Temporal and Spatial Variabilities of Chemical and Physical Parameters on the Heron Island Coral Reef Platform

Globally, coral reefs are threatened by ocean warming and acidification. The degree to which acidification will impact reefs is dependent on the local hydrodynamics, benthic community composition, and biogeochemical processes, all of which vary on different temporal and spatial scales. Characterizing the natural spatiotemporal variability of seawater carbonate chemistry across different reefs is critical for elucidating future impacts on coral reefs. To date, most studies have focused on select habitats, whereas fewer studies have focused on reef scale variability. Here, we investigate the temporal and spatial seawater physicochemical variability across the entire Heron Island coral reef platform, Great Barrier Reef, Australia, for a limited duration of six days. Autonomous sensor measurements at three sites across the platform were complemented by reef-wide boat surveys and discrete sampling of seawater carbonate chemistry during the morning and evening. Variability in both temporal and spatial physicochemical properties were predominantly driven by solar irradiance (and its effect on biological activity) and the semidiurnal tidal cycles but were influenced by the local geomorphology resulting in isolation of the platform during low tide and rapid flooding during rising tides. As a result, seawater from previous tidal cycles was sometimes trapped in different parts of the reef leading to unexpected biogeochemical trends in space and time. This study illustrates the differences and limitations of data obtained from high-frequency measurements in a few locations compared to low-frequency measurements at high spatial resolution and coverage, showing the need for a combined approach to develop predictive capability of seawater physicochemical properties on coral reefs.

     

A framework for spatio-temporal scales and concepts from different disciplines: the ‘vulnerability cube’

The concept of vulnerability is increasingly used in the fields of disaster risk reduction and climate change adaptation, as well as socioeconomic studies. This paper reviews research inputs into the concept of vulnerability and highlights the challenges of resolving its spatial and temporal variability with building resilience and adaptation. We hypothesise that a clear understanding of scale is key to integrating these related issues, by differentiating three dimensions of scale when analysing relationships between the observed and the intrinsic scale of a given phenomenon, namely space, time and dimensional level. The paper analyses 20 vulnerability assessment approaches, ranging from the global down to the local scale, and positions them with regard to their integration of the spatial component. We then develop a vulnerability cube as a framework to position existing approaches and to map them in a three-dimensional space. The three axes represent space, time and dimension and provide a structure for the different notions of scales and ultimately for a spatial analysis workflow. The vulnerability cube framework helps us to position different vulnerability assessments and to identify overlaps, differences and specific characteristics. Additionally, this three-dimensional conceptualisation allows the identification and discussion of appropriate scaling issues.     

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan,China

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.     

Innovative landslide susceptibility mapping supported by geomorphon and geographical detector methods

Landslides are among the most common and dangerous natural hazards in mountainous regions that can cause damage to properties and loss of lives. Landslide susceptibility mapping (LSM) is a critical tool for preventing or mitigating the negative impacts of landslides. Although many previous studies have employed various statistical methods to produce quantitative maps of the landslide susceptibility index (LSI) based on inventories of past landslides and contributing factors, they are mostly ad hoc to a specific area and their success has been hindered by the lack of a methodology that could produce the right mapping units at proper scale and by the lack of a general framework for objectively accounting for the differing contribution of various preparatory factors. This paper addresses these issues by integrating the geomorphon and geographical detector methods into LSM to improve its performance. The geomorphon method, an innovative pattern recognition approach for identifying landform elements based on the line of sight concept, is adapted to delineate ridge lines and valley lines to form slope units at self-adjusted spatial scale suitable for LSM. The geographical detector method, a spatial variance analysis method, is integrated to objectively assign the weights of contributing factors for LSM. Applying the new integrated approach to I-Lan, Taiwan produced very significant improvement in LSI mapping performance than a previous model, especially in highly susceptible areas. The new method offers a general framework for better mapping landslide susceptibility and mitigating its negative impacts.     

