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1.
Cynthia Nafula Wakhungu Isaiah Masinde Tabu O. Daniel Otaye Wafula Victor Wasike 《Archives Of Phytopathology And Plant Protection》2017,50(7-8):398-414
A study was carried out to determine Fusarium wilt distribution in Bambara nut farmers’ fields and its management using farm yard manure (FYM). Four villages in Busia County were purposively sampled for the study. The data generated were subjected to analysis of variance and treatment means separated by least significant difference test. Fusarium wilt incidence in the fields ranged from 14.63 to 43.56%. In the greenhouse, FYM reduced the disease incidence by 10.2% and severity by 9.5% on the black landrace and 1.9 and 12.8%, respectively, on the red landrace. In the field, FYM reduced disease incidence by 9.1% and severity by 6.9% on the black landrace and 10.4 and 10.4%, respectively, on the red landrace. Farm yard manure had the lowest area under disease progress curve irrespective of the landrace. The study confirmed the presence of the pathogen in the fields and the ability to manage the disease using FYM. 相似文献
2.
Betaw G. Hirut Hussein A. Shimelis Rob Melis Mengistu Fentahun Walter De Jong 《Journal of Phytopathology》2017,165(1):1-14
Late blight disease of potato caused by Phytophthora infestans poses a significant threat to potato production in Ethiopia. The development of new high yielding genotypes with adequate late blight disease resistance will provide a strong component of an integrated management strategy for farmers. The objective of this study was to determine late blight resistance and yield of potato clones under field condition in north‐western Ethiopia. Twenty‐four clones (17 from the International Potato Centre B3C2 population and seven widely grown cultivars) were evaluated at three locations. The experiment was laid in a randomized complete block design with two replications. Late blight resistance and yield‐related traits were determined. Results showed that clones differ significantly for all traits across locations. The following five clones combine high to moderate resistance to late blight with high yields: 396029.250, 395017.229, 396004.263, 396034.103 and 395077.12. These clones are useful genetic resources for resistance breeding against late blight disease and for enhanced yields. 相似文献
3.
全球气候变化已影响到传染病发生、传播与变化的各个环节,从病原体及其携带者、传播途径和人体自身抵抗力等方面直接或间接影响传染病的发病趋势,从而对人类健康造成了巨大的威胁。所以加强对气候变化与传染病间关系、预测预报研究,对进一步认识、预防和控制传染病的爆发流行具有重要意义。本文首先阐述了全球气候变化对生物物种的地理分布和人类健康的影响,气候变化改变了生物物种的地理分布范围,增加了某些物种的潜在分布区域,并造成生物物侯期的改变;同时,极端气候事件成为导致种群数量波动的一个重要驱动力。气候变化对人类健康有直接和间接影响,它使得传染病发病率增加、传染病分布范围扩大、人群对疾病易感性增强。文章重点评述了气候变化对疟疾、登革热、霍乱、流行性乙型脑炎、流感、SARS、肠道传染病、鼠疫、血吸虫病等常见传染病流行机制和传播过程的影响研究进展。评述了传染病和气象因子关系分析中常用的定性和定量分析方法,传统的研究多以定性分析为主,方法较单一;目前,利用流行病学资料与同期的气象因子进行单因素相关分析、多元回归分析是常用的研究方法;主成分回归分析、逐步判别分析、灰色关联分析法、RS和GIS等方法近年来逐渐得到应用;数学建模、实验室生物学仿真实验方法是今后需强化的方向。提出了该研究领域国内外研究普遍存在和亟待解决的问题,针对目前的研究现状和存在的问题,提出了未来的研究重点和发展方向。 相似文献
4.
- When thermal tolerances differ between interacting species, extreme temperature events (heat waves) will alter the ecological outcomes. The parasitoid wasp Cotesia congregata suffers high mortality when reared throughout development at temperatures that are nonstressful for its host, Manduca sexta. However, the effects of short‐term heat stress during parasitoid development are unknown in this host–parasitoid system.
