Rating for sustainable subdivision neighbourhood design (RSSND) : case of Bangkok metropolitan region (BMR), Thailand an eco-efficiency modelling approach

Bangkok Metropolitan Region (BMR) is the centre for various major activities in Thailand including political, industry, agriculture, and commerce. Consequently, the BMR is the highest and most densely populated area in Thailand. Thus, the demand for houses in the BMR is also the largest, especially in subdivision developments. For these reasons, the subdivision development in the BMR has increased substantially in the past 20 years and generated large numbers of subdivision developments (AREA, 2009; Kridakorn Na Ayutthaya & Tochaiwat, 2010). However, this dramatic growth of subdivision development has caused several problems including unsustainable development, especially for subdivision neighbourhoods, in the BMR. There have been rating tools that encourage the sustainability of neighbourhood design in subdivision development, but they still have practical problems. Such rating tools do not cover the scale of the development entirely; and they concentrate more on the social and environmental conservation aspects, which have not been totally accepted by the developers (Boonprakub, 2011; Tongcumpou & Harvey, 1994). These factors strongly confirm the need for an appropriate rating tool for sustainable subdivision neighbourhood design in the BMR. To improve level of acceptance from all stakeholders in subdivision developments industry, the new rating tool should be developed based on an approach that unites the social, environmental, and economic approaches, such as eco-efficiency principle. Eco-efficiency is the sustainability indicator introduced by the World Business Council for Sustainable Development (WBCSD) since 1992. The eco-efficiency is defined as the ratio of the product or service value according to its environmental impact (Lehni & Pepper, 2000; Sorvari et al., 2009). Eco-efficiency indicator is concerned to the business, while simultaneously, is concerned with to social and the environment impact. This study aims to develop a new rating tool named "Rating for sustainable subdivision neighbourhood design (RSSND)". The RSSND methodology is developed by a combination of literature reviews, field surveys, the eco-efficiency model development, trial-and-error technique, and the tool validation process. All required data has been collected by the field surveys from July to November 2010. The ecoefficiency model is a combination of three different mathematical models; the neighbourhood property price (NPP) model, the neighbourhood development cost (NDC) model, and the neighbourhood occupancy cost (NOC) model which are attributable to the neighbourhood subdivision design. The NPP model is formulated by hedonic price model approach, while the NDC model and NOC model are formulated by the multiple regression analysis approach. The trial-and-error technique is adopted for simplifying the complex mathematic eco-efficiency model to a user-friendly rating tool format. Credibility of the RSSND has been validated by using both rated and non-rated of eight subdivisions. It is expected to meet the requirements of all stakeholders which support the social activities of the residents, maintain the environmental condition of the development and surrounding areas, and meet the economic requirements of the developers.

