一株碱性果胶酶高产细菌的分离、系统发育分析和产酶条件的初步优化

从腐烂的苹果表皮筛选到一株碱性果胶酶的高产菌株,命名为WSHB04-02.分离菌株为革兰氏阳性细菌,有芽孢,菌落颜色为乳白色.分离菌株WSHB04-02的16SrDNA全序列分析表明,该菌株与Bacillussubtilus具有99%的相似性,并与其他13株产碱性果胶酶菌株的16SrDNA结果进行同源性分析,并构建系统发育树.发现菌株WSHB04-02在不含果胶类物质与Mg2 的培养基上能高产碱性果胶酶,在优化的培养条件下,碱性果胶酶的酶活达到34U/mL,在国内还未见报道.图6表2参15     

Local population dynamics of an invasive tree species with a complex life-history cycle: A stochastic matrix model

Biological invasions are widely accepted as having a major impact on ecosystem functioning worldwide, giving urgency to a better understanding of the factors that control their spread. Modelling tools have been developed for this purpose but are often discrete-space, discrete-time spatial-mechanistic models that adopt a computer simulation approach and resist mathematical analysis. We constructed a simple demographic matrix model to explore the local population dynamics of an invasive species with a complex life history and whose invasive success depends on resource availability, which occurs stochastically. As a case study we focused on the American black cherry (Prunus serotina Ehrh.), a gap-dependent tree able both to constitute a long-living seedling bank under unfavourable light conditions and to resprout vigorously once cut-down, which is invading European temperate forests. The model used was a stage-classified matrix population model (i.e., Lefkovitch matrix), integrating environmental stochasticity. Stochastic matrix projection analysis was combined with elasticity analysis and stochastic simulations to search for the species’ ‘Achille heel’. As expected, the population growth rate (i.e., Lyapunov exponent), which measures the risk of P. serotina invasion at the stand scale, increased with light frequency. There was a critical value above which the population of P. serotina explodes and below which it locally goes extinct. The resprouting capacity usually speed up the invasion but appeared to play a minor role. The mean duration of stand invasion was measured and important life stage transitions that mostly contribute to the local stochastic growth rate were identified. Some relevant management implications are discussed and the interest of such models for the understanding of demographic characteristics of invasive species is stressed.     

Clustering species using a model of population dynamics and aggregation theory

The high species diversity of some ecosystems like tropical rainforests goes in pair with the scarcity of data for most species. This hinders the development of models that require enough data for fitting. The solution commonly adopted by modellers consists in grouping species to form more sizeable data sets. Classical methods for grouping species such as hierarchical cluster analysis do not take account of the variability of the species characteristics used for clustering. In this study a clustering method based on aggregation theory is presented. It takes account of the variability of species characteristics by searching for the grouping that minimizes the quadratic error (square bias plus variance) of some model’s prediction. This method allows one to check whether the gain in variance brought by data pooling compensate for the bias that it introduces. This method was applied to a data set on 94 tree species in a tropical rainforest in French Guiana, using a Usher matrix model to predict species dynamics. An optimal trade-off between bias and variance was found when grouping species. Grouping species appeared to decrease the quadratic error, except when the number of groups was very small. This clustering method yielded species groups similar to those of the hierarchical cluster analysis using Ward’s method when variance was small, that is when the number of groups was small.     

Sensitivity analysis with a phosphorus diagenesis model (SPIEL)

Sensitivity analysis is an important part of the modelling procedure. In this paper, sensitivity analysis of a phosphorus diagenesis model (SPIEL) was used for determining the most important parameters and forcing functions, as well as the potential influence of technical in-lake measures on phosphorus (P) release from the sediment. The model “Sedimentary Phosphorus In Eutrophic Lakes” (SPIEL) includes sub-modules for calculating the aerobic layer thickness, the iron–sulphur cycle and the free aluminium sorption capacity. The results of a detailed sensitivity analysis for different module combinations were compared. By means of graphical representation of the cause and effect chains, the synergistic and compensatory effects of different processes on P release in Lake Sempach were discussed. The importance of the iron–sulphur cycle and of the aerobic layer thickness for the P release in this lake is demonstrated.     