- Here, we investigate how duration of exposure, daily maximum temperature, and the developmental timing of heat waves impact the performance of C. congregata and its host¸ M. sexta. We find that the developmental timing of short‐term heat waves strongly determines parasitoid and host outcomes.
- Heat waves during parasitoid embryonic development resulted in complete wasp mortality and the production of giant, long‐lived hosts. Heat waves during the 1st‐instar had little effect on wasp success, whereas heat waves during the parasitoid''s nutritionally and hormonally critical 2nd instar greatly reduced wasp emergence and eclosion. The temperature and duration of heat waves experienced early in development determined what proportion of hosts had complete parasitoid mortality and abnormal phenotypes.
- Our results suggest that the timing of extreme temperature events will be crucial to determining the ecological impacts on this host–parasitoid system. Discrepancies in thermal tolerance between interacting species and across development will have important ramifications on ecosystem responses to climate change.
5.
Summary . Free-response assessment of diagnostic systems continues to gain acceptance in areas related to the detection, localization, and classification of one or more \"abnormalities\" within a subject. A free-response receiver operating characteristic (FROC) curve is a tool for characterizing the performance of a free-response system at all decision thresholds simultaneously. Although the importance of a single index summarizing the entire curve over all decision thresholds is well recognized in ROC analysis (e.g., area under the ROC curve), currently there is no widely accepted summary of a system being evaluated under the FROC paradigm. In this article, we propose a new index of the free-response performance at all decision thresholds simultaneously, and develop a nonparametric method for its analysis. Algebraically, the proposed summary index is the area under the empirical FROC curve penalized for the number of erroneous marks, rewarded for the fraction of detected abnormalities, and adjusted for the effect of the target size (or \"acceptance radius\"). Geometrically, the proposed index can be interpreted as a measure of average performance superiority over an artificial \"guessing\" free-response process and it represents an analogy to the area between the ROC curve and the \"guessing\" or diagonal line. We derive the ideal bootstrap estimator of the variance, which can be used for a resampling-free construction of asymptotic bootstrap confidence intervals and for sample size estimation using standard expressions. The proposed procedure is free from any parametric assumptions and does not require an assumption of independence of observations within a subject. We provide an example with a dataset sampled from a diagnostic imaging study and conduct simulations that demonstrate the appropriateness of the developed procedure for the considered sample sizes and ranges of parameters. 相似文献
6.
Bo Cao Chengke Bai Kunyi Wu Ting La Yiyang Su Lingyu Che Meng Zhang Yumeng Lu Pufan Gao Jingjing Yang Ying Xue Guishuang Li 《Global Change Biology》2023,29(13):3723-3746
Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change. 相似文献
7.
Erik E. Osnas Qing Zhao Michael C. Runge G. Scott Boomer 《The Journal of wildlife management》2016,80(7):1227-1241
8.
Zhiting Chen Hongyan Liu Chongyang Xu Xiuchen Wu Boyi Liang Jing Cao Deliang Chen 《Ecology and evolution》2021,11(12):7335
Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature. 相似文献
9.
Yield reduction of pea (Pisum sativum) due to various types of infections by Mycosphaerella pinodes on pods was assessed. A range of disease severities was created on pods of pea plants grown in the glasshouse, by painting the pods with different concentrations of spore suspensions, at three different pod development stages: lag phase, the beginning of seed filling (BSF) and mid-filling of the seeds. Seed number at harvest was reduced only if the pods were infected before BSF, as shown previously for whole plant infections. Pod infections led to individual seed weight (ISW) losses from zero (for late infections, at mid-filling) to 20% (for earlier infections and severe disease). Infection during the lag phase affected ISW by reducing seed growth rate, whereas infection at BSF tended to reduce the duration of seed filling. There was a linear relationship between the area under the disease progress curve and the percentage decrease in ISW. This model should be complemented by the effect of leaves and stem infections, in order to predict ISW losses in diseased crop conditions, in which epidemics occur on all aerial parts of the pea plant. 相似文献
10.