Multi-hazard model for developing countries

Disaster risk assessment related to natural events has generally been carried out separately by specialists in each area of earth sciences, which has two negative consequences: Firstly, results of investigations are presented in different formats, mainly maps, which differ significantly from each other in aspects such as scale, symbols and units; secondly, it is common for an area or territory to contain several hazards that can potentially interact with each other, generating cascade effects or synergies. While some authors have proposed a multi-hazard analysis framework based on the use of probabilities, the quality and quantity of data required for this approach are rarely available in developing countries. Qualitative methods, on the other hand, have traditionally been limited to overlapping maps, without considering possible spatial interactions. Given the importance of integrated assessment of natural hazards for land use planning and risk management, this article proposes a heuristic multi-hazard model appropriate for developing countries, based on a standardization of classifications and a spatial interaction matrix between hazards. The model can be adjusted to be applied at different scales and in different territories; to demonstrate its versatility, it is applied to the municipality of Poás, Costa Rica, a territory with multiple natural hazards.

     

Towards a geocomputational landscape epidemiology: surveillance,modelling, and interventions

The ability to explicitly represent infectious disease distributions and their risk factors over massive geographical and temporal scales has transformed how we investigate how environment impacts health. While landscape epidemiology studies have shed light on many aspects of disease distribution and risk differentials across geographies, new computational methods combined with new data sources such as citizen sensors, global spatial datasets, sensor networks, and growing availability and variety of satellite imagery offer opportunities for a more integrated approach to understanding these relationships. Additionally, a large number of new modelling and mapping methods have been developed in recent years to support the adoption of these new tools. The complexity of this research context results in study-dependent solutions and prevents landscape approaches from deeper integration into operational models and tools. In this paper we consider three common research contexts for spatial epidemiology; surveillance, modelling to estimate a spatial risk distribution and the need for intervention, and evaluating interventions and improving healthcare. A framework is proposed and a categorization of existing methods is presented. A case study into leptospirosis in Sri Lanka provides a working example of how the different phases of the framework relate to real research problems. The new framework for geocomputational landscape epidemiology encompasses four key phases: characterizing assemblages, characterizing functions, mapping interdependencies, and examining outcomes. Results from Sri Lanka provide evidence that the framework provides a useful way to structure and interpret analyses. The framework reported here is a new way to structure existing methods and tools of geocomputation that are increasingly relevant to researchers working on spatially explicit disease-landscape studies.     

A multi-dimensional assessment of urban vulnerability to climate change in Sub-Saharan Africa

In this paper, we develop and apply a multi-dimensional vulnerability assessment framework for understanding the impacts of climate change-induced hazards in Sub-Saharan African cities. The research was carried out within the European/African FP7 project CLimate change and Urban Vulnerability in Africa, which investigated climate change-induced risks, assessed vulnerability and proposed policy initiatives in five African cities. Dar es Salaam (Tanzania) was used as a main case with a particular focus on urban flooding. The multi-dimensional assessment covered the physical, institutional, attitudinal and asset factors influencing urban vulnerability. Multiple methods were applied to cover the full range of vulnerabilities and to identify potential response strategies, including: model-based forecasts, spatial analyses, document studies, interviews and stakeholder workshops. We demonstrate the potential of the approach to assessing several dimensions of vulnerability and illustrate the complexity of urban vulnerability at different scales: households (e.g., lacking assets); communities (e.g., situated in low-lying areas, lacking urban services and green areas); and entire cities (e.g., facing encroachment on green and flood-prone land). Scenario modeling suggests that vulnerability will continue to increase strongly due to the expected loss of agricultural land at the urban fringes and loss of green space within the city. However, weak institutional commitment and capacity limit the potential for strategic coordination and action. To better adapt to urban flooding and thereby reduce vulnerability and build resilience, we suggest working across dimensions and scales, integrating climate change issues in city-level plans and strategies and enabling local actions to initiate a ‘learning-by-doing’ process of adaptation.