中国东北温带样带区域和景观尺度生态模型的研究

样带是沿全球变化某一驱动因素的主要梯度而设置的由一系列研究站点构成的区域，被认为是研究全球变化与陆地生态系统关系的最有效的途径。而模型研究是全球变化研究中不可或缺的手段。本文即采用模型研究方法研究中国东北温带样带(NECT)区域，试图揭示温带生态系统对于全球变化（尤其是降水）的反应机制。 中国东北温带样带（NECT)位于42°N - 46°N，108°E - 132°E，长约二千多公里，是最早被列入GCTE的四条样带之一，从东到西有明显的湿度梯度，被认为是温带区域研究水分梯度的代表性样带。本文研究主要集中在： 1．NECT中环境数据库的建立,本文采用EIS作为数据管理系统。由于EIS管理空间数据的特点是根据确定的地理坐标来提供空间定位，因而每一环境因子的属性值分布都有确定的地理坐标与其对应，特别适合于样带这种研究区域较大，同时又要求有精确空间定位的区域。NECT环境数据库包括地形、气候、植被、土壤、土地利用、水文、孢粉数据及社会经济等分库、本数据库力图提供各环境因子的各种属性值而代替仅仅提供类型值。 2．NECT中PFTs的划分PFTs的划分被认为是建立DGVM的前提。本文认为PFTs的划分是模型研究中一个尺度上升过程的结果，不同的尺度，不同的研究目标导致不同的PFTs的划分。在NECT区域中，考虑植被对全球变化中降水因子的不同反映机制，采用生活型、高度、耐旱特性、叶子大小、叶子季相、主根深度和木质化程度等指标根据- TWINSPAN和FCLUS进行划分，得到以下9种NECT区域中植被功能类型：常绿针叶树种、落叶针叶树种、落叶阔叶树种、落叶小叶灌木、落叶小叶半灌木、落叶强旱生半灌木、多年生中旱生草本、适应旱生环境的多年生草本和多年生强旱生草本。对NECT区域中PFTs的DCA分析表明降水是控制PFTs在NECT区域中分布的主要环境因子。在代表景观层次的长白山PFTs的划分中，则采用树种有记载的最大寿命、最大胸径、最大树高、各树种生长参数、树种自然分布区内>5℃的有效积温的最小值和最大值、耐阴、耐旱、喜肥特性、树种的扩散更新，就地下种更新和萌条更新能力参数及叶子大小和类型等指标采用上述软件得到的以下PFTs:即不耐荫阔叶树种、耐荫阔叶树种、耐荫针叶树种和不耐荫的阳生针叶树种。 3.NECT中BCM模型的建立和预测 本文认为土壤水是决定SPC系统水分状况的直接指标。而均衡土壤水分剖面代表了土壤水的多年平均状态，因而本文以Watershed模型为基础，模拟NECT区域中任意一点的均衡土壤水分剖面（精度为每经纬网格32×48个点）;然后根据这个均衡水分剖面用计算LAI子模型确定该水分剖面所能支持的LAI;进而根据这个LAI由Biome等模型划分出Biome在NECT中的分布。全球变化的结果将改变区域中任意一点的土壤水分状况，从而影响植被的LAI，进而导致Biome的改变。本模型成功的模拟了LAI和Biome在NECT区域中的分布，利用85-90生长季每月平均的NDVI作相关检验表明除5月份以外，相关系数都>0.7，而5月份也达到0,6457，都达到了极显著的程度。尤为重要的是，模型对于不同植被类型的NDVI与LAI的对应关系有良好的模拟，如针叶林的LAI在相同的NDVI值下明显比阔叶林小，因而模型模拟的LAI在NECT东部针叶林分布区LAI值比针阔混交林明显偏小，而与Spanmen等(1990)所提出的针叶林叶面积指数与NDVI关系非常一致。模型的预测显示：(1) T+20C (PET+15%)，Precipitation+20%，LAI总体上变化不大，且空间变化呈现复杂性，总体上表现出草原植被LAI减少，而森林的LAI增加;Biome层次表现出针阔混交林和矮草原面积扩大，针叶林和森林草原面积减少，其中对于该情形下变化最为明显的是针叶林和森林草原。NECT东部区域发育在沙性土上的植被的LAI明显增加，而科尔沁沙地植被的LAI则维持不变。(2)T+40C (PET+30%)，Precipitation+20%，LAI总体上将减小0.14，但空间分布不均。东部森林区域LA1将维持不变或增加（主要为针叶林），草原植被LAI仍表现出减少趋势;在Biome层次上则表现出草原面积的扩大。对于第一种情形下LAI有增有减的森林革原地区则表现出减小的一致性，总体来说，第二种情形比第一种情形表现出相当的干旱性。从对两种全球变化情形的反应来看，针叶林和森林草原是NECT中对全球变化驱动因子温度和降水的敏感植被类型;丽科尔沁沙地植被表现出相当的稳定性，表明该沙地的敏感性主要是由于人类活动这个因子造成的。 4.NECT中景观层次NPP模型的建立和预测 景观层次之所以成为模型研究中一个独特的层次，是由于地形效应的存在。地形效应对于水、热。营养物质的进行重新分配，从而进一步控制了生态系统的分布。本文选择NECT区域中森林生态系统的代表性分布小流域一二道白河小流域为研究区域。首先，应用Sunlight模型来模拟小流域任意一点所截取的能用于光合作用的太阳辐射能。Sunlight模型充分考虑了由于栅格的坡度、坡向和遮蔽度对可照时间和太阳直射辐射的影响以及坡度和可祝度对太阳散射辐射的影响，并提供了消除大气状况从站点观察数据推测的方法，即太阳直射辐射转换系数Rb和太阳散射辐射转换系数R，结合植被的分布特性，得到IPR在小流域中的分布。结果表明，IPR在小流域中相差不大，与高程呈正相关。进而利用温度修正模型得到温度修正系数，平均为0.446，表明温度对NPP的限制效应比较大;而水分修正系数则通过Topmodel模拟每一栅格的地下水位，由这个地下水位通过前述Waterbalance模型模拟均衡土壤水分剖面，进而求出水分修正系数，平均为0.86，表明该流域水分状况良好，水分状况对NPP的限制性不强。模拟结果显示：海拔NPP为16.05 t.ha-1年;分布于llOOm至1700m的针叶林平均NPP为12.71 t.ha-1年d;>1700m的岳桦林平均NPP为7.31t.ha-l年“两实测的NPP值分别为20.19 t.ha-l年 13.45 t.ha-l年‘1和5.15 t.ha-1年”。可见模型模拟的整个NPP的分布趋势与现实NPP分布一致。模型的预测表明：(1)．T+2℃( PET+15%)，P+20%时整个小流域的平均NPP将从14.60 t.ha-1年-1增加到16.65 t.ha_l年，且不同生态系统的增加幅度大致类似。以岳桦林生态系统稍高，增加幅度为15.3%，引起该小流域NPP增加的主要原因是温度状况的改善，而水分状况与变化前一致。(2)T+4℃( PET+30%)，P+20%的变化前景下NPP的增加幅度更大，整个小流域的平均NPP将达到18.63 t.ha-1年，且不同生态系统变化幅度不同．阔叶红松林、暗针叶林和岳桦林生态系统NPP增加幅度将分别达到25.8%，28.3%和32.8%.引起整个小流域NPP增加的主要原因仍旧是温度状况的大幅度提高，平均从变化前的0.477提高到0.610，而水分状况则仍保持相当的稳定性。