- Curlyleaf pondweed (Potamogeton crispus) is one of the most widespread and widely managed aquatic invasive plants in North America. Despite decades of management, the efficacy of long-term management strategies and the effects of environmental drivers on curlyleaf pondweed populations remain uncertain.
- To evaluate the effects of management and environmental factors on within-lake distribution and local density of curlyleaf pondweed, we collated monitoring data from point–intercept surveys collected by a variety of lake managers across Minnesota, U.S.A. Using this dataset, comprising 177 lake-years of plant data, we examined the influence of herbicide treatment, water clarity, snow depth, and ice cover duration on curlyleaf pondweed distribution and density between 2006 and 2015.
- We evaluated the effects of herbicides on curlyleaf pondweed at three time points relative to treatment: within year, carryover effects the following year, and cumulative effects over multiple years of treatment. All three temporal measures were associated with significant reductions of curlyleaf pondweed. Additionally, herbicidal management reduced both the density and distribution of curlyleaf pondweed. Given that herbicide management led to reductions that carried over into future years, managers may be able to design multi-year treatments to reduce total management effort over time.
- We also found strong effects of environmental conditions on curlyleaf pondweed. Elevated lake productivity and decreased winter snow cover were associated with increased springtime distributions of curlyleaf pondweed, whereas duration of winter ice cover had no influence. The influence of productivity suggests that reductions of this invasive species may be an ancillary benefit of water-quality improvements that lower lakes’ trophic status. Our results also show that decreased winter snow cover, as predicted under climate change, could exacerbate problematic growth of curlyleaf pondweed.
- Harnessing monitoring data from multiple projects, as this study does, allows for robust inference about environmental and management constraints on macrophytes. Because of environmental and management variability, we suggest that treatment regimens follow an adaptive management cycle, with outcomes of management monitored and evaluated, and strategies updated accordingly. It is also vital to continue monitoring both managed and unmanaged lakes to enable stronger inferences about treatment effectiveness.
11.
In many clinical settings, a commonly encountered problem is to assess accuracy of a screening test for early detection of a disease. In these applications, predictive performance of the test is of interest. Variable selection may be useful in designing a medical test. An example is a research study conducted to design a new screening test by selecting variables from an existing screener with a hierarchical structure among variables: there are several root questions followed by their stem questions. The stem questions will only be asked after a subject has answered the root question. It is therefore unreasonable to select a model that only contains stem variables but not its root variable. In this work, we propose methods to perform variable selection with structured variables when predictive accuracy of a diagnostic test is the main concern of the analysis. We take a linear combination of individual variables to form a combined test. We then maximize a direct summary measure of the predictive performance of the test, the area under a receiver operating characteristic curve (AUC of an ROC), subject to a penalty function to control for overfitting. Since maximizing empirical AUC of the ROC of a combined test is a complicated nonconvex problem (Pepe, Cai, and Longton, 2006, Biometrics62, 221-229), we explore the connection between the empirical AUC and a support vector machine (SVM). We cast the problem of maximizing predictive performance of a combined test as a penalized SVM problem and apply a reparametrization to impose the hierarchical structure among variables. We also describe a penalized logistic regression variable selection procedure for structured variables and compare it with the ROC-based approaches. We use simulation studies based on real data to examine performance of the proposed methods. Finally we apply developed methods to design a structured screener to be used in primary care clinics to refer potentially psychotic patients for further specialty diagnostics and treatment. 相似文献
12.
WILLIAM F. LAURANCE 《Austral ecology》2008,33(1):1-9
Abstract Pounds et al. recently argued that the dramatic, fungal pathogen‐linked extinctions of numerous harlequin frogs (Atelopus spp.) in upland rainforests of South America mostly occurred immediately following exceptionally warm years, implicating global warming as a likely trigger for these extinctions. I tested this hypothesis using temperature data for eastern Australia, where at least 14 upland‐rainforest frog species have also experienced extinctions or striking population declines attributed to the same fungal pathogen, and where temperatures have also risen significantly in recent decades. My analyses provide little direct support for the warm‐year hypothesis of Pounds et al., although my statistical power to detect effects of small (0.5°C) temperature increases was limited. However, I found stronger support for a modified version of the warm‐year hypothesis, whereby frog declines were likely to occur following three consecutive years of unusually warm weather. This trend was apparent only at tropical latitudes, where rising minimum temperatures were greatest. Although much remains uncertain, my findings appear consistent with the notion that global warming could predispose some upland amphibian populations to virulent pathogens. 相似文献
13.