Importance of individual and environmental variation for invasive species spread: a spatial integral projection model

Plant survival, growth, and flowering are size dependent in many plant populations but also vary among individuals of the same size. This individual variation, along with variation in dispersal caused by differences in, e.g., seed release height, seed characteristics, and wind speed, is a key determinant of the spread rate of species through homogeneous landscapes. Here we develop spatial integral projection models (SIPMs) that include both demography and dispersal with continuous state variables. The advantage of this novel approach over discrete-stage spread models is that the effect of variation in plant size and size-dependent vital rates can be studied at much higher resolution. Comparing Neubert-Caswell matrix models to SIPMs allowed us to assess the importance of including individual variation in the models. As a test case we parameterized a SIPM with previously published data on the invasive monocarpic thistle Carduus nutans in New Zealand. Spread rate (c*) estimates were 34% lower than for standard spatial matrix models and stabilized with as few as seven evenly distributed size classes. The SIPM allowed us to calculate spread rate elasticities over the range of plant sizes, showing the size range of seedlings that contributed most to c* through their survival, growth and reproduction. The annual transitions of these seedlings were also the most important ones for local population growth (lambda). However, seedlings that reproduced within a year contributed relatively more to c* than to lambda. In contrast, plants that grow over several years to reach a large size and produce many more seeds, contributed relatively more to lambda than to c*. We show that matrix models pick up some of these details, while other details disappear within wide size classes. Our results show that SIPMs integrate various sources of variation much better than discrete-stage matrix models. Simpler, heuristic models, however, remain very valuable in studies where the main goal is to investigate the general impact of a life history stage on population dynamics. We conclude with a discussion of future extensions of SIPMs, including incorporation of continuous time and environmental drivers.     

Optimization model for a wolf-ungulate system

Public outcries against predator control create a need to devise management policies that optimally balance the cost (managerial and environmental) of predator control against the benefit of ungulate harvesting. To address this problem, an optimization procedure utilizing stochastic dynamic programming is described. Through this approach, optimal feedback strategies for a wolf-ungulate system in Alaska are estimated. The dynamic predator-prey model used in the analysis is based on parameter estimates from data collected over an eight-year period in Denali (Mt. McKinley) National Park. Stability analysis of the system revealed that stability properties depend on predator search efficiency. The effects of random fluctuations in winter severity and alternative objective functions are considered in the estimation of optimal feedback strategies. Optimal moose harvesting strategies appear to be dependent on wolf control costs. If no wolf control cost is assessed, optimal moose harvest is independent of wolf density. Optimal wolf control strategies are completely insensitive to moose density. The strategies are compared to current and simplified management policies.     

Cytochrome c used as a model system to probe the structural properties of benthic mucilage

Benthic mucilage, whether native or artificially fragmented to microscopic dimensions by ultrasonic treatment, was mixed with cytochrome c, which was used as a 12 000 Da polycationic model compound. Cytochrome c binding profiles proved to depend on the aggregation state of the mucilage. The native mucus matrix binds cytochrome c quasi hyperbolically with an apparent affinity constant K = 1 × 10⁶  M ⁻¹. As shown by chemical modification of both the mucilage and cytochrome c, the binding expression is dependent on the availability of both the positive charges on the cytochrome c surface and the negative charges within the mucus matrix. The extent of binding is sensitive to the ionic strength of the medium. The ultrasonic-stabilized mucus fragments display a peculiar binding profile, with an apparent low affinity, abruptly entering into a high affinity binding region. The results suggest that, depending on the mucus to polycation ratio, a polymeric reticulus builds up. This reticulus can accommodate molecules of at least 12 000 Da molecular weight. The results are also discussed with respect to biological implications. Received: 23 April 1997 / Accepted: 24 November 1997     

Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model

Species distribution models are usually evaluated with cross-validation. In this procedure evaluation statistics are computed from model predictions for sites of presence and absence that were not used to train (fit) the model. Using data for 226 species, from six regions, and two species distribution modeling algorithms (Bioclim and MaxEnt), I show that this procedure is highly sensitive to "spatial sorting bias": the difference between the geographic distance from testing-presence to training-presence sites and the geographic distance from testing-absence (or testing-background) to training-presence sites. I propose the use of pairwise distance sampling to remove this bias, and the use of a null model that only considers the geographic distance to training sites to calibrate cross-validation results for remaining bias. Model evaluation results (AUC) were strongly inflated: the null model performed better than MaxEnt for 45% and better than Bioclim for 67% of the species. Spatial sorting bias and area under the receiver-operator curve (AUC) values increased when using partitioned presence data and random-absence data instead of independently obtained presence-absence testing data from systematic surveys. Pairwise distance sampling removed spatial sorting bias, yielding null models with an AUC close to 0.5, such that AUC was the same as null model calibrated AUC (cAUC). This adjustment strongly decreased AUC values and changed the ranking among species. Cross-validation results for different species are only comparable after removal of spatial sorting bias and/or calibration with an appropriate null model.     