     

水权交易对生态环境影响研究进展

在经济社会发展受到区域水资源总量限制的情况下,水权交易作为解决当今世界严峻水资源危机的重要手段之一,已在国内外进行了广泛的实践。水权交易改变了水资源的时空配置,对水生态和水环境产生有利或不利的影响,然而关于水权交易对生态环境影响的研究尚未有系统的梳理。总结了水权交易对水资源系统影响研究的主要发展历程,着重论述了水权交易对水资源系统影响的4个重点研究方面:可交易生态环境水权的研究、水权交易对水量、水生态、水环境影响的研究。未来应当加强水权交易对生态环境影响的定量研究,进一步提升水权交易对水质、地下水、退水、陆生生态环境影响的研究,明确不同交易类型的不同影响,还应考虑不确定性因素的影响。     

A multi-dimensional assessment of urban vulnerability to climate change in Sub-Saharan Africa

In this paper, we develop and apply a multi-dimensional vulnerability assessment framework for understanding the impacts of climate change-induced hazards in Sub-Saharan African cities. The research was carried out within the European/African FP7 project CLimate change and Urban Vulnerability in Africa, which investigated climate change-induced risks, assessed vulnerability and proposed policy initiatives in five African cities. Dar es Salaam (Tanzania) was used as a main case with a particular focus on urban flooding. The multi-dimensional assessment covered the physical, institutional, attitudinal and asset factors influencing urban vulnerability. Multiple methods were applied to cover the full range of vulnerabilities and to identify potential response strategies, including: model-based forecasts, spatial analyses, document studies, interviews and stakeholder workshops. We demonstrate the potential of the approach to assessing several dimensions of vulnerability and illustrate the complexity of urban vulnerability at different scales: households (e.g., lacking assets); communities (e.g., situated in low-lying areas, lacking urban services and green areas); and entire cities (e.g., facing encroachment on green and flood-prone land). Scenario modeling suggests that vulnerability will continue to increase strongly due to the expected loss of agricultural land at the urban fringes and loss of green space within the city. However, weak institutional commitment and capacity limit the potential for strategic coordination and action. To better adapt to urban flooding and thereby reduce vulnerability and build resilience, we suggest working across dimensions and scales, integrating climate change issues in city-level plans and strategies and enabling local actions to initiate a ‘learning-by-doing’ process of adaptation.     

基于遥感和GIS的新疆绿洲城市扩展时空动态变化分析

以新疆16座城市为研究对象, 运用多时相卫星遥感资料, 利用遥感和GIS技术提取城市的空间特征信息, 并通过城市扩展强度、扩展速率以及城市空间形态紧凑度和分形维数等指标定量分析了1990-2010年以来新疆城市扩展时空动态变化的过程和特征. 结果表明: 新疆城市的空间分布由其独特的自然环境和绿洲经济所决定, 许多城市的发展依托于绿洲, 城镇的形成具有"亲水性"的特点, 由于新疆地域辽阔, 交通干线附近往往形成城镇相对集中的城市带或城市群. 南北疆城市之间在扩展速度及强度上存在较明显的差异, 位于北疆天山北坡经济带上的城市大多属于扩展速度相对较快、扩展强度相对较大的扩张类型, 而南疆城市的扩展速度则相对较慢、扩展强度也相对较小.通过对城市紧凑度和分维数变化的分析发现, 新疆城市平均紧凑度呈下降趋势, 而分形维数呈增长的趋势, 说明整体上新疆城市空间结构有趋于松散化的趋势, 城市的空间结构不够合理, 有待改善.     