中国北方草地及东部森林季节生长格局模拟

近现代以来，由于人类对自然植被的不合理利用，导致植被退化，严重影响了我国的环境质量及社会经济的发展。因此，根据植被的净第一性生产力(NPP)制定植被资源的利用强度，依据环境承载力确定退化土地的植被恢复盖度，对于我国自然资源的合理利用及可持续的退化生态系统恢复具有重要意义，急需在区域上对NPP及最适植被盖度进行科学估计。 以我国北方草地、东部森林样带为研究对象，采用以植物群落生长与环境容纳量相平衡的基本生态学理论为基础的植物群落生理生态学模型模拟植物群落的蒸发系数(k)、叶片投影盖度(FPC)及NPP的分布状况，分析其最适盖度与NPP的空间分布及NPP的季节变化。结果表明： (1) 温性草地自东向西，青藏高原自东南向西北，植物群落3个模拟参数 k、NPP与FPC呈递减趋势。北方草地NPP的模拟值较低，仅高寒草甸和温性草甸草原的NPP均值大于2 t•hm-2•a-1，高寒草甸和高寒草原的叶片投影盖度为93%和79%。高寒草甸的3个模拟参数均最高，高寒草原FPC仅次于高寒草甸，而NPP却与温性典型草原相近，温性典型荒漠的3个参数最低。 (2) 东部森林NPP表现为从南到北逐渐减少的纬度地带性分布趋势，从最南端热带雨林季雨林的31.62 t•hm-2•a-1依次向北减少至寒温带针叶林的3.45 t•hm-2•a-1。k与FPC没有表现出递减趋势，而且变化幅度不大，分别为05-0.4和87%-77%。 (3) 高寒草甸、高寒草原、温性草甸草原、温性典型草原、温性荒漠草原、温性草原化荒漠、温性典型荒漠这7个类型草地的畜群承载力约为：5.2、2.3、3.6、2.1、1.0、0.6、0.2只羊单位•hm-2。 (4) 我国东部森林FPC大多数大于70%，可以支持密度较高的森林植被类型。北方温性草原大部分地区FPC约为50%或者更小，宜维持现有的以草本、灌木及半灌木植物为主的植被类型及生态环境功能，而不宜进行大面积的农田开垦或恢复高密度的人工植被。