Observed phenological changes can be explained either by individual phenotypic plasticity or by evolutionary changes, but there is more evidence pointing towards phenotypic plasticity to explain the mechanism behind changes in bird phenology. However, most studies on phenology have been conducted on insectivorous bird species for which breeding is closely tied to temperature and insect emergence. In this study, we examined the consequences of climatic conditions on the nesting phenology of temperate breeding Canada Geese Branta canadensis maxima, which rely on a continuous food supply, during a 14‐year period (2003–16). We determined whether laying dates were plastically adjusted to spring environmental conditions, and whether this adjustment resulted in a laying date advancement. We further estimated the strength and shape of selection acting on breeding timing, by looking at the effect of laying date on the relative number of young successfully hatched in a nest. We found that Geese plastically adjusted their laying date to spring maximum temperature (and not to precipitation or ice break‐up), resulting in a 9‐day advancement of laying date in the population for that period. Laying date was also moderately repeatable (r = 0.23) and subject to directional selection, but stabilizing selection was negligible. We thus demonstrate how Canada Geese plastically adjust laying dates to temperature, which may further be beneficial to nesting success. Evolutionary change of laying date to selection related to climate change, however, is still possible. 相似文献
14.
15.
Hwei-Ming Wang Tzu-Hao Chang Feng-Mao Lin Te-Hsin Chao Wei-Chih Huang Chao Liang Chao-Fang Chu Chih-Min Chiu Wei-Yun Wu Ming-Cheng Chen Chen-Tsung Weng Shun-Long Weng Feng-Fan Chiang Hsien-Da Huang 《Gene》2013
Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development. 相似文献
16.
Jeffrey Maynard Ruben van Hooidonk C. Drew Harvell C. Mark Eakin Gang Liu Bette L. Willis Gareth J. Williams Maya L. Groner Andrew Dobson Scott F. Heron Robert Glenn Kathleen Reardon Jeffrey D. Shields 《Philosophical transactions of the Royal Society of London. Series B, Biological sciences》2016,371(1689)
To forecast marine disease outbreaks as oceans warm requires new environmental surveillance tools. We describe an iterative process for developing these tools that combines research, development and deployment for suitable systems. The first step is to identify candidate host–pathogen systems. The 24 candidate systems we identified include sponges, corals, oysters, crustaceans, sea stars, fishes and sea grasses (among others). To illustrate the other steps, we present a case study of epizootic shell disease (ESD) in the American lobster. Increasing prevalence of ESD is a contributing factor to lobster fishery collapse in southern New England (SNE), raising concerns that disease prevalence will increase in the northern Gulf of Maine under climate change. The lowest maximum bottom temperature associated with ESD prevalence in SNE is 12°C. Our seasonal outlook for 2015 and long-term projections show bottom temperatures greater than or equal to 12°C may occur in this and coming years in the coastal bays of Maine. The tools presented will allow managers to target efforts to monitor the effects of ESD on fishery sustainability and will be iteratively refined. The approach and case example highlight that temperature-based surveillance tools can inform research, monitoring and management of emerging and continuing marine disease threats. 相似文献
17.