基于遥感夜间灯光数据的大连城市用地扩张的空间特征分析

为揭示大连城市用地扩张的空间分布特征,基于DSMP/OLS夜间灯光数据提取1998—2013年大连地域边界,并得到各地区的灯光阈值及地域边界分区统计面积。通过计算不同时期不同区域的城市用地增长景观格局指数,研究该市16年来的城市用地扩张方向、强度和空间景观格局变化,以揭示大连20年来城市用地扩张的空间分布特征。结果表明,城市用地扩张主要集中在沙河口区、中山区和西岗区,并以其为中心向甘井子区、旅顺口区、金州区等区域扩张。城市用地空间格局总体基本稳定,受地理条件、空间距离、经济发展和政策指引等因素的影响,城市用地扩张在不同方向上差异化显著。研究成果可作为大连城市规划的依据。     

Consequences of Climate Change on the Ecogeomorphology of Coastal Wetlands

Climate impacts on coastal and estuarine systems take many forms and are dependent on the local conditions, including those set by humans. We use a biocomplexity framework to provide a perspective of the consequences of climate change for coastal wetland ecogeomorphology. We concentrate on three dimensions of climate change affects on ecogeomorphology: sea level rise, changes in storm frequency and intensity, and changes in freshwater, sediment, and nutrient inputs. While sea level rise, storms, sedimentation, and changing freshwater input can directly impact coastal and estuarine wetlands, biological processes can modify these physical impacts. Geomorphological changes to coastal and estuarine ecosystems can induce complex outcomes for the biota that are not themselves intuitively obvious because they are mediated by networks of biological interactions. Human impacts on wetlands occur at all scales. At the global scale, humans are altering climate at rapid rates compared to the historical and recent geological record. Climate change can disrupt ecological systems if it occurs at characteristic time scales shorter than ecological system response and causes alterations in ecological function that foster changes in structure or alter functional interactions. Many coastal wetlands can adjust to predicted climate change, but human impacts, in combination with climate change, will significantly affect coastal wetland ecosystems. Management for climate change must strike a balance between that which allows pulsing of materials and energy to the ecosystems and promotes ecosystem goods and services, while protecting human structures and activities. Science-based management depends on a multi-scale understanding of these biocomplex wetland systems. Causation is often associated with multiple factors, considerable variability, feedbacks, and interferences. The impacts of climate change can be detected through monitoring and assessment of historical or geological records. Attribution can be inferred through these in conjunction with experimentation and modeling. A significant challenge to allow wise management of coastal wetlands is to develop observing systems that act at appropriate scales to detect global climate change and its effects in the context of the various local and smaller scale effects.     

城市洪涝中人体失稳机理与判别标准研究进展

受全球气候变化和人类活动影响,近年来极端降水事件增多,由此引发的城市洪涝灾害频发。行人在洪水作用下易失去稳定,威胁生命安全,研究洪水中人体的失稳机理与判别标准,能为城市洪涝灾害的风险评估与管理提供科学依据。本文首先总结了国内外城市洪涝中人体失稳机理研究的相关成果,评估了现有人体失稳判别标准的适用范围及优缺点。基于力学分析和实测数据率定的计算公式虽然在推导过程中有一定的简化,但能较好地反映洪水中人体失稳的动力学机理,可以评估不同人群与不同洪水条件下的人体稳定性。针对当前城市洪涝中人体稳定性研究存在的不足,需要开展真实洪水中行人逃生以及沿漫水楼梯行走时的失稳机理与判别标准研究,并深入研究行人站立姿势调整对洪水中人体稳定性的影响;还需基于大数据等手段获取互联网上洪水中人体失稳的影像资料,构建洪水中人体失稳的实测数据库;同时还需推动人体失稳判别标准在洪水风险管理中的具体应用,最大程度地降低城市洪涝灾害带来的不利影响。     

