A Bayesian strategy for combining predictions from empirical and process-based models

We present a strategy for using an empirical forest growth model to reduce uncertainty in predictions made with a physiological process-based forest ecosystem model. The uncertainty reduction is carried out via Bayesian melding, in which information from prior knowledge and a deterministic computer model is conditioned on a likelihood function. We used predictions from an empirical forest growth model G-HAT in place of field observations of aboveground net primary productivity (ANPP) in a deciduous temperate forest ecosystem. Using Bayesian melding, priors for the inputs of the process-based forest ecosystem PnET-II were propagated through the model, and likelihoods for the PnET-II output ANPP were calculated using the G-HAT predictions. Posterior distributions for ANPP and many PnET-II inputs obtained using the G-HAT predictions largely matched posteriors obtained using field data. Since empirical growth models are often more readily available than extensive field data sets, the method represents a potential gain in efficiency for reducing the uncertainty of process-based model predictions when reliable empirical models are available but high-quality data are not.     

Organoiodine formation during humification in peatlands

Although two billion people in the world are suffering from iodine deficiency there is little information on the chemical fate of iodine in the terrestrial environment. Here we show that peatlands play a major role in terrestrial iodine cycling. Chemical data from two peat profiles from Patagonia, Chile imply that transformation of iodine from its inorganic form to organoiodine compounds during early humification in peatlands is a key process in storage of iodine in the terrestrial environment. Once bound in peat, iodine remains stable for thousands of years. In the earths peatlands, net accumulation of iodine since the last glacial period is estimated to be 12–36 teragrams (1 Tg=10¹² g). These data suggest that peatlands are a major reservoir of iodine in terrestrial ecosystems. Our novel model of iodine distribution in the terrestrial environment demonstrates the key role of peatlands in burial and reemission of organically bound iodine.     

Application of a coupled ecosystem-chemical equilibrium model, DayCent-Chem, to stream and soil chemistry in a Rocky Mountain watershed

Atmospheric deposition of sulfur and nitrogen species have the potential to acidify terrestrial and aquatic ecosystems, but nitrate and ammonium are also critical nutrients for plant and microbial productivity. Both the ecological response and the hydrochemical response to atmospheric deposition are of interest to regulatory and land management agencies. We developed a non-spatial biogeochemical model to simulate soil and surface water chemistry by linking the daily version of the CENTURY ecosystem model (DayCent) with a low temperature aqueous geochemical model, PHREEQC. The coupled model, DayCent-Chem, simulates the daily dynamics of plant production, soil organic matter, cation exchange, mineral weathering, elution, stream discharge, and solute concentrations in soil water and stream flow. By aerially weighting the contributions of separate bedrock/talus and tundra simulations, the model was able to replicate the measured seasonal and annual stream chemistry for most solutes for Andrews Creek in Loch Vale watershed, Rocky Mountain National Park. Simulated soil chemistry, net primary production, live biomass, and soil organic matter for forest and tundra matched well with measurements. This model is appropriate for accurately describing ecosystem and surface water chemical response to atmospheric deposition and climate change.     

Long-term temporal-spatial dynamics of marine coastal water quality in the Tolo Harbor, Hong Kong, China

IntroductionToloHarborislocatedinthenortheasternpartofHongKong .Itisanearlyland lockedwaterbodywithonlyonenarrowexittotheopenseaatMirsBay(Fig .1) .Itslengthandsurfaceareaareapproximately 15kmand 5 2km2 ,respectively .Theaveragedepthvariesfromlessthan10min…     

长江干流关键点流量变化及其生态影响分析

文章详细介绍了水文变动指标IHA法32个水文参数及其生态影响,计算分析了长江干流4个关键点寸滩、宜昌、汉口和大通在"自然变化阶段"、"受人类活动干扰阶段"和多年长系列3个不同时期的多年平均月流量状况,并采用IHA法计算了各控制点的32个水文参数,确定了各参数相应的水文变化等级,分析了长江干流流量格局的变化情况及潜在的生态影响。结果表明,长江干流关键点流量格局的变化主要是:年内月平均流量1～4月枯季流量增加,6～7月汛期流量增加;寸滩和宜昌流量减少主要集中在下半年8～11月,汉口和大通流量减少的时间推迟,主要集中在10～11月;最小流量参数组的平均值增加,年最小1日流量日期均提前;干扰后呈现连续日上涨率减小,下降率增加的趋势;潜在的生态影响主要是生物多样性降低,大型水生植物丰度增加,大型无脊椎动物现存量减少和丰度减少,对产漂流性卵的鱼类影响较大,动植物生活史模式发生变化,易造成本地物种消失,外来物种入侵的后果等几个方面。     