Irena F. Creed Adam T. Spargo Julia A. Jones Jim M. Buttle Mary B. Adams Fred D. Beall Eric G. Booth John L. Campbell Dave Clow Kelly Elder Mark B. Green Nancy B. Grimm Chelcy Miniat Patricia Ramlal Amartya Saha Stephen Sebestyen Dave Spittlehouse Shannon Sterling Mark W. Williams Rita Winkler Huaxia Yao 《Global Change Biology》2014,20(10):3191-3208
Climate warming is projected to affect forest water yields but the effects are expected to vary. We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long‐term experimental catchments across Canada and the United States over 5‐year cool and warm periods. Using the theoretical framework of the Budyko curve, we calculated the effects of climate warming on the annual partitioning of precipitation (P) into evapotranspiration (ET) and water yield. Deviation (d) was defined as a catchment's change in actual ET divided by P [AET/P; evaporative index (EI)] coincident with a shift from a cool to a warm period – a positive d indicates an upward shift in EI and smaller than expected water yields, and a negative d indicates a downward shift in EI and larger than expected water yields. Elasticity was defined as the ratio of interannual variation in potential ET divided by P (PET/P; dryness index) to interannual variation in the EI – high elasticity indicates low d despite large range in drying index (i.e., resilient water yields), low elasticity indicates high d despite small range in drying index (i.e., nonresilient water yields). Although the data needed to fully evaluate ecosystems based on these metrics are limited, we were able to identify some characteristics of response among forest types. Alpine sites showed the greatest sensitivity to climate warming with any warming leading to increased water yields. Conifer forests included catchments with lowest elasticity and stable to larger water yields. Deciduous forests included catchments with intermediate elasticity and stable to smaller water yields. Mixed coniferous/deciduous forests included catchments with highest elasticity and stable water yields. Forest type appeared to influence the resilience of catchment water yields to climate warming, with conifer and deciduous catchments more susceptible to climate warming than the more diverse mixed forest catchments. 相似文献
18.
草甸化草原优势牧草冷地早熟禾生长发育对气候变化的响应 总被引：5，自引：0，他引：5
利用青海湖北岸天然草地中冷地早熟禾(Poa crymophila)定位观测资料,应用数理统计方法,分析了该地区气候变化特征及其对牧草生长发育和产量形成的影响。结果表明:研究区年平均气温呈极显著上升趋势,升幅为0.512℃·10a-1,秋冬季气温上升幅度大于春夏季;年降水量增加主要是由春秋季降水增加所贡献的,年降水量有一个9年左右的周期;牧草生长季的干燥指数呈上升趋势,20世纪90年代末至2010年明显趋于暖干化;冷地早熟禾返青期、抽穗期、开花期和种子成熟期提前,黄枯期推迟,从而使冷地早熟禾整个生育期延长;Logistic模拟结果表明,冷地早熟禾返青后的第72天,其生长速度达到最大,为0.29cm·d-1;从返青后49d开始,由缓慢生长转为迅速生长阶段,从返青后第95天开始,其生长从迅速生长又转为缓慢生长,迅速生长期为46d;冷地早熟禾高度和地上生物量年际变化呈逐年增加趋势;热量对冷地早熟禾产量变化敏感期为5月,旬平均气温升高1℃,产量增加20～30kg·hm-2;抽穗开花期是冷地早熟禾需水敏感期,降水量增大,牧草产量增加。 相似文献
19.
Temperature sums are widely used to predict the seasonal timing of yearly recurring biological events, such as flowering, budburst, and hatching. We use a classic energy allocation model for annual plants to compare a strategy for reproductive timing that follows a temperature sum rule (TSR) with a strategy that follows an optimal control rule (OCR) maximizing reproductive output. We show that the OCR corresponds to a certain TSR regardless of how temperature is distributed over the growing season as long as the total temperature sum over the whole growing season is constant between years. We discuss such scenarios, thus outlining under which type of variable growth conditions TSR maximizes reproductive output and should be favored by natural selection. By providing an ultimate explanation for a well‐documented empirical pattern this finding enhances the credibility of temperature sums as predictors of the timing of biological events. However, TSR and OCR respond in opposite directions when the total yearly temperature sum changes between years, representing, for example, variation in the length of the growing season. Our findings have implications for predicting optimal responses of organisms to climatic changes and suggest under which conditions natural selection should favor photoperiod versus temperature control. 相似文献