphological Traits in <Emphasis Type="Italic">Trimerotropis Pallidipennis</Emphasis> (Orthoptera)

Trimerotropis pallidipennis is a New World grasshopper whose South-American populations are polymorphic for six pericentric inversions. Previous work has demonstrated that the frequences of these inversions correlate with climatic variables, and hence a possible adaptive pattern was put forward. In the present work we analysed a sample of a natural population of T. pallidipennis to ascertain whether the chromosomal inversions have effects on exophenotypes. Two hundred and sixty-eight males coming from a natural population at Uspallata, Mendoza Province, Argentina were analysed, and it was observed that most inversions had significant effects on phenotypes. Furthermore, some body size-related characteristics (such as tegmina length) were correlated with the number of inversions. Individuals from populations at higher altitude or latitude (i.e., at lower minimum temperatures), along with higher frequencies of standard sequences, were significantly smaller, and this coherence between interpopulational with intrapopulational results may indicate that the diminished body size of the standard sequence-carrying individuals may be caused by an effect of the inversions, or genes within the inversions, on body size. We finally put forward the hypothesis that reduced body size in a context of reduced minimum temperature may be a response to shortened development season, and so smaller individuals may be advantageous.     

A study on relations of vegetation,climate and soils in Shanxi province,China

Relationships of vegetation, climate and soils in Shanxi plateau wereanalyzed by use of Canonical Correspondence Analysis (CCA). Shanxi province,located at 34°35–40°43 N, 110°15–114°33 E, was divided into a series of rectangular districts of30 latitude by 20 longitude. Areas of vegetation formations and soil types ineach district were measured carefully using fine grain on the vegetation andsoil maps of Shanxi. Climatic data were mean values of 25 years records in eachdistrict. Three data matrices of climate, vegetation and soil were combined byCCA. The results showed that the distribution of vegetation is closely relatedto the variety of climates and to soils distribution.