An efficient fluorescent polymer sensing material for detection of traces of benzo[a]pyrene in environmental samples

A selective sensing polymer for detecting the air pollution marker benzo[a]pyrene (B[a]P) was prepared by molecular imprinting. When the B[a]P adsorb onto the polymer at an excited wavelength 266?nm, it emits a characteristic signal at 432?nm. The intensity of fluorescence signal corresponds to the concentration of B[a]P adsorbed onto the polymer. The cross-selectivity of the sensing polymer using other 5 PAHs was proven by comparing fluorescence intensities, and the effect of matrix in terms of total dissolved solids on sensing property of the polymer was evaluated. Using this polymeric sensor, it is possible to detect 1 part per trillion (ppt) concentration of B[a]P in environmental samples without laborious solvent extraction procedure generally used in gas chromatograph analysis.     

Calibration and uncertainty analysis of a simple model of silica-limited diatom growth in the Elbe River

A simple Lagrangian water quality model was designed to investigate the hypothesis of sporadic silica limitations of diatom growth in the lower Elbe River in Germany. For each fluid parcel a limited reservoir of silica was specified to be consumed by diatoms. The model's simplicity notwithstanding, a set of six selected model parameters could not be fully identified from existing observations at one station. After the introduction of prior knowledge of the ranges of meaningful parameter values, calibration of the over-parameterised model manifested itself primarily in the generation of posterior parameter covariances. Estimations of the covariance matrix based on (a) second order partial derivatives of a quadratic cost function at its optimum and (b) Monte Carlo simulations exploring the whole space of parameter values gave consistent results. Diagonalisation of the covariance matrix yielded two linear parameter combinations that were most effectively controlled by data from periods with and without lack of silica, respectively. The two parameter combinations were identified as the essential inputs that govern the successful simulation of intermittently decreasing chlorophyll a concentrations in summer. A satisfactory simulation of the pronounced chlorophyll a minimum in spring, by contrast, was found to be beyond the means of the simple model.     

Agrobacterium-mediated transformation of Nicotiana attenuata, a model ecological expression system

Summary. Research into the genetic basis of the ecological sophistication of plants is hampered by the availability of transformable systems with a wealth of well-described ecological interactions. We present an Agrobacterium-mediated transformation system for the model ecological expression system, Nicotiana attenuata, a native tobacco that occupies the post-fire niche in the Great Basin Desert of North America. We describe a transformation vector and a transformation procedure that differs from the standard cultivated tobacco transformation protocols in its use of selectable markers, explants, media and cultivation conditions. We illustrate its utility in the transformations with genes coding for key enzymes in the oxylipin cascade (lipoxygenase, allene oxide synthase, hydroperoxide lyase) in antisense orientations and present high-throughput screens useful for the detection of altered phenotypes for the oxylipin cascade (green leaf volatiles and jasmonic acid after wounding). Received 14 March 2002; accepted 10 May 2002     

Assessment of nitrogen leaching from arable land in large river basins: Part I. Simulation experiments using a process-based model

A two-step procedure for analysing nitrogen leaching from arable land in large river basins is suggested: (1) application of a process-based dynamic model for a set of representative conditions in a large river basin to simulate water and nitrogen fluxes and (2) development of a fuzzy-rule based metamodel using the simulated nitrogen fluxes in Step 1 as a training set. After that the metamodel can be used for rapid assessment of water quality inside the considered ranges of parameters, describing natural conditions and management practices. This paper describes Step 1 of the procedure. Step 2 is described in an accompanying paper (Haberlandt et al., Ecological Modelling 150 (3) (2002) 277–294). The advantage of this approach is that it combines the ‘process-based foundation’ with the resulting simplicity of the metamodel. Simulation experiments for analysing nitrogen (N) leaching from arable land were performed using the Soil and Water Integrated Model (SWIM) for a set of representative conditions in the Saale basin (23 687 km²) in Central Europe. The Saale River is one of the main tributaries of the Elbe. In advance, hydrological validation of the model was done for the whole Saale basin and validation of nitrogen dynamics was fulfilled in two mesoscale sub-basins of the Elbe. For the simulation experiments the drainage basin area was sub-divided into five climate zones and nine representative soil classes were chosen. The basic rotation and fertilisation schemes were established using regional information obtained from literature. In addition, the effects of changing the basic rotation to more/less intensive ones and changing fertilisation rates by 50% increase/decrease were studied. The ranges of simulated nitrogen fluxes for the basic rotation and fertilisation schemes are comparable to available regional estimates and differences between sub-regions and soils are plausible. The relative importance of natural and anthropogenic factors affecting nitrogen leaching for the Saale River basin was as follows: (1) soil, (2) climate, (3) fertilisation rate and (4) crop rotation. The simulation experiments provide a basis for a fuzzy-rule based metamodel approach, which aims at rapid water quality assessment of large regions.     

