南海4种珊瑚附生可培养真菌多样性分析

本研究利用从南海采集的4种珊瑚分离附生真菌,并通过菌株的分类鉴定及系统发育分析获得珊瑚附生可培养真菌的多样性信息.选用酵母麦芽糖琼脂培养基(YM)、马铃薯葡萄糖琼脂培养基(PDA)、马丁氏培养基(Martin)、察氏琼脂培养基(CDA)和孟加拉红培养基(RBM)等5种培养基,采用平板涂布法培养分离附生真菌,基于ITS-rRNA基因序列对真菌菌株进行鉴定和系统发育分析.从4种珊瑚上共分离获得10个属的120株真菌,分别是:青霉属(Penicillum)56株、曲霉属(Aspergillus)25株、枝顶孢属(Acremonium)2株、枝孢属(Cladosporium)5株、毕赤酵母属(Meyerozyma)14株、隔孢伏革属(Peniophora)2株、拟茎点霉属(Phomopsis)1株、裂褶菌属(Schizophyllum)1株、梗孢酵母属(Sterigmatomyces)13株、篮状菌属(Talaromyces)1株.通过对不同珊瑚品种分离获得的附生真菌的比较,发现小叶鹿角珊瑚(Acropora microphthalma)和花鹿角珊瑚(Acropora floride)上分离到的菌株多样性最高,包含6属10种.进一步的分析发现不同珊瑚样品上真菌种类分布有较大差异,隔孢伏革属和裂褶菌属真菌均分离自小叶鹿角珊瑚,梗孢酵母属和篮状菌属均分离自角孔珊瑚(Goniopora sp.),扁脑珊瑚(Platygyra sp.)上则分离到拟茎点霉属.同时还发现不同培养基分离真菌的能力不同,YM培养基分离的菌株最多,CDA培养基分离真菌的多样性最多.以上的研究结果表明,南海珊瑚上存在大量且丰富的真菌资源,可以为后续生物活性物质的开发利用提供良好的菌种资源.     

Uncertainty in resilience to climate change in India and Indian states

This study builds on an earlier analysis of resilience of India and Indian states to climate change. The previous study (Brenkert and Malone, Clim Change 72:57–102, 2005) assessed current resilience; this research uses the Vulnerability–Resilience Indicators Model (VRIM) to project resilience to 2095 and to perform an uncertainty analysis on the deterministic results. Projections utilized two SRES-based scenarios, one with fast-and-high growth, one with delayed growth. A detailed comparison of two states, the Punjab and Orissa, points to the kinds of insights that can be obtained using the VRIM. The scenarios differ most significantly in the timing of the uncertainty in economic prosperity (represented by GDP per capita) as a major factor in explaining the uncertainty in the resilience index. In the fast-and-high growth scenario the states differ most markedly regarding the role of ecosystem sensitivity, land use and water availability. The uncertainty analysis shows, for example, that resilience in the Punjab might be enhanced, especially in the delayed growth scenario, if early attention is paid to the impact of ecosystems sensitivity on environmental well-being of the state. By the same token, later in the century land-use pressures might be avoided if land is managed through intensification rather than extensification of agricultural land. Thus, this methodology illustrates how a policy maker can be informed about where to focus attention on specific issues, by understanding the potential changes at a specific location and time—and, thus, what might yield desired outcomes. Model results can point to further analyses of the potential for resilience-building.     

A Snapshot of the Sun Near Solar Minimum: The Whole Heliosphere Interval

We present an overview of the data and models collected for the Whole Heliosphere Interval, an international campaign to study the three-dimensional solar?Cheliospheric?Cplanetary connected system near solar minimum. The data and models correspond to solar Carrington Rotation 2068 (20 March??C?16 April 2008) extending from below the solar photosphere, through interplanetary space, and down to Earth??s mesosphere. Nearly 200 people participated in aspects of WHI studies, analyzing and interpreting data from nearly 100 instruments and models in order to elucidate the physics of fundamental heliophysical processes. The solar and inner heliospheric data showed structure consistent with the declining phase of the solar cycle. A closely spaced cluster of low-latitude active regions was responsible for an increased level of magnetic activity, while a highly warped current sheet dominated heliospheric structure. The geospace data revealed an unusually high level of activity, driven primarily by the periodic impingement of high-speed streams. The WHI studies traced the solar activity and structure into the heliosphere and geospace, and provided new insight into the nature of the interconnected heliophysical system near solar minimum.     