Photoacclimation of natural phytoplankton communities

Phytoplankton regulate internal pigment concentrations in response to light and nutrient availability. Chlorophyll to carbon ratios (Chl:Cphyto) are commonly reported as a function of growth irradiance (Eg) for evaluating the photoacclimation response of phytoplankton. In contrast to most culture experiments, natural phytoplankton communities experience fluctuating environmental conditions making it difficult to compare field and lab observations. Observing and understanding photoacclimation in nature is important for deciphering changes in Chl:Cphyto resulting from environmental forcings and for accurately estimating net primary production (NPP) in models which rely on a parameterized description of photoacclimation. Here we employ direct analytical measurements of Cphyto and parallel high-resolution biomass estimates from particulate backscattering (bbp) and flow cytometry to investigate Chl:Cphyto in natural phytoplankton communities. Chl:Cphyto observed over a wide range of Eg in the field was consistent with photoacclimation responses inferred from satellite observations. Field-based photoacclimation observations for a mixed natural community contrast with laboratory results for single species grown in continuous light and nutrient replete conditions. Applying a carbon-based net primary production (NPP) model to our field data for a north-south transect in the Atlantic Ocean results in estimates that closely match 14C depth-integrated NPP for the same cruise and with historical records for the distinct biogeographic regions of the Atlantic Ocean. Our results are consistent with previous satellite and model observations of cells growing in natural or fluctuating light and showcase how direct measurements of Cphyto can be applied to explore phytoplankton photophysiology, growth rates, and production at high spatial resolution in-situ.

The CLIMATE data base of monthly normals for globally gridded climatic variables (version 2.1)

This database (Leemans & Cramer 1991) contains monthly averages of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5 degree longitude/latitude resolution. All grd-files contain the same 62483 pixels in the same order, with 30' latitude and longitude resolution. The coordinates are in degree-decimals and indicate the SW corner of each pixel. Topography is from ETOPO5 and indicates modal elevation. Data were generated from a large data base, using the partial thin-plate splining algorithm (Hutchinson & Bischof 1983). This version is widely used around the globe, notably by all groups participating in the IGBP NPP model intercomparison.

An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe

Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.

Anti-Aversive Effects of Cannabidiol on Innate Fear-Induced Behaviors Evoked by an Ethological Model of Panic Attacks Based on a Prey vs the Wild Snake Epicrates cenchria crassus Confrontation Paradigm

Several pharmacological targets have been proposed as modulators of panic-like reactions. However, interest should be given to other potential therapeutic neurochemical agents. Recent attention has been given to the potential anxiolytic properties of cannabidiol, because of its complex actions on the endocannabinoid system together with its effects on other neurotransmitter systems. The aim of this study was to investigate the effects of cannabidiol on innate fear-related behaviors evoked by a prey vs predator paradigm. Male Swiss mice were submitted to habituation in an arena containing a burrow and subsequently pre-treated with intraperitoneal administrations of vehicle or cannabidiol. A constrictor snake was placed inside the arena, and defensive and non-defensive behaviors were recorded. Cannabidiol caused a clear anti-aversive effect, decreasing explosive escape and defensive immobility behaviors outside and inside the burrow. These results show that cannabidiol modulates defensive behaviors evoked by the presence of threatening stimuli, even in a potentially safe environment following a fear response, suggesting a panicolytic effect. Neuropsychopharmacology (2012) 37, 412-421; doi:10.1038/npp.2011.188; published online 14 September 2011

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Application of noise analysis for sensor surveillance in Trillo NPP

It is a known fact that noise analysis is a suitable method for sensor performance surveillance. In particular, controlling the response time of a sensor is an efficient way to anticipate failures and to have the opportunity to prevent them. In this work the response times of several sensors of Trillo NPP are estimated by means of noise analysis. The procedure applied consists of modeling each sensor with autoregressive methods and getting the searched parameter by analyzing the response of the model when a ramp is simulated as the input signal. Core exit thermocouples and in core self-powered neutron detectors are the main sensors analyzed but other plant sensors are studied as well. Since several measurement campaigns have been carried out, it has been also possible to analyze the evolution of the estimated parameters during more than one fuel cycle. Some sensitivity studies for the sample frequency of the signals and its influence on the response time are also included. Calculations and analysis have been done in the frame of a collaboration agreement between Trillo NPP operator (CNAT) and the School of Mines of Madrid.

An approximate method for the solution of an influence function foil rolling model

Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.