广州市风水林群落空间异质性及其对区域物种多样性的贡献

以广州地区村边风水林为研究对象,选取了67个风水林斑块,并在每个斑块内建立了一个20m×20m的样方,调查了其胸径大于1cm的植物组成。首先以种面积关系外推法和非参数法估计了风水林群落对区域生物多样性的贡献;然后以加法准则拆分了gamma多样性,以分析风水林群落物种组成的异质性;最后根据每个风水林群落的物种丰富度、稀有种(在所有群落中只出现一次的物种)数目和谱系多样性分析了在保护中需要优先考虑的区域。结果发现：（1）广州地区风水林群落至少保存了32.74%的区域物种多样性;（2）gamma多样性(184)中绝大部分由beta多样性(163.43)构建,只有很小部分来自于alpha多样性(20.57)。这表明风水林群落在物种组成上具有较高的空间异质性,要想尽可能多地保护风水林内物种多样性,就需要尽可能多地保护风水林群落斑块;（3）相对于平原地区,位于山区的风水林群落具有更高的物种丰富度和谱系多样性以及更多的稀有种数目。在保护资金和土地资源有限的情况下,位于山区的风水林群落应该给予优先考虑。     

南方红壤区3年生茶园土壤呼吸特征

为探讨南方红壤区茶园的土壤呼吸特征,采用LI-Cor8100开路式土壤碳通量测定系统观测3年生茶园系统的土壤呼吸速率,对茶园土壤呼吸速率的季节变化和在茶行尺度上的空间异质性进行了研究。结果表明,茶园土壤呼吸速率的月动态变化呈明显的单峰曲线特征,峰值出现在8月;茶园土壤呼吸速率的月动态变化与温度呈极显著相关(P<0.01),土壤10 cm的温度能够解释茶园不同观测区域土壤呼吸速率月动态变化的67.79%~88.52%;用指数方程计算的茶园不同观测区域土壤呼吸Q10值为1.58~1.86。在茶行尺度上,茶园土壤呼吸速率存在明显的空间异质性,土壤呼吸速率通常在距离茶树基部较近的位置较高;根系生物量能够解释茶园土壤呼吸速率在茶行尺度上空间变异的82.68%。因此,根系分布的空间差异是造成茶园土壤呼吸速率空间异质性的主要原因。     

The advantage of laser‐capture microdissection over whole tissue analysis in proteomic profiling studies

Laser‐capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label‐free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p‐value < 0.001). 2D analysis on co‐expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 ( http://proteomecentral.proteomexchange.org/dataset/PXD002381 ).     

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.     

Environmental variability and population dynamics: do European and North American ducks play by the same rules?

Density dependence, population regulation, and variability in population size are fundamental population processes, the manifestation and interrelationships of which are affected by environmental variability. However, there are surprisingly few empirical studies that distinguish the effect of environmental variability from the effects of population processes. We took advantage of a unique system, in which populations of the same duck species or close ecological counterparts live in highly variable (north American prairies) and in stable (north European lakes) environments, to distinguish the relative contributions of environmental variability (measured as between‐year fluctuations in wetland numbers) and intraspecific interactions (density dependence) in driving population dynamics. We tested whether populations living in stable environments (in northern Europe) were more strongly governed by density dependence than populations living in variable environments (in North America). We also addressed whether relative population dynamical responses to environmental variability versus density corresponded to differences in life history strategies between dabbling (relatively “fast species” and governed by environmental variability) and diving (relatively “slow species” and governed by density) ducks. As expected, the variance component of population fluctuations caused by changes in breeding environments was greater in North America than in Europe. Contrary to expectations, however, populations in more stable environments were not less variable nor clearly more strongly density dependent than populations in highly variable environments. Also, contrary to expectations, populations of diving ducks were neither more stable nor stronger density dependent than populations of dabbling ducks, and the effect of environmental variability on population dynamics was greater in diving than in dabbling ducks. In general, irrespective of continent and species life history, environmental variability contributed more to variation in species abundances than did density. Our findings underscore the need for more studies on populations of the same species in different environments to verify the generality of current explanations about population dynamics and its association with species life history.     

Environmental heterogeneity among lakes promotes hyper β‐diversity across phytoplankton communities

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Demographic buffering and compensatory recruitment promotes the persistence of disease in a wildlife population

Demographic buffering allows populations to persist by compensating for fluctuations in vital rates, including disease‐induced mortality. Using long‐term data on a badger (Meles meles Linnaeus, 1758) population naturally infected with Mycobacterium bovis, we built an integrated population model to quantify impacts of disease, density and environmental drivers on survival and recruitment. Badgers exhibit a slow life‐history strategy, having high rates of adult survival with low variance, and low but variable rates of recruitment. Recruitment exhibited strong negative density‐dependence, but was not influenced by disease, while adult survival was density independent but declined with increasing prevalence of diseased individuals. Given that reproductive success is not depressed by disease prevalence, density‐dependent recruitment of cubs is likely to compensate for disease‐induced mortality. This combination of slow life history and compensatory recruitment promotes the persistence of a naturally infected badger population and helps to explain the badger's role as a persistent reservoir of M. bovis.     

Relationships between wild bees,hoverflies and pollination success in apple orchards with different landscape contexts

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Distinct cellular states determine calcium signaling response

The heterogeneity in mammalian cells signaling response is largely a result of pre‐existing cell‐to‐cell variability. It is unknown whether cell‐to‐cell variability rises from biochemical stochastic fluctuations or distinct cellular states. Here, we utilize calcium response to adenosine trisphosphate as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states coexist. We use a functional definition of cellular state that is based on a mechanistic dynamical systems model of calcium signaling. Using Bayesian parameter inference, we obtain high confidence parameter value distributions for several hundred cells, each fitted individually. Clustering the inferred parameter distributions revealed three major distinct cellular states within the population. The existence of distinct cellular states raises the possibility that the observed variability in response is a result of structured heterogeneity between cells. The inferred parameter distribution predicts, and experiments confirm that variability in IP3R response explains the majority of calcium heterogeneity. Our work shows how mechanistic models and single‐cell parameter fitting can uncover hidden population structure and demonstrate the need for parameter inference at the single‐cell level.