浅析城市地下空间室内环境特点及设计思路:以西安赛格国际购物中心为例

随着中国城镇化进程的迅猛发展,城市规模不断扩大,人口不断增长,城市交通拥堵、环境污染、土地资源日益紧缺等问题日益凸显。城市地下空间作为城市资源的重要组成部分,适当的城市地下化发展可以在一定程度上缓解这些问题。文章简要叙述了目前我国城市地下空间开发利用的现状及城市地下空间的应用类型,分析了地下空间的恒温性、隔热性、湿度较大、环境封闭空气流通性差、天然光线不足、缺乏自然景观、没有外部形态等内部环境特点。以西安赛格国际购物中心为例,从自然采光、人工照明、植物水体和界面设计的角度概述了地下综合体室内设计的核心理念和关键步骤。最后提出了如下关于城市地下商业空间室内设计的优化思路：(1)空间布局明确,符合人的空间认知习惯;(2)通过扩大建筑入口和先进的技术手段,引入天然光;(3)运用照明模拟自然光;(4)引入自然元素,使室内外环境自然过渡,增加地下空间的活力,改善封闭感,缓解人的心理和生理障碍;(5)地下空间的各类尺度应符合人体尺度,避免产生不适感;(6)注重行动不便的人群,设置人性化的无障碍设施;(7)设计充足的休憩场所;(8)注重设计本土化,展现地域文化特色。     

Urban malaria in Africa: an environmental and socio-economic modelling approach for Yaoundé, Cameroon

Most of the existing predictive malaria risks spatial models use very broad spatial scales, and they are usually built-up for continental or national outlines. These models usually do not account for the complexity of socio-economic variables intervening into the malaria transmission process as well malaria prevention strategies. These spatial and thematic shortcomings are particularly interesting when looking at urban environments. This paper explains why a focus on urban malaria overcomes these shortcomings. A set of environmental variables derived from remotely sensed and ground climate station sources was used to build-up an ecological model. An original data collection process based on GPS measurements and retrospective interviews was introduced for the creation of various geoepidemiological and geosocial variables. Multinomial logistic models were used to predict and evaluate the contribution of various thematically separated groups of variables to malaria risk. Finally, it was possible to statistically and spatially evaluate the contribution of ecologic, socio-ecologic, socio-economic and behavioural characteristics of these groups of variables to malaria risks.     

Scales as a challenge for vulnerability assessment

The aim of this paper is to introduce scale as a basic tool for improving the conceptual structure of vulnerability assessments. The terminology useful for vulnerability assessments and the current use of scale issues in theoretical vulnerability frameworks will be discussed briefly. Two case studies working on sub-national and on local level will demonstrate problems as well as benefits resulting from scale implications. Both assessments analyse vulnerability in context to river floods in Germany. In order to develop a spatial comparison and to integrate topics like environment and society, vulnerability assessments need to be aware of scale implications. The main point is that a scale debate on a broader spectrum than just in technical spatial terms is missing in vulnerability and risk conceptualisations so far. Vulnerability assessments and scale are highly intertwined, not only in technical application but also in conceptualisation, which needs more scientific development.     

土地利用变化对全球气候影响的研究进展与方法初探

综合分析了土地利用与土地覆盖变化（LUCC）对全球气候影响研究的重要科学问题和国内外研究现状,在此基础上,考虑各学科的相互交叉、渗透和耦合等特点,提出并初步设计了土地利用变化对全球气候影响研究的星地一体化LUCC—气候—生态系统耦合研究技术方法体系,并就土地利用变化对全球气候影响的LUCC演变规律及动力学机制、LUCC...     

Multi-scalar inequality: Structured mobility and the narrative construction of scale in translocal Cambodia

Focusing on three neighbouring villages in Cambodia, this paper argues the need for a multi-scalar interpretation of the relationship between mobility and wealth. It analyses migrant livelihoods in both sender and receiving areas to show that single scale measurements of mobility are inappropriate in the context of translocal livelihoods because livelihoods enacted across multiple places may possess multiple values of scale and mobility, each co-existing within the same migrant lifeworld. In seeking an improved conception of these complexities, the paper has combined spatial and qualitative analysis of translocal livelihoods to highlight the linkages between mobility in multiple places. On this basis, it posits that the mobility of translocal livelihoods must be assessed at least three scales: the scale appropriate to the sending environment, the scale appropriate to the receiving environment, and the scale on which potential migrations are judged. Making use of this framework allows clear relationships to be observed between mobility and inequality in both the narratives and structures of the communities under investigation.