不同碳源条件下草菇内切型纤维素酶基因（eg1）转录表达的分析

利用Northernblot方法分析了不同碳源条件下草菇切型纤维素酶基因(eg1)的表达.结果发现,在含有纤维素的液体培养基中生长10d,eg1在草菇菌丝中有高效表达;纤维二糖、α-乳糖、β-乳糖,也能诱导eg1的表达,但和纤维素相比,eg1的表达量相对较低,并且它们的诱导效应在加入这类糖12h后迅速减弱;槐糖和龙胆二糖的诱导作用非常弱.在天然稻草为基质的固体栽培料生长时,草菇eg1的表达和草菇菌丝生长与出菇相对应,在菌丝生长期(d8)可见eg1的表达,d12时菌丝已长满,表达减弱,在出菇及菇体的分化及增大期,eg1的表达量逐渐增强,在成熟期达到最高水平;表明在草菇菇体发育中需要更多碳源及能源的补充,eg1在这方面起着非常重要的作用.图4参14     

Conservation and Management of a Threatened Madagascar Palm Species, Neodypsis decaryi, Jumelle

The dynamics of a remnant population of the palm Neodypsis decaryi were characterized using a linear, stage-structured demographic model. This palm is a threatened keystone species restricted to a narrow ecological zone in southeastern Madagascar. The population showed high mortality rates in the early stages of the life cycle, followed by a period of lower adult mortality. Demographic results indicated that the population was either stable or increasing inside the reserve (λ _m close to 1.0). Sensitivity and elasticity analyses indicated that adult stage classes were the most sensitive to producing changes in population growth rates. Continued biological monitoring is appropriate for the long-term conservation management of this palm inside the reserve. Outside the protected area the population appears to be declining rapidly, mainly because of anthropogenic effects (especially fire and grazing). If the conservation of Neodypsis decaryi is to be successful in the long term, then conservation methods must be carried out in cooperation with local villagers, and the species should be managed as a renewable resource in situ and ex situ. In situ conservation should include cultivation of this species throughout its natural range and protection of the existing viable natural populations. Alternative conservation management practices, both ecologically and economically sustainable, may be useful to alleviate the human pressures on this renewable resource. If leaves of N. decaryi are to be harvested by local people, we recommend restricting annual harvesting to about 25% of leaves per tree per year. Based on sensitivity analysis, seed collection should be kept well below 95% of the yearly crop if harvesting is not to have a significant impact on population growth rates.     

A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation

In this study we combined an extensive database of observed wildfires with high-resolution meteorological data to build a novel spatially and temporally varying survival model to analyze fire regimes in the Mediterranean ecosystem in the Cape Floristic Region (CFR) of South Africa during the period 1980-2000. The model revealed an important influence of seasonally anomalous weather on fire probability, with increased probability of fire in seasons that are warmer and drier than average. In addition to these local-scale influences, the Antarctic Ocean Oscillation (AAO) was identified as an important large-scale influence or teleconnection to global circulation patterns. Fire probability increased in seasons during positive AAO phases, when the subtropical jet moves northward and low level moisture transport decreases. These results confirm that fire occurrence in the CFR is strongly affected by climatic variability at both local and global scales, and thus likely to respond sensitively to future climate change. Comparison of the modelled fire probability between two periods (1951-1975 and 1976-2000) revealed a 4-year decrease in an average fire return time. If, as currently forecasted, climate change in the region continues to produce higher temperatures, more frequent heat waves, and/or lower rainfall, our model thus indicates that fire frequency is likely to increase substantially. The regional implications of shorter fire return times include shifting community structure and composition, favoring species that tolerate more frequent fires.     

Can entropy maximization use functional traits to explain species abundances? A comprehensive evaluation

Entropy maximization (EM) is a method that can link functional traits and community composition by predicting relative abundances of each species in a community using limited trait information. We developed a complementary suite of tests to examine the strengths and limitations of EM and the community-aggregated traits (CATs; i.e., weighted averages) on which it depends that can be applied to virtually any plant community data set. We show that suites of CATs can be used to differentiate communities and that EM can address the classic problem of characterizing ecological niches by quantifying constraints (CATs) on complex trait relationships in local communities. EM outperformed null models and comparable regression models in communities with different levels of dominance, diversity, and trait similarity. EM predicted well the abundance of the dominant species that drive community-level traits; it typically identified rarer species as such, although it struggled to predict the abundances of the rarest species in some cases. Predictions were sensitive to choice of traits, were substantially improved by using informative priors based on null models, and were robust to variation in trait measurement due to intraspecific variability or measurement error. We demonstrate how similarity in species' traits confounds predictions and provide guidelines for applying EM.     

Building statistical models to analyze species distributions.

Models of the geographic distributions of species have wide application in ecology. But the nonspatial, single-level, regression models that ecologists have often employed do not deal with problems of irregular sampling intensity or spatial dependence, and do not adequately quantify uncertainty. We show here how to build statistical models that can handle these features of spatial prediction and provide richer, more powerful inference about species niche relations, distributions, and the effects of human disturbance. We begin with a familiar generalized linear model and build in additional features, including spatial random effects and hierarchical levels. Since these models are fully specified statistical models, we show that it is possible to add complexity without sacrificing interpretability. This step-by-step approach, together with attached code that implements a simple, spatially explicit, regression model, is structured to facilitate self-teaching. All models are developed in a Bayesian framework. We assess the performance of the models by using them to predict the distributions of two plant species (Proteaceae) from South Africa's Cape Floristic Region. We demonstrate that making distribution models spatially explicit can be essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results. Adding hierarchical levels to the models has further advantages in allowing human transformation of the landscape to be taken into account, as well as additional features of the sampling process.     

不同碳源条件下草菇内切型纤维素酶基因(egl)转录表达的分析

利用Northern blot方法分析了不同碳源条件下草菇內切型纤维素酶基因(eg1)的表达.结果发现,在含有纤维素的液体培养基中生长10 d,eg1在草菇菌丝中有高效表达;纤维二糖、α-乳糖、β-乳糖,也能诱导eg1的表达,但和纤维素相比,eg1的表达量相对较低,并且它们的诱导效应在加入这类糖12 h后迅速减弱;槐糖和龙胆二糖的诱导作用非常弱.在天然稻草为基质的固体栽培料生长时,草菇eg1的表达和草菇菌丝生长与出菇相对应,在菌丝生长期(d 8)可见eg1的表达,d 12时菌丝已长满,表达减弱,在出菇及菇体的分化及增大期,eg1的表达量逐渐增强,在成熟期达到最高水平;表明在草菇菇体发育中需要更多碳源及能源的补充,eg1在这方面起着非常重要的作用. 图4 参14