Spatial variability of soil nutrients in Punta Fort William,Greenwich Island,maritime Antarctic

This study aims to report baseline soil nutrients, specifically the organic carbon, nitrogen and phosphorus profile, in soil samples collected from Puntta Fort William on Greenwich Island in maritime Antarctic. Samples were collected along two transect lines during the early summer of 2008. Ward＇s method of hierarchical agglomerative clustering was employed to group the sampling points based on their physico-chemical properties. In this context, the soil samples can be grouped into three major clus- ters： （1） Samples with intensive biological activities, （2） samples from the area recently exposed by glacial retreat and （3） samples from barren and dried areas. Nutrient contents in Punta Fort William are driven by the intensity of biological activities as well as melt water from the Qnito glacier.     

An automated 3D modeling of topological indoor navigation network

Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future.     

SWAT-based hydrological modelling of tropical land-use scenarios

Abstract

The Hulu Langat basin, a strategic watershed in Malaysia, has in recent decades been exposed to extensive changes in land-use and consequently hydrological conditions. In this work, the impact of Land Use and Cover Change (LUCC) on hydrological conditions (water discharge and sediment load) of the basin were investigated using the Soil and Water Assessment Tool (SWAT). Four land-use scenarios were defined for land-use change impact analysis, i.e. past, present (baseline), future and water conservation planning. The land-use maps, dated 1984, 1990, 1997 and 2002, were defined as the past scenarios for LUCC impact analysis. The present scenario was defined based on the 2006 land-use map. The 2020 land-use map was simulated using a cellular automata-Markov model and defined as the future scenario. Water conservation scenarios were produced based on guidelines published by Malaysia’s Department of Town and Country Planning and Department of Environment. Model calibration and uncertainty analysis was performed using the Sequential Uncertainty Fitting (SUFI-2) algorithm. The model robustness for water discharge simulation for the period 1997–2008 was good. However, due to uncertainties, mainly resulting from intense urban development in the basin, its robustness for sediment load simulation was only acceptable for the calibration period 1997–2004. The optimized model was run using different land-use maps over the periods 1997–2008 and 1997–2004 for water discharge and sediment load estimation, respectively. In comparison to the baseline scenario, SWAT simulation using the past and conservative scenarios showed significant reduction in monthly direct runoff and monthly sediment load, while SWAT simulation based on the future scenario showed significant increase in monthly direct runoff, monthly sediment load and groundwater recharge.

Editor D. Koutsoyiannis; Associate editor C. Perrin     

A population health model for integrated assessment models

In this paper we present the initial results from a project to develop a population health model so we can extend the scenarios included in the IPCC’s Special Report on Emission Scenarios to include population health status. Our initial hypothesis was that some climatic variable, particularly temperature, would have a significant impact on health outcomes. After experiments – using the Global Burden of Disease (GBD) data on Years of Life Lost (YLL) and Years Lived with disability (YLD) both by WHO region and by five degree latitude band as outcome variables – failed, we settled on life expectancy (LE) as the best measure of health status. We discovered that there is a solid relationship between LE and the GBD data from our first experiments, allowing us to extend the results from the LE model. The LE model used cross section data on LE for 91 countries and included temperature, per capita income, access to clean water and sanitation, literacy, simple medical attention, nutrition, per capita medical expenditure, electricity use per capita, and automobiles per capita as independent variables. While all were individually associated with LE, our model of choice included literacy, access to clean water and sanitation, simple medical attention, an indictor variable for Sub-Saharan Africa and purchasing-power parity per capita income. Note that neither temperature nor calories enter into this model. The fit between life expectancy, as predicted by this model, and actual life expectancy was quite good (R ² =0.90), except for Rwanda, Uganda, and Madagascar; these countries accounted for one half of the unexplained variation in the model. The LE model was then used to develop trajectories of life expectancy in India for the four IPCC SRES storylines, where values for the independent variables were extrapolated based on the story line content. YLL and YLD estimates were created using the current cross relationship of these outcomes to LE. Given the lack of a general role for climate in our LE model, future work is planned to explore how to add detailed climate related impacts, to explore alternative nutritional variables, as well as extend the data set to allow a cross-section time-series approach.     

Biotechnology: Its place in geography

Biotechnology is the manipulation of organisms to carry out specific processes. It has various applications that are relevant to many aspects of geography. At a fundamental level biotechnology is directed at manipulating energy flows, especially those in agriculture. Improved crop varieties, disease and pest control, as well as nutrient enhancement can all be achieved by biotechnology, culminating in increased agricultural productivity. There are significant environmental advantages though there are also constraints imposed by economic considerations. Mineral extraction, metal recycling and pollution abatement can also be improved by biotechnology which thus contributes to more efficient resource use and enhanced environmental quality. Food and fuel energy, notably biomass fuels, can also be so produced. The manifold implications of this technology for earth and social sciences thus require its inclusion in geographical studies.