Simulated dynamics of carbon stocks driven by changes in land use, management and climate in a tropical moist ecosystem of Ghana

Sub-Saharan Africa is large and diverse with regions of food insecurity and high vulnerability to climate change. This project quantifies carbon stocks and fluxes in the humid forest zone of Ghana, as a part of an assessment in West Africa. The General Ensemble biogeochemical Modeling System (GEMS) was used to simulate the responses of natural and managed systems to projected scenarios of changes in climate, land use and cover, and nitrogen fertilization in the Assin district of Ghana. Model inputs included historical land use and cover data, historical climate records and projected climate changes, and national management inventories. Our results show that deforestation for crop production led to a loss of soil organic carbon (SOC) by 33% from 1900 to 2000. The results also show that the trend of carbon emissions from cropland in the 20th century will continue through the 21st century and will be increased under the projected warming and drying scenarios. Nitrogen (N) fertilization in agricultural systems could offset SOC loss by 6% with 30 kg N ha⁻¹ year⁻¹ and by 11% with 60 kg N ha⁻¹ year⁻¹. To increase N fertilizer input would be one of the vital adaptive measures to ensure food security and maintain agricultural sustainability through the 21st century.     

Optimizing the biodiversity gain from agri-environment schemes

How best to optimize the biodiversity gain from agri-environment schemes (AES) has recently been identified as a key policy-relevant question. Here, the effects of two features of lowland agricultural landscapes on the abundance and diversity of larger moths are contrasted. Although both features bring about positive effects, hedgerow trees have a larger impact than 6 m wide grassy field margins. Whilst AES payments are given to create and maintain grass margins, no financial reward is currently offered for the retention of hedgerow trees. Furthermore, it was only in areas where the amount of land under AES was experimentally increased, by targeting farmers, that the presence of hedgerow trees resulted in a substantially higher abundance (+60%) and diversity (+38%) of moths. Thus, by using larger moths as bio-indicators of landscape-scale quality, it is demonstrated that improvements to the cost-effectiveness of AES could be achieved, firstly, by providing more appropriate financial rewards to farmers for different landscape features, and secondly, through landscape-scale targeting of farmers to encourage participation in AES.     

Development of collision risk indicators for autonomous subsea inspection maintenance and repair

The objective of this article is to present a method for developing collision risk indicators applicable for autonomous remotely operated vehicles (AROVs), which are essential for promoting situation awareness in decisions support systems. Three suitable risk based collision indicators are suggested for AROVs namely, time to collision, mean time to collision and mean impact energy. The proposed indicators are classified into different thresholds; low, intermediate and high. An AROV flight path is simulated to gather input data to calculate the proposed indicators and three collision targets are established, i.e., subsea structure, seabed and a cooperating AROV. The proposed indicator development method together with the case study show a proof-of-concept that the combination of mean time to collision and mean impact energy indicators can identify risk prone waypoints in the AROV path. The method results in an overall risk picture for a given AROV path. The results may provide useful input in replanning of mission paths and for implementation of risk reducing measures. Even though the method focuses on collision risk, it can be used for other accident scenarios for AROVs.     

基于离散仿真分析的废弃电器电子产品回收网络优化

优化电子废弃物回收网络对控制回收成本、降低环境污染具有重要意义.因此,本文建立了一种综合考虑运输、存储及淡旺季的回收过程离散仿真模型,提出了一种以经济、能源及环境为指标的回收网络评价方法.同时,以安徽省为例,结合现有回收模式,分别设计了4种回收网络布局及运输方案,在不同的回收覆盖率及库存能力条件下以回收成本、燃油消耗及CO2排放为优化目标对比分析各备选方案,提出了在报废量大于0.15万t·a-1的地区建立回收点并采取全局运输模式的最优方案.研究表明,本文提出的方法同样适用于我国其他省市回收网络的优化.