Determination of metallic cobalt in the atmosphere

Due to the fact that, among the different chemical species, metallic cobalt is characterized by the highest toxicity, in this paper is proposed a procedure for its determination in the atmospheric paniculate. The air is filtered on a cellulose or glass fiber membrane, to collect the paniculate containing among the other species, metallic cobalt: the determination is based on a selective dissolution of the metallic cobalt possibly present followed by its determination by atomic absorption spectroscopy. The typical interferences that can be present in the matrix are discussed and suggestions for their minimisation are proposed. By the following procedure is also possible to determine separately the sum of the insoluble and water soluble cobalt compounds.     

Quality of Agroecological Matrix in a Tropical Montane Landscape: Ants in Coffee Plantations in Southern Mexico

Abstract: Conservation efforts in fragmented landscapes frequently focus on characteristics of the habitat fragments. We propose that the matrix within which habitat fragments occur is of equal importance and focus on quality of the matrix as an interesting variable. We studied ground-foraging ants in isolated montane forest fragments in the matrix of coffee agroecosystems of southwestern Chiapas, Mexico. We sampled the ants, with tuna fish as bait, in plots at various distances from a forest fragment (2–750 m) on two farms, one an organic farm with considerable shade, the other a conventional farm with only spotty shade. Each plot contained a grid of 49 ( 7 × 7) or 100 (10 × 10) baits. The species richness of ground-foraging ants was not significantly different between the forest fragment and the high-quality matrix, but it was significantly lower in the low-quality matrix than in the forest. Furthermore, species richness decreased with distance from the forest fragment in both matrix types. However, the rate of decrease in species richness was greater in the conventional farm ( poor-quality matrix) than in the organic farm ( high-quality matrix), suggesting that the quality of the agricultural matrix is important for the conservation of ant diversity.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Mapping woodland vegetation in SW Ethiopia based on a hybrid model

SUMMARY

Despite the fact that indigenous inhabitants have sustainably managed the forests and woodlands for centuries, Ethiopia's woodland resources are now under severe pressure. At the request of the Ethiopian Government, in 1996/97 the Savanna Woodland Management Study Project was initiated by the German Technical Cooperation (GTZ). A detailed analysis of the woodland resources in SW Ethiopia and a vegetation map were produced. The map was generated using multispectral remote-sensing data, and provides details of the variety within Ethiopian woodlands. A hybrid data classification procedure was applied to incorporate relief and climatic conditions. After analysis of the remote sensing data by image processing, a spatial overlay was performed to incorporate the additional site condition factors. The vegetation map shows the spatial distribution of all existing woodland types in the area and enhances our knowledge of the rich biodiversity of SW Ethiopia. Such mapping gives us a better understanding of existing ecosystems and indigenous land-use systems, and hence, can lead to more sustainable management of the natural resources in the future.     

Simulating wildfire patterns using a small-world network model

This paper presents the development and validation results of a weighted small-world network model designed to simulate fire patterns in real heterogeneous landscapes. Fire spread is simulated on a gridded landscape, a mosaic in which each cell represents an area of the land surface. In this model, the interaction between burning and non-burning cells (here, due to flame radiation) may extend well beyond nearest neighbors, and depends on local conditions of wind, topography, and vegetation. An approach based on the coupling of the solid flame model with the Monte Carlo method is used to predict the radiative heat flux from the flame generated by the burning of each combustible cell to its neighbors. The weighting procedure takes into account latency (a combustible cell will only ignite when it has accumulated enough energy along time) and flaming persistence of burning cells. The model is applied to very different fire scenarios: a historical Mediterranean fire that occurred in southeastern France in 2005 and experimental fires conducted in arid savanna fuels in South Africa in 1992. Model results are found to be in agreement with real fire patterns, in terms both of rate of spread, and of the area and shape of the burn. This work also shows that the fractal properties of fire patterns predicted by the model are similar to those observed from satellite images of three other Mediterranean fire scars.     

On interacting bee/mite populations: a stochastic model with analysis using cumulant truncation

Parasitism by the Varroa mite has had recent drastic impact on both managed and feral bee colonies. This paper proposes a stochastic population dynamics model for interacting African bee colony and Varroa mite populations. Cumulant truncation procedures are used to obtain approximate transient cumulant functions, unconstrained by the usual assumption of bivariate Normality, for an assumed large-scale model. The apparent size of the variance and skewness functions suggest the importance of the proposed truncation procedure which retains some higher-order cumulants, but determining the accuracy of the approximations is problematical. A smaller-scale bee/Varroa mite model is hence proposed and investigated. The accuracy for the means is exceptional, for the second-order cumulants is moderate, and for some third-order cumulants is poor. Notwithstanding the poor accuracy of a skewness approximation, the saddlepoint approximations for the marginal transient population size distributions are excellent. The cumulant truncation methodology is very general, and research is continuing in its application to this new class of host-parasite models.